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This paper presents a new unmixing methodology of multispectral fluorescence lifetime imaging microscopy (m-FLIM) data, in which the spectrum is defined as the combination of time-domain fluorescence decays at multiple emission wavelengths. The method is based on a quadratic constrained optimization (CO) algorithm that provides a closed-form solution under equality and inequality restrictions. In this paper, it is assumed that the time-resolved fluorescence spectrum profiles of the constituent components are linearly independent and known a priori. For comparison purposes, the standard least squares (LS) solution and two constrained versions nonnegativity constrained least squares (NCLS) and fully constrained least squares (FCLS) (Heinz and Chang, 2001) are also tested. Their performance was evaluated by using synthetic simulations, as well as imaged samples from fluorescent dyes and ex vivo tissue. In all the synthetic evaluations, the CO obtained the best accuracy in the estimations of the proportional contributions. CO could achieve an improvement ranging between 41% and 59% in the relative error compared to LS, NCLS, and FCLS at different signal-to-noise ratios. A liquid mixture of fluorescent dyes was also prepared and imaged in order to provide a controlled scenario with real data, where CO and FCLS obtained the best performance. The CO and FCLS were also tested with 20 ex vivo samples of human coronary arteries, where the expected concentrations are qualitatively known. A certainty measure was employed to assess the confidence in the estimations made by each algorithm. The experiments confirmed a better performance of CO, since this method is optimal with respect to equality and inequality restrictions in the linear unmixing formulation. Thus, the evaluation showed that CO achieves an accurate characterization of the samples. Furthermore, CO is a computational efficient alternative to estimate the abundance of components in m-FLIM data, since- a global optimal solution is always guaranteed in a closed form. Read more
Here, we report the development of an integrated laser Doppler blood flow micrometer for chickens. This sensor weighs only 18 g and is one of the smallest-sized blood flow meters, with no wired line, these are features necessary for attaching the sensor to the chicken. The structure of the sensor chip consists of two silicon cavities with a photo diode and a laser diode, which was achieved using the microelectromechanical systems technique, resulting in its small size and significantly low power consumption. In addition, we introduced an intermittent measuring arrangement in the measuring system to reduce power consumption and to enable the sensor to work longer. We were successfully able to measure chicken blood flow for five consecutive days, and discovered that chicken blood flow shows daily fluctuations. Read more
IEEE Transactions on Biomedical Engineering publication information
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Presents the table of contents for this issue of the periodical. Read more
Noninvasive Biomagnetic Detection of Isolated Ischemic Bowel Segments
The slow wave activity was measured in the magnetoenterogram (MENG) of normal porcine subjects (
Surgical Tool Alignment Guidance by Drawing Two Cross-Sectional Laser-Beam Planes
Conventional surgical navigation requires for surgeons to move their sight and conscious off the surgical field when checking surgical tool’s positions shown on the display panel. Since that takes high risks of surgical exposure possibilities to the patient’s body, we propose a novel method for guiding surgical tool position and orientation directly in the surgical field by a laser beam. In our navigation procedure, two cross-sectional planar laser beams are emitted from the two laser devices attached onto both sides of an optical localizer, and show surgical tool’s entry position on the patient’s body surface and its orientation on the side face of the surgical tool. In the experiments, our method gave the surgeons precise and accurate surgical tool adjusting and showed the feasibility to apply to both of open and percutaneous surgeries. Read more
Childhood avascular necrosis (AVN) of the femoral head leads to its progressive deformation and compensatory changes of the adjacent acetabulum. To simulate this disease for laboratory study, we used an AVN model of the hip in a skeletally immature piglet. The 3-D visualization and analysis of this piglet’s deforming femur and hip form the basis for this paper. In particular, the data for this analysis were generated via serial CT images of bilateral femurs and acetabula of a piglet at regular time intervals following experimental unilateral induction of femoral head AVN. The contralateral femur and acetabulum served as the control. We applied a shape analysis technique that effectively captured not only the temporal shape changes of the femurs and acetabula, but also their codependencies. The resulting computational framework not only confirmed the widely accepted deformational changes of the femoral head following AVN; it also revealed the underappreciated compensatory changes of the surrounding acetabulum. The 3-D visualization of these dynamically changing structures provided a visual understanding of the shape changes associated with the AVN and control models. By quantitatively mapping the deformation trajectory of these shapes over time, we created an objective tool for clinical decision making. Read more
In color flow imaging, it is a challenging work to accurately extract blood flow information from ultrasound Doppler echoes dominated by the strong clutter components. In this paper, we provide an in-depth analysis of ridge ensemble empirical mode decomposition (R-EEMD) and compare it with the conventional empirical mode decomposition (EMD) framework. R-EEMD facilitates nonuniform and trial-dependent weights obtained by an optimization procedure during ensemble combination and results in less decomposition errors when compared with the conventional ensemble empirical mode decomposition techniques. A theoretic result is then extended to demonstrate that R-EEMD has an ability to solve the mode mixing problem frequently encountered in EMD and improve the decomposition performance with adequate noise strength when separating a composite two-tone signal. Based on the proposed R-EEMD framework, a novel clutter rejection filter for ultrasound color flow imaging is designed. In a series of simulations, the R-EEMD-based filter achieves a significant improvement on blood flow velocity estimation over the state-of-the-art regression filters and decomposition-based filters, such as eigen-based and EMD filters. An experiment on human carotid artery data also verifies that the R-EEMD algorithm achieves minimum clutter energy and maximum blood-to-clutter energy ratio among all the tested techniques. Read more
Current hearing-aid systems have fixed sound wave decomposition plans due to the use of fixed filterbanks, thus cannot provide enough flexibility for the compensation of different hearing impairment cases. In this paper, a reconfigurable filterbank that consists of a multiband-generation block and a subband-selection block is proposed. Different subbands can be produced according to the control parameters without changing the structure of the filterbank system. The use of interpolation, decimation, and frequency-response masking enables us to reduce the computational complexity by realizing the entire system with only three prototype filters. Reconfigurability of the proposed filterbank enables hearing-impaired people to customize hearing aids based on their own specific conditions to improve their hearing ability. We show, by means of examples, that the proposed filterbank can achieve a better matching to the audiogram and has smaller complexity compared with the fixed filterbank. The drawback of the proposed method is that the throughput delay is relatively long (>20 ms), which needs to be further reduced before it can be used in a real hearing-aid application. Read more
Consciousness and Depth of Anesthesia Assessment Based on Bayesian Analysis of EEG Signals
This study applies Bayesian techniques to analyze EEG signals for the assessment of the consciousness and depth of anesthesia (DoA). This method takes the limiting large-sample normal distribution as posterior inferences to implement the Bayesian paradigm. The maximum a posterior (MAP) is applied to denoise the wavelet coefficients based on a shrinkage function. When the anesthesia states change from awake to light, moderate, and deep anesthesia, the MAP values increase gradually. Based on these changes, a new function
ECG Signal Quality During Arrhythmia and Its Application to False Alarm Reduction
An automated algorithm to assess electrocardiogram (ECG) quality for both normal and abnormal rhythms is presented for false arrhythmia alarm suppression of intensive care unit (ICU) monitors. A particular focus is given to the quality assessment of a wide variety of arrhythmias. Data from three databases were used: the Physionet Challenge 2011 dataset, the MIT-BIH arrhythmia database, and the MIMIC II database. The quality of more than 33 000 single-lead 10 s ECG segments were manually assessed and another 12 000 bad-quality single-lead ECG segments were generated using the Physionet noise stress test database. Signal quality indices (SQIs) were derived from the ECGs segments and used as the inputs to a support vector machine classifier with a Gaussian kernel. This classifier was trained to estimate the quality of an ECG segment. Classification accuracies of up to 99% on the training and test set were obtained for normal sinus rhythm and up to 95% for arrhythmias, although performance varied greatly depending on the type of rhythm. Additionally, the association between 4050 ICU alarms from the MIMIC II database and the signal quality, as evaluated by the classifier, was studied. Results suggest that the SQIs should be rhythm specific and that the classifier should be trained for each rhythm call independently. This would require a substantially increased set of labeled data in order to train an accurate algorithm. Read more
Late gadolinium enhanced (LGE) cardiac magnetic resonance (CMR) can directly visualize nonviable myocardium with hyperenhanced intensities with respect to normal myocardium. For heart attack patients, it is crucial to facilitate the decision of appropriate therapy by analyzing and quantifying their LGE CMR images. To achieve accurate quantification, LGE CMR images need to be processed in two steps: segmentation of the myocardium followed by classification of infarcts within the segmented myocardium. However, automatic segmentation is difficult usually due to the intensity heterogeneity of the myocardium and intensity similarity between the infarcts and blood pool. Besides, the slices of an LGE CMR dataset often suffer from spatial and intensity distortions, causing further difficulties in segmentation and classification. In this paper, we present a comprehensive 3-D framework for automatic quantification of LGE CMR images. In this framework, myocardium is segmented with a novel method that deforms coupled endocardial and epicardial meshes and combines information in both short- and long-axis slices, while infarcts are classified with a graph-cut algorithm incorporating intensity and spatial information. Moreover, both spatial and intensity distortions are effectively corrected with specially designed countermeasures. Experiments with 20 sets of real patient data show visually good segmentation and classification results that are quantitatively in strong agreement with those manually obtained by experts. Read more
Feature-Preserving Smoothing of Diffusion Weighted Images Using Nonstationarity Adaptive Filtering
Although promising for studying the microstructure of in vivo tissues, the performance and the potentiality of diffusion tensor magnetic resonance imaging are hampered by the presence of high-level noise in diffusion weighted (DW) images. This paper proposes a novel smoothing approach, called the nonstationarity adaptive filtering, which estimates the intensity of a pixel by averaging intensities in its adaptive homogeneous neighborhood. The latter is determined according to five constraints and spatiodirectional nonstationarity measure maps. The proposed approach is compared with an anisotropic diffusion method used in DW image smoothing. Experimental results on both synthetic and real human DW images show that the proposed method achieves a better compromise between the smoothness of homogeneous regions and the preservation of desirable features such as boundaries, even for highly noisy data, thus leading to homogeneously consistent tensor fields and consequently more coherent fibers. Read more
An Impulse Radio Ultrawideband System for Contactless Noninvasive Respiratory Monitoring
We design a impulse radio ultrawideband radar monitoring system to track the chest wall movement of a human subject during respiration. Multiple sensors are placed at different locations to ensure that the backscattered signal could be detected by at least one sensor no matter which direction the human subject faces. We design a hidden Markov model to infer the subject facing direction and his or her chest movement. We compare the performance of our proposed scheme on
Ultrasound Probe and Needle-Guide Calibration for Robotic Ultrasound Scanning and Needle Targeting
Image-to-robot registration is a typical step for robotic image-guided interventions. If the imaging device uses a portable imaging probe that is held by a robot, this registration is constant and has been commonly named probe calibration. The same applies to probes tracked by a position measurement device. We report a calibration method for 2-D ultrasound probes using robotic manipulation and a planar calibration rig. Moreover, a needle guide that is attached to the probe is also calibrated for ultrasound-guided needle targeting. The method is applied to a transrectal ultrasound (TRUS) probe for robot-assisted prostate biopsy. Validation experiments include TRUS-guided needle targeting accuracy tests. This paper outlines the entire process from the calibration to image-guided targeting. Freehand TRUS-guided prostate biopsy is the primary method of diagnosing prostate cancer, with over 1.2 million procedures performed annually in the U.S. alone. However, freehand biopsy is a highly challenging procedure with subjective quality control. As such, biopsy devices are emerging to assist the physician. Here, we present a method that uses robotic TRUS manipulation. A 2-D TRUS probe is supported by a 4-degree-of-freedom robot. The robot performs ultrasound scanning, enabling 3-D reconstructions. Based on the images, the robot orients a needle guide on target for biopsy. The biopsy is acquired manually through the guide. In vitro tests showed that the 3-D images were geometrically accurate, and an image-based needle targeting accuracy was 1.55 mm. These validate the probe calibration presented and the overall robotic system for needle targeting. Targeting accuracy is sufficient for targeting small, clinically significant prostatic cancer lesions, but actual in vivo targeting will include additional error components that will have to be determined. Read more
This paper presents an efficient approach to achieve microparticles flocking with robotics and optical tweezers technologies. All particles trapped by optical tweezers can be automatically moved toward a predefined region without collision. The main contribution of this paper lies in the proposal of several solutions to the flocking manipulation of microparticles in microenvironments. First, a simple flocking controller is proposed to generate the desired positions and velocities for particles’ movement. Second, a velocity saturation method is implemented to prevent the desired velocities from exceeding a safe limit. Third, a two-layer control architecture is proposed for the motion control of optical tweezers. This architecture can help make many robotic manipulations achievable under microenvironments. The proposed approach with these solutions can be applied to many bioapplications especially in cell engineering and biomedicine. Experiments on yeast cells with a robot-tweezers system are finally performed to verify the effectiveness of the proposed approach. Read more
Unsupervised Nosologic Imaging for Glioma Diagnosis
In this letter a novel approach to create nosologic images of the brain using magnetic resonance spectroscopic imaging (MRSI) data in an unsupervised way is presented. Different tissue patterns are identified from the MRSI data using nonnegative matrix factorization and are then coded as different primary colors (i.e. red, green, and blue) in an RGB image, so that mixed tissue regions are automatically visualized as mixtures of primary colors. The approach is useful in assisting glioma diagnosis, where several tissue patterns such as normal, tumor, and necrotic tissue can be present in the same voxel/spectrum. Error-maps based on linear least squares estimation are computed for each nosologic image to provide additional reliability information, which may help clinicians in decision making. Tests on in vivo MRSI data show the potential of this new approach. Read more
This paper is concerned with parameter extraction for the double Debye model, which is used for analytically determining human skin permittivity. These parameters are thought to be the origin of contrast in terahertz (THz) images of skin cancer. The existing extraction methods could generate Debye models, which track their measurements accurately at frequencies higher than 1 THz but poorly at lower frequencies, where the majority of permittivity contrast between healthy and diseased skin tissues is actually observed. We propose a global optimization-based parameter extraction, which results in globally accurate tracking and thus supports the full validity of the Debye model for simulating human skin permittivity in the whole usable THz frequencies. Numerical results confirm viability of our novel methodology. Read more
Presents the cover/table of contents for this issue of the periodical. Read more
Mechatronic Design of a Fully Integrated Camera for Mini-Invasive Surgery
This paper describes the design features of an innovative fully integrated camera candidate for mini-invasive abdominal surgery with single port or transluminal access. The apparatus includes a CMOS imaging sensor, a light-emitting diode (LED)-based unit for scene illumination, a photodiode for luminance detection, an optical system designed according to the mechanical compensation paradigm, an actuation unit for enabling autofocus and optical zoom, and a control logics based on microcontroller. The bulk of the apparatus is characterized by a tubular shape with a diameter of 10 mm and a length of 35 mm. The optical system, composed of four lens groups, of which two are mobile, has a total length of 13.46 mm and an effective focal length ranging from 1.61 to 4.44 mm with a zoom factor of 2.75×, with a corresponding angular field of view ranging from 16° to 40°. The mechatronics unit, devoted to move the zoom and the focus lens groups, is implemented adopting miniature piezoelectric motors. The control logics implements a closed-loop mechanism, between the LEDs and photodiode, to attain automatic control light. Bottlenecks of the design and some potential issues of the realization are discussed. A potential clinical scenario is introduced. Read more
Effects of Robotic Knee Exoskeleton on Human Energy Expenditure
A number of studies discuss the design and control of various exoskeleton mechanisms, yet relatively few address the effect on the energy expenditure of the user. In this paper, we discuss the effect of a performance augmenting exoskeleton on the metabolic cost of an able-bodied user/pilot during periodic squatting. We investigated whether an exoskeleton device will significantly reduce the metabolic cost and what is the influence of the chosen device control strategy. By measuring oxygen consumption, minute ventilation, heart rate, blood oxygenation, and muscle EMG during 5-min squatting series, at one squat every 2 s, we show the effects of using a prototype robotic knee exoskeleton under three different noninvasive control approaches: gravity compensation approach, position-based approach, and a novel oscillator-based approach. The latter proposes a novel control that ensures synchronization of the device and the user. Statistically significant decrease in physiological responses can be observed when using the robotic knee exoskeleton under gravity compensation and oscillator-based control. On the other hand, the effects of position-based control were not significant in all parameters although all approaches significantly reduced the energy expenditure during squatting. Read more
In this paper, we propose an electronic cleansing method using a novel reconstruction model for removing tagged materials (TMs) in computed tomography (CT) images. To address the partial volume (PV) and pseudoenhancement (PEH) effects concurrently, material fractions and structural responses are integrated into a single reconstruction model. In our approach, colonic components including air, TM, an interface layer between air and TM, and an interface layer between soft-tissue (ST) and TM (IL
The use of a bone-anchored device to transmit electrical signals from internalized muscle electrodes was studied in a sheep model. The bone-anchored device was used as a conduit for the passage of a wire connecting an internal epimysial electrode to an external signal-recording device. The bone-anchored device was inserted into an intact tibia and the electrode attached to the adjacent M. peroneus tertius. “Physiological” signals with low signal-to-noise ratios were successfully obtained over a 12-week period by walking the sheep on a treadmill. Reliable transmission of multiple muscle signals across the skin barrier is essential for providing intuitive, biomimetic upper limb prostheses. This technology has the potential to provide a better functional and reliable solution for upper limb amputee rehabilitation: attachment and control. Read more
Denoising MRI Using Spectral Subtraction
Improving the signal-to-noise-ratio (SNR) of magnetic resonance imaging (MRI) using denoising techniques could enhance their value, provided that signal statistics and image resolution are not compromised. Here, a new denoising method based on spectral subtraction of the measured noise power from each signal acquisition is presented. Spectral subtraction denoising (SSD) assumes no prior knowledge of the acquired signal and does not increase acquisition time. Whereas conventional denoising/filtering methods are compromised in parallel imaging by spatially dependent noise statistics, SSD is performed on signals acquired from each coil separately, prior to reconstruction. Using numerical simulations, we show that SSD can improve SNR by up to ∼45% in MRI reconstructed from both single and array coils, without compromising image resolution. Application of SSD to phantom, human heart, and brain MRI achieved SNR improvements of ∼40% compared to conventional reconstruction. Comparison of SSD with anisotropic diffusion filtering showed comparable SNR enhancement at low-SNR levels (SNR = 5–15) but improved accuracy and retention of structural detail at a reduced computational load. Read more
We report the development of a surrogate spinal cord for evaluating the mechanical suitability of electrode arrays for intraspinal implants. The mechanical and interfacial properties of candidate materials (including silicone elastomers and gelatin hydrogels) for the surrogate cord were tested. The elastic modulus was characterized using dynamic mechanical analysis, and compared with values of actual human spinal cords from the literature. Forces required to indent the surrogate cords to specified depths were measured to obtain values under static conditions. Importantly, to quantify surface properties in addition to mechanical properties normally considered, interfacial frictional forces were measured by pulling a needle out of each cord at a controlled rate. The measured forces were then compared to those obtained from rat spinal cords. Formaldehyde-crosslinked gelatin, 12 wt% in water, was identified as the most suitable material for the construction of surrogate spinal cords. To demonstrate the utility of surrogate spinal cords in evaluating the behavior of various electrode arrays, cords were implanted with two types of intraspinal electrode arrays (one made of individual microwires and another of microwires anchored with a solid base), and cord deformation under elongation was evaluated. The results demonstrate that the surrogate model simulates the mechanical and interfacial properties of the spinal cord, and enables in vitro screening of intraspinal implants. Read more
Confidence-Based Rejection for Improved Pattern Recognition Myoelectric Control
This study describes a novel myoelectric control scheme that is capable of motion rejection. As an extension of the commonly used linear discriminant analysis (LDA), this system generates a confidence score for each decision, providing the ability to reject those with a score below a selected threshold. The thresholds are class-specific and affect only the rejection characteristics of the associated class. Furthermore, because the rejection stage is implemented using the outputs of the LDA, the active motion classification accuracy of the proposed system is shown to outperform that of the LDA for all values of rejection threshold. The proposed scheme was compared to a baseline LDA-based pattern recognition system using a real-time Fitts’ law-based target acquisition task. The use of velocity-based myoelectric control using the rejection classifier is shown to obey Fitts’ law, producing linear regression fittings with high coefficients of determination
A vestibular neural prosthesis was designed on the basis of a cochlear implant for treatment of Meniere’s disease and other vestibular disorders. Computer control software was developed to generate patterned pulse stimuli for exploring optimal parameters to activate the vestibular nerve. Two rhesus monkeys were implanted with the prototype vestibular prosthesis and they were behaviorally evaluated post implantation surgery. Horizontal and vertical eye movement responses to patterned electrical pulse stimulations were collected on both monkeys. Pulse amplitude modulated (PAM) and pulse rate modulated (PRM) trains were applied to the lateral canal of each implanted animal. Robust slow-phase nystagmus responses following the PAM or PRM modulation pattern were observed in both implanted monkeys in the direction consistent with the activation of the implanted canal. Both PAM and PRM pulse trains can elicit a significant amount of in-phase modulated eye velocity changes and they could potentially be used for efficiently coding head rotational signals in future vestibular neural prostheses. Read more
In time-correlated single photon counting (TCSPC) systems, the maximum signal throughput is limited by the occurrence of pile-up and other effects. In many biological applications that exhibit high levels of fluorescence intensity (FI), pile-up-related distortions yield serious distortions in the fluorescence lifetime (FLT) calculation as well as significant decrease in the signal-to-noise ratio (SNR). Recent developments that allow the use of high-repetition-rate light sources (in the range of 50–100 MHz) in fluorescence lifetime imaging (FLIM) experiments enable minimization of pile-up-related distortions. However, modern TCSPC configurations that use high-repetition-rate excitation sources for FLIM suffer from dead-time-related distortions that cause unpredictable distortions of the FI signal. In this study, the loss of SNR is described by F- value as it is typically done in FLIM systems. This F-value describes the relation of the relative standard deviation in the estimated FLT to the relative standard deviation in FI measurements. Optimization of the F-value allows minimization of signal distortion, as well as shortening of the acquisition time for certain samples. We applied this method for Fluorescein, Rhodamine B, and Erythrosine fluorescent solutions that have different FLT values (4 ns, 1.67 ns, and 140 ps, respectively). Read more
The effect of GSM-like electromagnetic fields with the resting electroencephalogram (EEG) alpha band activity was investigated in a double-blind cross-over experimental paradigm, testing the hypothesis that pulsed but not continuous radio frequency (RF) exposure would affect alpha activity, and the hypothesis that GSM-like pulsed low frequency fields would affect alpha. Seventy-two healthy volunteers attended a single recording session where the eyes open resting EEG activity was recorded. Four exposure intervals were presented (sham, pulsed modulated RF, continuous RF, and pulsed low frequency) in a counterbalanced order where each exposure lasted for 20 min. Compared to sham, a suppression of the global alpha band activity was observed under the pulsed modulated RF exposure, and this did not differ from the continuous RF exposure. No effect was seen in the extremely low frequency condition. That there was an effect of pulsed RF that did not differ significantly from continuous RF exposure does not support the hypothesis that “pulsed” RF is required to produce EEG effects. The results support the view that alpha is altered by RF electromagnetic fields, but suggest that the pulsing nature of the fields is not essential for this effect to occur. Read more
Novel Bayesian Vectorcardiographic Loop Alignment for Improved Monitoring of ECG and Fetal Movement
The continuous analysis of electrocardiographic (ECG) signals is complicated by morphological variability in the ECG due to movement of the heart. By aligning vectorcardiographic loops, movement-induced ECG variations can be partly corrected for. Existing methods for loop alignment can account for loop rotation, scaling, and time delays, but they lack the possibility to include a priori information on any of these transformations, and they are unreliable in case of low-quality signals, such as fetal ECG signals. The inclusion of a priori information might aid in the robustness of loop alignment and is, hence, proposed in this paper. We provide a generic Bayesian framework to derive our loop alignment method. In this framework, existing methods can be readily derived as well, as a simplification of our method. The loop alignment is evaluated by comparing its performance in loop alignment to two existing methods, for both adult and fetal ECG recordings. For the adult ECG recordings, a quantitative performance assessment shows that the developed method outperforms the existing method in terms of robustness. For the fetal ECG recordings, it is demonstrated that the developed method can be used to correct ECG signals for movement-induced morphology changes (enabling diagnostics) and that the method is capable of classifying recorded ECG signals to periods of fetal movement or rest (
Reduction of the Linear Reflex Gain Explained From the M1–M2 Refractory Period
Linear system identification methods combined with neuromechanical modeling enable the quantification of reflex gains from recorded joint angular perturbation, torque, and/or electromyography (EMG). However, the stretch reflex response as recorded by EMG consists of multiple consecutive activation volleys (M1 and M2 responses) separated by a period of reduced activity and is nonlinearly related to joint perturbation. The goal of this study is to assess to what extent linear assumptions hold when quantifying these reflexive responses. Series of ramp-and-hold angular perturbations with fixed velocity but different ramp durations (and, therefore, different amplitudes) were applied to the wrist joint of seven healthy volunteers. Evoked EMG responses were compared to the reflex response estimated from a common linear reflex model relating EMG to perturbation velocity. Model fits described the measured EMG responses best when the perturbation and M1 response durations were equivalent. With increasing perturbation duration, i.e., amplitude, EMG response increased but reflex gain decreased due to the inert period after M1, which is believed to be related to alignment of the refractory period of the motoneurons. For angular joint perturbations exceeding the M1 duration (coinciding with 2
It is challenging to construct an accurate and smooth mesh for noisy and small
We present an approach to performing rapid calculations of temperature within tissue by interleaving, at regular time intervals, 1) an analytical solution to the Pennes (or other desired) bioheat equation excluding the term for thermal conduction and 2) application of a spatial filter to approximate the effects of thermal conduction. Here, the basic approach is presented with attention to filter design. The method is applied to a few different cases relevant to magnetic resonance imaging, and results are compared to those from a full finite-difference (FD) implementation of the Pennes bioheat equation. It is seen that results of the proposed method are in reasonable agreement with those of the FD approach, with about 15% difference in the calculated maximum temperature increase, but are calculated in a fraction of the time, requiring less than 2% of the calculation time for the FD approach in the cases evaluated. Read more
Optimization of Mechanical Ventilator Settings for Pulmonary Disease States
The selection of mechanical ventilator settings that ensure adequate oxygenation and carbon dioxide clearance while minimizing the risk of ventilator-associated lung injury (VALI) is a significant challenge for intensive-care clinicians. Current guidelines are largely based on previous experience combined with recommendations from a limited number of in vivo studies whose data are typically more applicable to populations than to individuals suffering from particular diseases of the lung. By combining validated computational models of pulmonary pathophysiology with global optimization algorithms, we generate in silico experiments to examine current practice and uncover optimal combinations of ventilator settings for individual patient and disease states. Formulating the problem as a multiobjective, multivariable constrained optimization problem, we compute settings of tidal volume, ventilation rate, inspiratory/expiratory ratio, positive end-expiratory pressure and inspired fraction of oxygen that optimally manage the tradeoffs between ensuring adequate oxygenation and carbon dioxide clearance and minimizing the risk of VALI for different pulmonary disease scenarios. Read more
In this paper, a spiral-type medical robot based on an endoscopic capsule was propelled in a fluidic and tubular environment using electromagnetic actuation. Both modeling and experimental methods have been employed to characterize the propulsion of the robotic capsule. The experiments were performed not only in a simulated environment (vinyl tube filled with silicone oil) but also in a real small intestine. The effects of the spiral parameters including lead, spiral height, the number of spirals, and cross section of the spirals on the propulsion efficiency of the robot are investigated. Based on the transmission efficiency from rotation to translation as well as the balancing of the microrobot in operation, it is demonstrated that the robot with two spirals could provide the best propulsion performance when its lead is slightly smaller than the perimeter of the capsule. As for the spiral height, it is better to use a larger one as long as the intestine's size allows. Based on the simulation and experimental results presented, this study quantifies the influence of the spiral structure on the capsule's propulsion. It provides a helpful reference for the design and optimization of the traction topology of the microrobot navigating inside the mucus-filled small intestine. Read more
This paper presents the results of a feasibility study to demonstrate the application of ultrasound RF time series imaging to accurately differentiate ablated and nonablated tissue. For 12 ex vivo and two in situ tissue samples, RF ultrasound signals are acquired prior to, and following, high-intensity ultrasound ablation. Spatial and temporal features of these signals are used to characterize ablated and nonablated tissue in a supervised-learning framework. In cross-validation evaluation, a subset of four features extracted from RF time series produce a classification accuracy of 84.5%, an area under ROC curve of 0.91 for ex vivo data, and an accuracy of 85% for in situ data. Ultrasound RF time series is a promising approach for characterizing ablated tissue. Read more
There is no abstract available for this journal. Read more
Motion of the Kidney Between Preoperative and Intraoperative Positioning
For many laparoscopic surgical procedures, the preoperative images are taken with the patient in a different position than that in which the surgery is performed. The organ shift between positions can affect surgical image guidance, as the organ shifts can complicate image registration. In particular, for partial nephrectomy, the standard clinical approach requires supine preoperative computed tomography, while the surgery is performed in the flank position. We studied ten subjects in both supine and flank positions. Rigid registration was used to determine the relative motion of the kidneys, using the spine as a pose-independent landmark. Our results showed that the kidney can move as much as 46.5 mm as a result of a supine-to-flank change in patient position, and rotate as much as 25
IEEE Transactions on Biomedical Engineering Associate Editors
There is no abstract available for this journal. Read more