Targeting Transcutaneous Spinal Cord Stimulation Using a Supervised Machine Learning Approach Based on Mechanomyography.

Transcutaneous spinal cord stimulation (tSCS) provides a promising therapy option for individuals with injured spinal cords and multiple sclerosis patients with spasticity and gait deficits. Before the therapy, the examiner determines a suitable electrode position and stimulation current for a controlled application. For that, amplitude characteristics of posterior root muscle (PRM) responses in the electromyography (EMG) of the legs to double pulses are examined. This laborious procedure holds potential for simplification due to time-consuming skin preparation, sensor placement, and required expert knowledge. Here, we investigate mechanomyography (MMG) that employs accelerometers instead of EMGs to assess muscle activity. A supervised machine-learning classification approach was implemented to classify the acceleration data into no activity and muscular/reflex responses, considering the EMG responses as ground truth. The acceleration-based calibration procedure achieved a mean accuracy of up to 87% relative to the classical EMG approach as ground truth on a combined cohort of 11 healthy subjects and 11 patients. Based on this classification, the identified current amplitude for the tSCS therapy was in 85%, comparable to the EMG-based ground truth. In healthy subjects, where both therapy current and position have been identified, 91% of the outcome matched well with the EMG approach. We conclude that MMG has the potential to make the tuning of tSCS feasible in clinical practice and even in home use.

Avoiding screw overlength using dorsal horizon view in palmar plate osteosynthesis of distal radius fractures: a prospective randomized trial.

INTRODUCTION: Distal radius fractures are the most commonly reported fractures in adults. Treatment has changed in recent years to open reduction and palmar plate fixation. Penetration of the dorsal screw, however, is a well-known complication. Intraoperative anteroposterior and lateral radiographs lack the exact assessment of dorsal screw length and intraoperative measurement is therefore very likely to be inaccurate in a comminuted dorsal radial cortex. Secondary extensor tendon ruptures are reported in up to 6% following palmar plate fixation of distal radius fracture. MATERIALS AND METHODS: A prospective randomized trial was performed to assess the value of the dorsal horizon view. The hypothesis was that the traditional anteroposterior and lateral fluoroscopic views aided by an axial view of the dorsal part of the radius, named dorsal horizon view, could prevent dorsal screw penetration. A total of 40 patients, 6 male and 34 female, were included in the study. Standardized anteroposterior and lateral radiographs were performed intraoperatively in 18 patients (standard group = control group). In 22 patients, intraoperative axial fluoroscopic views (dorsal horizon view) were added to anteroposterior and lateral images (horizon group). Numbers of intraoperative screw changes due to the two different radiological examinations were analyzed as well as exact postoperative CT guided measurement of screw length. RESULTS: The total numbers of intraoperative screw changes were significantly higher in the horizon group. Forty-two screws were changed in 15 patients in the horizon group while only 8 screws were changed in 3 patients in the standard group. Postoperative computed tomography scans showed significantly lower total numbers of perforating screws in the horizon group with 11 screws in 22 patients compared to 20 screws in 18 patients in the standard group (p = 0.02). CONCLUSIONS: Based on the results of this study, the dorsal horizon view improves the assessment of the correct screw length and should routinely be used in palmar plate osteosynthesis of distal radius fractures. Since screw protrusion cannot be absolutely ruled out using the dorsal horizon view, monocortical drilling or screw downsizing is still mandatory. TRIAL REGISTRATION: This clinical trial was not registered because it was a clinical examination without any experimental techniques.

Reactive Exercises with Interactive Objects: Interim Analysis of a Randomized Trial on Task-Driven NMES Grasp Rehabilitation for Subacute and Early Chronic Stroke Patients.

Enriched environments and tools are believed to promote grasp rehabilitation after stroke. We designed S2, an interactive grasp rehabilitation system consisting of smart objects, custom orthoses for selective grasp constraining, and an electrode array system for forearm NMES. Motor improvements and perceived usability of a new enriched upper limb training system for sub-acute stroke patients was assessed in this interim analysis. INCLUSION CRITERIA: sub-acute stroke patients with MMSE>20, ipsilesional MI>80%, and contralesional MI<80%. Effects of 30-min therapy supplements, conventional vs. S2 prototype, are compared through a parallel two-arms dose-matched open-label trial, lasting 27 sessions. Clinical centres: Asklepios Neurologische Klinik Falkenstein, Königstein im Taunus, Germany, and Clinica Villa Beretta, Costa Masnaga, Italy. Assessment scales: ARAT, System Usability, and Technology Acceptance. METHODOLOGY: 26 participants were block randomized, allocated to the study (control N=12, experimental N=14) and underwent the training protocol. Among them, 11 participants with ARAT score at inclusion below 35, n = 6 in the experimental group, and n = 5 in the control group were analysed. RESULTS: participants in the enriched treatment group displayed a larger improvement in the ARAT scale (+14.9 pts, pval=0.0494). Perceived usability differed between clinics. No adverse effect was observed in relation to the treatments. Trial status: closed. CONCLUSIONS: The S2 system, developed according to shared clinical directives, was tested in a clinical proof of concept. Variations of ARAT scores confirm the feasibility of clinical investigation for hand rehabilitation after stroke.

Adaptive multichannel FES neuroprosthesis with learning control and automatic gait assessment.

BACKGROUND: FES (Functional Electrical Stimulation) neuroprostheses have long been a permanent feature in the rehabilitation and gait support of people who had a stroke or have a Spinal Cord Injury (SCI). Over time the well-known foot switch triggered drop foot neuroprosthesis, was extended to a multichannel full-leg support neuroprosthesis enabling improved support and rehabilitation. However, these neuroprostheses had to be manually tuned and could not adapt to the persons' individual needs. In recent research, a learning controller was added to the drop foot neuroprosthesis, so that the full stimulation pattern during the swing phase could be adapted by measuring the joint angles of previous steps. METHODS: The aim of this research is to begin developing a learning full-leg supporting neuroprosthesis, which controls the antagonistic muscle pairs for knee flexion and extension, as well as for ankle joint dorsi- and plantarflexion during all gait phases. A method was established that allows a continuous assessment of knee and foot joint angles with every step. This method can warp the physiological joint angles of healthy subjects to match the individual pathological gait of the subject and thus allows a direct comparison of the two. A new kind of Iterative Learning Controller (ILC) is proposed which works independent of the step duration of the individual and uses physiological joint angle reference bands. RESULTS: In a first test with four people with an incomplete SCI, the results showed that the proposed neuroprosthesis was able to generate individually fitted stimulation patterns for three of the participants. The other participant was more severely affected and had to be excluded due to the resulting false triggering of the gait phase detection. For two of the three remaining participants, a slight improvement in the average foot angles could be observed, for one participant slight improvements in the averaged knee angles. These improvements where in the range of 4circat the times of peak dorsiflexion, peak plantarflexion, or peak knee flexion. CONCLUSIONS: Direct adaptation to the current gait of the participants could be achieved with the proposed method. The preliminary first test with people with a SCI showed that the neuroprosthesis can generate individual stimulation patterns. The sensitivity to the knee angle reset, timing problems in participants with significant gait fluctuations, and the automatic ILC gain tuning are remaining issues that need be addressed. Subsequently, future studies should compare the improved, long-term rehabilitation effects of the here presented neuroprosthesis, with conventional multichannel FES neuroprostheses.

Supporting front crawl swimming in paraplegics using electrical stimulation: a feasibility study.

BACKGROUND: Participation in physical and therapeutic activities is usually severely restricted after a spinal cord injury (SCI). Reasons for this are the associated loss of voluntary motor function, inefficient temperature regulation of the affected extremities, and early muscle fatigue. Hydrotherapy or swim training offer an inherent weight relief, reduce spasticity and improve coordination, muscle strength and fitness. METHODS: We present a new hybrid exercise modality that combines functional electrical stimulation (FES) of the knee extensors and transcutaneous spinal cord stimulation (tSCS) with paraplegic front crawl swimming. tSCS is used to stimulate the afferent fibers of the L2-S2 posterior roots for spasticity reduction. By activating the tSCS, the trunk musculature is recruited at a motor level. This shall improve trunk stability and straighten the upper body. Within this feasibility study, two complete SCI subjects (both ASIA scale A, lesion level Th5/6), who have been proficient front crawl swimmers, conducted a 10-week swim training with stimulation support. In an additional assessment swim session nine months after the training, the knee extension, hip extension, and trunk roll angles where measured using waterproof inertial measurement units (IMUs) and compared for different swimming conditions (no stimulation, tSCS, FES, FES plus tSCS). RESULTS: For both subjects, a training effect over the 10-week swim training was observed in terms of measured lap times (16 m pool) for all swimming conditions. Swimming supported by FES reduced lap times by 15.4% and 8.7% on average for Subject A and Subject B, respectively. Adding tSCS support yielded even greater mean decreases of 19.3% and 20.9% for Subjects A and B, respectively. Additionally, both subjects individually reported that swimming with tSCS for 30-45 minutes eliminated spasticity in the lower extremities for up to 4 hours beyond the duration of the session. Comparing the median as well as the interquartile range of all different settings, the IMU-based motion analysis revealed that FES as well as FES+tSCS improve knee extension in both subjects, while hip extension was only increased in one subject. Trunk roll angles were similar for all swimming conditions. tSCS had no influence on the knee and hip joint angles. Both subjects reported that stimulation-assisted swimming is comfortable, enjoyable, and they would like to use such a device for recreational training and rehabilitation in the future. CONCLUSIONS: Stimulation-assisted swimming seems to be a promising new form of hybrid exercise for SCI people. It is safe to use with reusable silicone electrodes and can be performed independently by experienced paraplegic swimmers except for transfer to water. The study results indicate that swimming speed can be increased by the proposed methods and spasticity can be reduced by prolonged swim sessions with tSCS and FES. The combination of stimulation with hydrotherapy might be a promising therapy for neurologic rehabilitation in incomplete SCI, stroke or multiples sclerosis patients. Therefore, further studies shall incorporate other neurologic disorders and investigate the potential benefits of FES and tSCS therapy in the water for gait and balance.

A Tangible Solution for Hand Motion Tracking in Clinical Applications.

Objective real-time assessment of hand motion is crucial in many clinical applications including technically-assisted physical rehabilitation of the upper extremity. We propose an inertial-sensor-based hand motion tracking system and a set of dual-quaternion-based methods for estimation of finger segment orientations and fingertip positions. The proposed system addresses the specific requirements of clinical applications in two ways: (1) In contrast to glove-based approaches, the proposed solution maintains the sense of touch. (2) In contrast to previous work, the proposed methods avoid the use of complex calibration procedures, which means that they are suitable for patients with severe motor impairment of the hand. To overcome the limited significance of validation in lab environments with homogeneous magnetic fields, we validate the proposed system using functional hand motions in the presence of severe magnetic disturbances as they appear in realistic clinical settings. We show that standard sensor fusion methods that rely on magnetometer readings may perform well in perfect laboratory environments but can lead to more than 15 cm root-mean-square error for the fingertip distances in realistic environments, while our advanced method yields root-mean-square errors below 2 cm for all performed motions.

User-centered practicability analysis of two identification strategies in electrode arrays for FES induced hand motion in early stroke rehabilitation.

BACKGROUND: Surface electrode arrays have become popular in the application of functional electrical stimulation (FES) on the forearm. Arrays consist of multiple, small elements, which can be activated separately or in groups, forming virtual electrodes (VEs). As technology progress yields rising numbers of possible elements, an effective search strategy for suitable VEs in electrode arrays is of increasing importance. Current methods can be time-consuming, lack user integration, and miss an evaluation regarding clinical acceptance and practicability. METHODS: Two array identification procedures with different levels of user integration-a semi-automatic and a fully automatic approach-are evaluated. The semi-automatic method allows health professionals to continuously modify VEs via a touchscreen while the stimulation intensities are automatically controlled to maintain sufficient wrist extension. The automatic approach evaluates stimulation responses of various VEs for different intensities using a cost function and joint-angles recordings. Both procedures are compared in a clinical setup with five sub-acute stroke patients with moderate hand disabilities. The task was to find suitable VEs in two arrays with 59 elements in total to generate hand opening and closing for a grasp-and-release task. Practicability and acceptance by patients and health professionals were investigated using questionnaires and interviews. RESULTS: Both identification methods yield suitable VEs for hand opening and closing in patients who could tolerate the stimulation. However, the resulting VEs differed for both approaches. The average time for a complete search was 25% faster for the semi-automatic approach (semi-automatic: 7.3min, automatic: 10.5min). User acceptance was high for both methods, while no clear preference could be identified. CONCLUSIONS: The semi-automatic approach should be preferred as the search strategy in arrays on the forearm. The observed faster search duration will further reduce when applying the system repeatedly on a patient as only small position adjustments for VEs are required. However, the setup time will significantly increase for generation of various grasp types and adaptation to different arm postures. We recommend different levels of user integration in FES systems such that the search strategy can be chosen based on the users' preferences and application scenario.

Automated detection and evaluation of swallowing using a combined EMG/bioimpedance measurement system.

INTRODUCTION: Developing an automated diagnostic and therapeutic instrument for treating swallowing disorders requires procedures able to reliably detect and evaluate a swallow. We tested a two-stage detection procedure based on a combined electromyography/bioimpedance (EMBI) measurement system. EMBI is able to detect swallows and distinguish them from similar movements in healthy test subjects. STUDY DESIGN: The study was planned and conducted as a case-control study (EA 1/019/10, and EA1/160/09, EA1/161/09). METHOD: The study looked at differences in swallowing parameters in general and in the event of penetration during swallows in healthy subjects and in patients with an oropharyngeal swallowing disorder. A two-stage automated swallow detection procedure which used electromyography (EMG) and bioimpedance (BI) to reliably detect swallows was developed. RESULTS: Statistically significant differences between healthy subjects and patients with a swallowing disorder were found in swallowing parameters previously used to distinguish between swallowing and head movements. Our two-stage algorithm was able to reliably detect swallows (sensitivity = 96.1%, specificity = 97.1%) on the basis of these differences. DISCUSSION: Using a two-stage detection procedure, the EMBI measurement procedure is able to detect and evaluate swallows automatically and reliably. The two procedures (EMBI + swallow detection) could in future form the basis for automated diagnosis and treatment (stimulation) of swallowing disorders.

IMU-based joint angle measurement for gait analysis.

This contribution is concerned with joint angle calculation based on inertial measurement data in the context of human motion analysis. Unlike most robotic devices, the human body lacks even surfaces and right angles. Therefore, we focus on methods that avoid assuming certain orientations in which the sensors are mounted with respect to the body segments. After a review of available methods that may cope with this challenge, we present a set of new methods for: (1) joint axis and position identification; and (2) flexion/extension joint angle measurement. In particular, we propose methods that use only gyroscopes and accelerometers and, therefore, do not rely on a homogeneous magnetic field. We provide results from gait trials of a transfemoral amputee in which we compare the inertial measurement unit (IMU)-based methods to an optical 3D motion capture system. Unlike most authors, we place the optical markers on anatomical landmarks instead of attaching them to the IMUs. Root mean square errors of the knee flexion/extension angles are found to be less than 1° on the prosthesis and about 3° on the human leg. For the plantar/dorsiflexion of the ankle, both deviations are about 1°.

On-Demand Gait-Synchronous Electrical Cueing in Parkinson's Disease Using Machine Learning and Edge Computing: A Pilot Study.

Goal: Parkinson's disease (PD) can lead to gait impairment and Freezing of Gait (FoG). Recent advances in cueing technologies have enhanced mobility in PD patients. While sensor technology and machine learning offer real-time detection for on-demand cueing, existing systems are limited by the usage of smartphones between the sensor(s) and cueing device(s) for data processing. By avoiding this we aim at improving usability, robustness, and detection delay. Methods: We present a new technical solution, that runs detection and cueing algorithms directly on the sensing and cueing devices, bypassing the smartphone. This solution relies on edge computing on the devices' hardware. The wearable system consists of a single inertial sensor to control a stimulator and enables machine-learning-based FoG detection by classifying foot motion phases as either normal or FoG-affected. We demonstrate the system's functionality and safety during on-demand gait-synchronous electrical cueing in two patients, performing freezing of gait assessments. As references, motion phases and FoG episodes have been video-annotated. Results: The analysis confirms adequate gait phase and FoG detection performance. The mobility assistant detected foot motions with a rate above 94 % and classified them with an accuracy of 84 % into normal or FoG-affected. The FoG detection delay is mainly defined by the foot-motion duration, which is below the delay in existing sliding-window approaches. Conclusions: Direct computing on the sensor and cueing devices ensures robust detection of FoG-affected motions for on demand cueing synchronized with the gait. The proposed solution can be easily adopted to other sensor and cueing modalities.

MUNDUS project: MUltimodal neuroprosthesis for daily upper limb support.

BACKGROUND: MUNDUS is an assistive framework for recovering direct interaction capability of severely motor impaired people based on arm reaching and hand functions. It aims at achieving personalization, modularity and maximization of the user's direct involvement in assistive systems. To this, MUNDUS exploits any residual control of the end-user and can be adapted to the level of severity or to the progression of the disease allowing the user to voluntarily interact with the environment. MUNDUS target pathologies are high-level spinal cord injury (SCI) and neurodegenerative and genetic neuromuscular diseases, such as amyotrophic lateral sclerosis, Friedreich ataxia, and multiple sclerosis (MS). The system can be alternatively driven by residual voluntary muscular activation, head/eye motion, and brain signals. MUNDUS modularly combines an antigravity lightweight and non-cumbersome exoskeleton, closed-loop controlled Neuromuscular Electrical Stimulation for arm and hand motion, and potentially a motorized hand orthosis, for grasping interactive objects. METHODS: The definition of the requirements and of the interaction tasks were designed by a focus group with experts and a questionnaire with 36 potential end-users. RESULTS: The functionality of all modules has been successfully demonstrated. User's intention was detected with a 100% success. Averaging all subjects and tasks, the minimum evaluation score obtained was 1.13 ± 0.99 for the release of the handle during the drinking task, whilst all the other sub-actions achieved a mean value above 1.6. All users, but one, subjectively perceived the usefulness of the assistance and could easily control the system. Donning time ranged from 6 to 65 minutes, scaled on the configuration complexity. CONCLUSIONS: The MUNDUS platform provides functional assistance to daily life activities; the modules integration depends on the user's need, the functionality of the system have been demonstrated for all the possible configurations, and preliminary assessment of usability and acceptance is promising.

Evaluation of an EMG bioimpedance measurement system for recording and analysing the pharyngeal phase of swallowing.

A neuroprosthetic device for treating swallowing disorders requires an implantable measurement system capable to analysing the timing and quality of the swallowing process in real time. A combined EMG bioimpedance (EMBI) measurement system was developed and is evaluated here. The study was planned and performed as a case-control study. The studies were approved by the Charité Berlin ethics committee in votes EA1/160/09 and EA1/161/09. Investigations were carried out on healthy volunteers in order to examine the usefulness and reproducibility of measurements, the ability to distinguish between swallowing and head movements and the effect of different food consistencies. The correlation between bioimpedance and anatomical and functional changes occurring during the pharyngeal phase of swallowing in non-healthy patients was examined using videofluoroscopy (VFSS). 31 healthy subjects (15♂, 16♀) were tested over the course of 1350 swallows and 19 (17♂, 2♀) non-healthy patients over the course of 54 swallows. The signal curves obtained from both transcutaneous and subcutaneous measurement were similar, characteristic and reproducible (r > 0.5) and correlated with anatomical and functional changes during the pharyngeal phase of swallowing observed using VFSS. Statistically significant differences between head movements and swallowing movements, food volumes and consistencies were found. Neither the conductivity of the food, the sex of the test subject nor the position of the measurement electrodes exerted a statistically significant effect on the measured signal. EMBI is able to reproducibly map the pharyngeal phase of swallowing and changes associated with it both transcutaneously and subcutaneously. The procedure therefore appears to be suitable for use in performing automated evaluation of the swallowing process and for use as a component of an implant.

Review-Emerging Portable Technologies for Gait Analysis in Neurological Disorders.

The understanding of locomotion in neurological disorders requires technologies for quantitative gait analysis. Numerous modalities are available today to objectively capture spatiotemporal gait and postural control features. Nevertheless, many obstacles prevent the application of these technologies to their full potential in neurological research and especially clinical practice. These include the required expert knowledge, time for data collection, and missing standards for data analysis and reporting. Here, we provide a technological review of wearable and vision-based portable motion analysis tools that emerged in the last decade with recent applications in neurological disorders such as Parkinson's disease and Multiple Sclerosis. The goal is to enable the reader to understand the available technologies with their individual strengths and limitations in order to make an informed decision for own investigations and clinical applications. We foresee that ongoing developments toward user-friendly automated devices will allow for closed-loop applications, long-term monitoring, and telemedical consulting in real-life environments.

Rodent models for gait network disorders in Parkinson's disease - a translational perspective.

Gait impairments in Parkinson's disease remain a scientific and therapeutic challenge. The advent of new deep brain stimulation (DBS) devices capable of recording brain activity from chronically implanted electrodes has fostered new studies of gait in freely moving patients. The hope is to identify gait-related neural biomarkers and improve therapy using closed-loop DBS. In this context, animal models offer a wealth of opportunities to investigate gait network impairments at multiple biological scales and address unresolved questions from clinical research. Yet, the contribution of rodent models to the development of future neuromodulation therapies will rely on translational validity. In this review, we summarize the most effective strategies to model parkinsonian gait in rodents. We discuss how clinical observations have inspired targeted brain lesions in animal models, and whether resulting motor deficits and network oscillations match recent findings in humans. We conclude that future research should incorporate behavioral tests with increased cognitive demands to potentially uncover episodic gait impairments in rodents. Additionally, we expect that basic research will benefit from the implementation of evolving signal processing strategies from clinical research. This coevolution of translational research may contribute to the future optimization of gait therapy in Parkinson's disease.

Algorithms for Automated Calibration of Transcutaneous Spinal Cord Stimulation to Facilitate Clinical Applications.

Transcutaneous spinal cord stimulation (tSCS) is a promising intervention that can benefit spasticity control and augment voluntary movement in spinal cord injury (SCI) and multiple sclerosis. Current applications require expert knowledge and rely on the thorough visual analysis of electromyographic (EMG) responses from lower-limb muscles to optimize attainable treatment effects. Here, we devised an automated tSCS setup by combining an electrode array placed over low-thoracic to mid-lumbar vertebrae, synchronized EMG recordings, and a self-operating stimulation protocol to systematically test various stimulation sites and amplitudes. A built-in calibration procedure classifies the evoked responses as reflexes or direct motor responses and identifies stimulation thresholds as recommendations for tSCS therapy. We tested our setup in 15 individuals (five neurologically intact, five SCI, and five Parkinson's disease) and validated the results against blinded ratings from two clinical experts. Congruent results were obtained in 13 cases for electrode positions and in eight for tSCS amplitudes, with deviations of a maximum of one position and 5 to 10 mA in amplitude in the remaining cases. Despite these minor deviations, the calibration found clinically suitable tSCS settings in 13 individuals. In the remaining two cases, the automatic setup and both experts agreed that no reflex responses could be detected. The presented technological developments may facilitate the dissemination of tSCS into non-academic environments and broaden its use for diagnostic and therapeutic purposes.

Real-Time Detection of Freezing Motions in Parkinson's Patients for Adaptive Gait Phase Synchronous Cueing.

Parkinson's disease is the second most common neurodegenerative disease worldwide reducing cognitive and motoric abilities of affected persons. Freezing of Gait (FoG) is one of the severe symptoms that is observed in the late stages of the disease and considerably impairs the mobility of the person and raises the risk of falls. Due to the pathology and heterogeneity of the Parkinsonian gait cycle, especially in the case of freezing episodes, the detection of the gait phases with wearables is challenging in Parkinson's disease. This is addressed by introducing a state-automaton-based algorithm for the detection of the foot's motion phases using a shoe-placed inertial sensor. Machine-learning-based methods are investigated to classify the actual motion phase as normal or FoG-affected and to predict the outcome for the next motion phase. For this purpose, spatio-temporal gait and signal parameters are determined from the segmented movement phases. In this context, inertial sensor fusion is applied to the foot's 3D acceleration and rate of turn. Support Vector Machine (SVM) and AdaBoost classifiers have been trained on the data of 16 Parkinson's patients who had shown FoG episodes during a clinical freezing-provoking assessment course. Two clinical experts rated the video-recorded trials and marked episodes with festination, shank trembling, shuffling, or akinesia. Motion phases inside such episodes were labeled as FoG-affected. The classifiers were evaluated using leave-one-patient-out cross-validation. No statistically significant differences could be observed between the different classifiers for FoG detection (p>0.05). An SVM model with 10 features of the actual and two preceding motion phases achieved the highest average performance with 88.5 ± 5.8% sensitivity, 83.3 ± 17.1% specificity, and 92.8 ± 5.9% Area Under the Curve (AUC). The performance of predicting the behavior of the next motion phase was significantly lower compared to the detection classifiers. No statistically significant differences were found between all prediction models. An SVM-predictor with features from the two preceding motion phases had with 81.6 ± 7.7% sensitivity, 70.3 ± 18.4% specificity, and 82.8 ± 7.1% AUC the best average performance. The developed methods enable motion-phase-based FoG detection and prediction and can be utilized for closed-loop systems that provide on-demand gait-phase-synchronous cueing to mitigate FoG symptoms and to prevent complete motoric blockades.

A Robotic System with EMG-Triggered Functional Eletrical Stimulation for Restoring Arm Functions in Stroke Survivors.

BACKGROUND: Robotic systems combined with Functional Electrical Stimulation (FES) showed promising results on upper-limb motor recovery after stroke, but adequately-sized randomized controlled trials (RCTs) are still missing. OBJECTIVE: To evaluate whether arm training supported by RETRAINER, a passive exoskeleton integrated with electromyograph-triggered functional electrical stimulation, is superior to advanced conventional therapy (ACT) of equal intensity in the recovery of arm functions, dexterity, strength, activities of daily living, and quality of life after stroke. METHODS: A single-blind RCT recruiting 72 patients was conducted. Patients, randomly allocated to 2 groups, were trained for 9 weeks, 3 times per week: the experimental group performed task-oriented exercises assisted by RETRAINER for 30 minutes plus ACT (60 minutes), whereas the control group performed only ACT (90 minutes). Patients were assessed before, soon after, and 1 month after the end of the intervention. Outcome measures were as follows: Action Research Arm Test (ARAT), Motricity Index, Motor Activity Log, Box and Blocks Test (BBT), Stroke Specific Quality of Life Scale (SSQoL), and Muscle Research Council. RESULTS: All outcomes but SSQoL significantly improved over time in both groups (P < .001); a significant interaction effect in favor of the experimental group was found for ARAT and BBT. ARAT showed a between-group change of 11.5 points (P = .010) at the end of the intervention, which increased to 13.6 points 1 month after. Patients considered RETRAINER moderately usable (System Usability Score of 61.5 ± 22.8). CONCLUSIONS: Hybrid robotic systems, allowing to perform personalized, intensive, and task-oriented training, with an enriched sensory feedback, was superior to ACT in improving arm functions and dexterity after stroke.

Design of a symmetry controller for cycling induced by electrical stimulation: preliminary results on post-acute stroke patients.

This study deals with the design of a controller for cycling induced by functional electrical stimulation. The controller will be exploitable in the rehabilitation of hemiparetic patients who need to recover motor symmetry. It uses the pulse width as the control variable in the stimulation of the two legs in order to nullify the unbalance between the torques produced at the two crank arms. It was validated by means of isokinetic trials performed both by healthy subjects and stroke patients. The results showed that the controller was able to reach, and then maintain, a symmetrical pedaling. In the future, the controller will be validated on a larger number of stroke patients.

Inertial-Robotic Motion Tracking in End-Effector-Based Rehabilitation Robots.

End-effector-based robotic systems provide easy-to-set-up motion support in rehabilitation of stroke and spinal-cord-injured patients. However, measurement information is obtained only about the motion of the limb segments to which the systems are attached and not about the adjacent limb segments. We demonstrate in one particular experimental setup that this limitation can be overcome by augmenting an end-effector-based robot with a wearable inertial sensor. Most existing inertial motion tracking approaches rely on a homogeneous magnetic field and thus fail in indoor environments and near ferromagnetic materials and electronic devices. In contrast, we propose a magnetometer-free sensor fusion method. It uses a quaternion-based algorithm to track the heading of a limb segment in real time by combining the gyroscope and accelerometer readings with position measurements of one point along that segment. We apply this method to an upper-limb rehabilitation robotics use case in which the orientation and position of the forearm and elbow are known, and the orientation and position of the upper arm and shoulder are estimated by the proposed method using an inertial sensor worn on the upper arm. Experimental data from five healthy subjects who performed 282 proper executions of a typical rehabilitation motion and 163 executions with compensation motion are evaluated. Using a camera-based system as a ground truth, we demonstrate that the shoulder position and the elbow angle are tracked with median errors around 4 cm and 4°, respectively; and that undesirable compensatory shoulder movements, which were defined as shoulder displacements greater ±10 cm for more than 20% of a motion cycle, are detected and classified 100% correctly across all 445 performed motions. The results indicate that wearable inertial sensors and end-effector-based robots can be combined to provide means for effective rehabilitation therapy with likewise detailed and accurate motion tracking for performance assessment, real-time biofeedback and feedback control of robotic and neuroprosthetic motion support.

A Hybrid Robotic System for Arm Training of Stroke Survivors: Concept and First Evaluation.

OBJECTIVE: To develop and evaluate a hybrid robotic system for arm recovery after stroke, combining ElectroMyoGraphic (EMG)-triggered functional electrical stimulation (FES) with a passive exoskeleton for upper limb suspension. METHODS: The system was used in a structured exercise program resembling activities of daily life. Exercises execution was continuously controlled using angle sensor data and radio-frequency identification technology. The training program consisted of 27 sessions lasting 30 min each. Seven post-acute stroke patients were recruited from two clinical sites. The efficacy of the system was evaluated in terms of action research arm test, motricity index, motor activity log, and box & blocks tests. Furthermore, kinematics-based and EMG-based outcome measures were derived directly from data collected during training sessions. RESULTS: All patients showed an improvement of motor functions at the end of the training program. After training, the exercises were in most cases executed faster, smoother, and with an increased range of motion. Subjects were able to trigger FES, but in some cases, they did not maintain the voluntary effort during task execution. All subjects but one considered the system usable. CONCLUSION: The preliminary results showed that the system can be used in a clinical environment with positive effects on arm functional recovery. However, only the final results of the currently ongoing clinical trial will unveil the system's full potential. SIGNIFICANCE: The presented hybrid robotic system is highly customizable, allows to monitor the daily performance, requires low supervision of the therapist, and might have the potential to enhance arm recovery after stroke.