ALBERT

Beschreibung: Objective: To develop a pipeline for realistic head models of nonhuman primates (NHPs) for simulations of noninvasive brain stimulation, and use these models together with empirical threshold measurements to demonstrate that the models capture individual anatomical variability. Methods: Based on structural MRI data, we created models of the electric field (E-field) induced by right unilateral (RUL) electroconvulsive therapy (ECT) in four rhesus macaques. Individual motor threshold (MT) was measured with transcranial electric stimulation (TES) administered through the RUL electrodes in the same subjects. Results: The interindividual anatomical differences resulted in 57% variation in median E-field strength in the brain at fixed stimulus current amplitude. Individualization of the stimulus current by MT reduced the E-field variation in the target motor area by 27%. There was significant correlation between the measured MT and the ratio of simulated electrode current and E-field strength ( $r^{2} = 0.95$ , $p = 0.026$ ). Exploratory analysis revealed significant correlations of this ratio with anatomical parameters including of the superior electrode-to-cortex distance, vertex-to-cortex distance, and brain volume ( $r^{2} > 0.96$ , $p 〈 0.02$ ). The neural activation threshold was estimated to be $0.45 pm 0.07$ V/cm for 0.2-ms stimulus pulse width. Conclusion: These results suggest that our individual-specific NHP E-field models appropriately capture individual anatomical variability relevant to the dosing of TES/ECT. These findings are exploratory due to the small number of subjects. Sign- ficance: This study can contribute insight in NHP studies of ECT and other brain stimulation interventions, help link the results to clinical studies, and ultimately lead to more rational brain stimulation dosing paradigms.

Beschreibung: Ectopic electrical activity that originates in the peri-infarct region can give rise to potentially lethal re-entrant arrhythmias. The spatial variation in electrotonic loading that results from structural remodelling in the infarct border zone may increase the probability that focal activity will trigger electrical capture, but this has not previously been investigated systematically. This study uses in-silico experiments to examine the structural modulation of effective refractory period on ectopic beat capture. Informed by 3-D reconstructions of myocyte organization in the infarct border zone, a region of rapid tissue expansion is abstracted to an idealized representation. A novel metric is introduced that defines the local electrotonic loading as a function of passive tissue properties and boundary conditions. The effective refractory period correlates closely with local electrotonic loading, while the action potential duration, conduction, and upstroke velocity reduce in regions of increasing electrotonic load. In the presence of focal ectopic stimuli, spatial variation in effective refractory period can cause unidirectional conduction block providing a substrate for reentrant arrhythmias. Consequently, based on the observed results, a possible novel mechanism for arrhythmogenesis in the infarct border zone is proposed.

Beschreibung: Automatic processing and accurate diagnosis of pathological electrocardiogram (ECG) signals remains a challenge. As long-term ECG recordings continue to increase in prevalence, driven partly by the ease of remote monitoring technology usage, the need to automate ECG analysis continues to grow. In previous studies, a model-based ECG filtering approach to ECG data from healthy subjects has been applied to facilitate accurate online filtering and analysis of physiological signals. We propose an extension of this approach, which models not only normal and ventricular heartbeats, but also morphologies not previously encountered. A switching Kalman filter approach is introduced to enable the automatic selection of the most likely mode (beat type), while simultaneously filtering the signal using appropriate prior knowledge. Novelty detection is also made possible by incorporating a third mode for the detection of unknown (not previously observed) morphologies, and denoted as X-factor. This new approach is compared to state-of-the-art techniques for the ventricular heartbeat classification in the MIT-BIH arrhythmia and Incart databases. $F_1$ scores of $mathbf {98.3%}$ and $mathbf {99.5%}$ were found on each database, respectively, which are superior to other published algorithms’ results reported on the same databases. Only $mathbf {3%}$ of all the beats were discarded as X-factor, and the majority of these beats contained high levels of noise. The proposed technique demonstrates accurate beat classification in the presence of previously unseen (and unlearned) morphologies and noise, and provides an automated method for morphological analysis of arbitrary (unknown) ECG leads.

Beschreibung: Objective : A hybrid imaging technique, ultrasound-modulated luminescence tomography, that uses ultrasound to modulate diffusely propagating light has been shown to improve the spatial resolution of optical images. This paper investigates the underlying modulation mechanisms and the feasibility of applying this technique to improve spatial resolution in bioluminescence tomography. Methods : Ultrasound-modulated bioluminescence tomography was studied numerically to identify the effects of four factors (reduced optical scattering coefficient, optical absorption coefficient, refractive index, and luciferase concentration) on the depth of light modulation. In practice, an open source finite-element method tool for simulation of diffusely propagating light, near infrared fluorescence and spectral tomography, was modified to incorporate the effects of ultrasound modulation. The signal-to-noise ratios of detected modulated bioluminescent emissions are calculated using the optical and physical properties of a mouse model. Results : The modulation depth of the bioluminescent emission affected by the US induced variation of local concentration of the light emitting enzyme luciferase was at least two orders of magnitude greater than that caused by variations in the other factors. For surface radiances above approximately $10^7$ $hbox{photons}$ / $hbox{s}$ / $hbox{cm}^{2}$ / $hbox{sr,}$ the corresponding SNRs are detectable with the currently available detector technologies. Conclusion : The dominant effect in generation of ultrasound-modulated bioluminescence is ultrasound induced variation in luciferase concentration. The SNR analysis confirms the- feasibility of applying ultrasound-modulated bioluminescence tomography in preclinical imaging of mice. Significance : The simulation model developed suggests ultrasound-modulated bioluminescence tomography is a potential technique to improve the spatial resolution of bioluminescence tomography.

Beschreibung: Mechanical ventilation of patients with acute respiratory distress syndrome (ARDS) is a necessary life support measure which may lead to ventilator-induced lung injury, a complication that can be reduced or ameliorated by using appropriate tidal volumes and positive end-expiratory pressures. However, the optimal mechanical ventilation parameters are almost certainly different for each patient, and will vary with time as the injury status of the lung changes. In order to optimize mechanical ventilation in an individual ARDS patient, therefore, it is necessary to track the manner in which injury status is reflected in the mechanical properties of the lungs. Accordingly, we developed an algorithm for assessing the time-dependent manner in which different lung regions open (recruit) and close (derecruit) as a function of the pressure waveform that is applied to the airways during mechanical ventilation. We used this algorithm to test the notion that variable ventilation provides the dynamic perturbations in lung volume necessary to accurately identify recruitment/derecruitment dynamics in the injured lung. We performed this test on synthetic pressure and flow data generated with established numerical models of lung function corresponding to both healthy mice and mice with lung injury. The data were generated by subjecting the models to a variety of mechanical ventilation regimens including variable ventilation. Our results support the hypothesis that variable ventilation can be used as a diagnostic tool to identify the injury status of the lung in ARDS.

Beschreibung: Goal: Many brain–computer interface (BCI) classification techniques rely on a large number of labeled brain responses to create efficient classifiers. A large database representing all of the possible variability in the signal is impossible to obtain in a short period of time, and prolonged calibration times prevent efficient BCI use. We propose to improve BCIs based on the detection of event-related potentials (ERPs) in two ways. Methods: First, we increase the size of the training database by considering additional deformed trials. The creation of the additional deformed trials is based on the addition of Gaussian noise, and on the variability of the ERP latencies. Second, we exploit the variability of the ERP latencies by combining decisions across multiple deformed trials. These new methods are evaluated on data from 16 healthy subjects participating in a rapid serial visual presentation task. Results: The results show a significant increase in the performance of single-trial detection with the addition of artificial trials, and the combination of decisions obtained from altered trials. When the number of trials to train a classifier is low, the proposed approach allows us improve performance from an AUC of $0.533pm 0.080$ to $0.905pm 0.053$ . This improvement represents approximately an 80% reduction in classification error. Conclusion: These results demonstrate that artificially increasing the training dataset leads to improved single-trial detection. Significance: Calibration sessions can be shortened for BCIs based on ERP detection.

Beschreibung: Goal: The existing ISFET-based DNA sequencing detects hydrogen ions released during the polymerization of DNA strands on microbeads, which are scattered into microwell array above the ISFET sensor with unknown distribution. However, false pH detection happens at empty microwells due to crosstalk from neighboring microbeads. In this paper, a dual-mode CMOS ISFET sensor is proposed to have accurate pH detection toward DNA sequencing. Methods: Dual-mode sensing, optical and chemical modes, is realized by integrating a CMOS image sensor (CIS) with ISFET pH sensor, and is fabricated in a standard 0.18-μm CIS process. With accurate determination of microbead physical locations with CIS pixel by contact imaging, the dual-mode sensor can correlate local pH for one DNA slice at one location-determined microbead, which can result in improved pH detection accuracy. Moreover, toward a high-throughput DNA sequencing, a correlated-double-sampling readout that supports large array for both modes is deployed to reduce pixel-to-pixel nonuniformity such as threshold voltage mismatch. Results: The proposed CMOS dual-mode sensor is experimentally examined to show a well correlated pH map and optical image for microbeads with a pH sensitivity of 26.2 mV/pH, a fixed pattern noise (FPN) reduction from 4% to 0.3%, and a readout speed of 1200 frames/s. Conclusion: A dual-mode CMOS ISFET sensor with suppressed FPN for accurate large-arrayed pH sensing is proposed and demonstrated with state-of-the-art measured results toward accurate and high-throughput DNA sequencing. Significance: The developed dual-mode CMOS ISFET sensor has great potential for future personal genome diagnostics with high accuracy and low cost.

Beschreibung: Goal : Visual feedback can be used during gait rehabilitation to improve the efficacy of training. We presented a paradigm called visual feedback distortion; the visual representation of step length was manipulated during treadmill walking. Our prior work demonstrated that an implicit distortion of visual feedback of step length entails an unintentional adaptive process in the subjects’ spatial gait pattern. Here, we investigated whether the implicit visual feedback distortion, versus conscious correction, promotes efficient locomotor adaptation that relates to greater retention of a task. Methods: Thirteen healthy subjects were studied under two conditions: (1) we implicitly distorted the visual representation of their gait symmetry over 14 min, and (2) with help of visual feedback, subjects were told to walk on the treadmill with the intent of attaining the gait asymmetry observed during the first implicit trial. After adaptation, the visual feedback was removed while subjects continued walking normally. Over this 6-min period, retention of preserved asymmetric pattern was assessed. Results: We found that there was a greater retention rate during the implicit distortion trial than that of the visually guided conscious modulation trial. Conclusion: This study highlights the important role of implicit learning in the context of gait rehabilitation by demonstrating that training with implicit visual feedback distortion may produce longer lasting effects. Significance: This suggests that using visual feedback distortion could improve the effectiveness of treadmill rehabilitation processes by influencing the retention of motor skills.

Beschreibung: This paper explores the development of biomechanical models for evaluating a new class of passive mechanical implants for orthopedic surgery. The proposed implants take the form of passive engineered mechanisms, and will be used to improve the functional attachment of muscles to tendons and bone by modifying the transmission of forces and movement inside the body. Specifically, we present how two types of implantable mechanisms may be modeled in the open-source biomechanical software OpenSim. The first implant, which is proposed for hand tendon-transfer surgery, differentially distributes the forces and movement from one muscle across multiple tendons. The second implant, which is proposed for knee-replacement surgery, scales up the forces applied to the knee joint by the quadriceps muscle. This paper's key innovation is that such mechanisms have never been considered before in biomechanical simulation modeling and in surgery. When compared with joint function enabled by the current surgical practice of using sutures to make the attachment, biomechanical simulations show that the surgery with 1) the differential mechanism (tendon network) implant improves the fingers’ ability to passively adapt to an object's shape significantly during grasping tasks (2.74× as measured by the extent of finger flexion) for the same muscle force, and 2) the force-scaling implant increases knee-joint torque by 84% for the same muscle force. The critical significance of this study is to provide a methodology for the design and inclusion of the implants into biomechanical models and validating the improvement in joint function they enable when compared with current surgical practice.

Beschreibung: The impact of pulse repetition rate (PRR) in modulating electroporation (EP) induced by nanosecond pulsed electric fields (nsPEFs) in mammalian cells was approached here by performing both biological and numerical analysis. Plasma membrane permeabilization and viability of Jurkat cells were analyzed after exposure to 500, 1.3 MV/m, 40 ns PEFs with variable PRR (2–30 Hz). A finite-element model was used to investigate EP dynamics in a single cell under the same pulsing conditions, by looking at the time course of transmembrane voltage and pore density on the ns time scale. The biological observations showed an increased EP and reduced viability of the exposed cells at lower PRR in the considered range. The numerical analysis resulted in different dynamics of plasma membrane response when ns pulses were delivered with different PRR, consistently with a phenomenon of electrodesensitization recently hypothesized by another research group.

Beschreibung: Gastroscopy plays an important role in the diagnosis of gastric disease. In this paper, we develop an image panoramic system to assist endoscopists in improving lesion surveillance and reducing many of the tedious operations associated with gastroscopy. The constructed panoramic view has two categories: 1) the local view broadens the endoscopist's field of view in real time. Combining with the original gastroscopic video, this mosaicking view enables the endoscopist to diagnose the lesion comprehensively; 2) the global view constructs a large-area panoramic scene of the internal gastric surface, which can be used for intraoperative surgical navigation and postoperative scene review. Due to the irregular texture and inconsistent reflection of the gastric internal surface, common registration methods cannot accurately stitch this surface. Thereby, a six degree of freedom position tracking endoscope is devised to accommodate for the accumulated mosaicking error and provide efficient mosaicking results. For the global view, a dual-cube constraint model and a Bundle Adjustment algorithm are incorporated to deal with the mosaicking error caused by the irregular inflation and nonrigid deformation of the stomach. Moreover, texture blending and frame selection schemes are developed to make the mosaicking results feasible in real-clinical applications. The experimental results demonstrate that our system performs with a speed of 7.12 frames/s in a standard computer environment, and the mosaicking mean error is 0.43 mm for local panoramic view and 3.71 mm for global panoramic view.

Beschreibung: In this paper, we present a smart capsule for location-specific drug release in the gastrointestinal tract. Once activated through a magnetic proximity fuse, the capsule opens up and releases its powdered payload in a location specified by an implanted miniature magnetic marker or an externally worn larger magnet. The capsule (9 mm × 26 mm) comprises of two compartments: one contains a charged capacitor and a reed switch, while the second one houses the drug reservoir capped by a taut nylon thread intertwined with a nichrome wire. The nichrome wire is connected to the capacitor through the reed switch. The capacitor is charged to 2.7 V before ingestion and once within the proximity of the permanent magnet; the reed switch closes, discharging the capacitor through the nichrome wire, melting the nylon thread, detaching the cap, and emptying the drug reservoir.

Beschreibung: Goal: The purpose of this paper was to evaluate a nitinol tine fixation design for a transcatheter pacemaker in order to determine if the tines could be easily deployed and safely removed from the myocardium, enable low, stable pacing thresholds, and minimize the potential for dislodgment. Methods: The penetration properties of 13 human hearts were compared to the deployment and fixation energy of the tines to determine if the tines could be easily deployed and removed from the myocardium. The safety factor for dislodgement was calculated by comparing the kinetic energy of the device to the fixation energy of the tines. The fixation stability was tested in 113 chronic implants across 89 animals via pacing threshold measurements or evidence of dislodgement at necropsy. Results: Based on the tine fixation and tissue energy analysis, the tines can easily penetrate the heart. The tines can be safely removed from the myocardium based on the increased tine surface area during retraction. There were no dislodgements observed in the animals and the mean pacing threshold at implant was 0.59 +/− 0.21 V and at termination was 0.65 +/− 0.36 V. The safety factor for dislodgement was determined to be 15X during simulated exercise conditions. Conclusion: The nitinol tine fixation design enabled the implant of a self-contained pacemaker within the right ventricle and was effective in meeting the design requirements. Significance: This fixation technology provides a novel solution to enable the attachment of a transcatheter pacemaker directly within the heart.

Beschreibung: Presents a listing of the handling editors for this issue of the publication.

Beschreibung: Presents corrections to the article, ???Learning to detect vocal hyperfunction from ambulatory neck-surface acceleration features: Initial results for vocal fold nodules,??? (Ghassemi, M., et al), IEEE Trans. Biomed. Eng., vol. 61, no. 6, pp. 1668???1675, Jun. 2014.

Beschreibung: Fabricated vessel-mimetic microtubes are essential for delivering sufficient nutrient to engineered composite tissues. In this paper, vascular-like microtubes are engineered by automated assembly of donut-shaped micromodules that embed fibroblast cells. A microrobotic system is set up with dual manipulators of 30-nm positioning resolution under an optical microscope. The system assembles the micromodules by repeated single-step pick-up motions. This process is specifically designed to avoid human interference and ensure high reproducibility for automation. We optimized the single-step motion by calibrating the key parameters (the micromodule dimensions) in a force analysis. The optimal motion achieved a 98% pick-up success rate. The automated repetitive single-step assembly is achieved by an algorithm that acquires the 3-D location and tracks the micromanipulator without being affected by low contrast. The accuracy of the acquired 3-D location was experimentally determined as approximately 1 pixel (2 μm under 4× magnification), and the tracking under different observation conditions is proved effective. Finally, we automatically assembled microtubes at 6 micromodules/min, sufficiently fast for fabricating macroscopic vessel-mimetic substitutes in biological applications.

Beschreibung: Goal: This study tests and validates a new method to remove power line interference from monopolar EMGs detected by multichannel systems: the filtered virtual reference (FVR). FVR is an adaptation of the virtual reference (VR) method, which consists in referencing signals detected by each electrode in a grid to their spatial average. Signals may however be distorted with the VR approach, in particular when the skin region where the detection system is positioned does not cover the entire muscle. Methods: Simulated and experimental EMGs were used to compare the performance of FVR and VR in terms of interference reduction and distortion of monopolar signals referred to a remote reference. Results : Simulated data revealed the monopolar EMG signals processed with FVR were significantly less distorted than those filtered by VR. These results were similarly observed for experimental signals. Moreover, FVR method outperformed VR in removing power line interference when it was distributed unevenly across the signals of the grid. Conclusion: Key results demonstrated that FVR improves the VR method as it reduces interference while preserving the information content of monopolar signals. Significance: Although the actual distribution of motor unit action potential is represented in monopolar EMGs, collecting high quality monopolar signals is challenging. This study presents a possible solution to this issue; FVR provides undistorted monopolar signals with negligible interference and is insensitive to muscle architecture. It is therefore relevant for EMG applications benefiting from a clean monopolar detection (e.g., decomposition, control of prosthetic devices, motor unit number estimation).

Beschreibung: This study concentrates on finite-element-method (FEM)-based electroencephalography (EEG) forward simulation in which the electric potential evoked by neural activity in the brain is to be calculated at the surface of the head. The main advantage of the FEM is that it allows realistic modeling of tissue conductivity inhomogeneity. However, it is not straightforward to apply the classical model of a dipolar source with the FEM, due to its strong singularity and the resulting irregularity. The focus of this study is on comparing different methods to cope with this problem. In particular, we evaluate the accuracy of Whitney (Raviart–Thomas)-type dipole-like source currents compared to two reference dipole modeling methods: the St. Venant and partial integration approach. Common to all these methods is that they enable direct approximation of the potential field utilizing linear basis functions. In the present context, Whitney elements are particularly interesting, as they provide a simple means to model a divergence-conforming primary current vector field satisfying the square integrability condition. Our results show that a Whitney-type source model can provide simulation accuracy comparable to the present reference methods. It can lead to superior accuracy under optimized conditions with respect to both source location and orientation in a tetrahedral mesh. For random source orientations, the St. Venant approach turns out to be the method of choice over the interpolated version of the Whitney model. The overall moderate differences obtained suggest that practical aspects, such as the focality, should be prioritized when choosing a source model.

Beschreibung: This paper presents a wearable vital signs monitor at the ear. The monitor measures the electrocardiogram (ECG), ballistocardiogram (BCG), and photoplethysmogram (PPG) to obtain pre-ejection period (PEP), stroke volume (SV), cardiac output (CO), and pulse transit time (PTT). The ear is demonstrated as a natural anchoring point for the integrated sensing of physiological signals. All three signals measured can be used to obtain heart rate (HR). Combining the ECG and BCG allows for the estimation of the PEP, while combining the BCG and PPG allows for the measurement of PTT. Additionally, the J-wave amplitude of the BCG is correlated with the SV and, when combined with HR, yields CO. Results from a clinical human study on 13 subjects demonstrate this proof-of-concept device.

Beschreibung: Objective: We present the framework for wearable joint rehabilitation assessment following musculoskeletal injury. We propose a multimodal sensing (i.e., contact based and airborne measurement of joint acoustic emission) system for at-home monitoring. Methods: We used three types of microphones—electret, MEMS, and piezoelectric film microphones—to obtain joint sounds in healthy collegiate athletes during unloaded flexion/extension, and we evaluated the robustness of each microphone's measurements via: 1) signal quality and 2) within-day consistency. Results: First, air microphones acquired higher quality signals than contact microphones (signal-to-noise-and-interference ratio of 11.7 and 12.4 dB for electret and MEMS, respectively, versus 8.4 dB for piezoelectric). Furthermore, air microphones measured similar acoustic signatures on the skin and 5 cm off the skin (∼4.5× smaller amplitude). Second, the main acoustic event during repetitive motions occurred at consistent joint angles (intra-class correlation coefficient ICC(1, 1) = 0.94 and ICC(1, k) = 0.99). Additionally, we found that this angular location was similar between right and left legs, with asymmetry observed in only a few individuals. Conclusion: We recommend using air microphones for wearable joint sound sensing; for practical implementation of contact microphones in a wearable device, interface noise must be reduced. Importantly, we show that airborne signals can be measured consistently and that healthy left and right knees often produce a similar pattern in acoustic emissions. Significance: These proposed methods have the potential for enabling knee joint acoustics measurement outside the clinic/lab and permitting long-term monitoring of knee health for patients rehabilitating an acute knee joint injury.

Beschreibung: As telehealth applications emerge, the need for accurate and reliable biosignal quality indices has increased. One typical modality used in remote patient monitoring is the electrocardiogram (ECG), which is inherently susceptible to several different noise sources, including environmental (e.g., powerline interference), experimental (e.g., movement artifacts), and physiological (e.g., muscle and breathing artifacts). Accurate measurement of ECG quality can allow for automated decision support systems to make intelligent decisions about patient conditions. This is particularly true for in-home monitoring applications, where the patient is mobile and the ECG signal can be severely corrupted by movement artifacts. In this paper, we propose an innovative ECG quality index based on the so-called modulation spectral signal representation. The representation quantifies the rate of change of ECG spectral components, which are shown to be different from the rate of change of typical ECG noise sources. The proposed modulation spectral-based quality index, MS-QI, was tested on 1) synthetic ECG signals corrupted by varying levels of noise, 2) single-lead recorded data using the Hexoskin garment during three activity levels (sitting, walking, running), 3) 12-lead recorded data using conventional ECG machines (Computing in Cardiology 2011 dataset), and 4) two-lead ambulatory ECG recorded from arrhythmia patients (MIT-BIH Arrhythmia Database). Experimental results showed the proposed index outperforming two conventional benchmark quality measures, particularly in the scenarios involving recorded data in real-world environments.

Beschreibung: Platelet-rich plasma (PRP) is a volume of autologous plasma that has a higher platelet concentration above baseline. It has already been approved as a new therapeutic modality and investigated in clinics, such as bone repair and regeneration, and oral surgery, with low cost-effectiveness ratio. At present, PRP is mostly prepared using a centrifuge. However, this method has several shortcomings, such as long preparation time (30 min), complexity in operation, and contamination of red blood cells (RBCs). In this paper, a new PRP preparation approach was proposed and tested. Ultrasound waves (4.5 MHz) generated from piezoelectric ceramics can establish standing waves inside a syringe filled with the whole blood. Subsequently, RBCs would accumulate at the locations of pressure nodes in response to acoustic radiation force, and the formed clusters would have a high speed of sedimentation. It is found that the PRP prepared by the proposed device can achieve higher platelet concentration and less RBCs contamination than a commercial centrifugal device, but similar growth factor (i.e., PDGF-ββ). In addition, the sedimentation process under centrifugation and sonication was simulated using the Mason–Weaver equation and compared with each other to illustrate the differences between these two technologies and to optimize the design in the future. Altogether, ultrasound method is an effective method of PRP preparation with comparable outcomes as the commercially available centrifugal products.

Beschreibung: A new wireless sensor was designed, fabricated, and applied for in situ monitoring of tensile force at a wound site. The sensor was comprised of a thin strip of magnetoelastic material with its two ends connected to suture threads for securing the sensor across a wound repair site. Since the sensor was remotely interrogated by applying an ac magnetic field and capturing the resulting magnetic field, it did not require direct wire connections to an external device or internal battery for long-term use. Due to its magnetoelastic property, the application of a tensile force changed the magnetic permeability of the sensor, altering the amplitude of the measured magnetic field. This study presents two sensor designs: one for high and one for low-force ranges. A sensor was fabricated by directly adhering the magnetoelastic strip to the suture. This sensor showed good sensitivity at low force, but its response saturated at about 1.5 N. To monitor high tensile force, the magnetoelastic strip was attached to a metal strip for load sharing. The suture thread was attached to the both ends of the metal strip so only a fraction of the applied force was directed to the sensor, allowing it to exhibit good sensitivity even at 44.5 N. The sensor was applied to two ex vivo models: a sutured section of porcine skin and a whitetail deer Achilles tendon. The results demonstrate the potential for in vivo force monitoring at a wound repair site.

Beschreibung: This study presents a precise way to detect the third ( $S_{3}$ ) heart sound, which is recognized as an important indication of heart failure, based on nonlinear single decomposition and time–frequency localization. The detection of the $S_{3}$ is obscured due to its significantly low energy and frequency. Even more, the detected $S_{3}$ may be misunderstood as an abnormal second heart sound with a fixed split, which was not addressed in the literature. To detect such $S_{3}$ , the Hilbert vibration decomposition method is applied to decompose the heart sound into a certain number of subcomponents while intactly preserving the phase information. Thus, the time information of all of the decomposed components are unchanged, which further expedites the identification and localization of any module/section of a signal properly. Next, the proposed localization step is applied to the decomposed subcomponents by using smoothed pseudo Wigner–Ville distribution followed by the reassignment method. Finally, based on the positional information, the $S_{3}$ is distinguished and confirmed by measuring time delays between the $S_{2}$ and $S_{3}$ . In total, 82 sets of cardiac cycles collected from different databases including Texas Heart Institute database are examined for evaluation of the proposed method. The result analysis shows that the proposed method can detect the $S_{3}$ correctly, even when the - ormalized temporal energy of $S_{3}$ is larger than 0.16, and the frequency of those is larger than 34 Hz. In a performance analysis, the proposed method demonstrates that the accuracy rate of $S_{3}$ detection is as high as 93.9%, which is significantly higher compared with the other methods. Such findings prove the robustness of the proposed idea for detecting substantially low-energized $S_{3}$ .

Beschreibung: Electromagnetic (EM) tracking systems are highly susceptible to field distortion. The interference can cause measurement errors up to a few centimeters in clinical environments, which limits the reliability of these systems. Unless corrected for, this measurement error imperils the success of clinical procedures. It is therefore fundamental to dynamically calibrate EM tracking systems and compensate for measurement error caused by field distorting objects commonly present in clinical environments. We propose to combine a motion model with observations of redundant EM sensors and compensate for field distortions in real time. We employ a simultaneous localization and mapping technique to accurately estimate the pose of the tracked instrument while creating the field distortion map. We conducted experiments with six degrees-of-freedom motions in the presence of field distorting objects in research and clinical environments. We applied our approach to improve the EM tracking accuracy and compared our results to a conventional sensor fusion technique. Using our approach, the maximum tracking error was reduced by 67% for position measurements and by 64% for orientation measurements. Currently, clinical applications of EM trackers are hampered by the adverse distortion effects. Our approach introduces a novel method for dynamic field distortion compensation, independent from preoperative calibrations or external tracking devices, and enables reliable EM navigation for potential applications.

Beschreibung: A feasibility study on a new technique capable of monitoring localized sweat rate is explored in this paper. Wearable devices commonly used in clinical practice for sweat sampling (i.e., Macroducts) were positioned on the body of an athlete whose sweat rate was then monitored during cycling sessions. The position at which the sweat fills the Macroduct was indicated by a contrasting marker and captured via a series of time-stamped photos or a video recording of the device during an exercise period. Given that the time of each captured image/frame is known (either through time stamp on photos or the constant frame rate of the video capture), it was, therefore, possible to estimate the sweat flow rate through a simple calibration model. The importance of gathering such valuable information is described, together with the results from a number of exercise trials to investigate the viability of this approach.

Beschreibung: Objective: A novel high-precision approach [lifetime-decomposition measurement (LTDM)] for the assessment of the glomerular filtration rate (GFR) based on clearance measurements of exogenous filtration marker. Methods: The time-correlated single photon counting (TCSPC) acquisition in combination with a new decomposition method allows the separation of signal and background from transcutaneous measurements of GFR. Results: The performance of LTDM is compared versus the commercially available NIC-kidney patch-based system for transcutaneous GFR measurement. Measurements are performed in awake Sprague Dawley (SD) rats. Using the standard concentration required for the NIC-kidney system [7-mg/100-g body weight (b.w.) FITC-Sinistrin] as reference, the mean difference (bias) of the elimination curves GFR between LTDM and NIC-kidney was 4.8%. On the same animal and same day, the capability of LTDM to measure GFR with a FITC-Sinistrin dose reduced by a factor of 200 (35-μg/100-g b.w.) was tested as well. The mean differences (half lives with low dose using LTDM compared with those using first, the NIC-Kidney system and its standard concentration, and second, LTDM with the same concentration as for the NIC-Kidney system) were 3.4% and 4.5%, respectively. Conclusion: We demonstrate that with the LTDM strategy substantial reductions in marker concentrations are possible at the same level of accuracy. Significance: LTDM aims to resolve the issue of the currently necessary large doses of fluorescence tracer required for transcutaneous GFR measurement. Due to substantially less influences from autofluorescence and artifacts, the proposed method outperforms other existing techniques for accurate percutaneous organ function measurement.

Beschreibung: Classic brain–machine interface (BMI) approaches decode neural signals from the brain responsible for achieving specific motor movements, which subsequently command prosthetic devices. Brain activities adaptively change during the control of the neuroprosthesis in BMIs, where the alteration of the preferred direction and the modulation of the gain depth are observed. The static neural tuning models have been limited by fixed codes, resulting in a decay of decoding performance over the course of the movement and subsequent instability in motor performance. To achieve stable performance, we propose a dual sequential Monte Carlo adaptive point process method, which models and decodes the gradually changing modulation depth of individual neuron over the course of a movement. We use multichannel neural spike trains from the primary motor cortex of a monkey trained to perform a target pursuit task using a joystick. Our results show that our computational approach successfully tracks the neural modulation depth over time with better goodness-of-fit than classic static neural tuning models, resulting in smaller errors between the true kinematics and the estimations in both simulated and real data. Our novel decoding approach suggests that the brain may employ such strategies to achieve stable motor output, i.e., plastic neural tuning is a feature of neural systems. BMI users may benefit from this adaptive algorithm to achieve more complex and controlled movement outcomes.

Beschreibung: Objective: This work evaluates current 3-D image registration tools on clinically acquired abdominal computed tomography (CT) scans. Methods: Thirteen abdominal organs were manually labeled on a set of 100 CT images, and the 100 labeled images (i.e., atlases) were pairwise registered based on intensity information with six registration tools (FSL, ANTS-CC, ANTS-QUICK-MI, IRTK, NIFTYREG, and DEEDS). The Dice similarity coefficient (DSC), mean surface distance, and Hausdorff distance were calculated on the registered organs individually. Permutation tests and indifference-zone ranking were performed to examine the statistical and practical significance, respectively. Results: The results suggest that DEEDS yielded the best registration performance. However, due to the overall low DSC values, and substantial portion of low-performing outliers, great care must be taken when image registration is used for local interpretation of abdominal CT. Conclusion: There is substantial room for improvement in image registration for abdominal CT. Significance: All data and source code are available so that innovations in registration can be directly compared with the current generation of tools without excessive duplication of effort.

Beschreibung: Goal : In K-edge tomographic imaging with photon counting detectors, the energy window width of photon counting detectors significantly affects the signal-to-noise ratio (SNR) of measured intensity data and the contrast-to-noise ratio (CNR) of reconstructed images. In this paper, we present an optimization method to determine an optimal window width around a K-edge for optimal SNR and CNR. Methods : An objective function is designed to describe SNR of the projection data based on the Poisson distribution of detected X-ray photons. Then, a univariate optimization method is applied to obtain an X-ray energy window width. Results : Numerical simulations are performed to evaluate the proposed method, and the results show that the optimal energy window width obtained from the proposed method produces not only optimal SNR data in the projection domain but also optimal CNR values in the image domain. Conclusion : The proposed method in the projection domain can determine an optimal energy window width for X-ray photon counting imaging, and achieve optimality in both projection and image domains. Significance : Our study provides a practical way to determine the optimal energy window width of photon counting detectors, which helps improve contrast resolution for X-ray K-edge tomographic imaging.

Beschreibung: Objective: The propagation of electrophysiological activity measured by multichannel devices could have significant clinical implications. Gastric slow waves normally propagate along longitudinal paths that are evident in recordings of serosal potentials and transcutaneous magnetic fields. We employed a realistic model of gastric slow wave activity to simulate the transabdominal magnetogastrogram (MGG) recorded in a multichannel biomagnetometer and to determine characteristics of electrophysiological propagation from MGG measurements. Methods: Using MGG simulations of slow wave sources in a realistic abdomen (both superficial and deep sources) and in a horizontally-layered volume conductor, we compared two analytic methods (second-order blind identification, SOBI and surface current density, SCD) that allow quantitative characterization of slow wave propagation. We also evaluated the performance of the methods with simulated experimental noise. The methods were also validated in an experimental animal model. Results: Mean square errors in position estimates were within 2 cm of the correct position, and average propagation velocities within 2 mm/s of the actual velocities. SOBI propagation analysis outperformed the SCD method for dipoles in the superficial and horizontal layer models with and without additive noise. The SCD method gave better estimates for deep sources, but did not handle additive noise as well as SOBI. Conclusion: SOBI-MGG and SCD-MGG were used to quantify slow wave propagation in a realistic abdomen model of gastric electrical activity. Significance: These methods could be generalized to any propagating electrophysiological activity detected by multichannel sensor arrays.

Beschreibung:   Goal : This study aims at a systematic assessment of five computational models of a birdcage coil for magnetic resonance imaging (MRI) with respect to accuracy and computational cost. Methods : The models were implemented using the same geometrical model and numerical algorithm, but different driving methods (i.e., coil “defeaturing”). The defeatured models were labeled as: specific ( S2 ), generic ( G32 , G16 ), and hybrid ( H16, $hbox{H16}_{{rm fr}text{-}{rm forced}}$ ). The accuracy of the models was evaluated using the “symmetric mean absolute percentage error” (“SMAPE”), by comparison with measurements in terms of frequency response, as well as electric ( $|{vec E}|$ ) and magnetic ( $| {vec B} |$ ) field magnitude. Results : All the models computed the $| {vec B} |$ within 35% of the measurements, only the S2 , G32, and H16 were able to accurately model the $|{vec E}|$ inside the phantom with a maximum SMAPE of 16%. Outside the phantom, only the S2 showed a SMAPE lower than 11%. Conclusions : Results showed that assessing the accuracy of $| {vec B} |$ based only on comparison along the central longitudinal line of the coil can be misleading. Generic or hybrid coils — when properly modeling the currents along the rings/rungs — were sufficient to accur- tely reproduce the fields inside a phantom while a specific model was needed to accurately model $|{vec E}|$ in the space between coil and phantom. Significance : Computational modeling of birdcage body coils is extensively used in the evaluation of radiofrequency-induced heating during MRI. Experimental validation of numerical models is needed to determine if a model is an accurate representation of a physical coil.

Beschreibung: Objective: The objective of this research was to develop a bioimpedance platform for monitoring fluid volume in residual limbs of people with trans-tibial limb loss using prostheses. Methods: A customized multifrequency current stimulus profile was sent to thin flat electrodes positioned on the thigh and distal residual limb. The applied current signal and sensed voltage signals from four pairs of electrodes located on the anterior and posterior surfaces were demodulated into resistive and reactive components. An established electrical model (Cole) and segmental limb geometry model were used to convert results to extracellular and intracellular fluid volumes. Bench tests and testing on amputee participants were conducted to optimize the stimulus profile and electrode design and layout. Results: The proximal current injection electrode needed to be at least 25 cm from the proximal voltage sensing electrode. A thin layer of hydrogel needed to be present during testing to ensure good electrical coupling. Using a burst duration of 2.0 ms, intermission interval of 100 μs, and sampling delay of 10 μs at each of 24 frequencies except 5 kHz, which required a 200-μs sampling delay, the system achieved a sampling rate of 19.7 Hz. Conclusion: The designed bioimpedance platform allowed system settings and electrode layouts and positions to be optimized for amputee limb fluid volume measurement. Significance: The system will be useful toward identifying and ranking prosthetic design features and participant characteristics that impact residual limb fluid volume.

Beschreibung: Surface electromyography (sEMG) has been the predominant method for sensing electrical activity for a number of applications involving muscle–computer interfaces, including myoelectric control of prostheses and rehabilitation robots. Ultrasound imaging for sensing mechanical deformation of functional muscle compartments can overcome several limitations of sEMG, including the inability to differentiate between deep contiguous muscle compartments, low signal-to-noise ratio, and lack of a robust graded signal. The objective of this study was to evaluate the feasibility of real-time graded control using a computationally efficient method to differentiate between complex hand motions based on ultrasound imaging of forearm muscles. Dynamic ultrasound images of the forearm muscles were obtained from six able-bodied volunteers and analyzed to map muscle activity based on the deformation of the contracting muscles during different hand motions. Each participant performed 15 different hand motions, including digit flexion, different grips (i.e., power grasp and pinch grip), and grips in combination with wrist pronation. During the training phase, we generated a database of activity patterns corresponding to different hand motions for each participant. During the testing phase, novel activity patterns were classified using a nearest neighbor classification algorithm based on that database. The average classification accuracy was 91%. Real-time image-based control of a virtual hand showed an average classification accuracy of 92%. Our results demonstrate the feasibility of using ultrasound imaging as a robust muscle–computer interface. Potential clinical applications include control of multiarticulated prosthetic hands, stroke rehabilitation, and fundamental investigations of motor control and biomechanics.

Beschreibung: We have been developing an automated cardiovascular drug infusion system for simultaneous control of arterial pressure (AP), cardiac output (CO), and left atrial pressure (P LA ) in decompensated heart failure (HF). In our prototype system, CO and P LA were measured invasively through thoracotomy. Furthermore, the control logic inevitably required use of inotropes to improve hemodynamics, which was not in line with clinical HF guidelines. The goal of this study was to solve these problems and develop a clinically feasible system. We integrated to the system minimally invasive monitors of CO and pulmonary capillary wedge pressure (PCWP, surrogates for P LA ) that we developed recently. We also redesigned the control logic to reduce the use of inotrope. We applied the newly developed system to nine dogs with decompensated HF. Once activated, our system started to control the infusion of vasodilator and diuretics in all the animals. Inotrope was not infused in three animals, and infused at minimal doses in six animals that were intolerant of vasodilator infusion alone. Within 50 min, our system controlled AP, CO, and PCWP to their respective targets accurately. Pulmonary artery catheterization confirmed optimization of hemodynamics (AP, from 98 ± 4 to 74 ± 11 mmHg; CO, from 2.2 ± 0.5 to 2.9 ± 0.3 L·min −1 ·m −2 ; PCWP, from 27.0 ± 6.6 to 13.8 ± 3.0 mmHg). In a minimally invasive setting while reducing the use of inotrope, our system succeeded in automatically optimizing the overall hemodynamics in canine models of HF. The present results pave the way for clinical application of our automated drug infusion system.

Beschreibung: Image registration is a key problem in a variety of applications, such as computer vision, medical image processing, pattern recognition, etc., while the application of registration is limited by time consumption and the accuracy in the case of large pose differences. Aimed at these two kinds of problems, we propose a fast rotation-free feature-based rigid registration method based on our proposed accelerated-NSIFT and GMM registration-based parallel optimization (PO-GMMREG). Our method is accelerated by using the GPU/CUDA programming and preserving only the location information without constructing the descriptor of each interest point, while its robustness to missing correspondences and outliers is improved by converting the interest point matching to Gaussian mixture model alignment. The accuracy in the case of large pose differences is settled by our proposed PO-GMMREG algorithm by constructing a set of initial transformations. Experimental results demonstrate that our proposed algorithm can fast rigidly register 3-D medical images and is reliable for aligning 3-D scans even when they exhibit a poor initialization.

Beschreibung: Glaucoma is a neurological disorder leading to blindness initially through the loss of retinal ganglion cells, followed by loss of neurons higher in the visual system. Some work has been undertaken to develop prostheses for glaucoma patients targeting tissues along the visual pathway, including the lateral geniculate nucleus (LGN) of the thalamus, but especially the visual cortex. This review makes the case for a visual prosthesis that targets the LGN. The compact nature and orderly structure of this nucleus make it a potentially better target to restore vision than the visual cortex. Existing research for the development of a thalamic visual prosthesis will be discussed along with the gaps that need to be addressed before such a technology could be applied clinically, as well as the challenge posed by the loss of LGN neurons as glaucoma progresses.

Beschreibung: Alterations in the health of muscles can be evaluated through the use of electrical impedance myography (EIM). To date, however, nearly all work in this field has relied upon the measurement of muscle at rest. To provide an insight into the contractile mechanisms of healthy and disease muscle, we evaluated the alterations in the spectroscopic impedance behavior of muscle during the active process of muscle contraction. The gastrocnemii from a total of 13 mice were studied (five wild type, four muscular dystrophy animals, and four amyotrophic lateral sclerosis animals). Muscle contraction was induced via monophasic current pulse stimulation of the sciatic nerve. Simultaneously, multisine EIM (1 kHz to 1 MHz) and force measurements of the muscle were performed. Stimulation was applied at three different rates to produce mild, moderate, and strong contractions. We identified changes in both single and multifrequency data, as assessed by the Cole impedance model parameters. The processes of contraction and relaxation were clearly identified in the impedance spectra and quantified via derivative plots. Reductions in the center frequency ${f}_{mathrm{c}}$ were observed during the contraction consistent with the increasing muscle fiber diameter. Different EIM stimulation rate-dependencies were also detected across the three groups of animals.

Beschreibung: We describe a novel motion-tracking system, called MASK (magnetoarticulography for the assessment of speech kinematics) designed to track detailed orofacial movements during magnetoencephalographic (MEG) measures of human brain activity. A three-dimensional electromagnetic-tracking method was employed using lightweight coils energized with high-frequency sinusoidal currents, creating magnetic dipoles that can be continuously localized by the MEG sensors. In addition to being compatible with commercial MEG devices, this system has advantages over optical or video methods in that it can record nonline-of-sight movements (e.g., tongue movements) and advantages over surface electromyographic recordings, which are prone to movement-related artifacts and signal crosstalk. Static and dynamic tracking accuracy was evaluated using calibration devices with fixed intercoil distances. MEG data were collected in two healthy adult volunteers to test feasibility of tracking movements during tongue and facial movement, and during overt speech. The MASK system was shown to have sufficient static and dynamic accuracy to track orofacial movements within the MEG helmet. We successfully acquired spatially precise kinematic information time-locked to brain activity with high temporal resolution. We demonstrated successful tracking of oromotor and speech movements together with brain activity using the MASK system. This novel technology will provide an innovative tool in support of research and clinical applications for individuals with speech and other oromotor disorders.

Beschreibung: Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked autoencoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework, image registration experiments were conducted on 7.0-T brain MR images. In all experiments, the results showed that the new image registration framework consistently demonstrated more accurate registration results when compared to state of the art.

Beschreibung: Embryo biopsies are routinely performed for preimplantation genetic diagnosis (PGD). In order to avoid blastomere membrane rupture and cell lysis, correct selection of a suitable dissection position on the zona pellucida (ZP) is necessary. Although, the technology for automated cell manipulation has advanced greatly over the past decade, fully automated embryo biopsy in PGD has not been realized yet. Automated PGD may ultimately set a new clinical standard that improves the consistency of outcomes, increases cell survival rates, flattens the learning curve of the manual procedure, and reduces the effects of human fatigue. In this paper, we present the first approach to automatically select a suitable ZP dissection position prior to embryo biopsy from a single focused embryo image based on edge detection. The proposed method consists of a technique that estimates the elliptical ZP boundaries and another two techniques that select the suitable position for ZP dissection. These techniques achieved success rates of 96%, 94%, and 94% respectively. In addition, the proposed ZP boundary estimation technique has the potential to perform ZP thickness variation (ZPTV) test and other ZP morphology measurements with further improvement in the future. Our methods provide a starting point for fast position selection prior to automatic embryo biopsy.

Beschreibung: Goal: The purpose of this study is to evaluate the usefulness of the boosting algorithm AdaBoost (AB) in the context of the sleep apnea-hypopnea syndrome (SAHS) diagnosis. Methods: We characterize SAHS in single-channel airflow (AF) signals from 317 subjects by the extraction of spectral and nonlinear features. Relevancy and redundancy analyses are conducted through the fast correlation-based filter to derive the optimum set of features among them. These are used to feed classifiers based on linear discriminant analysis (LDA) and classification and regression trees (CART). LDA and CART models are sequentially obtained through AB, which combines their performances to reach higher diagnostic ability than each of them separately. Results: Our AB-LDA and AB-CART approaches showed high diagnostic performance when determining SAHS and its severity. The assessment of different apnea-hypopnea index cutoffs using an independent test set derived into high accuracy: 86.5% (5 events/h), 86.5% (10 events/h), 81.0% (15 events/h), and 83.3% (30 events/h). These results widely outperformed those from logistic regression and a conventional event-detection algorithm applied to the same database. Conclusion: Our results suggest that AB applied to data from single-channel AF can be useful to determine SAHS and its severity. Significance: SAHS detection might be simplified through the only use of single-channel AF data.

Beschreibung: Objective: Lumpectomy, breast conserving tumor excision, is the standard surgical treatment in early stage breast cancer. A common problem with lumpectomy is that the tumor may not be completely excised, and additional surgery becomes necessary. We investigated if a surgical navigation system using intraoperative ultrasound improves the outcomes of lumpectomy and if such a system can be implemented in the clinical environment. Methods: Position sensors were applied on the tumor localization needle, the ultrasound probe, and the cautery, and 3-D navigation views were generated using real-time tracking information. The system was tested against standard wire-localization procedures on phantom breast models by eight surgical residents. Clinical safety and feasibility was tested in six palpable tumor patients undergoing lumpectomy by two experienced surgical oncologists. Results: Navigation resulted in significantly less tissue excised compared to control procedures (10.3 ± 4.4 versus 18.6 ± 8.7 g, p = 0.01) and lower number of tumor-positive margins (1/8 versus 4/8) in the phantom experiments. Excision-tumor distance was also more consistently outside the tumor margins with navigation in phantoms. The navigation system has been successfully integrated in an operating room, and user experience was rated positively by surgical oncologists. Conclusion: Electromagnetic navigation may improve the outcomes of lumpectomy by making the tumor excision more accurate. Significance: Breast cancer is the most common cancer in women, and lumpectomy is its first choice treatment. Therefore, the improvement of lumpectomy outcomes has a significant impact on a large patient population.

Beschreibung: Goal: The purpose of this paper is to develop a classification method that combines both spectral and spatial information for distinguishing cancer from healthy tissue on hyperspectral images in an animal model. Methods: An automated algorithm based on a minimum spanning forest (MSF) and optimal band selection has been proposed to classify healthy and cancerous tissue on hyperspectral images. A support vector machine classifier is trained to create a pixel-wise classification probability map of cancerous and healthy tissue. This map is then used to identify markers that are used to compute mutual information for a range of bands in the hyperspectral image and thus select the optimal bands. An MSF is finally grown to segment the image using spatial and spectral information. Conclusion: The MSF based method with automatically selected bands proved to be accurate in determining the tumor boundary on hyperspectral images. Significance: Hyperspectral imaging combined with the proposed classification technique has the potential to provide a noninvasive tool for cancer detection.

Beschreibung:   Objective: This work aimed to find and evaluate a new method for detecting errors in continuous brain–computer interface (BCI) applications. Instead of classifying errors on a single-trial basis, the new method was based on multiple events (MEs) analysis to increase the accuracy of error detection. Methods: In a BCI-driven car game, based on motor imagery (MI), discrete events were triggered whenever subjects collided with coins and/or barriers. Coins counted as correct events, whereas barriers were errors. This new method, termed ME method, combined and averaged the classification results of single events (SEs) and determined the correctness of MI trials, which consisted of event sequences instead of SEs. The benefit of this method was evaluated in an offline simulation. In an online experiment, the new method was used to detect erroneous MI trials. Such MI trials were discarded and could be repeated by the users. Results: We found that, even with low SE error potential (ErrP) detection rates, feasible accuracies can be achieved when combining MEs to distinguish erroneous from correct MI trials. Online, all subjects reached higher scores with error detection than without, at the cost of longer times needed for completing the game. Conclusion: Findings suggest that ErrP detection may become a reliable tool for monitoring continuous states in BCI applications when combining MEs. Significance: This paper demonstrates a novel technique for detecting errors in online continuous BCI applications, which yields promising results even with low single-trial detection rates.

Beschreibung: Goal: Target-controlled infusion of anesthesia is a closed-loop automated drug delivery method with a computer-aided control. Our goal is to design and test an automated drug infusion platform for propofol delivery in total intravenous anesthesia (TIVA) administration. Methods: In the proposed method, a dilution chamber with first-order exponential decay characteristics was used to model the pharmacodynamics decay of a drug. The dilution chamber was connected to a flow system through an electrochemical cell containing an organic film-coated glassy carbon electrode as working electrode. To set up the feedback-controlled delivery platform and optimize its parameters, ferrocene methanol was used as a proxy of the propofol. The output signal of the sensor was connected to a PI controller, which prompted a syringe pump for feedback-controlled drug infusion. Results: The result is a bench-top drug infusion platform to automate the delivery of a propofol based on the measurement of concentration with an organic film-coated voltammetric sensor. Conclusion: To evaluate the performance characteristics of the infusion platform, the propofol concentration in the dilution chamber was monitored with the organic film-coated glassy carbon electrode and the difference between the set and measured concentrations was assessed. The feasibility of measurement-based feedback-controlled propofol delivery is demonstrated and confirmed. Significance: This platform will contribute to high-performance TIVA application of intravenous propofol anesthesia.

Beschreibung: Involuntary muscle activations are diagnostic indicators of neurodegenerative pathologies. Currently detected by invasive intramuscular electromyography, these muscle twitches are found to be visible in ultrasound images. We present an automated computational approach for the detection of muscle twitches, and apply this to two muscles in healthy and motor neuron disease-affected populations. The technique relies on motion tracking within ultrasound sequences, extracting local movement information from muscle. A statistical analysis is applied to classify the movement, either as noise or as more coherent movement indicative of a muscle twitch. The technique is compared to operator identified twitches, which are also assessed to ensure operator agreement. We find that, when two independent operators manually identified twitches, higher interoperator agreement (Cohen's $kappa$ ) occurs when more twitches are present ( $kappa = 0.94$ ), compared to a lower number ( $kappa = 0.49$ ). Finally, we demonstrate, via analysis of receiver operating characteristics, that our computational technique detects muscle twitches across the entire dataset with a high degree of accuracy ( $0.83〈$ accuracy $〈0.96$ ).

Beschreibung: Goal: This paper presents a fast and accurate patient-specific electrocardiogram (ECG) classification and monitoring system. Methods: An adaptive implementation of 1-D convolutional neural networks (CNNs) is inherently used to fuse the two major blocks of the ECG classification into a single learning body: feature extraction and classification. Therefore, for each patient, an individual and simple CNN will be trained by using relatively small common and patient-specific training data, and thus, such patient-specific feature extraction ability can further improve the classification performance. Since this also negates the necessity to extract hand-crafted manual features, once a dedicated CNN is trained for a particular patient, it can solely be used to classify possibly long ECG data stream in a fast and accurate manner or alternatively, such a solution can conveniently be used for real-time ECG monitoring and early alert system on a light-weight wearable device. Results: The results over the MIT-BIH arrhythmia benchmark database demonstrate that the proposed solution achieves a superior classification performance than most of the state-of-the-art methods for the detection of ventricular ectopic beats and supraventricular ectopic beats. Conclusion: Besides the speed and computational efficiency achieved, once a dedicated CNN is trained for an individual patient, it can solely be used to classify his/her long ECG records such as Holter registers in a fast and accurate manner. Significance: Due to its simple and parameter invariant nature, the proposed system is highly generic, and, thus, applicable to any ECG dataset.

Beschreibung: The accredited biomarker alpha-fetoprotein (AFP) offers limited sensitivity and specificity in the early detection of hepatocellular carcinoma (HCC). To improve the screening performance, des-gamma-carboxy prothrombin (DCP) has been identified as another promising biomarker of HCC, combined with AFP biomarkers. The results of the commercial optical enzyme-linked immunosorbent assay (ELISA) kit easily have the interference problem due to the optical methodology. The immunomagnetic reduction (IMR) assay based on the magnetic measurement was utilized to assay DCP biomarkers without the excellent antiinterference performances. A DCP magnetic reagent, composed of iron-oxide (Fe 3 O 4 ) magnetic nanoparticles coated with anti-DCP antibodies solved in phosphoryl-buffer solution, was synthesized and characterized. In the test of standard DCP antigens, superior antiinterference and sensitivity than optical ELISA were proved. In the animal test, the results indicate good agreement between the IMR assay findings and the tumor sizes of HCC rats at all time points after the HCC implantation. The feasibility of the developed DCP magnetic reagent with the IMR for the detection of DCP is verified, and demonstrates the high potential for future clinical applications.

Beschreibung: Goal: Minimally invasive continuous glucose monitoring (CGM) sensors measure in the subcutis a current signal, which is converted into interstitial glucose (IG) concentration by a calibration process periodically updated using fingerstick blood glucose (BG) references. Though important in diabetes management, CGM sensors still suffer from accuracy problems. Here, we propose a new online calibration method improving accuracy of CGM glucose profiles with respect to manufacturer calibration. Method: The proposed method fits CGM current signal against the BG references collected twice a day for calibration purposes, by a time-varying calibration function whose parameters are identified in a Bayesian framework using a priori second-order statistical knowledge. The distortion introduced by BG-to-IG kinetics is compensated before parameter identification via nonparametric deconvolution. Results: The method was tested on a database where 108 CGM signals were collected for 7 days by the Dexcom G4 Platinum sensor. Results show the new method drives to a statistically significant accuracy improvement as measured by three commonly used metrics: mean absolute relative difference reduced from 12.73% to 11.47%; percentage of accurate glucose estimates increased from 82.00% to 89.19%; and percentage of values falling in the “A” zone of the Clark error grid increased from 82.22% to 88.86%. Conclusion: The new calibration method significantly improves CGM glucose profiles accuracy with respect to manufacturer calibration. Significance: The proposed algorithm provides a real-time improvement of CGM accuracy, which can be crucial in several CGM-based applications, including the artificial pancreas, thus providing a potential great impact in the diabetes technology research community.

Beschreibung: Provides a listing of the editors, board members, and current staff for this issue of the publication.

Beschreibung: In some biomedical applications such as wireless capsule endoscopy, the localization of an in-body radio-frequency (RF) source is important for the positioning of any abnormality inside the gastrointestinal tract. With knowledge of the location, therapeutic operations can be performed precisely at the position of the abnormality. Electrical properties (relative permittivity and conductivity) of the tissues and their distribution are utilized to estimate the position. This paper presents a method for the localization of an in-body RF source based on microwave imaging. The electrical properties of the tissues and their distribution at 403.5 MHz are found from microwave imaging and the position of an RF source is then estimated based on the image. The method is applied on synthetic noisy data, obtained after the addition of white Gaussian noise to simulated data of a simple circular phantom, and a realistic phantom in a 2-D case. The root-mean-square of the error distance between the actual and the estimated position is found to be within 10 and 4 mm for the circular and the realistic phantom, respectively, showing the capability of the proposed algorithm to work with a good accuracy even in the presence of noise for the localization of the in-body RF source.

Beschreibung: Recent advances in high-density surface electromyogram (EMG) decomposition have made it a feasible task to discriminate single motor unit activity from surface EMG interference patterns, thus providing a noninvasive approach for examination of motor unit control properties. In the current study, we applied high-density surface EMG recording and decomposition techniques to assess motor unit firing behavior alterations poststroke. Surface EMG signals were collected using a 64-channel 2-D electrode array from the paretic and contralateral first dorsal interosseous (FDI) muscles of nine hemiparetic stroke subjects at different isometric discrete contraction levels between 2 to 10 N with a 2 N increment step. Motor unit firing rates were extracted through decomposition of the high-density surface EMG signals and compared between paretic and contralateral muscles. Across the nine tested subjects, paretic FDI muscles showed decreased motor unit firing rates compared with contralateral muscles at different contraction levels. Regression analysis indicated a linear relation between the mean motor unit firing rate and the muscle contraction level for both paretic and contralateral muscles (p 〈 0.001), with the former demonstrating a lower increment rate (0.32 pulses per second (pps)/N) compared with the latter (0.67 pps/N). The coefficient of variation (averaged over the contraction levels) of the motor unit firing rates for the paretic muscles (0.21 ± 0.012) was significantly higher than for the contralateral muscles (0.17 ± 0.014) (p 〈 0.05). This study provides direct evidence of motor unit firing behavior alterations poststroke using surface EMG, which can be an important factor contributing to hemiparetic muscle weakness.

Beschreibung: A new adaptive beamforming algorithm for imaging via small-aperture 1-D ultrasonic-phased arrays through composite layered structures is reported. Such structures cause acoustic phase aberration and wave refraction at undulating interfaces and can lead to significant distortion of an ultrasonic field pattern produced by conventional beamforming techniques. This distortion takes the form of defocusing the ultrasonic field transmitted through the barrier and causes loss of resolution and overall degradation of image quality. To compensate for the phase aberration and the refractional effects, we developed and examined an adaptive beamforming algorithm for small-aperture linear-phased arrays. After accurately assessing the barrier's local geometry and sound speed, the method calculates a new timing scheme to refocus the distorted beam at its original location. As a tentative application, implementation of this method for trans-skull imaging of certain types of head injuries through human skull is discussed. Simulation and laboratory results of applying the method on skull-mimicking phantoms are presented. Correction of up to 2.5 cm focal point displacement at up to 10 cm depth under our skull phantom is demonstrated. Quantitative assessment of the method in a variety of temporal focusing scenarios is also reported. Overall temporal deviation on the order of a few nanoseconds was observed between the simulated and experimental results. The single-point adaptive focusing results demonstrate strong potential of our approach for diagnostic imaging through intact human skull. The algorithms were implemented on an ultrasound advanced open-platform controlling 64 active elements on a 128-element phased array.

Beschreibung: RNA secondary structures are vital in determining the 3-D structures of noncoding RNA molecules, which in turn affect their functions. Computational RNA secondary structure alignment and analysis are biologically significant, because they help identify numerous functionally important motifs. Unfortunately, many analysis methods suffer from computational intractability in the presence of pseudoknots. The conversion of knotted to knot-free secondary structures is an essential preprocessing step, and is regarded as pseudoknot removal. Although exact methods have been proposed for this task, their computational complexities are undetermined, and so their efficiencies in processing complex pseudoknots are currently unknown. We transformed the pseudoknot removal problem into a circle graph maximum weight independent set (MWIS) problem, in which each MWIS represents a unique optimal deknotted structure. An existing circle graph MWIS algorithm was extended to report either single or all solutions. Its time complexity depends on the number of MWISs, and is guaranteed to report one solution in polynomial time. Experimental results suggest that our extended algorithm is much more efficient than the state-of-the-art tool. We also devised a novel concept called the structural scoring function, and investigated its effectiveness in more accurate solution candidate selection for a certain criteria.

Beschreibung: Goal: The aim of this study was to investigate the normalization of the intrinsic functional activity and connectivity of TS adolescents before and after the cranial electrotherapy stimulation (CES) with alpha stim device. Methods: We performed resting-state functional magnetic resonance imaging on eight adolescents before and after CES with mean age of about nine-years old who had Tourette's syndrome with moderate to severe tics symptom. Independent component analysis (ICA) with hierarchical partner matching method was used to examine the functional connectivity between regions within cortico-striato-thalamo-cortical (CSTC) circuit. Granger causality was used to investigate effective connectivity among these regions detected by ICA. We then performed pattern classification on independent components with significant group differences that served as endophenotype markers to distinguish the adolescents between TS and the normalized ones after CES. Results: Results showed that TS adolescents after CES treatment had stronger functional activity and connectivity in anterior cingulate cortex (ACC), caudate and posterior cingulate cortex while had weaker activity in supplementary motor area within the motor pathway compared with TS before CES. Conclusion: The results suggest that the functional activity and connectivity in motor pathway was suppressed while activities in the control portions within CSTC loop including ACC and caudate were increased in TS adolescents after CES compared with adolescents before CES. Significance: The normalization of the balance between motor and control portions of the CSTC circuit may result in the recovery of TS adolescents.

Beschreibung: Focused ultrasound with microbubbles is an emerging technique for blood–brain barrier opening. Here, a comprehensive theoretical model of a bubble-fluid-vessel system has been developed which accounts for the bubble's nonspherical oscillations inside a microvessel, and its resulting acoustic emissions. Numerical simulations of unbound and confined encapsulated bubbles were performed to evaluate the effect of the vessel wall on acoustic emissions and vessel wall stresses. Using a Marmottant shell model, the normalized second harmonic to fundamental emissions first decreased as a function of pressure (>50 kPa) until reaching a minima (“transition point”) at which point they increased. The transition point of unbound compared to confined bubble populations occurred at different pressures and was associated with an accompanying increase in shear and circumferential wall stresses. As the wall stresses depend on the bubble to vessel wall distance, the stresses were evaluated for bubbles with their wall at a constant distance to a flat wall. As a result, the wall stresses were bubble size and frequency dependent and the peak stress values induced by bubbles larger than resonance remained constant versus frequency at a constant mechanical index.

Beschreibung: Although patients undergoing hemodialysis treatment often suffer from cardiovascular disease, monitoring of cardiac rhythm is not performed on a routine basis. Without requiring any extra sensor, this study proposes a method for extracting a cardiac signal from the built-in extracorporeal venous pressure sensor of the hemodialysis machine. The extraction is challenged by the fact that the cardiac component is much weaker than the pressure component caused by the peristaltic blood pump. To further complicate the extraction problem, the cardiac component is difficult to separate when the pump and heart rates coincide. The proposed method estimates a cardiac signal by subtracting an iteratively refined blood pump model signal from the signal measured at the extracorporeal venous pressure sensor. The method was developed based on simulated pressure signals, and evaluated on clinical pressure signals acquired during hemodialysis treatment. The heart rate estimated from the clinical pressure signal was compared to that derived from a photoplethysmographic reference signal, resulting in a difference of 0.07 $pm$ 0.84 beats/min. The accuracy of the heartbeat occurrence times was studied for different strengths of the cardiac component, using both clinical and simulated signals. The results suggest that the accuracy is sufficient for analysis of heart rate and certain arrhythmias.

Beschreibung: Goal: For conventional modeling methods, the work of model identification has to be repeated with sufficient data for each subject because different subjects may have different response to exogenous inputs. This may cause repetitive cost and burden for patients and clinicians and require a lot of modeling efforts. Here, to overcome the aforementioned problems, a rapid model development strategy for new subjects is proposed using the idea of model migration for online glucose prediction. Methods: First, a base model is obtained that can be empirically identified from any subject or constructed by a priori knowledge. Then, parameters of inputs in the base model are properly revised based on a small amount of new data from new subjects so that the updated models can reflect the specific glucose dynamics excited by inputs for new subjects. These problems are investigated by developing autoregressive models with exogenous inputs (ARX) based on 30 in silico subjects using UVA/Padova metabolic simulator. Results: The prediction accuracy of the rapid modeling method is comparable to that for subject-dependent modeling method for some cases. Also, it can present better generalization ability. Conclusion: The proposed method can be regarded as an effective and economic modeling method instead of repetitive subject-dependent modeling method especially for lack of modeling data.

Beschreibung: Goal: The objective of this paper is to demonstrate a multiplexed inductive force sensor for simultaneously measuring normal force and shear forces on a foot. Methods: The sensor measures the normal force and shear forces by monitoring the inductance changes of three planar sensing coils. Resonance frequency division multiplexing was applied to signals from the multiple sensing coils, making it feasible to simultaneously measure the three forces (normal force, shear forces in x- and y -axis) on a foot using only one set of measurement electronics with high sensitivity and resolution. Results: The testing results of the prototype sensor have shown that the sensor is capable of measuring normal force ranging from 0 to 800 N and shear forces ranging from 0 to 130 N in real time. Conclusion: With its high resolution, high sensitivity, and the capability of monitoring forces at different positions of a foot simultaneously, this sensor can be potentially used for real-time measurement of plantar normal force and shear forces distribution on diabetes patient's foot. Significance: Real-time monitoring of the normal force and shear forces on diabetes patient's foot can provide useful information for physicians and diabetes patients to take actions in preventing foot ulceration.

Beschreibung: The time course of grip force from object contact to onset of manipulation has been extensively studied to gain insight into the underlying control mechanisms. Of particular interest to the motor neuroscience and clinical communities is the phenomenon of bell-shaped grip force rate (GFR) that has been interpreted as indicative of feedforward force control. However, this feature has not been assessed quantitatively. Furthermore, the time course of grip force may contain additional features that could provide insight into sensorimotor control processes. In this study, we addressed these questions by validating and applying two computational approaches to extract features from GFR in humans: 1) fitting a Gaussian function to GFR and quantifying the goodness of the fit [root-mean-square error, (RMSE)]; and 2) continuous wavelet transform (CWT), where we assessed the correlation of the GFR signal with a Mexican Hat function. Experiment 1 consisted of a classic pseudorandomized presentation of object mass (light or heavy), where grip forces developed to lift a mass heavier than expected are known to exhibit corrective responses. For Experiment 2, we applied our two techniques to analyze grip force exerted for manipulating an inverted T-shaped object whose center of mass was changed across blocks of consecutive trials. For both experiments, subjects were asked to grasp the object at either predetermined or self-selected grasp locations (“constrained” and “unconstrained” task, respectively). Experiment 1 successfully validated the use of RMSE and CWT as they correctly distinguished trials with versus without force corrective responses. RMSE and CWT also revealed that grip force is characterized by more feedback-driven corrections when grasping at self-selected contact points. Future work will examine the application of our analytical approaches to a broader range of tasks, e.g., assessment of recovery of sensorimotor function- following clinical intervention, interlimb differences in force control, and force coordination in human–machine interactions.

Beschreibung: Objective: Characteristics of vortices within intracranial aneurysmal flow patterns have been associated with increased risk of rupture. The classifications of these vortex characteristics are commonly based upon qualitative scores, and are, therefore, subjective to user interpretation. We present a quantitative method for automatic time-resolved characterization of 3-D flow patterns and vortex detection within aneurysms. Methods: Our approach is based upon the combination of kernel deconvolution and Jacobian analysis of the velocity field. The deconvolution approach is accurate in detecting vortex centers but cannot discriminate between vortices and high-shear regions. Therefore, this approach is combined with analysis of the Jacobian of the velocity field. Scale-space theory is used to evaluate aneurysmal flow velocity fields at various scales. Results: The proposed algorithm is applied to computational fluid dynamics and time-resolved 3-D phase-contrast magnetic resonance imaging of aneurysmal flow. Conclusion: Results show that the proposed algorithm efficiently detects, visualizes, and quantifies vortices in intracranial aneurysmal velocity patterns at multiple scales and follows the temporal evolution of these patterns. Significance: Quantitative analysis performed with this method has the potential to reduce interobserver variability in aneurysm classification.

Beschreibung: Recent advances have led to renewed interest in ballistocardiography (BCG), a noninvasive measure of the small movements of the body due to cardiovascular events. A broad range of platforms have been developed and verified for BCG measurement including beds, chairs, and weighing scales: while the body is coupled to such a platform, the cardiogenic movements are measured. Wearable BCG, measured with an accelerometer affixed to the body, may enable continuous, or more regular, monitoring during the day; however, the signals from such wearable BCGs represent local or distal accelerations of skin and tissue rather than the whole body. In this paper, we propose a novel method to reconstruct the BCG measured with a weighing scale (WS BCG) from a wearable sensor via a training step to remove these local effects. Preliminary validation of this method was performed with 15 subjects: the wearable sensor was placed at three locations on the surface of the body while WS BCG measurements were recorded simultaneously. A regularized system identification approach was used to reconstruct the WS BCG from the wearable BCG. Preliminary results suggest that the relationship between local and central disturbances is highly dependent on both the individual and the location where the accelerometer is placed on the body and that these differences can be resolved via calibration to accurately measure changes in cardiac output and contractility from a wearable sensor. Such measurements could be highly effective, for example, for improved monitoring of heart failure patients at home.

Beschreibung: Objective: Glaucoma is an irreversible chronic eye disease that leads to vision loss. As it can be slowed down through treatment, detecting the disease in time is important. However, many patients are unaware of the disease because it progresses slowly without easily noticeable symptoms. Currently, there is no effective method for low-cost population-based glaucoma detection or screening. Recent studies have shown that automated optic nerve head assessment from 2-D retinal fundus images is promising for low-cost glaucoma screening. In this paper, we propose a method for cup to disc ratio (CDR) assessment using 2-D retinal fundus images. Methods: In the proposed method, the optic disc is first segmented and reconstructed using a novel sparse dissimilarity-constrained coding (SDC) approach which considers both the dissimilarity constraint and the sparsity constraint from a set of reference discs with known CDRs. Subsequently, the reconstruction coefficients from the SDC are used to compute the CDR for the testing disc. Results: The proposed method has been tested for CDR assessment in a database of 650 images with CDRs manually measured by trained professionals previously. Experimental results show an average CDR error of 0.064 and correlation coefficient of 0.67 compared with the manual CDRs, better than the state-of-the-art methods. Our proposed method has also been tested for glaucoma screening. The method achieves areas under curve of 0.83 and 0.88 on datasets of 650 and 1676 images, respectively, outperforming other methods. Conclusion: The proposed method achieves good accuracy for glaucoma detection. Significance: The method has a great potential to be used for large-scale population-based glaucoma screening.

Beschreibung: Objective: The efficacy of catheter-based cardiac ablation procedures can be significantly improved if real-time information is available concerning contact forces between the catheter tip and cardiac tissue. However, the widely used ablation catheters are not equipped for force sensing. This paper proposes a technique for estimating the contact forces without direct force measurements by studying the changes in the shape of the deflectable distal section of a conventional 7-Fr catheter (henceforth called the “deflectable distal shaft,” the “deflectable shaft,” or the “shaft” of the catheter) in different loading situations. Method: First, the shaft curvature when the tip is moving in free space is studied and based on that, a kinematic model for the deflectable shaft in free space is proposed. In the next step, the shaft shape is analyzed in the case where the tip is in contact with the environment, and it is shown that the curvature of the deflectable shaft provides useful information about the loading status of the catheter and can be used to define an index for determining the range of contact forces exerted by the ablation tip. Results: Experiments with two different steerable ablation catheters show that the defined index can detect the range of applied contact forces correctly in more than 80% of the cases. Based on the proposed technique, a framework for obtaining contact force information by using the shaft curvature at a limited number of points along the deflectable shaft is constructed. Conclusion: The proposed kinematic model and the force estimation technique can be implemented together to describe the catheter's behavior before contact, detect tip/tissue contact, and determine the range of contact forces. Significance: This study proves that the flexibility of the catheter's distal shaft provide- a means of estimating the force exerted on tissue by the ablation tip.

Beschreibung: Tumor recurrence following surgery is a common and unresolved medical problem of great importance since surgery is the most widely used treatment for solid-mass tumors worldwide. A contributing factor to tumor recurrence is the presence of residual tumor remaining at or near the surgical site following surgery. Goal: The primary objective of this study was to develop and evaluate an image-guided surgery system based on a near-infrared, handheld excitation source and spectrograph in combination with a widefield video imaging system. Methods: This system was designed to detect the fluorescence of near-infrared contrast agents and, in particular, indocyanine green (ICG). The imaging system was evaluated for its optical performance and ability to detect the presence of ICG in tumors in an ectopic murine tumor model as well as in spontaneous tumors arising in canines. Results: In both settings, an intravenous ICG infusion provided tumor contrast. In both the murine models and surgical specimens from canines, ICG preferentially accumulated in tumor tissue compared to surrounding normal tissue. The resulting contrast was sufficient to distinguish neoplasia from normal tissue; in the canine surgical specimens, the contrast was sufficient to permit identification of neoplasia on the marginal surface of the specimen. Conclusion: These results demonstrate a unique concept in image-guided surgery by combining local excitation and spectroscopy with widefield imaging. Significance: The ability to readily detect ICG in canines with spontaneous tumors in a clinical setting exemplifies the potential for further clinical translation; the promising results of detecting neoplasia on the marginal specimen surface underscore the clinical utility.

Beschreibung: Gastric cancer is the second leading cause of cancer death worldwide and screening programs have had a significant impact on reducing mortality. The majority of cases occur in low- and middle-income countries (LMIC), where endoscopy resources are traditionally limited. In this paper, we introduce a platform designed to enable inexpensive gastric screening to take place in remote areas of LMIC. The system consists of a swallowable endoscopic capsule connected to an external water distribution system by a multichannel soft tether. Pressurized water is ejected from the capsule to orient the view of the endoscopic camera. After completion of a cancer screening procedure, the outer shell of the capsule and the soft tether can be disposed, while the endoscopic camera is reclaimed without needing further reprocessing. The capsule, measuring 12 mm in diameter and 28 mm in length, is able to visualize the inside of the gastric cavity by combining waterjet actuation and the adjustment of the tether length. Experimental assessment was accomplished through a set of bench trials, ex vivo analysis, and in vivo feasibility validation. During the ex vivo trials, the platform was able to visualize the main landmarks that are typically observed during a gastric cancer screening procedure in less than 8 min. Given the compact footprint, the minimal cost of the disposable parts, and the possibility of running on relatively available and inexpensive resources, the proposed platform can potentially widen gastric cancer screening programs in LMIC.

Beschreibung: Current state-of-the-art remote photoplethysmography (rPPG) algorithms are capable of extracting a clean pulse signal in ambient light conditions using a regular color camera, even when subjects move significantly. In this study, we investigate the feasibility of rPPG in the (near)-infrared spectrum, which broadens the scope of applications for rPPG. Two camera setups are investigated: one setup consisting of three monochrome cameras with different optical filters, and one setup consisting of a single RGB camera with a visible light blocking filter. Simulation results predict the monochrome setup to be more motion robust, but this simulation neglects parallax. To verify this, a challenging benchmark dataset consisting of 30 videos is created with various motion scenarios and skin tones. Experiments show that both camera setups are capable of accurate pulse extraction in all motion scenarios, with an average SNR of +6.45 and +7.26 dB, respectively. The single camera setup proves to be superior in scenarios involving scaling, likely due to parallax of the multicamera setup. To further improve motion robustness of the RGB camera, dedicated LED illumination with two distinct wavelengths is proposed and verified. This paper demonstrates that accurate rPPG measurements in infrared are feasible, even with severe subject motion.

Beschreibung: Prolonged bed rest has significant negative impacts on the human body, particularly on the cardiovascular system. To overcome adverse effects and enhance functional recovery in bedridden patients, the goal is to mobilize patients as early as possible while controlling and stabilizing their cardiovascular system. In this paper, we used a robotic tilt table that allows early mobilization by modulating body inclination and automated leg movement to control the cardiovascular variables heart rate (HR) or systolic or diastolic blood pressures (sBP, dBP). The design and use of a control system is often done with a simulation model of a plant, but the time-variant and nonlinear nature of the cardiovascular system and subject-specific responses to external stimuli makes the modeling and identification challenging. Instead, we implemented an intelligent self-learning fuzzy controller that does not need any prior knowledge about the plant. The controller modulates the body inclination in order to adjust the cardiovascular parameters, with leg movement considered as a perturbing factor to the controller. The controller performance was evaluated in six healthy subjects. Measured mean values of HR, sBP, and dBP differed from desired reference values by 1.11 beats/min, 5.10 mmHg, and 2.69 mmHg, respectively. With this new control strategy, HR and dBP could be successfully controlled within medically tolerable ranges (deviations 〈 2.5 beats/min and 〈 5 mmHg from desired values, respectively). The control of sBP was less accurate; the results suggest that simultaneous control of multiple input stimuli rather than only adaptive automatic change of the tilt table angle might improve the controllability.

Beschreibung: Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

Beschreibung: Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

Beschreibung: Goal: In this paper, a fully automatic probabilistic method for multiple sclerosis (MS) lesion classification is presented, whereby the posterior probability density function over healthy tissues and two types of lesions (T1-hypointense and T2-hyperintense) is generated at every voxel. Methods: During training, the system explicitly models the spatial variability of the intensity distributions throughout the brain by first segmenting it into distinct anatomical regions and then building regional likelihood distributions for each tissue class based on multimodal magnetic resonance image (MRI) intensities. Local class smoothness is ensured by incorporating neighboring voxel information in the prior probability through Markov random fields. The system is tested on two datasets from real multisite clinical trials consisting of multimodal MRIs from a total of 100 patients with MS. Lesion classification results based on the framework are compared with and without the regional information, as well as with other state-of-the-art methods against the labels from expert manual raters. The metrics for comparison include Dice overlap, sensitivity, and positive predictive rates for both voxel and lesion classifications. Results: Statistically significant improvements in Dice values ( $p 〈 0.01$ ), for voxel-based and lesion-based sensitivity values ( $p 〈 0.001$ ), and positive predictive rates ( $p 〈 0.001$ and $p 〈 0.01$ respectively) are shown when the proposed method is compared to the method without regional information, and to a widely used method [1] . This holds particularly true in the posterior fossa, an ar- a where classification is very challenging. Significance: The proposed method allows us to provide clinicians with accurate tissue labels for T1-hypointense and T2-hyperintense lesions, two types of lesions that differ in appearance and clinical ramifications, and with a confidence level in the classification, which helps clinicians assess the classification results.

Beschreibung: The current diagnosis process of dementia is resulting in a high percentage of cases with delayed detection. To address this problem, in this paper, we explore the feasibility of autonomously detecting mild cognitive impairment (MCI) in the older adult population. We implement a signal processing approach equipped with a machine learning paradigm to process and analyze real-world data acquired using home-based unobtrusive sensing technologies. Using the sensor and clinical data pertaining to 97 subjects, acquired over an average period of three years, a number of measures associated with the subjects’ walking speed and general activity in the home were calculated. Different time spans of these measures were used to generate feature vectors to train and test two machine learning algorithms namely support vector machines and random forests. We were able to autonomously detect MCI in older adults with an area under the ROC curve of 0.97 and an area under the precision-recall curve of 0.93 using a time window of 24 weeks. This study is of great significance since it can potentially assist in the early detection of cognitive impairment in older adults.

Beschreibung: Alternative extrapulmonary oxygenation technologies are needed to treat patients suffering from severe hypoxemia refractory to mechanical ventilation. We previously demonstrated that peritoneal microbubble oxygenation (PMO), in which phospholipid-coated oxygen microbubbles (OMBs) are delivered into the peritoneal cavity, can successfully oxygenate rats suffering from a right pneumothorax. This study addressed the need to scale up the procedure to a larger animal with a splanchnic cardiac output similar to humans. Our results show that PMO therapy can double the survival time of rabbits experiencing complete tracheal occlusion from $6.6 pm 0.6$ min for the saline controls to $12.2 pm 3.0$ min for the bolus PMO-treated cohort. Additionally, we designed and tested a new peritoneal delivery system to circulate OMBs through the peritoneal cavity. Circulation achieved a similar survival benefit to bolus delivery under these conditions. Overall, these results support the feasibility of the PMO technology to provide extrapulmonary ventilation for rescue of severely hypoxic patients.

Beschreibung: These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.

Beschreibung: Goal: The objective of this study was to evaluate the ability of linear regression models to decode patterns of muscle coactivation from intramuscular electromyogram (EMG) and provide simultaneous myoelectric control of a virtual 3-DOF wrist/hand system. Performance was compared to the simultaneous control of conventional myoelectric prosthesis methods using intramuscular EMG (parallel dual-site control)—an approach that requires users to independently modulate individual muscles in the residual limb, which can be challenging for amputees. Methods: Linear regression control was evaluated in eight able-bodied subjects during a virtual Fitts’ law task and was compared to performance of eight subjects using parallel dual-site control. An offline analysis also evaluated how different types of training data affected prediction accuracy of linear regression control. Results: The two control systems demonstrated similar overall performance; however, the linear regression method demonstrated improved performance for targets requiring use of all three DOFs, whereas parallel dual-site control demonstrated improved performance for targets that required use of only one DOF. Subjects using linear regression control could more easily activate multiple DOFs simultaneously, but often experienced unintended movements when trying to isolate individual DOFs. Offline analyses also suggested that the method used to train linear regression systems may influence controllability. Conclusion and Significance: Linear regression myoelectric control using intramuscular EMG provided an alternative to parallel dual-site control for 3-DOF simultaneous control at the wrist and hand. The two methods demonstrated different strengths in controllability, highlighting the tradeoff between providing simultaneous control and the ability to isolate individual DOFs when desired.

Beschreibung: Photoplethysmography (PPG) is a noninvasive optical technique for detecting microvascular blood volume changes in tissues. Its ease of use, low cost and convenience make it an attractive area of research in the biomedical and clinical communities. Nevertheless, its single spot monitoring and the need to apply a PPG sensor directly to the skin limit its practicality in situations such as perfusion mapping and healing assessments or when free movement is required. The introduction of fast digital cameras into clinical imaging monitoring and diagnosis systems, the desire to reduce the physical restrictions, and the possible new insights that might come from perfusion imaging and mapping inspired the evolution of the conventional PPG technology to imaging PPG (IPPG). IPPG is a noncontact method that can detect heart-generated pulse waves by means of peripheral blood perfusion measurements. Since its inception, IPPG has attracted significant public interest and provided opportunities to improve personal healthcare. This study presents an overview of the wide range of IPPG systems currently being introduced along with examples of their application in various physiological assessments. We believe that the widespread acceptance of IPPG is happening, and it will dramatically accelerate the promotion of this healthcare model in the near future.

Beschreibung: Respiratory motion analysis based on range imaging (RI) has emerged as a popular means of generating respiration surrogates to guide motion management strategies in computer-assisted interventions. However, existing approaches employ heuristics, require substantial manual interaction, or yield highly redundant information. In this paper, we propose a framework that uses preprocedurally obtained 4-D shape priors from patient-specific breathing patterns to drive intraprocedural RI-based real-time respiratory motion analysis. As the first contribution, we present a shape motion model enabling an unsupervised decomposition of respiration induced high-dimensional body surface displacement fields into a low-dimensional representation encoding thoracic and abdominal breathing. Second, we propose a method designed for GPU architectures to quickly and robustly align our models to high-coverage multiview RI body surface data. With our fully automatic method, we obtain respiration surrogates yielding a Pearson correlation coefficient (PCC) of 0.98 with conventional surrogates based on manually selected regions on RI body surface data. Compared to impedance pneumography as a respiration signal that measures the change of lung volume, we obtain a PCC of 0.96. Using off-the-shelf hardware, our framework enables high temporal resolution respiration analysis at 50 Hz.

Beschreibung: Goal : This paper describes the development and testing of various position sensing systems (PSSs) for miniaturized long-term applications with a focus on their validation in a total artificial heart (TAH). After a short description of the TAH's functioning principle, the special requirements for the PSS resulting from the application in a TAH are investigated. Methods : Three PSS's were designed according to these requirements. A specially designed test method was used to first validate each PSS for general use in a miniaturized application. This test method validated the speed, resolution, and accuracy requirements for the PSS. In a second step, the PSS's were integrated in a TAH to measure its stroke position for the drive control. In this application, further requirements apart from miniaturization were considered. Each PSS's functionality in the TAH was validated in a mock circulation loop, which simulates the human circulatory system. Results : Two of the three designed PSS's showed satisfactory results for all tested requirements inside the pump, whereas the third PSS did not operate properly at full-pump capacity. The best performing PSS was chosen for further use in the TAH. It performed up to a beat rate of 220 b/m. Conclusion : The extensive validation resulted in an accurate, miniature PSS for a TAH. Significance : Besides the use in a TAH, the presented PSS's can be employed in a wide use of miniaturized applications. The introduced testing method allows the validation for general miniaturized applications, e.g., linear motor drives.

Beschreibung: Pulse trains are widely used in electroporation (EP) for both general biomedical research and clinical applications such as nonthermal tumor ablation. Here we use a computational method based on a meshed transport network to investigate a cell system model's response to a train of identical, evenly spaced electric field pulses. We obtain an unexpected result: the number of membrane pores decreases during the application of twenty 1.0 kV/cm, 100  $mu$ s pulses, delivered at 1 Hz. This pulse train initially creates 13,000 membrane pores, but pore number decreases by a factor of 15 to about 830 pores throughout subsequent pulses. We conclude that pore number can greatly diminish during a train of identical pulses, with direct consequences for the transport of solutes across an electroporated membrane. Although application of additional pulses is generally intended to increase the effects of EP, we show that these pulses do not significantly enhance calcium delivery into the cell. Instead, calcium delivery can be significantly increased by varying inter-pulse intervals. We show that inserting a 300-s interruption midway in a widely used eight-pulse train (a protocol for electrosensitization) yields a $sim$ twofold delivery increase. Overall, our modeling shows support for electrosensitization, in which multiple pulse protocols that maximize pore number over time can yield significant increase of transport of calcium compared to standard pulse trains.

Beschreibung: Goal: The purpose of this paper is to improve the detection of high-frequency sounds from the heart for better identification of turbulent blood flow in partially occluded coronary arteries. This paper also describes a method for the quantitative assessment of data quality. Methods: A very light-weight dual accelerometer has been developed that places a small mechanical load on the chest. When used in conjunction with a novel correlation-based analysis, this dual-signal transducer provides an estimate to the signal-to-noise ratio (SNR) of the acoustic signal. Results: The new transducer has significantly better SNR properties than the traditional cardiac microphones. This improvement is due to increased sensitivity to high-frequency signals not a reduction in noise and is likely the result of reduced mechanical loading on the chest. Conclusion: Substantial improvement in the detection of high-frequency heart sounds is possible as is quantitative assessment of data quality. Significance: The new transducer and analysis will lead to substantial improvements in the acoustic detection of partially occluded arteries associated with coronary artery disease. It is finally possible to obtain a measurement of the quality of heart sound signals as they are being recorded.

Beschreibung: The objective of this paper is to propose an asymmetric Gaussian function as an alternative to the existing active force-length models, and to optimize this model along with several other existing models by using the least squares curve fitting method. The minimal set of coefficients is identified for each of these models to facilitate the least squares curve fitting. Sarcomere simulated data and one set of rabbits extensor digitorum II experimental data are used to illustrate optimal curve fitting of the selected force–length functions. The results shows that all the curves fit reasonably well with the simulated and experimental data, while the Gordon–Huxley–Julian model and asymmetric Gaussian function are better than other functions in terms of statistical test scores root mean squared error and R-squared. However, the differences in RMSE scores are insignificant (0.3–6%) for simulated data and (0.2–5%) for experimental data. The proposed asymmetric Gaussian model and the method of parametrization of this and the other force–length models mentioned above can be used in the studies on active force–length relationships of skeletal muscles that generate forces to cause movements of human and animal bodies.

Beschreibung: This paper demonstrates flexible epineural strip electrodes (FLESE) for recording from small nerves. Small strip-shaped FLESE enables us to easily and closely stick on various sized nerves for less damage in a nerve and optimal recording quality. In addition, in order to enhance the neural interface, the gold electrode contacts were coated with carbon nanotubes, which reduced the impedance of the electrodes. We used the FLESEs to record electrically elicited nerve signals (compound neural action potentials) from the sciatic nerve in rats. Bipolar and differential bipolar configurations for the recording were investigated to optimize the recording configuration of the FLESEs. The successful results from differential bipolar recordings showed that the total length of FLESEs could be further reduced, maintaining the maximum recording ability, which would be beneficial for recording in very fine nerves. Our results demonstrate that new concept of FLESEs could play an important role in electroceuticals in near future.

Beschreibung: These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.

Beschreibung: IEEE Transactions on Biomedical Engineering handling editors.

Beschreibung: Goal: A new method for heart rate monitoring using photoplethysmography (PPG) during physical activities is proposed. Methods : It jointly estimates the spectra of PPG signals and simultaneous acceleration signals, utilizing the multiple measurement vector model in sparse signal recovery. Due to a common sparsity constraint on spectral coefficients, the method can easily identify and remove the spectral peaks of motion artifact (MA) in the PPG spectra. Thus, it does not need any extra signal processing modular to remove MA as in some other algorithms. Furthermore, seeking spectral peaks associated with heart rate is simplified. Results : Experimental results on 12 PPG datasets sampled at 25 Hz and recorded during subjects’ fast running showed that it had high performance. The average absolute estimation error was 1.28 beat/min and the standard deviation was 2.61 beat/min. Conclusion and Significance : These results show that the method has great potential to be used for PPG-based heart rate monitoring in wearable devices for fitness tracking and health monitoring.

Beschreibung: Most prosthetic myoelectric control studies have shown good performance for unimpaired subjects. However, performance is generally unacceptable for amputees. The primary problem is the poor quality of electromyography (EMG) signals of amputees compared with healthy individuals. To improve clinical performance of myoelectric control, this study explored transcranial direct current stimulation (tDCS) to modulate brain activity and enhance EMG quality. We tested six unilateral transradial amputees by applying active and sham anodal tDCS separately on two different days. Surface EMG signals were acquired from the affected and intact sides for 11 hand and wrist motions in the pre-tDCS and post-tDCS sessions. Autoregression coefficients and linear discriminant analysis classifiers were used to process the EMG data for pattern recognition of the 11 motions. For the affected side, active anodal tDCS significantly reduced the average classification error rate (CER) by 10.1%, while sham tDCS had no such effect. For the intact side, the average CER did not change on the day of sham tDCS but increased on the day of active tDCS. These results demonstrated that tDCS could modulate brain function and improve EMG-based classification performance for amputees. It has great potential in dramatically reducing the length of learning process of amputees for effectively using myoelectrically controlled multifunctional prostheses.

Beschreibung: Objective: Principle aim of this study is to investigate the performance of a matching pursuit (MP)-based bispectral analysis in the detection and quantification of quadratic phase couplings (QPC) in biomedical signals. Nonlinear approaches such as time-variant bispectral analysis are able to provide information about phase relations between oscillatory signal components. Methods: Time-variant QPC analysis is commonly performed using Gabor transform (GT) or Morlet wavelet transform (MWT), and is affected by either constant or frequency-dependent time–frequency resolution (TFR). The matched Gabor transform (MGT), which emerges from the incorporation of GT into MP, can overcome this obstacle by providing a complex time–frequency plane with an individually tailored TFR for each transient oscillatory component. QPC analysis was performed by MGT, and MWT was used as the state-of-the-art method for comparison. Results: Results were demonstrated using simulated data, which present the general case of QPC, and biomedical benchmark data with a priori knowledge about specific signal components. HRV of children during temporal lobe epilepsy and EEG during burst–interburst pattern of neonates during quiet sleep were used for the biomedical signal analysis to investigate the two main areas of biomedical signal analysis: The cardiovascular–cardiorespiratory system and neurophysiological brain activities, respectively. Simulations were able to show the applicability and reliability of the MGT for bispectral analysis. HRV and EEG analysis demonstrate the general validity of the MGT for QPC detection by quantifying statistically significant time patterns of QPC. Conclusion and Significance: Results confirm that MGT - based bispectral analysis provides significant benefits for the analysis of QPC in biomedical signals.

Beschreibung: Provides a listing of the editors, board members, and current staff for this issue of the publication.

Beschreibung: Goal: This study aims to develop highly accurate heart rate monitoring from the hand-held contact signal within a noisy environment during exercise. Methods: The periodic pattern and uncertainties of a physiological signal are modeled by a Laplacian random process. Based on this statistical model, a highly accurate pulse predictor (HAPPEE) is derived and implemented in real-time on a Cypress PSoC 5LP development board. A real-time experiment is designed to compare HAPPEE with a commercial heart rate monitor from POLAR. The percentage of credible estimates and the mean square error (MSE) of credible estimates are reported for experiments with seven healthy subjects. Results: The overall percentage of credible estimates is $99.2%$ for HAPPEE and $93.6%$ for POLAR. The overall MSE of credible estimates is $3.1$ for HAPPEE and $7.7$ for POLAR. These results show that HAPPEE is more accurate than POLAR. Conclusion: HAPPEE is able to accurately monitor heart rate within a noisy environment during exercise. Significance: Unlike existing heart rate estimation methods, HAPPEE does not require pulse detection or tuning parameters. It can be easily implemented in real-time on a low power and low cost development board for exercise equipment and outperforms a commercial heart rate monitor.

Beschreibung: A novel approach in tonic cold pain characterization, based on electroencephalograph (EEG) data analysis using wavelet higher order spectral (WHOS) features, is presented here. The proposed WHOS-based feature space extends the relative power spectrum-based (phase blind) approaches reported so far a step forward; this is realized via dynamic monitoring of the nonlinerities of the EEG brain response to tonic cold pain stimuli by capturing the change in the underlying quadratic phase coupling at the bifrequency wavelet bispectrum/bicoherence domain due to the change of the pain level. Three pain characterization scenarios were formed and experimentally tested involving WHOS-based analysis of EEG data, acquired from 17 healthy volunteers that were subjected to trials of tonic cold pain stimuli. The experimental and classification analysis results, based on four well-known classifiers, have shown that the WHOS-based features successfully discriminate relax from pain status, provide efficient identification of the transition from relax to mild and/or severe pain status, and translate the subjective perception of pain to an objective measure of pain endurance. These findings seem quite promising and pave the way for adopting WHOS-based approaches to pain characterization under other types of pain, e.g., chronic pain and various clinical scenarios.

Beschreibung: The cardiovascular control system is continuously engaged to maintain homeostasis, but it is known to fail in a large cohort of patients suffering from orthostatic intolerance. Numerous clinical studies have been put forward to understand how the system fails, yet noninvasive clinical data are sparse, typical studies only include measurements of heart rate and blood pressure, as a result it is difficult to determine what mechanisms that are impaired. It is known, that blood pressure regulation is mediated by changes in heart rate, vascular resistance, cardiac contractility, and a number of other factors. Given that numerous factors contribute to changing these quantities, it is difficult to devise a physiological model describing how they change in time. One way is to build a model that allows these controlled quantities to change and to compare dynamics between subject groups. To do so, it requires more knowledge of how these quantities change for healthy subjects. This study compares two methods predicting time-varying changes in cardiac contractility and vascular resistance during head-up tilt. Similar to the study by Williams et al. [51] , the first method uses piecewise linear splines, while the second uses the ensemble transform Kalman filter (ETKF) [1] , [11] , [12] , [33] . In addition, we show that the delayed rejection adaptive Metropolis (DRAM) algorithm can be used for predicting parameter uncertainties within the spline methodology, which is compared with the variability obtained with the ETKF. While the spline method is easier to set up, this study shows that the ETKF has a significantly shorter computational time. Moreover, while uncertainty of predictions can be augmented to spline predictions using DRAM, these are readily avail- ble with the ETKF.