Functional Electrical Stimulation Device Research Articles

Recognition of Human Lower Limb Motion and Muscle Fatigue Status Using a Wearable FES-sEMG System.

Functional electrical stimulation (FES) devices are widely employed for clinical treatment, rehabilitation, and sports training. However, existing FES devices are inadequate in terms of wearability and cannot recognize a user's intention to move or muscle fatigue. These issues impede the user's ability to incorporate FES devices into their daily life. In response to these issues, this paper introduces a novel wearable FES system based on customized textile electrodes. The system is driven by surface electromyography (sEMG) movement intention. A parallel structured deep learning model based on a wearable FES device is used, which enables the identification of both the type of motion and muscle fatigue status without being affected by electrical stimulation. Five subjects took part in an experiment to test the proposed system, and the results showed that our method achieved a high level of accuracy for lower limb motion recognition and muscle fatigue status detection. The preliminary results presented here prove the effectiveness of the novel wearable FES system in terms of recognizing lower limb motions and muscle fatigue status.

Weft-Knitted Strain Sensors for Motion Capture

Motion capture, especially of the knee angle, is an important component for situational triggering of functional electrical stimulation (FES). One major disadvantage of commercial FES devices is their bulky design that prevents unobtrusive wearing in everyday life and limits the patient’s free choice of appearance. This paper presents an alternative approach of sensors for motion capture in form of textile-based strain sensors. These can be integrated in a FES system in form of functional leggings, which make the FES system suitable for an unobtrusive daily use. Textile sensors, especially knitted sensors have already proven to be very promising to detect tensile strain. In particular, weft-knitted strain sensors, which can be integrated directly into the clothing during the knitting process, have the potential to detect the knee angle and therefore derive the gait phase due to the bending of the limbs without disturbing the wearer unnecessarily. Different designs of the weft-knitted strain sensor and their influence on the measurement behaviour of the sensor have been investigated. The weft-knitted strain sensor can be directly integrated in the knee area of the functional leggings to be used as a soft trigger to initiate electrical impulses for FES.

Literature review: User interface of system functional electrical stimulation (FES) and arm robotic rehabilitation

Interface technology development for human-robot interaction (HRI) in rehabilitation systems has increased in recent years. HRI can effectively achieve specific motor goals desired in rehabilitation, such as combining human intentions and actions with robotic devices to perform the desired stroke rehabilitation movements. Rehabilitation devices are starting to be directed towards using devices that integrate functional electrical stimulation (FES) with robotic arms because they have succeeded in providing promising interventions to restore arm function by intensively activating the muscles of post-stroke patients. However, FES requires a high level of accuracy to position the limbs for the functional tasks given because excessive electrical stimulation can cause fatigue in the patient, so it is necessary to provide electrical stimulation with an amplitude that suits the patient's needs. Unfortunately, most studies have a constant voltage amplitude and do not consider the voltage that matches the patient's muscle needs; this treatment can cause fatigue in the patient. Robotic devices as rehabilitation aids have the potential to support external power and adapt electrical stimulation needs to the voltage amplitude applied to the FES. Integrating FES with a robotic arm support system into one hybrid neuroprosthesis is attractive because the mechanical device can complement muscle action and increase rehabilitation's repeatability and accuracy rate. The integration of FES and robotic arms is a promising approach in the future. This article reviews the state of the art regarding motor rehabilitation using functional electrical stimulation (FES) devices and robotic arms for the upper limbs of post-stroke patients. A narrative review was done through a literature search using the IEEE-Xplore, Scopus, and PubMed databases. Nine different rehabilitation system articles were identified. The selected systems were compared critically by considering the design and actuators, components, technological aspects, and technological challenges that could be developed in the future. This article also examines the development of HRI and emerging research trends in HRI-based rehabilitation

CHECGAIT: A Functional Electrical Stimulation Clinical Pathway to Reduce Foot Drop during Walking in Adult Patients with Upper Motor Neuron Lesions.

Foot drop during the swing phase of gait and at initial foot contact is a current kinematic abnormality that can occur following an upper motor neuron (UMN) lesion. Functional electrical stimulation (FES) of the common peroneal nerve through an assistive device is often used in neuro-rehabilitation to help patients regain mobility. Although there are FES-specific guideline recommendations, it remains a challenge for clinicians to appropriately select patients eligible for the daily use of FES devices, as very few health insurance systems cover its cost in Europe. In Luxembourg, since 2018, successfully completing an FES clinical pathway called CHECGAIT is a prerequisite to receiving financial coverage for FES devices from the national health fund (Caisse Nationale de Santé-CNS). This study describes the structure and steps of CHECGAIT and reports our experience with a cohort of 100 patients enrolled over a three-year period. The clinical and gait outcomes of all patients were retrospectively quantified, and a specific analysis was performed to highlight differences between patients with and without an FES device prescription at the end of a CHECGAIT. Several significant gait differences were found between these groups. These results and CHECGAIT may help clinicians to better select patients who can most benefit from this technology in their daily lives. In addition, CHECGAIT could provide significant savings to public health systems by avoiding unnecessary deliveries of FES devices.

Adaptive Sliding Mode Feedback Control Algorithm for a Nonlinear Knee Extension Model

Functional electrical stimulation (FES) has been widely used to treat spinal cord injury (SCI) patients. Many research studies employ a closed-loop FES system to monitor the stimulated muscle response and provide a precise amount of charge to the muscle. However, most closed-loop FES devices perform poorly and sometimes fail when muscle nonlinearity effects such as fatigue, time delay response, stiffness, spasticity, and subject change happen. The poor performance of the closed-loop FES device is mainly due to discrepancies in the feedback control algorithms. Most of the existing feedback control algorithms were not designed to adapt to new changes in patients with different nonlinearity effects, resulting in early muscle fatigue. Therefore, this research proposes an adaptive sliding mode (SM) feedback control algorithm that could adapt and fine-tune internal control settings in real-time according to the current subject’s nonlinear and time-varying muscle response during the rehabilitation (knee extension) exercise. The adaptive SM feedback controller consists mainly of system identification, direct torque control, and tunable feedback control settings. Employing the system identification unit in the feedback control algorithm enables real-time self-tuning and adjusting of the SM internal control settings according to the current patient’s condition. Initially, the patient’s knee trajectory response was identified by extracting meaningful information, which included time delay, rise time, overshoot, and steady-state error. The extracted information was used to fine-tune and update the internal SM control settings. Finally, the performance of the proposed adaptive SM feedback control algorithm in terms of system response time, stability, and rehabilitation time was analysed using a nonlinear knee model. The findings from the simulation results indicate that the adaptive SM feedback controller demonstrated the best control performance in accurately tracking the desired knee angle movement by having faster response times, smaller overshoots, and lower steady-state errors when compared with the conventional SM across four reference angle settings (20°, 30°, 40°, and 76°). The adaptive feedback SM controller was also observed to compensate for muscle nonlinearities, including fatigue, stiffness, spasticity, time delay, and other disturbances.

A Novel Functional Electrical Stimulation Device Plus Telerehabilitation Improves Walking in People with Multiple Sclerosis: A Case Series

Background and purpose Foot drop in people with multiple sclerosis (PwMS) commonly leads to decreased mobility and quality of life (QOL). Functional electrical stimulation (FES) of the peroneal nerve can improve gait but access to wearable FES devices is limited by cost and burden of in-person visits for device optimization. Therefore, the purpose of this case series was to assess the effectiveness and feasibility of a telehealth-monitored FES device. Methods Ten PwMS (50.2 years [SD 11.3]; 2 males) with moderate disability (median EDSS 4.75; IQR 3.75 – 5.75) were provided an EvoWalk FES device. Participants were prescribed an 8-week wear-schedule. A wearable accelerometer (ActiGraph) recorded daily step count at week 0 and 8. For week 0 activity levels, the EvoWalk was donned but not activated, and settings were progressed over three bi-weekly telehealth sessions. Effectiveness was assessed by Timed-25 Foot Walk (T25FW), 2-Minute Walk test (2MWT), Timed-Up and Go (TUG), and self-report of walking, fatigue, and QOL collected in-person at baseline and study end. Feasibility was assessed by percentage of telehealth visits completed and participant-reported satisfaction. Results All (100%) telehealth visits were completed with high levels of satisfaction reported, mean score 4.7/5 (SD .51). ActiGraph data were available for 3 participants: average daily step count pre (2,996; SD 1,235) was lower than post (3,930: SD 1,157) EvoWalk use. At study completion, use of FES resulted in a larger orthotic effect in gait speed for T25FW (-14.2%), TUG (-17.0%) and distance on the 2MWT (14.6%). Post-trial self-report measures showed improvements in subjective walking (-15.6%), QOL (-13.6%) and fatigue (-7.5%). Discussion Telehealth was safe and feasible for progressing FES intervention. Gait speed, walking distance, and QOL improved following the intervention. Using telerehabilitation to monitor FES intervention may simultaneously improve access and reduce patient burden. Future research should include follow-up to assess long-term effects Foot drop in people with multiple sclerosis (PwMS) commonly leads to decreased mobility and quality of life (QOL). Functional electrical stimulation (FES) of the peroneal nerve can improve gait but access to wearable FES devices is limited by cost and burden of in-person visits for device optimization. Therefore, the purpose of this case series was to assess the effectiveness and feasibility of a telehealth-monitored FES device. Ten PwMS (50.2 years [SD 11.3]; 2 males) with moderate disability (median EDSS 4.75; IQR 3.75 – 5.75) were provided an EvoWalk FES device. Participants were prescribed an 8-week wear-schedule. A wearable accelerometer (ActiGraph) recorded daily step count at week 0 and 8. For week 0 activity levels, the EvoWalk was donned but not activated, and settings were progressed over three bi-weekly telehealth sessions. Effectiveness was assessed by Timed-25 Foot Walk (T25FW), 2-Minute Walk test (2MWT), Timed-Up and Go (TUG), and self-report of walking, fatigue, and QOL collected in-person at baseline and study end. Feasibility was assessed by percentage of telehealth visits completed and participant-reported satisfaction. All (100%) telehealth visits were completed with high levels of satisfaction reported, mean score 4.7/5 (SD .51). ActiGraph data were available for 3 participants: average daily step count pre (2,996; SD 1,235) was lower than post (3,930: SD 1,157) EvoWalk use. At study completion, use of FES resulted in a larger orthotic effect in gait speed for T25FW (-14.2%), TUG (-17.0%) and distance on the 2MWT (14.6%). Post-trial self-report measures showed improvements in subjective walking (-15.6%), QOL (-13.6%) and fatigue (-7.5%). Telehealth was safe and feasible for progressing FES intervention. Gait speed, walking distance, and QOL improved following the intervention. Using telerehabilitation to monitor FES intervention may simultaneously improve access and reduce patient burden. Future research should include follow-up to assess long-term effects

Enhancing Mobility in Persons with Footdrop in Multiple Sclerosis through Functional Electrical Stimulation

Background Footdrop is a significant problem in individuals living with multiple sclerosis (MS), leading to falls and reduced quality of life. Functional electrical stimulation (FES) is a common treatment for footdrop. Technological advances are leading to the development of the next generation of FES devices, such as the non-invasive EvoWalk (Evolution Devices, Inc). Prior to widespread use the accuracy of the device's gait detection needs to be validated. Aim To validate EvoWalk's gait analysis accuracy based on ground truths from a pressure-based walkway gait analysis system and examine the improvement in gait with FES in pwMS. Method Individuals living with MS, unilateral footdrop and capable of walking 10m with or without an assistive device were eligible. Participants performed a series of walking and stair-climbing tasks while wearing the EvoWalk device with and without FES stimulation active on the affected leg. Data was simultaneously recorded on the EvoWalk device, and the Zeno pressure-based walkway gait analysis system. Results Data from two pwMS with unilateral footdrop and one healthy control was analyzed. Compared to the pressure-based walkway system, EvoWalk yielded an average heel-strike and toe-off onset detection differences of 32.7ms (SE=15.3, 95% CI = [2.72,62.7]) and 59.1ms (SE=36.4, 95% CI = [0,130.4]), respectively. Also, in one pwMS, swing-time improved by 11.83% when the stimulation was active. Due to technical issues, we were unable to compare the stimulation results for the other pwMS and stimulation was inactive for the control participant. Discussion The wearable FES device tested here was accurate in detecting gait events and has some benefit to gait parameters. Further research concerning the device is warranted. Footdrop is a significant problem in individuals living with multiple sclerosis (MS), leading to falls and reduced quality of life. Functional electrical stimulation (FES) is a common treatment for footdrop. Technological advances are leading to the development of the next generation of FES devices, such as the non-invasive EvoWalk (Evolution Devices, Inc). Prior to widespread use the accuracy of the device's gait detection needs to be validated. To validate EvoWalk's gait analysis accuracy based on ground truths from a pressure-based walkway gait analysis system and examine the improvement in gait with FES in pwMS. Individuals living with MS, unilateral footdrop and capable of walking 10m with or without an assistive device were eligible. Participants performed a series of walking and stair-climbing tasks while wearing the EvoWalk device with and without FES stimulation active on the affected leg. Data was simultaneously recorded on the EvoWalk device, and the Zeno pressure-based walkway gait analysis system. Data from two pwMS with unilateral footdrop and one healthy control was analyzed. Compared to the pressure-based walkway system, EvoWalk yielded an average heel-strike and toe-off onset detection differences of 32.7ms (SE=15.3, 95% CI = [2.72,62.7]) and 59.1ms (SE=36.4, 95% CI = [0,130.4]), respectively. Also, in one pwMS, swing-time improved by 11.83% when the stimulation was active. Due to technical issues, we were unable to compare the stimulation results for the other pwMS and stimulation was inactive for the control participant. The wearable FES device tested here was accurate in detecting gait events and has some benefit to gait parameters. Further research concerning the device is warranted.

Ankle dorsiflexion assist using a single sensor-based FES: Results from clinical study on patients with stroke.

Ankle foot orthosis (AFO) commonly prescribed to manage foot-drop following stroke restricts ankle mobility. Commercially available functional electrical stimulation (FES) is an expensive alternative to achieve desired dorsiflexion during swing phase of the gait cycle. An in-house cost-effective innovative solution was designed and developed to address this problem.The aim of the study was to compare spatiotemporal gait characteristics of patients with foot-drop following stroke using commercially available FES against in-house developed versatile single sensor-based FES. Ten patients with cerebrovascular accident of at least 3 months duration and ambulant with/without AFO were recruited prospectively. They were trained with Device-1 (Commercial Device) and Device-2 (In-house developed, Re-Lift) for 7 h over 3 consecutive days with each device. Outcome measures included timed-up-and-go-test (TUG), six-minute-walk-test (6MWT), ten-meter-walk-test (10MWT), physiological cost index (PCI), instrumented gait analysis derived spatiotemporal parameters, and patient satisfaction feedback questionnaire. We calculated intraclass correlation between devices and median interquartile range. Statistical analysis included Wilcoxon-signed-rank-test and F-test (P < 0.05 was considered statistically significant). Bland Altman and scatter plots were plotted for both devices. Intraclass correlation coefficient for 6MWT (0.96), 10MWT (0.97), TUG test (0.99), and PCI (0.88) reflected high agreement between the two devices. Scatter plot and Bland Altman plots for the outcome parameters showed good correlation between two FES devices. Patient satisfaction scores were equal for both Device-1 and Device-2. There was statistically significant change in swing phase ankle dorsiflexion. The study demonstrated good correlation between commercial FES and Re-Lift suggestive of the utility of low-cost FES device in clinical setting.

Integrated Low-Voltage Compliance and Wide-Dynamic Stimulator Design for Neural Implantable Devices

In this study, a pulse frequency modulation (PFM)-based stimulator is proposed for use in biomedical implantable devices. Conventionally, functional electrical stimulation (FES) techniques have been used to reinforce damaged nerves, such as retina tissue and brain tissue, by injecting a certain amount of charge into tissues. Although several design methods are present for implementing FES devices, an FES stimulator for retinal implants is difficult to realize because of the chip area, which needs to be inserted in a fovea, sized 5 mm x 5 mm, and power limitations to prevent the heat generation that causes tissue damage. In this work, we propose a novel stimulation structure to reduce the compliance voltage during stimulation, which can result in high-speed and low-voltage operation. A new stimulator that is composed of a modified high-speed PFM, a 4-bit counter, a serializer, a digital controller, and a current driver is designed and verified using a DB HiTek standard 0.18 μm process. This proposed stimulator can generate a charge up to 130 nC, consumes an average power of 375 µW during a stimulation period, and occupies a total area of 700 µm × 68 µm.

Methodology for Selecting the Appropriate Electric Motor for Robotic Modular Systems for Lower Extremities.

Torque calculation is essential for selecting the appropriate motor to achieve the required torque at each joint of a hybrid exoskeleton. In recent years, the combined use of functional electrical stimulation (FES) and robotic devices, called hybrid robotic rehabilitation systems, has emerged as a promising approach for the rehabilitating of lower limb motor functions. Specifically, the implementation strategy of functional electrical stimulation walking aid combined with the design of the exoskeleton part is the main focus of our research team. This work copes with issues of the design process of a robotic exoskeleton. The importance of robotic exoskeletons for providing walking aid to people with mobility disorders or the elderly is discussed. Furthermore, the approaches to calculating the joint torques are investigated, and the mathematical models and parameters of interest are identified. This further includes the comparative data for servo motors: robotic exoskeleton characteristics and actuator analysis in the robotic exoskeleton. The aforementioned is used to propose a mathematical model based on previous models (Zatsiorsky BSP and Dempster BSP body segment parameters models, forward kinematics models), which was extended to include added adjustable parameters such as length, area, volume, mass, density, the centre of mass, human body characteristics, and considering both static and dynamic parameter extraction. Then, an analytic method is presented, exploiting the results from the mathematical model to select the appropriate motor for each joint of the lower extremities. The detailed description of the method is followed by examples, experimental measurements, and statistical analysis of qualitative and quantitative characteristics. The results showed deviations from typical calculation methods, offering a better understanding of the motor requirements for each joint of the exoskeleton and avoiding selections of marginal functionality features of the motors. In addition, researchers are offered a tool for replicating the results of this work, allowing them to configure the parameters associated with the servo motor features. The researcher can either use the embedded library developed for this work or enter new data into it, affecting the calculated torques of the model joints. The extracted results assist the researcher in choosing the appropriate motor among commercially available brushed and brushless motors based on the torques applied at each joint in robotic articulated systems.

Effect of Functional Electrical Stimulation on Gait Parameters in Children with Cerebral Palsy: A Meta-Analysis.

Objective At present, there are controversies on the effectiveness of functional electrical stimulation devices in gait improvement in the clinic, and the results reported in limited literature are contradictory. This paper summarizes and analyzes the relationship between functional electrical stimulation treatment and gait parameter changes in children with cerebral palsy, thus exploring the above controversies' results. Methods Two researchers conducted a detailed search of the literature from the establishment of the database to June 2022. Literature retrieved from databases, including PubMed, Embase, Ovid, Cochrane Library, and Web of Science and the search process followed the principles of Cochrane. The search keywords were “cerebral palsy”, “functional electrical stimulation”, “gait”, or “walk”. Gait and balance parameters were extracted from the literature. Gait parameters, such as walking speed and step length, were included in the meta-analysis. The study used standard mean difference (STD) and 95% confidence interval (CI) to calculate the mean difference between the two groups. The statistic I2 was used to evaluate the heterogeneity between the evaluation studies. Begg's test detected publication bias and the funnel chart was used for visual analysis. Furthermore, Review Manager software was used to make a risk bias map for literature publication bias analysis. Results 9 literatures were included in the analysis, with a total of 282 children with cerebral palsy, including 142 patients in the functional electrical stimulation treatment group and 140 patients in the comfort treatment, general nursing, or other physical therapy. The randomization scheme and result report used in most studies were low risk, which was important for the credibility of this study. Most studies have limitations in the blinding method of participants and subjects, and most of them were single-blind studies, which might have a high risk. The results showed that functional electrical stimulation could increase the walking speed of children with cerebral palsy (SMD = 0.82, P < 0.0001) and increase the walking step length of children with cerebral palsy (SMD = 1.34, 95%CI = 1.07, 1.60, Z = 9.91, P < 0.0001). Funnel plot analysis showed that the literature distribution was uniform and symmetrical, and Begg's test showed no publication bias in included literature. Conclusion This study compared the effects of the functional nerve stimulation treatment group and control group on improving gait parameters of children with cerebral palsy. The results indicated that functional nerve stimulation treatment could increase the gait speed and step length of children with cerebral palsy, which could improve the walking of children with cerebral palsy. Furthermore, this study needs more research data to support our findings. The results of this study might better guide the clinical practice and better use of health as well as financial resources.

SmartStim: A Recurrent Neural Network Assisted Adaptive Functional Electrical Stimulation for Walking

Abstract According to the Neuro Patience report of the Neurological Alliance, 1 in 6 people in the UK has a neurological condition. With the growth in technology, rehabilitation for neurological problems is one of the fastgrowing fields. Functional Electrical Stimulation (FES) is one of those neuro-rehabilitation methods that uses electrical nerve stimulation to restore functional muscle movements that are lost due to neurological problems such as stroke and multiple sclerosis. This neuroprosthetic device is frequently used to assist walking by treating a condition called Drop Foot, a result of paralysis of the pretibial muscles. This study proposes a two-channel FES device called the SmartStim, which has the ability to modulate its stimulation levels according to various obstacles such as stairs and ramps. This system employs a sensor-based module with a Recurrent Neural Network to classify these different walking scenarios. The module is built with Inertial Measurement sensors embedded in a pair of shoes, and the Recurrent Neural Network uses data from these sensors to predict various obstacles as the user is walking. These predictions are then used by a Fuzzy Logic Controller to control and regulate the stimulation current in two channels of the SmartStim system. In the two channels of the system, one channel will help aid with drop foot, while the other will be used to stimulate another muscle group to help access stairs and ramps by the user. The Recurrent Neural Network module in this system has been trained and tested using the k-fold cross-validation. The evaluation of this trained model shows that it can predict obstacles from sensor data at 97 percent accuracy. Currently, further testing is being performed to assess the workings of the fuzzy logic controller in combination with the Recurrent Neural Network in healthy individuals. It is expected that the SmartStim system may aid users in accessing various walking scenarios more efficiently.

Analysis of the movements generated by a multi-field functional electrical stimulation device for upper extremity rehabilitation.

The most common chronic sequela after stroke is the loss of arm function, and functional electrical stimulation (FES) applied to the forearm muscles is one of the options to treat it. Surface multi-field electrodes have emerged, showing a great potential to improve the selectivity of the stimulation, delay muscle fatigue, and provide easier donning and doffing. The muscular selectivity takes on special relevance in the rehabilitation of the upper extremity as hand dexterity requires a wide diversity of specific muscle actions. This pilot study analyses the movements generated in the wrist and fingers using a commercial multi-field technology-based FES device (Fesia Grasp). The study included five patients with hemiplegic subacute stroke, in which scanning of all cathodes of the electrode was carried out daily for 5 days, in two different forearm positions, with the resulting movements being labeled by experienced therapists. The aim of this pilot study was to determine if there were differences between subjects and between forearm positions in terms of produced movements. Movements of the wrist (two movements) and the fingers (six movements) could be achieved in two different forearm positions. The multi-field electrode of Fesia Grasp enables to generate a wide range of movements of the hand in different positions. This fact could allow to produce more physiological movement patterns during the rehabilitation process with FES, which could have a beneficial effect on the recovery of patients with neurological diseases.

Orthotic Intervention for Ageing Individuals with Spinal Cord Injury: A Brief Review

Background and aim: The lifespan of individuals with spinal cord injury has increased significantly for the past decade due to improved healthcare and rehabilitation. However, ageing with SCI requires a unique management approach, including orthotic intervention for mobility function. This review explores the use of orthotic intervention among the elderly with SCI. Methods: A literature search was conducted via Medline and ScienceDirect for articles published from 2001 to 2021 with the following terms: “orthotic” or “orthosis” or “orthoses” and “spinal cord injury” and “elderly” or “geriatric” or “ageing”. Selected articles must be English and evaluate the usage of orthotic intervention among the elderly (aged &gt;65 years) with a history of SCI. Reviews articles, case reports, and dissertations were excluded studies as well that included concomitant use of other interventions such as functional electrical stimulation devices. Results: The literature search yielded 25 articles, and after the screening, 3 studies fulfilled the eligibility criteria. Mostly used orthosis was reciprocal gait orthosis, hip-knee-ankle-foot orthosis, and knee-ankle-foot orthosis among the elderly with SCI. Between 25.8% to one-third of the studied population were reported not compliant with the orthotic interventions due to difficulties of donning and using them in day-to-day activities. Age was not a significant factor for poor compliance with the use of an orthosis (p &gt; 0.05). None of the articles has evaluated the use of orthosis for improving hand function in tetraplegia. Conclusions: Longevity research in SCI must focus on orthotic interventions among ageing SCI individuals, especially on poor compliance and its causes, as well as the use of upper limb orthosis for tetraplegic hands.

Brain-Computer Interface Controlled Functional Electrical Stimulation: Evaluation With Healthy Subjects and Spinal Cord Injury Patients

This work presents the design, implementation, and feasibility evaluation of a Motor Imagery (MI) based Brain-Computer Interface (BCI) developed to control a Functional Electrical Stimulation (FES) device. The aim of this system is to assist the upper limb motor recovery of patients with spinal cord injury (SCI). With this BCI-controlled FES system, the user performs open and close MI with either the left or right hand, which if detected is used to provide visual feedback and electroestimulation to muscles in the forearm to perform the corresponding grasping movement. The system was evaluated with seven healthy subjects (HS group) and two SCI patients (SC group) in several experimental sessions across different days. Each experimental session consisted of a training routine devoted to collect calibration EEG data to train the BCI machine learning model, and of a validation routine devoted to validate system in online operation. The online system validation showed an accuracy of the recognition of the MI task that ranged between 78&#x0025; and 81&#x0025; for HS participants and between 63&#x0025; and 93&#x0025; for SCI participants. Additionally, the time taken by the BCI system to trigger the FES device ranged between 7.05 and 7.29 s for HS participants and between 8.43 s and 13.91 s for SCI participants. Finally, significant negative correlations were observed (<inline-formula> <tex-math notation="LaTeX">$r=-0.418$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$p=0.024$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$r=-0.437$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$p=0.018$ </tex-math></inline-formula> for left and right hand MI conditions, respectively) between the online BCI performance with a quantitative EEG parameter based on event-related desynchronization/synchronization analysis. The results of this work indicate the feasibility of the proposed BCI coupled to a FES device to be used for SCI patients with a moderate level of disability and provides evidence of the functionality of the proposed BCI system in a motor rehabilitation context.

An Optimal Transport Based Transferable System for Detection of Erroneous Somato-Sensory Feedback from Neural Signals.

This study is aimed at the detection of single-trial feedback, perceived as erroneous by the user, using a transferable classification system while conducting a motor imagery brain–computer interfacing (BCI) task. The feedback received by the users are relayed from a functional electrical stimulation (FES) device and hence are somato-sensory in nature. The BCI system designed for this study activates an electrical stimulator placed on the left hand, right hand, left foot, and right foot of the user. Trials containing erroneous feedback can be detected from the neural signals in form of the error related potential (ErrP). The inclusion of neuro-feedback during the experiments indicated the possibility that ErrP signals can be evoked when the participant perceives an error from the feedback. Hence, to detect such feedback using ErrP, a transferable (offline) decoder based on optimal transport theory is introduced herein. The offline system detects single-trial erroneous trials from the feedback period of an online neuro-feedback BCI system. The results of the FES-based feedback BCI system were compared to a similar visual-based (VIS) feedback system. Using our framework, the error detector systems for both the FES and VIS feedback paradigms achieved an F1-score of 92.66% and 83.10%, respectively, and are significantly superior to a comparative system where an optimal transport was not used. It is expected that this form of transferable and automated error detection system compounded with a motor imagery system will augment the performance of a BCI and provide a better BCI-based neuro-rehabilitation protocol that has an error control mechanism embedded into it.

Multi-point surface FES hand rehabilitation system for stroke patients based on eye movement control

Recently, the number of stroke patients has increased greatly. Most of them suffer from hand motor impairment, which creates the need for effective rehabilitation systems. Functional electrical stimulation (FES) is a neurorehabilitation method based on brain plasticity, which is widely accepted because it is non-invasive and convenient. However, it is still a challenge to achieve fine finger control by using surface FES. Here, we use multi-point surface FES to achieve individual finger motion. Besides, simple FES does not engage the subjects' attention, and an optimal stimulation position is difficult to identify. Hence, we try to integrate FES with sensory control by presenting a multi-point FES system based on eye movement control. By programming the electrodes display interface and establishing communication with the FES device and the eye tracker, subjects can change stimulation points via their eye movements. Experiments were performed to test the validity and safety of the proposed system. Feedback data was obtained using a 3D motion capture device. The results indicate that achieving individual finger motion is possible and stimulation points can be changed via eye movements. The system is practical and can be used in hand motor training for stroke patients to shorten the rehabilitation period.

Development of EMG-Triggered Functional Electrical Stimulation Device for Upper Extremity Bilateral Movement Training in Stroke Patients: Feasibility and Pilot study

Development of EMG-Triggered Functional Electrical Stimulation Device for Upper Extremity Bilateral Movement Training in Stroke Patients: Feasibility and Pilot study

Feasibility and significance of stimulating interscapular muscles using transcutaneous functional electrical stimulation in able-bodied individuals

Objective The study objective was to assess the feasibility of stimulating the lower trapezius (LT), the upper trapezius (UT) and serratus anterior (SA) muscles along with anterior or middle deltoid, using surface functional electrical stimulation (FES). The secondary aim was to understand the effects of LT, UT, and SA stimulation on maximum arm reach achieved in shoulder flexion and abduction. Design Single arm interventional study. Setting Inpatient Rehabilitation Hospital. Participants Ten healthy volunteers. Intervention Participants completed 10 trials for each of the 3 conditions in flexion and abduction, i.e. (1) Active voluntary flexion or abduction, (2) FES for anterior deltoid for flexion or middle deltoid for abduction, and (3) FES for LT, UT, and SA along with anterior deltoid for flexion or middle deltoid for abduction. Outcome Measures Maximum arm reach and percent angle relative to the voluntary movement were computed from motion capture data for each condition. Wilcoxon signed-rank test was used to compare the maximum reach between two FES conditions. Results The study results showed that all three interscapular muscles can be stimulated using surface FES. Maximum reach in abduction was greater for FES of middle deltoid along with the interscapular muscles (51.77° ± 17.54°) compared to FES for middle deltoid alone (43.76° ± 15.32°; Z = −2.701, P = 0.007). Maximum reach in flexion for FES of anterior deltoid, along with interscapular muscles, was similar to that during FES of anterior deltoid alone. Conclusion Interscapular muscles can be stimulated using surface FES devices and should be engaged during rehabilitation as appropriate.

Design of an FPGA-Based Fuzzy Feedback Controller for Closed-Loop FES in Knee Joint Model.

Functional electrical stimulation (FES) device has been widely used by spinal cord injury (SCI) patients in their rehab exercises to restore motor function to their paralysed muscles. The major challenge of muscle contraction induced by FES is early muscle fatigue due to the open-loop stimulation strategy. To reduce the early muscle fatigue phenomenon, a closed-loop FES system is proposed to track the angle of the limb’s movement and provide an accurate amount of charge according to the desired reference angle. Among the existing feedback controllers, fuzzy logic controller (FLC) has been found to exhibit good control performance in handling complex non-linear systems without developing any complex mathematical model. Recently, there has been considerable interest in the implementation of FLC in hardware embedded systems. Therefore, in this paper, a digital fuzzy feedback controller (FFC) embedded in a field-programmable gate array (FPGA) board was proposed. The digital FFC mainly consists of an analog-to-digital converter (ADC) Data Acquisition and FLC sub-modules. The FFC was designed to monitor and control the progress of knee extension movement by regulating the stimulus pulse width duration to meet the target angle. The knee is expected to extend to a maximum reference angle setting (70°, 40° or 30°) from its normal position of 0° once the stimulus charge is applied to the muscle by the FES device. Initially, the FLC was modelled using MATLAB Simulink. Then, the FLC was hardcoded into digital logic using hardware description language (HDL) Verilog codes. Thereafter, the performance of the digital FLC was tested with a knee extension model using the HDL co-simulation technique in MATLAB Simulink. Finally, for real-time verification, the designed digital FFC was downloaded to the Intel FPGA (DE2-115) board. The digital FFC utilized only 4% of the total FPGA (Cyclone IV E) logic elements (LEs) and required 238 µs to regulate stimulus pulse width data, including 3 µs for the FLC computation. The high processing speed of the digital FFC enables the stimulus pulse width duration to be updated every stimulation cycle. Furthermore, the implemented digital FFC has demonstrated good control performance in accurately controlling the stimulus pulse width duration to reach the desired reference angle with very small overshoot (1.4°) and steady-state error (0.4°). These promising results are very useful for a real-world closed-loop FES application.