Voluntary Motion Research Articles

Design and Validation of a Modular, Backdrivable Ankle Exoskeleton.

Partial-assist ankle exoskeletons have been limited by inherent trade-offs between favorable characteristics including high torque capacity, high control bandwidth, back-drivability, compliance, and low mass. Emerging quasi-direct drive actuators have a rigid transmission with a low gear ratio, enabling inherent backdrivability and compliance with accurate torque and position control. Our existing modular, backdrivable exoskeleton system (M-BLUE) uses quasi-direct drive actuators at the hip and/or knee to deliver high assistive torques alongside low dynamic backdrive torques, enabling natural interaction with users with remnant voluntary motion. This paper extends our modular system with the design and validation of a back-drivable ankle exoskeleton module to assist both plantarflexion and dorsiflexion. The bi-directional torque capabilities enable the study of control methods and gait outcomes for able-bodied users and users with gait impairments. Benchtop tests of the actuator performance and control bandwidth indicate that the position, voltage, and current control modes can provide assistance to the ankle joint across activities of daily living (ADLs). We also implement an optimal task-agnostic energy shaping controller for an experiment with a single human subject to validate the ability of the ankle exoskeleton to provide biomimetic torque assistance across a circuit of ADLs.

Reducing Motion Artifacts in Craniocervical Background Subtraction Angiography with Deformable Registration and Unsupervised Deep Learning

Abstract Background In clinical practice, digital subtraction angiography (DSA) often suffers from misregistration artifact due to voluntary, respiratory, and cardiac motion during acquisition. Most prior efforts to register the background DSA mask to subsequent post-contrast images rely on key point registration using iterative optimization, which has limited real-time application. Purpose Leveraging state-of-the-art, unsupervised deep learning, we aim to develop a fast, deformable registration model to substantially reduce DSA misregistration in craniocervical angiography without compromising spatial resolution or introducing new artifacts. Methods We extend HyperMorph, an open source deep learning deformable registration framework, to reduce motion artifacts in DSA. Novel image similarity loss functions with vessel layer estimation were introduced to optimize background registration, making it robust to the variable presence of intravascular iodinated contrast. Results A total of 516 studies with 5,240 angiographic series were collected and divided into training (5046 series) and hold-out test (194 series) sets. Blinded algorithm rankings and Likert scores on five-point scales (1 = worst, 5 = best) were generated by three practicing interventional neuroradiologists using 50 series randomly selected from the hold-out test set. Compared to traditional DSA, our learning-based background subtraction angiography (BSA) significant improved vascular fidelity (2.4 ± 0.6 for DSA vs. 3.6 ± 0.5 for BSA), subtraction artifacts (2.0 ± 0.4 for DSA vs. 3.9 ± 0.3 for BSA), and overall quality (2.1 ± 0.5 for DSA vs. 3.9 ± 0.4 for BSA) (p < 0.0001). Learning-based BSA also significantly outperformed affine registration-based BSA (p < 0.0001). The average inference time for learning-based BSA was 30 milliseconds per frame on our hardware. Conclusion The results demonstrate that deep learning deformable registration, combined with an appropriate loss function, can significantly reduce the motion artifacts that degrade DSA.

Decoupled optimal control of 3D biped for human voluntary motion.

The sit-to-stand (STS) model from a biomechanical point of view is an enormously important subject, with motor controls simulating human intended behavior. Physiological motion-based biomechanical research is important for designing whole-body prosthetics and understanding physical disabilities. The control strategies for biomechanical models can effectively synergize with the central nervous system (CNS) to facilitate the desired movements of individuals with neurological disabilities. In this study, we present our novel 3D biped model by decoupling it into healthy and neurologically deficient joints. The developed 8-segment model (i.e., 2× feet, 2× shanks, 2× thighs, 1× pelvic, and 1× Head Arm Torso (HAT) segment) with 10 joints is decoupled into 6 healthy joints and 4 deficient joints. This decoupling mimics stroke patients or subjects with neuromuscular deficiency. This novel decoupling establishes through asymmetrical torques in frontal and sagittal plane joints on a bipedal design with one foot fixed and the other a sliding tilt joint. In this design, two decoupled controllers collaborate to stabilize the nonlinear model for biped STS transfer. Utilizing the xml files from SOLIDWORKS, the model is linearized in SIMSCAPE / SIMULINK. We further imply the Linear Quadratic Regulator (LQR) optimal controller design in MATLAB / SIMULINK for torques in both the sagittal and frontal planes, respectively, for six healthy and four deficient joints. We also comprehend the forward thrust velocity controls to pragmatically model the STS of stroke patients. This decoupling enhanced the overall stability of the system and simulated more relevant angular and velocity profiles for neurologically deficient substances.

Dynamic causal model application on hierarchical human motor control estimation in visuomotor tasks.

In brain function research, each brain region has been investigated independently, and how different parts of the brain work together has been examined using the correlations among them. However, the dynamics of how different brain regions interact with each other during time-varying tasks, such as voluntary motion tasks, are still not well-understood. To address this knowledge gap, we conducted functional magnetic resonance imaging (fMRI) using target tracking tasks with and without feedback. We identified the motor cortex, cerebellum, and visual cortex by using a general linear model during the tracking tasks. We then employed a dynamic causal model (DCM) and parametric empirical Bayes to quantitatively elucidate the interactions among the left motor cortex (ML), right cerebellum (CBR) and left visual cortex (VL), and their roles as higher and lower controllers in the hierarchical model. We found that the tracking task with visual feedback strongly affected the modulation of connection strength in ML → CBR and ML↔VL. Moreover, we found that the modulation of VL → ML, ML → ML, and ML → CBR by the tracking task with visual feedback could explain individual differences in tracking performance and muscle activity, and we validated these findings by leave-one-out cross-validation. We demonstrated the effectiveness of our approach for understanding the mechanisms underlying human motor control. Our proposed method may have important implications for the development of new technologies in personalized interventions and technologies, as it sheds light on how different brain regions interact and work together during a motor task.

An OpenSim-Based Closed-Loop Biomechanical Wrist Model for Subject-Specific Pathological Tremor Simulation.

A pathological tremor (PT) is an involuntary rhythmic movement of varying frequency and amplitude that affects voluntary motion, thus compromising individuals' independence. A comprehensive model incorporating PT's physiological and biomechanical aspects can enhance our understanding of the disorder and provide valuable insights for therapeutic approaches. This study aims to build a biomechanical model of pathological tremors using OpenSim's realistic musculoskeletal representation of the human wrist with two degrees of freedom. We implemented a Matlab/OpenSim interface for a forward dynamics simulation, which allows for the modeling, simulation, and design of a physiological H∞ closed-loop control. This system replicates pathological tremors similar to those observed in patients when their arm is extended forward, the wrist is pronated, and the hand is subject to gravity forces. The model was individually tuned to five subjects (four Parkinson's disease patients and one diagnosed with essential tremor), each exhibiting distinct tremor characteristics measured by an inertial sensor and surface EMG electrodes. Simulation agreement with the experiments for EMGs, central frequency, joint angles, and angular velocities were evaluated by Jensen-Shannon divergence, histogram centroid error, and histogram intersection. The model emulated individual tremor statistical characteristics, including muscle activations, frequency, variability, and wrist kinematics, with greater accuracy for the four Parkinson's patients than the essential tremor. The proposed model replicated the main statistical features of subject-specific wrist tremor kinematics. Our methodology may facilitate the design of patient-specific rehabilitation devices for tremor suppression, such as neural prostheses and electromechanical orthoses.

Fast high-resolution prospective motion correction for single-voxel spectroscopy.

To develop a fast high-resolution image-based motion correction method using spiral navigators with multislice-to-volume registration. A semi-LASER sequence was modified to include a multislice spiral navigator for prospective motion correction (∼305 ms including acquisition, processing, and feedback) as well as shim and frequency navigators for prospective shim and frequency correction (∼100 ms for each). MR spectra were obtained in the prefrontal cortex in five healthy subjects at 3 T with and without prospective motion and shim correction. The effect of key navigator parameters (number of slices, image resolution, and excitation flip angle) on registration accuracy was assessed using simulations. Without prospective motion and shim correction, spectral quality degraded significantly in the presence of voluntary motion. In contrast, with prospective motion and shim correction, spectral quality was improved (metabolite linewidth = 6.7 ± 0.6 Hz, SNR= 67 ± 9) and in good agreement with baseline data without motion (metabolite linewidth = 6.9 ± 0.9 Hz, SNR = 73 ± 9). In addition, there was no significant difference in metabolites concentrations measured without motion and with prospective motion and shim correction in the presence of motion. Simulations showed that the registration precision was comparable when using three navigator slices with 3 mm resolution and when using the entire volume (all slices) with 8 mm resolution. The proposed motion correction scheme allows fast and precise prospective motion and shim correction for single-voxel spectroscopy at 3 T. With 3 mm resolution, only a few navigator slices are necessary to achieve excellent motion correction performance.

High-density transcranial direct current stimulation to improve upper limb motor function following stroke: study protocol for a double-blind randomized clinical trial targeting prefrontal and/or cerebellar cognitive contributions to voluntary motion

BackgroundFocal brain lesions following a stroke of the middle cerebral artery induce large-scale network disarray with a potential to impact multiple cognitive and behavioral domains. Over the last 20 years, non-invasive brain neuromodulation via electrical (tCS) stimulation has shown promise to modulate motor deficits and contribute to recovery. However, weak, inconsistent, or at times heterogeneous outcomes using these techniques have also highlighted the need for novel strategies and the assessment of their efficacy in ad hoc controlled clinical trials.MethodsWe here present a double-blind, sham-controlled, single-center, randomized pilot clinical trial involving participants having suffered a unilateral middle cerebral artery (MCA) stroke resulting in motor paralysis of the contralateral upper limb. Patients will undergo a 10-day regime (5 days a week for 2 consecutive weeks) of a newly designed high-definition transcranial direct current stimulation (HD-tDCS) protocol. Clinical evaluations (e.g., Fugl Meyer, NIHSS), computer-based cognitive assessments (visuo-motor adaptation and AX-CPT attention tasks), and electroencephalography (resting-state and task-evoked EEG) will be carried out at 3 time points: (I) Baseline, (II) Post-tDCS, and (III) Follow-up. The study consists of a four-arm trial comparing the impact on motor recovery of three active anodal tDCS conditions: ipsilesional DLPFC tDCS, contralesional cerebellar tDCS or combined DLPFC + contralesional cerebellar tDCS, and a sham tDCS intervention. The Fugl-Meyer Assessment for the upper extremity (FMA-UE) is selected as the primary outcome measure to quantify motor recovery. In every stimulation session, participants will receive 20 min of high-density tDCS stimulation (HD-tDCS) (up to 0.63 mA/cm2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathrm{cm}}^{2}$$\\end{document}) with πcm2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathrm{\\pi cm}}^{2}$$\\end{document} electrodes. Electrode scalp positioning relative to the cortical surface (anodes and cathodes) and intensities are based on a biophysical optimization model of current distribution ensuring a 0.25 V/m impact at each of the chosen targets.DiscussionOur trial will gauge the therapeutic potential of accumulative sessions of HD-tDCS to improve upper limb motor and cognitive dysfunctions presented by middle cerebral artery stroke patients. In parallel, we aim at characterizing changes in electroencephalographic (EEG) activity as biomarkers of clinical effects and at identifying potential interactions between tDCS impact and motor performance outcomes. Our work will enrich our mechanistic understanding on prefrontal and cerebellar contributions to motor function and its rehabilitation following brain damage.Trial registrationClinicalTrials.gov NCT05329818. April 15, 2022.

A treatment strategy for recurrent (ankle injuries) in Muay Thai athletes

Objective: An efficient solution for stabilization is the mobilization of the joints for the arthrokinematics affected by the positional defect of the CAI (i.e. chronic ankle instability). This study put to comparison the impacts of ankle dorsi flexion range of motion (DFROM) as well as dynamic balance ability (DBA) in the patients who have CAI using PJM (i.e. passive joint mobilization), a technique typically been used in previous works, and active joint mobilization (AJM), a technique which could have a greater impact on cortical excitability with the spontaneous movement. Design: rehabilitation program to treat recurrent ankle. Methods: A total of 10 players from the Iraqi clubs Muay Thai team were registered, 5 from each of the AJM and PJM groups. A total of 12 intervention sessions overall, lasting 10 mins each, were given to each participant over the course of three weeks. AJM employed angular motion of the joints to produce the patient's voluntary motion regarding lateral malleolus posterior gliding as well as medial malleolus anterior gliding, respectively, while PJM utilized Maitland's mobilization approach to perform mobilization of the joints with the talus in the posterior direction. Tape was used for measuring the ankle's DFROM, and the balance system was used to assess the ankle's DBA. Results: With the exception of DBA-right and DBA-anterior variables with regard to PJM group, considerable enhancements were seen following intervention in AJM as well as groups of the PJM. DBA-anterior, DFROM, DBA-right, and DBA-posterior, measures showed statistically significant differences between the PJM group and the AJM group. Conclusions: Joint mobilization, such as voluntary movement, was more successful thanks to the overall improvement regarding DBA and DFROM. The ankle's neuromuscular system is significantly impacted in the case when voluntary movement is present.

Uyghur–Chinese early successive bilingual children's acquisition of voluntary motion expressions

Abstract This study explores the implications of Talmy's (2000) motion event typology and its subsequent articulations in relation to Slobin's (1996, 2006) thinking-for-speaking hypothesis for the early successive bilingual acquisition of Uyghur (verb-framed) and Mandarin Chinese (equipollently-framed). Specifically, it examines how 4-, 6-, 8- and 10-year-old bilingual children acquire motion expressions in their L1 and L2 respectively, and how cross-linguistic influence shapes their L2 acquisition process. Results show that, in their L1 Uyghur, bilinguals follow general developmental trajectories observed for children acquiring verb-framed languages. While sensitive to the equipollent Chinese system from early on, due to L1 and other factors, bilinguals fully converge on the Chinese pattern only at age 10, a feat in place in monolinguals from age 3. Our findings highlight that bilingual children do eventually come to develop language-specific thinking-for-speaking patterns in their L2, but they traverse a distinct developmental path.

Endothelin Modulates Rhythm Disturbances and Autonomic Responses to Acute Emotional Stress in Rats.

The ubiquitous peptide endothelin is currently under investigation as a modulatory factor of autonomic responses to acute emotional stress. Baseline plasma levels of endothelin alter blood pressure responses, but it remains unclear whether autonomic activity and arrhythmogenesis (i.e., brady- or tachyarrhythmias) are affected. We recorded sympathetic and vagal indices (derived from heart rate variability analysis), rhythm disturbances, voluntary motion, and systolic blood pressure after acute emotional stress in conscious rats with implanted telemetry devices. Two strains were compared, namely wild-type and ETB-deficient rats, the latter displaying elevated plasma endothelin. No differences in heart rate or blood pressure were evident, but sympathetic responses were blunted in ETB-deficient rats, contrasting prompt activation in wild-type rats. Vagal withdrawal was observed in both strains at the onset of stress, but vagal activity was subsequently restored in ETB-deficient rats, accompanied by low voluntary motion during recovery. Reflecting such distinct autonomic patterns, frequent premature ventricular contractions were recorded in wild-type rats, as opposed to sinus pauses in ETB-deficient rats. Thus, chronically elevated plasma endothelin levels blunt autonomic responses to acute emotional stress, resulting in vagal dominance and bradyarrhythmias. Our study provides further insights into the pathophysiology of stress-induced tachyarrhythmias and syncope.

On Lexicalization Pattern of Caused Motion Events by Chinese Children

The lexicalization of Chinese motion events has been a controversial topic. Most of previous studies on the lexicalization patterns of Chinese movement events has been conducted with laboratory experiments, leaving the natural Chinese motion events in daily life unstudied. Therefore, this paper investigates the language acquisition process of Chinese children resulting in movement events based on naturalistic data of language development from 13 to 48 months in Mandarin-speaking children SWK, which greatly reduces the influence of human factors on the findings. The results showed that 1) path verbs developed slightly faster than manner verbs at all times. Besides, both kinds of verbs develop fastest at the age of 2-3 years, and peak at the age of 3 years. 2) Modern Chinese exhibits the characteristics of a satellite-framed language in some aspects. 3) Caused motion events develop slower than voluntary motion events.

Muscular and Kinematic Responses to Unexpected Translational Balance Perturbation: A Pilot Study in Healthy Young Adults.

Falls and fall-related injuries are significant public health problems in older adults. While balance-controlling strategies have been extensively researched, there is still a lack of understanding regarding how fast the lower-limb muscles contract and coordinate in response to a sudden loss of standing balance. Therefore, this pilot study aims to investigate the speed and timing patterns of multiple joint/muscles' activities among the different challenges in standing balance. Twelve healthy young subjects were recruited, and they received unexpected translational balance perturbations with randomized intensities and directions. Electromyographical (EMG) and mechanomyographical (MMG) signals of eight dominant-leg's muscles, dominant-leg's three-dimensional (3D) hip/knee/ankle joint angles, and 3D postural sways were concurrently collected. Two-way ANOVAs were used to examine the difference in timing and speed of the collected signals among muscles/joint motions and among perturbation intensities. This study has found that (1) agonist muscles resisting the induced postural sway tended to activate more rapidly than the antagonist muscles, and ankle muscles contributed the most with the fastest rate of response; (2) voluntary corrective lower-limb joint motions and postural sways could occur as early as the perturbation-induced passive ones; (3) muscles reacted more rapidly under a larger perturbation intensity, while the joint motions or postural sways did not. These findings expand the current knowledge on standing-balance-controlling mechanisms and may potentially provide more insights for developing future fall-prevention strategies in daily life.

Functional Outcome of Dual Reinnervation with Cross-Facial Nerve Graft and Masseteric Nerve Transfer for Facial Paralysis.

The combination of cross-facial nerve graft (CFNG) and masseteric nerve transfer (MNT) for reinnervation of facial paralysis may provide advantages of both neural sources. However, quantitative functional outcome reports with a larger number of patients are lacking in the literature. Here, the authors describe their 8-year experience with this surgical technique. Twenty patients who presented with complete facial paralysis (duration, <12 months) received dual reinnervation with CFNG and MNT. The functional outcome of the procedure was evaluated with the physician-graded outcome metric eFACE scale. The objective artificial intelligence-driven software Emotrics and FaceReader were used for oral commissure measurements and emotional expression assessment, respectively. The mean follow-up was 31.75 ± 23.32 months. In the eFACE score, the nasolabial fold depth and oral commissure at rest improved significantly ( P < 0.05) toward a more balanced state after surgery. Postoperatively, there was a significant decrease in oral commissure asymmetry while smiling (from 19.22 ± 6.1 mm to 12.19 ± 7.52 mm). For emotional expression, the median intensity score of happiness, as measured by the FaceReader software, increased significantly while smiling (0.28; interquartile range, 0.13 to 0.64). In five patients (25%), a secondary static midface suspension with fascia lata strip had to be performed because of unsatisfactory resting symmetry. Older patients and patients with greater preoperative resting asymmetry were more likely to receive static midface suspension. The authors' results suggest that the combination of MNT and CFNG for reinnervation of facial paralysis provides good voluntary motion and may lessen the use of static midface suspension in the majority of patients. Therapeutic, IV.

A Real-Time Voluntary Motion Extraction Method Based on an Adaptive Filter

Tremors are a symptom of several disorders of the central and peripheral nervous systems, such as Parkinson’s disease (PD). Exoskeletons have been investigated as noninvasive tremor suppression alternatives to medication and surgery. The challenge in musculoskeletal tremor suppression is attenuation of tremor motion without impeding the patient’s voluntary motion. Linear low-pass filters (LPFs) are commonly used for tremor removal. This study presents an alternative method based on an adaptive filter. We compare the effectiveness of the LPFs and adaptive filter on the recorded acceleration signals from an online database.

An Unobtrusive Method for Remote Quantification of Parkinson’s and Essential Tremor Using mm-Wave Sensing

Tremor is a primary symptom of common movement disorders such as Essential tremor and Parkinson’s disease. People experiencing tremors face difficulty in performing everyday tasks which negatively impacts their independence. Tremor quantification helps clinicians in evaluating disease progression and treatment response. Majority of the existing methods include cameras or motion sensors embedded in wearables and hand-held devices. The continuous wearing of contact sensors can be uneasy for the patients while the cameras cause privacy concerns. This paper proposes a novel method for tremor quantification using a Frequency Modulated Continuous Wave (FMCW) radar sensor. In this paper, an off-the shelf, low-cost FMCW radar has been configured to capture vibrations induced in distal limbs, a representative feature of Essential and Parkinson’s Tremors. Moreover, a signal processing chain is developed to extract characteristic tremor frequency and amplitude by reconstructing the tremor signal from the radar return signals. For robustness and increased accuracy, static clutter and voluntary body motion are eliminated. Extensive experiments were performed and results were compared to the state-of-the-art methods that use accelerometers and gyroscopes. A strong correlation ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> >0.97) is found between the reference sensor readings and predicted values for both quantified parameters. The mean error for the frequency and amplitude is 0.14Hz and 0.03cm, respectively. Results demonstrate a superior accuracy as compared to the existing non-contact techniques, with the added advantage of privacy and integrity preserving for the end-user. Hence, the proposed system can provide reliable long-term objective assessment, aiding clinicians in the evaluation of tremor severity and treatment effectiveness.

Deep learning for improving PET/CT attenuation correction by elastic registration of anatomical data.

For PET/CT, the CT transmission data are used to correct the PET emission data for attenuation. However, subject motion between the consecutive scans can cause problems for the PET reconstruction. A method to match the CT to the PET would reduce resulting artifacts in the reconstructed images. This work presents a deep learning technique for inter-modality, elastic registration of PET/CT images for improving PET attenuation correction (AC). The feasibility of the technique is demonstrated for two applications: general whole-body (WB) imaging and cardiac myocardial perfusion imaging (MPI), with a specific focus on respiratory and gross voluntary motion. A convolutional neural network (CNN) was developed and trained for the registration task, comprising two distinct modules: a feature extractor and a displacement vector field (DVF) regressor. It took as input a non-attenuation-corrected PET/CT image pair and returned the relative DVF between them-it was trained in a supervised fashion using simulated inter-image motion. The 3D motion fields produced by the network were used to resample the CT image volumes, elastically warping them to spatially match the corresponding PET distributions. Performance of the algorithm was evaluated in different independent sets of WB clinical subject data: for recovering deliberate misregistrations imposed in motion-free PET/CT pairs and for improving reconstruction artifacts in cases with actual subject motion. The efficacy of this technique is also demonstrated for improving PET AC in cardiac MPI applications. A single registration network was found to be capable of handling a variety of PET tracers. It demonstrated state-of-the-art performance in the PET/CT registration task and was able to significantly reduce the effects of simulated motion imposed in motion-free, clinical data. Registering the CT to the PET distribution was also found to reduce various types of AC artifacts in the reconstructed PET images of subjects with actual motion. In particular, liver uniformity was improved in the subjects with significant observable respiratory motion. For MPI, the proposed approach yielded advantages for correcting artifacts in myocardial activity quantification and potentially for reducing the rate of the associated diagnostic errors. This study demonstrated the feasibility of using deep learning for registering the anatomical image to improve AC in clinical PET/CT reconstruction. Most notably, this improved common respiratory artifacts occurring near the lung/liver border, misalignment artifacts due to gross voluntary motion, and quantification errors in cardiac PET imaging.

Commissioning, clinical implementation, and initial experience with a new brain tumor treatment package on a low-field MR-linac.

To evaluate the image quality, dosimetric properties, setup reproducibility, and planar cine motion detection of a high-resolution brain coil and integrated stereotactic brain immobilization system that constitute a new brain treatment package (BTP) on a low-field magnetic resonance imaging (MRI) linear accelerator (MR-linac). Image quality of the high-resolution brain coil was evaluated with the 17cm diameter spherical phantom and the American College of Radiology (ACR) Large MRI Phantom. Patient imaging studies approved by the institutional review board (IRB) assisted in selecting image acquisition parameters. Radiographic and dosimetric evaluation of the high-resolution brain coil and the associated immobilization devices was performed using dose calculations and ion chamber measurements. End-to-end testing was performed simulating a cranial lesion in a phantom. Inter-fraction setup variability and motion detection tests were evaluated on four healthy volunteers. Inter-fraction variability was assessed based on three repeat setups for each volunteer. Motion detection was evaluated using three-plane (axial, coronal, and sagittal) MR-cine imaging sessions, where volunteers were asked to perform a set of specific motions. The images were post-processed and evaluated using anin-house program. Contrast resolution of the high-resolution brain coil is superior to the head/neck and torso coils. The BTP receiver coils have an average HU value of 525 HU. The most significant radiation attenuation (3.14%) of the BTP, occurs through the lateral portion of the overlay board where the high-precision lateral-profile mask clips attach to the overlay. The greatest inter-fraction setup variability occurred in the pitch (average 1.08 degree) and translationally in the superior/inferior direction (average 4.88mm). Three plane cine imaging with the BTP was able to detect large and small motions. Small voluntary motions, sub-millimeter in magnitude (maximum 0.9mm), from motion of external limbs were detected. Imaging tests, inter-fraction setup variability, attenuation, and end-to-end measurements were quantified and performed for the BTP. Results demonstrate better contrast resolution and low contrast detectability that allows for better visualization of soft tissue anatomical changes relative to head/neck and torso coil systems.

Biomimetic Tendon-Based Mechanism for Finger Flexion and Extension in a Soft Hand Exoskeleton: Design and Experimental Assessment.

This study proposes a bioinspired exotendon routing configuration for a tendon-based mechanism to provide finger flexion and extension that utilizes a single motor to reduce the complexity of the system. The configuration was primarily inspired by the extrinsic muscle-tendon units of the human musculoskeletal system. The function of the intrinsic muscle-tendon units was partially compensated by adding a minor modification to the configuration of the extrinsic units. The finger kinematics produced by this solution during flexion and extension were experimentally evaluated on an artificial finger and compared to that obtained using the traditional mechanism, where one exotendon was inserted at the distal phalanx. The experiments were conducted on nine healthy subjects who wore a soft exoskeleton glove equipped with the novel tendon mechanism. Contrary to the traditional approach, the proposed mechanism successfully prevented the hyperextension of the distal interphalangeal (DIP) and the metacarpophalangeal (MCP) joints. During flexion, the DIP joint angles produced by the novel mechanism were smaller than the angles generated by the traditional approach for the same proximal interphalangeal (PIP) joint angles. This provided a flexion trajectory closer to the voluntary flexion motion and avoided straining the interphalangeal coupling between the DIP and PIP joints. Finally, the proposed solution generated similar trajectories when applied to a stiff artificial finger (simulating spasticity). The results, therefore, demonstrate that the proposed approach is indeed an effective solution for the envisioned soft hand exoskeleton system.

A Real-Time Bionic Method Inspired by Neural Oscillators for Estimation and Extraction of Pathological Tremor.

The typical representative of pathological tremor is Parkinson's disease. One of the pathogenesis is that the synchronized neural oscillations within and between brain areas are affected. Inspired by this, this work proposes an algorithm based on neural oscillator to extract voluntary motion and estimate tremor motion in real time, which is named as RTBNO. This algorithm is composed of multiple adaptive modified Hopf oscillators linear combiner. The combiner is divided into two parts: one is used to estimate tremor motion and the other is applied to estimate voluntary motion. As it is updated iteratively in real time, this method has no phase delay. The performance of the proposed method was verified by the simulated action tremor and the actual experimental results of twenty Parkinson's disease patients. For the rest tremor signals of patients, the mean Root Mean Square Error (RMSE) values between the estimated signal and the actual signal was 0.0272±0.0077. The mean RMSE values between the estimated voluntary movement from action tremor and the actual voluntary movement were 0.0360±0.0097 (pick and put motion) and 0.0380±0.0083 (drawing motion). The execution time for the corresponding 10 seconds data was 0.0478s. The comparison results between the proposed method and the existing methods demonstrated the effectiveness of the proposed method.

Retracted: Design of LoRa Antenna for Wearable Medical Applications

The intraoral Tongue Drive System (iTDS) is a wireless assistive technology (AT) that may be operated using a variety of user-defined voluntary tongue motions. In this study, we introduce a novel arch-shaped iTDS that takes up the buccal shelf space in the mouth without constricting tongue motions. Damage to the central nervous system that causes upper limb paralysis. For instance, severe spinal cord injuries, certain strokes or multiple amputations of the upper limbs can make it very difficult for a lot of individuals to go about their everyday lives since they cause them to lose function, control, and independence. Because its muscles are strong and dexterous and do not quickly tire when not necessary to exert power, the tongue is an excellent choice for controlling an AT. Additionally, through cranial nerves, which are unaffected by a spinal cord damage, the tongue is directly attached to the brain. Furthermore, since the tongue movements may be totally hidden from view, TDS-based AT safeguard users’ privacy. In order to provide an effective solution, this paper proposed a novel antenna design with dual-band and implantability. The antenna is modelled in single-layer human muscle considering the feasibility and computational time. Then, the performance is evaluated through multi-layered human oral cavity model. A protective layer is established to prevent direct contact between the antenna and human body. Simulation results show that the proposed antenna has better reflection coefficient, impedance, and radiation pattern as compared with existing antennas.