Functional Electrical Stimulation System Research Articles

Human-Like Rewards to Train a Reinforcement Learning Controller for Planar Arm Movement

High-level spinal cord injury (SCI) in humans causes paralysis below the neck. Functional electrical stimulation (FES) technology applies electrical current to nerves and muscles to restore movement, and controllers for upper extremity FES neuroprostheses calculate stimulation patterns to produce desired arm movement. However, currently available FES controllers have yet to restore natural movements. Reinforcement learning (RL) is a reward-driven control technique; it can employ user-generated rewards, and human preferences can be used in training. To test this concept with FES, we conducted simulation experiments using computer-generated “pseudo-human” rewards. Rewards with varying properties were used with an actor-critic RL controller for a planar two-degree-of-freedom biomechanical human arm model performing reaching movements. Results demonstrate that sparse, delayed pseudo-human rewards permit stable and effective RL controller learning. The frequency of reward is proportional to learning success, and human-scale sparse rewards permit greater learning than exclusively automated rewards. Diversity of training task sets did not affect learning. Long-term stability of trained controllers was observed. Using human-generated rewards to train RL controllers for upper-extremity FES systems may be useful. Our findings represent progress toward achieving human–machine teaming in control of upper-extremity FES systems for more natural arm movements based on human user preferences and RL algorithm learning capabilities.

A review of the design and clinical evaluation of the ShefStim array-based functional electrical stimulation system

Functional electrical stimulation has been shown to be a safe and effective means of correcting foot drop of central neurological origin. Current surface-based devices typically consist of a single channel stimulator, a sensor for determining gait phase and a cuff, within which is housed the anode and cathode. The cuff-mounted electrode design reduces the likelihood of large errors in electrode placement, but the user is still fully responsible for selecting the correct stimulation level each time the system is donned. Researchers have investigated different approaches to automating aspects of setup and/or use, including recent promising work based on iterative learning techniques. This paper reports on the design and clinical evaluation of an electrode array-based FES system for the correction of drop foot, ShefStim. The paper reviews the design process from proof of concept lab-based study, through modelling of the array geometry and interface layer to array search algorithm development. Finally, the paper summarises two clinical studies involving patients with drop foot. The results suggest that the ShefStim system with automated setup produces results which are comparable with clinician setup of conventional systems. Further, the final study demonstrated that patients can use the system without clinical supervision. When used unsupervised, setup time was 14min (9min for automated search plus 5min for donning the equipment), although this figure could be reduced significantly with relatively minor changes to the design.

Development of flexible multi-channel muscle interfaces with advanced sensing function

Functional Electrical Stimulation (FES) helps individuals with paralysis recover their muscle function. As opposed to voluntary muscle movement, which involves probabilistic recruitment of different muscle fibers at the neuromuscular junction, FES is usually performed using electrodes with just one channel, and as a result, tends to stimulate the same muscle fibers repeatedly. This induces excess muscle fatigue, which manifests itself as a loss of generated force after extended stimulation. Since the force generated is not typically measured in a FES system, electrical stimulation parameters need to be adjusted manually when muscle fatigue occurs. To address the problems of current FES, we propose a flexible muscle interface device with multiple stimulation electrodes and an integrated pH sensor. By using different subsets of electrodes for stimulation, alternating excitation of muscle fibers can be achieved to reduce fatigue in the muscles. At the same time, the pH sensor helps to provide quantified information about the state of the muscles, potentially allowing the stimulation parameters to be altered in a closed-loop fashion. Different interfacing materials were compared in terms of impedance and charge delivery ability. IrOx exhibited lower impedance of 0.7kΩ at 1kHz, and higher charge storage capacity (CSC) of 23.77mC/cm2. In in vivo muscle stimulation experiments, the use of alternating electrodes during stimulation induced less muscle fatigue, as well as less pH change, compared to using fixed electrode pairs. This flexible multi-channel stimulation device can potentially be used to reduce and monitor muscle fatigue during functional electrical stimulation.

Functional electrical stimulation (FES): The science is strong, the clinical practice not yet – A review of evidence

The mechanisms that govern the application of noninvasive functional electrical stimulation (FES) have been delineated and clearly described in numerous evidenced-based research publications. The aim of this review is to summarize the primary, multi-system effects of noninvasive FES on the musculoskeletal system, the peripheral vascular system, and the central nervous systems. The presentation will relate these effects to multiple efficacious clinical studies in neuro-rehabilitation. The presentation will include discussion of the latest technological advancement in wearable FES systems and their critical role in achieving functional recovery following damage to the brain. The presentation will also offer an advanced practice model guided by the latest trend in the medical field focusing on patient-centered, personalized intervention.

Dealing with time-varying recruitment and length in Hill-type muscle models

Hill-type muscle models are often used in muscle simulation studies and also in the design and virtual prototyping of functional electrical stimulation systems. These models have to behave in a sufficiently realistic manner when recruitment level and contractile element (CE) length change continuously. For this reason, most previous models have used instantaneous CE length in the muscle׳s force vs. length (F–L) relationship, but thereby neglect the instability problem on the descending limb (i.e. region of negative slope) of the F–L relationship. Ideally CE length at initial recruitment should be used but this requires a multiple-motor-unit muscle model to properly account for different motor-units having different initial lengths when recruited. None of the multiple-motor-unit models reported in the literature have used initial CE length in the muscle׳s F–L relationship, thereby also neglecting the descending limb instability problem. To address the problem of muscle modelling for continuously varying recruitment and length, and hence different values of initial CE length for different motor-units, a new multiple-motor-unit muscle model is presented which considers the muscle to comprise 1000 individual Hill-type virtual motor-units, which determine the total isometric force. Other parts of the model (F–V relationship and passive elements) are not dependent on the initial CE length and, therefore, they are implemented for the muscle as a whole rather than for the individual motor-units. The results demonstrate the potential errors introduced by using a single-motor-unit model and also the instantaneous CE length in the F–L relationship, both of which are common in FES control studies.

EEG-based BCI for the linear control of an upper-limb neuroprosthesis

Assistive technologies help patients to reacquire interacting capabilities with the environment and improve their quality of life. In this manuscript we present a feasibility study in which healthy users were able to use a non-invasive Motor Imagery (MI)-based brain computer interface (BCI) to achieve linear control of an upper-limb functional electrical stimulation (FES) controlled neuro-prosthesis. The linear control allowed the real-time computation of a continuous control signal that was used by the FES system to physically set the stimulation parameters to control the upper-limb position. Even if the nature of the task makes the operation very challenging, the participants achieved a mean selection accuracy of 82.5% in a target selection experiment. An analysis of limb kinematics as well as the positioning precision was performed, showing the viability of using a BCI–FES system to control upper-limb reaching movements. The results of this study constitute an accurate use of an online non-invasive BCI to operate a FES-neuroprosthesis setting a step toward the recovery of the control of an impaired limb with the sole use of brain activity.

SSVEP-Based Brain–Computer Interface Controlled Functional Electrical Stimulation System for Upper Extremity Rehabilitation

Traditional rehabilitation techniques have limited effects on the recovery of patients with tetraplegia. A brain–computer interface (BCI) provides an interactive channel that does not depend on the normal output of peripheral nerves and muscles. In this paper, an integrated framework of a noninvasive electroencephalogram (EEG)-based BCI with a noninvasive functional electrical stimulation (FES) is established, which can potentially enable the upper limbs to achieve more effective motor rehabilitation. The EEG signals based on steady-state visual evoked potential are used in the BCI. Their frequency domain characteristics identified by the pattern recognition method are utilized to recognize intentions of five subjects with average accuracy of 73.9%. Furthermore the movement intentions are transformed into instructions to trigger FES, which is controlled with iterative learning control method, to stimulate the relevant muscles of upper limbs tracking desired velocity and position. It is a useful technology with potential to restore, reinforce or replace lost motor function of patients with neurological injuries. Experiments with five healthy subjects demonstrate the feasibility of BCI integrated with upper extremity FES toward improved function restoration for an individual with upper limb disabilities, especially for patients with tetraplegia.

Real-time estimation of FES-induced joint torque with evoked EMG : Application to spinal cord injured patients.

BackgroundFunctional electrical stimulation (FES) is a neuroprosthetic technique for restoring lost motor function of spinal cord injured (SCI) patients and motor-impaired subjects by delivering short electrical pulses to their paralyzed muscles or motor nerves. FES induces action potentials respectively on muscles or nerves so that muscle activity can be characterized by the synchronous recruitment of motor units with its compound electromyography (EMG) signal is called M-wave. The recorded evoked EMG (eEMG) can be employed to predict the resultant joint torque, and modeling of FES-induced joint torque based on eEMG is an essential step to provide necessary prediction of the expected muscle response before achieving accurate joint torque control by FES.MethodsPrevious works on FES-induced torque tracking issues were mainly based on offline analysis. However, toward personalized clinical rehabilitation applications, real-time FES systems are essentially required considering the subject-specific muscle responses against electrical stimulation. This paper proposes a wireless portable stimulator used for estimating/predicting joint torque based on real time processing of eEMG. Kalman filter and recurrent neural network (RNN) are embedded into the real-time FES system for identification and estimation.ResultsPrediction results on 3 able-bodied subjects and 3 SCI patients demonstrate promising performances. As estimators, both Kalman filter and RNN approaches show clinically feasible results on estimation/prediction of joint torque with eEMG signals only, moreover RNN requires less computational requirement.ConclusionThe proposed real-time FES system establishes a platform for estimating and assessing the mechanical output, the electromyographic recordings and associated models. It will contribute to open a new modality for personalized portable neuroprosthetic control toward consolidated personal healthcare for motor-impaired patients.

A Hybrid Functional Electrical Stimulation for Real-Time Estimation of Joint Torque and Closed-Loop Control of Muscle Activation.

As a neuroprosthetic technique, functional electrical stimulation (FES) can restore lost motor performance of impaired patients. Through delivering electrical pulses to target muscles, the joint movement can be eventually elicited. This work presents a real-time FES system which is able to deal with two neuroprosthetic missions: one is estimating FES-induced joint torque with evoked electromyograph (eEMG), and the other is artificially controlling muscle activation with such eEMG feedback. The clinical experiment results on spinal cord injured (SCI) patients and healthy subjects show promising performance of the proposed FES system.

Evolution of Surface Motor Activation Zones in Hemiplegic Patients During 20 Sessions of FES Therapy with Multi-pad Electrodes.

The purpose of this study was to examine surface motor activation zones for wrist, fingers and thumb extension movements and their temporal change during 20 therapy sessions using advanced multi-pad functional electrical stimulation system. Results from four hemiplegic patients indicate that certain zones have higher probability of eliciting each of the target movements. However, mutual overlap and variations of the zones are present not just between the subjects, but also on the intrasubject level, reflected through these session to session transformations of the selected virtual electrodes. The obtained results could be used as a priori knowledge for semi-automated optimization algorithm and could shorten the time required for calibration of the multi-pad electrode.

Paired Associative Stimulation Using Brain-Computer Interfaces for Stroke Rehabilitation: A Pilot Study.

Conventional therapies do not provide paralyzed patients with closed-loop sensorimotor integration for motor rehabilitation. Paired associative stimulation (PAS) uses brain-computer interface (BCI) technology to monitor patients’ movement imagery in real-time, and utilizes the information to control functional electrical stimulation (FES) and bar feedback for complete sensorimotor closed loop. To realize this approach, we introduce the recoveriX system, a hardware and software platform for PAS. After 10 sessions of recoveriX training, one stroke patient partially regained control of dorsiflexion in her paretic wrist. A controlled group study is planned with a new version of the recoveriX system, which will use a new FES system and an avatar instead of bar feedback.

Fatigue and fracture of wires and cables for biomedical applications

Fine wires and cables play a critical role in the design of medical devices and subsequent treatment of a large array of medical diagnoses. Devices such as guide wires, catheters, pacemakers, stents, staples, functional electrical stimulation systems, eyeglass frames and orthodontic braces can be comprised of wires with diameters ranging from 10s to 100s of micrometres. Reliability is paramount as part of either internal or external treatment modalities. While the incidence of verified fractures in many of these devices is quite low, the criticality of these components requires a strong understanding of the factors controlling the fracture and fatigue behaviour.1,2 Additionally, optimisation of the performance and reliability of these devices necessitates characterisation of the fatigue and fracture properties of its constituent wires. A review of cable architecture and stress states experienced during testing is followed by an overview of the effects of changes in material composition, microstructure, processing and test conditions on fracture and fatigue behaviour of wire and cable systems used in biomedical applications. The review concludes with recommendations for future work.

BCI-FES system for neuro-rehabilitation of stroke patients

Nowadays, strokes are a growing cause of mortality and many people remain with motor sequelae and troubles in the daily activities. To treat this sequelae, alternative rehabilitation techniques are needed. In this article a Brain Computer Interface (BCI) system to control a Functional Electrical Stimulation (FES) system is presented. It can be used as a novel tool in easy setup clinical routines, to improve the rehabilitation process by mean of detecting patient´s motor intention, performing it by FES and finally receiving appropriate feedback The BCI-FES system presented here, consists of three blocks: the first one decodes the patient´s intention and it is composed by the patient, the acquisition hardware and the processing software (Emotiv EPOC®). The second block, based on Arduino’s technology, transforms the information into a valid command signal. The last one excites the patient´s neuromuscular system by means of a FES device. In order to evaluate the cerebral activity sensed by the device, topographic maps were obtained. The BCI-FES system was able to detect the patient´s motor intention and control the FES device. At the time of this publication, the system it’s being employing in a rehabilitation program with patients post stroke.

Functional electrical stimulation through direct 4-channel nerve stimulation to improve gait in multiple sclerosis: a feasibility study.

BackgroundGait dysfunction due to lower limb central paralysis, frequently involving drop foot, is a common cause of disability in multiple sclerosis and has been treated with transcutaneous functional electrical stimulation (FES). We provide here the first report of 4-channel semi-implantable FES of the peroneal nerve which has been successfully used for rehabilitation in patients following stroke.MethodsFES was implemented via a 4-channel semi-implantable closed-loop system (ActiGait®, ©Ottobock), generating dorsiflexion in drop foot. Walking distance, gait symmetry (temporospatial gait analyses, Vicon Motion Systems®), gait velocity (10 m walking test) and quality of life (SF-36 questionnaire) were measured to evaluate the therapeutic benefit of this system in two patients with progressive MS.ResultsWalking distance increased from 517 to 1884 m in Patient 1 and from 52 to 506 m in Patient 2. Gait velocity did not change significantly in Patient 1 and increased from 0.6 to 0.8 m/s in Patient 2. Maximum deviations of center of mass from the midline to each side changed significantly after 3 months of stimulation compared to baseline, decreasing from 15 to 12 mm in Patient 1 and from 47 to 37 mm in Patient 2. Both patients experienced reduced pain and fatigue and benefits to quality of life. Adverse events did not occur during the observation period.ConclusionWe conclude that implantable 4-channel FES systems are not only feasible but present a promising new alternative for treating central drop foot in MS patients.

Application of automatic energy-based pain recognition in functional electrical stimulation

Purpose: Validate and test a method for automatic detection of painful electrical stimulation using computer vision techniques. Context: In rehabilitation of stroke patients with motor deficits, functional electrical stimulation (FES) of muscles and nerves is a method used for activating the muscles and assisting body movements [1]. The stimulation can be painful, e.g. if the intensity is too high, electrode positioning is wrong or if the electrode/skin contact becomes poor. This is not desirable as it, most likely, discourages the patient to continue using the system. Therefore, a tele-rehabilitation FES system should incorporate methods for automatic detection of painful stimulation and ask the patient to reassess electrode contact and/or positioning upon detection.

Effects of implantable peroneal nerve stimulation on gait quality, energy expenditure, participation and user satisfaction in patients with post-stroke drop foot using an ankle-foot orthosis.

To investigate whether an implantable functional electrical stimulation (FES) system of the common peroneal nerve (ActiGait®) improves relevant aspects of gait in chronic stroke patients with a drop foot typically using an ankle-foot orthosis (AFO). Ten community-dwelling patients participated, of whom eight patients could be analysed. Gait quality (kinematic, kinetic, and spatiotemporal characteristics) during a 10-meter comfortable walk test, normalised net energy expenditure during a 6-minute walk test, participation (physical activity and stroke impact) and user satisfaction were tested before implantation and at various moments after FES-system activation up to 26 weeks. Walking with FES yielded increased maximum paretic ankle plantarflexion (FES: -0.12; AFO: -4.79°, p < 0.01), higher paretic peak ankle power (FES: 1.46; AFO: 0.98 W/kg, p < 0.05) and better step length symmetry (FES: 14.90; AFO: 21.45% , p < 0.05). User satisfaction was higher for FES, but was unrelated to objective gait improvements. Energy expenditure and participation did not change. Implantable FES improved the use of residual ankle plantarflexion motion, ankle power of the paretic leg and step length symmetry compared to using an AFO, however, not resulting in decreased energy expenditure or improved participation. User satisfaction was highest with FES, but this was not related to the observed gait improvements.

The feasibility of a brain-computer interface functional electrical stimulation system for the restoration of overground walking after paraplegia.

BackgroundDirect brain control of overground walking in those with paraplegia due to spinal cord injury (SCI) has not been achieved. Invasive brain-computer interfaces (BCIs) may provide a permanent solution to this problem by directly linking the brain to lower extremity prostheses. To justify the pursuit of such invasive systems, the feasibility of BCI controlled overground walking should first be established in a noninvasive manner. To accomplish this goal, we developed an electroencephalogram (EEG)-based BCI to control a functional electrical stimulation (FES) system for overground walking and assessed its performance in an individual with paraplegia due to SCI.MethodsAn individual with SCI (T6 AIS B) was recruited for the study and was trained to operate an EEG-based BCI system using an attempted walking/idling control strategy. He also underwent muscle reconditioning to facilitate standing and overground walking with a commercial FES system. Subsequently, the BCI and FES systems were integrated and the participant engaged in several real-time walking tests using the BCI-FES system. This was done in both a suspended, off-the-ground condition, and an overground walking condition. BCI states, gyroscope, laser distance meter, and video recording data were used to assess the BCI performance.ResultsDuring the course of 19 weeks, the participant performed 30 real-time, BCI-FES controlled overground walking tests, and demonstrated the ability to purposefully operate the BCI-FES system by following verbal cues. Based on the comparison between the ground truth and decoded BCI states, he achieved information transfer rates >3 bit/s and correlations >0.9. No adverse events directly related to the study were observed.ConclusionThis proof-of-concept study demonstrates for the first time that restoring brain-controlled overground walking after paraplegia due to SCI is feasible. Further studies are warranted to establish the generalizability of these results in a population of individuals with paraplegia due to SCI. If this noninvasive system is successfully tested in population studies, the pursuit of permanent, invasive BCI walking prostheses may be justified. In addition, a simplified version of the current system may be explored as a noninvasive neurorehabilitative therapy in those with incomplete motor SCI.Electronic supplementary materialThe online version of this article (doi:10.1186/s12984-015-0068-7) contains supplementary material, which is available to authorized users.

Real-time gait event detection for transfemoral amputees during ramp ascending and descending.

Events and phases detection of the human gait are vital for controlling prosthesis, orthosis and functional electrical stimulation (FES) systems. Wearable sensors are inexpensive, portable and have fast processing capability. They are frequently used to assess spatio-temporal, kinematic and kinetic parameters of the human gait which in turn provide more details about the human voluntary control and ampute-eprosthesis interaction. This paper presents a reliable real-time gait event detection algorithm based on simple heuristics approach, applicable to signals from tri-axial gyroscope for lower limb amputees during ramp ascending and descending. Experimental validation is done by comparing the results of gyroscope signal with footswitches. For healthy subjects, the mean difference between events detected by gyroscope and footswitches is 14 ms and 10.5 ms for initial contact (IC) whereas for toe off (TO) it is -5 ms and -25 ms for ramp up and down respectively. For transfemoral amputee, the error is slightly higher either due to the placement of footswitches underneath the foot or the lack of proper knee flexion and ankle plantarflexion/dorsiflexion during ramp up and down. Finally, repeatability tests showed promising results.

Assessment of brain–machine interfaces from the perspective of people with paralysis

Objective. One of the main goals of brain–machine interface (BMI) research is to restore function to people with paralysis. Currently, multiple BMI design features are being investigated, based on various input modalities (externally applied and surgically implantable sensors) and output modalities (e.g. control of computer systems, prosthetic arms, and functional electrical stimulation systems). While these technologies may eventually provide some level of benefit, they each carry associated burdens for end-users. We sought to assess the attitudes of people with paralysis toward using various technologies to achieve particular benefits, given the burdens currently associated with the use of each system. Approach. We designed and distributed a technology survey to determine the level of benefit necessary for people with tetraplegia due to spinal cord injury to consider using different technologies, given the burdens currently associated with them. The survey queried user preferences for 8 BMI technologies including electroencephalography, electrocorticography, and intracortical microelectrode arrays, as well as a commercially available eye tracking system for comparison. Participants used a 5-point scale to rate their likelihood to adopt these technologies for 13 potential control capabilities. Main Results. Survey respondents were most likely to adopt BMI technology to restore some of their natural upper extremity function, including restoration of hand grasp and/or some degree of natural arm movement. High speed typing and control of a fast robot arm were also of interest to this population. Surgically implanted wireless technologies were twice as ‘likely’ to be adopted as their wired equivalents. Significance. Assessing end-user preferences is an essential prerequisite to the design and implementation of any assistive technology. The results of this survey suggest that people with tetraplegia would adopt an unobtrusive, autonomous BMI system for both restoration of upper extremity function and control of external devices such as communication interfaces.

Coordinating Upper and Lower Body During FES-Assisted Transfers in Persons With Spinal Cord Injury in Order to Reduce Arm Support.

The goal of this study is to minimize arm forces applied during sit-to-stand (STS) transfers in persons with spinal cord injury (SCI) by using functional electrical stimulation (FES) applied to lower limbs muscles. A new FES system has been used to automatically trigger muscle stimulation of the lower limbs, at the desired moment in regards to trunk motion. The objective was to decrease arm participation during STS motion of a person with complete paraplegia and low-level tetraplegia. Six participants with chronic SCI participated in the study. Participants with SCI were recruited to complete STS movement using a new system for FES-assisted STS transfer. All participants attended one muscle mapping session to test their muscles condition, two training sessions to become familiarized with the experimental setup, and two measurement sessions using the proposed system for FES-assisted STS movement. The applied arm forces during STS movement were recorded and analyzed for different stimulation onset values with respect to the maximal trunk acceleration signal using one-way ANOVA statistical test. Post-hoc analysis was performed using Tukey's method. The results of this study showed that the moment of the stimulation onset has an influence on the arm forces applied during the STS motion. The lowest values of arm forces were obtained for STS movements where the electrical stimulation was triggered before and around the time corresponding to the maximal value of the trunk acceleration signal. Lowest arm forces values were obtained for STS motions that were similar to those of healthy persons in terms of trunk movements and beginning of lower limb movements in regards to maximal trunk acceleration signal. The FES system was able to mimic the rising motion of a healthy individual by triggering the FES at the appropriate moment. This method could prove useful for pivot transfer, therapeutic or functional verticalization.