Posts Tagged surface electromyography

[Abstract + References] A Multi-channel EMG-Driven FES Solution for Stroke Rehabilitation – Conference paper

Abstract

Functional electrical stimulation (FES) has been applied to stroke rehabilitation for many years. However, users are usually involved in open-loop fixed cycle FES systems in clinical, which is easy to cause muscle fatigue and reduce rehabilitation efficacy. This paper proposes a multi-surface EMG-driven FES integration solution for enhancing upper-limb stroke rehabilitation. This wireless portable system consists of sEMG data acquisition module and FES module, the former is used to capture sEMG signals, the latter of multi-channel FES output can be driven by the sEMG. Preliminary experiments proved that the system has outperformed existing similar systems and that sEMG can be effectively employed to achieve different FES intensity, demonstrating the potential for active stroke rehabilitation.

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[WEB SITE] What Modern Day Challenges Affect Epilepsy Treatment?

epilepsy

Researchers recently published an article in The Lancet Neurology discussing the difficulties facing seizure detection in patients with epilepsy.

Epilepsy is a neurological disorder that is characterised by short repetitive epileptic seizures.  These seizures can be harmful to the individual depending on the circumstances in which they occur, such as a seizure while driving. This disorder is set apart from other neurological disorders since there is a broad range of different physiological changes that can cause it, leading to a large variation in symptoms and making it difficult to treat. While 70% of sufferers can be treated with pharmacological agents, 30% have no reliable anti-epileptic drugs that are effective for their particular type of epilepsy.

In a recent study, Christian Elger and Christian Hoppe determined that a key challenge facing patients is that over 50% of patients under-report the number of seizures they experience, which has a serious impact on how well doctors are able to determine what treatments are most suitable for them. This also calls into question many of the previously published research on epilepsy treatments. They recently published this report in The Lancet Neurology.

Why are Epileptic Seizures Difficult to Detect?

In this personal view, the writers determined that the cause of under-reporting is primarily due to patients, or their caregivers, being unable to identify when seizures are occurring. Seizures can impair consciousness, may occur at night, or the physical symptoms may be so subtle that they are not easily noticed unless professionally trained to do so.

Technologies for Epilepsy DetectionThe gold standard for epilepsy detection is video-electroencephalography (VEEG), where patients have their brain activity monitored for epilepsy-specific activity and trained technicians can test for impairments to consciousness, cognition, language, and memory. Video footage from the VEEG can also be viewed at a later time to spot slight body movements indicative of a seizure. The limitation of this method is that it requires a hospital visit, increasing associated costs, and is only suitable for identifying how frequent a person has a seizure over a given time, it does not address the issue of a person (or their caregiver) being aware they are having a seizure in real time.

Automated System Required

It is clear that the future of seizure detection requires an automated system,  preferably one that patients can wear over the long-term and that will notify them or a nearby center when a seizure occurs. The main barriers to this technology is that a number of the current ambulatory systems for monitoring brain activity can be limited in monitoring time (72 hours) or require labor-intensive analysis of data, although as algorithms for analyzing brain activity improve this limitation will also decrease.

An analysis of movement via home-based video systems, or of various physical data outputs (i.e. accelerometry, magnetometry, gyroscopy, or pressure data) derived from worn sensors have some promise but so far the results have not been consistent.

Surface Electromyography

It appears that one of the most promising methods, which is also viewed favorably by patients, is surface electromyography (SEMG). This method involves self-adhesive sensors that are attached to muscles in areas of the body affected by seizures. Furthermore, multi-modal approaches that combine SEMG, EEG, and electrocardiography have a detection rate over 85% for the majority of seizure types.

Improved Seizure Detection Necessary

It is clear that improved seizure detection is necessary for ensuring that doctors provide the most appropriate treatment to individual patients, as well as ensuring that patients are protected from life-threatening seizures. Improving wearable, ambulatory technologies and advancements in algorithms for the analysis of seizure data will help provide comprehensive support to both physicians and to the patients that they monitor.

Written by Michael Healy, BSc, MSc

Reference: Elger C.E., Hoppe C. Diagnostic challenges in epilepsy: seizure under-reporting and seizure detection. Lancet Neurol 2018; 17: 279–88.

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[Abstract+References] Combined Transcranial Direct Current Stimulation and Virtual Reality-Based Paradigm for Upper Limb Rehabilitation in Individuals with Restricted Movements. A Feasibility Study with a Chronic Stroke Survivor with Severe Hemiparesis

Abstract

Impairments of the upper limb function are a major cause of disability and rehabilitation. Most of the available therapeutic options are based on active exercises and on motor and attentional inclusion of the affected arm in task oriented movements. However, active movements may not be possible after severe impairment of the upper limbs. Different techniques, such as mirror therapy, motor imagery, and non-invasive brain stimulation have been shown to elicit cortical activity in absence of movements, which could be used to preserve the available neural circuits and promote motor learning. We present a virtual reality-based paradigm for upper limb rehabilitation that allows for interaction of individuals with restricted movements from active responses triggered when they attempt to perform a movement. The experimental system also provides multisensory stimulation in the visual, auditory, and tactile channels, and transcranial direct current stimulation coherent to the observed movements. A feasibility study with a chronic stroke survivor with severe hemiparesis who seemed to reach a rehabilitation plateau after two years of its inclusion in a physical therapy program showed clinically meaningful improvement of the upper limb function after the experimental intervention and maintenance of gains in both the body function and activity. The experimental intervention also was reported to be usable and motivating. Although very preliminary, these results could highlight the potential of this intervention to promote functional recovery in severe impairments of the upper limb.

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[ARTICLE] Adaptation of a smart walker for stroke individuals: a study on sEMG and accelerometer signals – Full Text

ABSTRACT

Introduction:

Stroke is a leading cause of neuromuscular system damages, and researchers have been studying and developing robotic devices to assist affected people. Depending on the damage extension, the gait of these people can be impaired, making devices, such as smart walkers, useful for rehabilitation. The goal of this work is to analyze changes in muscle patterns on the paretic limb during free and walker-assisted gaits in stroke individuals, through accelerometry and surface electromyography (sEMG).

Methods

The analyzed muscles were vastus medialis, biceps femoris, tibialis anterior and gastrocnemius medialis. The volunteers walked three times on a straight path in free gait and, further, three times again, but now using the smart walker, to help them with the movements. Then, the data from gait pattern and muscle signals collected by sEMG and accelerometers were analyzed and statistical analyses were applied.

Results

The accelerometry allowed gait phase identification (stance and swing), and sEMG provided information about muscle pattern variations, which were detected in vastus medialis (onset and offset; p = 0.022) and biceps femoris (offset; p = 0.025). Additionally, comparisons between free and walker-assisted gaits showed significant reduction in speed (from 0.45 to 0.30 m/s; p = 0.021) and longer stance phase (from 54.75 to 60.34%; p = 0.008).

Conclusions

Variations in muscle patterns were detected in vastus medialis and biceps femoris during the experiments, besides user speed reduction and longer stance phase when the walker-assisted gait is compared with the free gait.

Keywords Stroke,sEMG,Smart walker,Gait,Accelerometer

INTRODUCTION

Stroke is considered a major health issue worldwide, since it is a leading cause of motor disabilities, affecting the independence and ability to perform daily tasks in most cases (Belda-Lois et al., 2011World…, 2015). There are two distinct types of stroke: the ischemic and the hemorrhagic. The first one is the most common and is responsible for 85-90% of cases, while the second type occurs in a smaller number (10-15%). In contrast, the mortality rate ranges from 8 to 12% for the ischemic type, while the hemorrhagic type has more fatal outcomes with numbers varying between 33% and 45% (Ovbiagele and Nguyen-Huynh, 2011).

Aside from the stroke type, the location and extension of the brain lesions may lead to different sequels (Deb et al., 2010) and, due to this reason there is a high heterogeneity among stroke sequels (Belda-Lois et al., 2011), varying according to the brain lesion location and extension. A lesion that occurs in the anterior cerebral artery, for example, may cause motor injuries predominantly in the lower extremity of the contralateral side, which interfere in the gait and body balance (Pare and Kahn, 2012).

Patients that had stroke usually have spastic muscles in the quadriceps femoris (vastus medialis, vastus lateralis, vastus intermedius and rectus femoris) and triceps surae (gastrocnemius medialis, gastrocnemius lateralis and soleus) while the hamstrings (biceps femoris, semitendinosus and semimembranosus) and tibialis anterior are flaccid, hindering the knee flexion and dorsiflexion (Murray et al., 2014Sheffler and Chae, 2015). In spite of flexor weakness, stroke individuals present more co-contractions between agonist and antagonist muscles when compared with healthy subjects (Shao et al., 2009), which occur in order to avoid knee and plantar hyperflexion.

All these conditions create a tendency on stroke individuals to produce a compensatory movement in order to walk, which is known as hip circumduction, typical in stroke gait (Whittle, 2007), causing an asymmetric gait, and overloading the non-paretic limb.

Due to this asymmetry and lack of balance, about 75% of stroke patients need assistance for walking independently during the first three months after stroke onset (Verma et al., 2012). However, there are no evidence-based criteria for choosing the device to help the patient (Verma et al., 2012). Tyson and Rogerson (2009) evaluated the use of cane and foot-ankle orthosis, which provided confidence and safety to the patients (20 stroke patients; mean age: 65.6 ± 10.4 years; mean time since stroke: 6.5 ± 5.7 weeks), improving their functional mobility. On the other hand, Suica et al. (2016) analyzed the immediate effect using a rollator, although for healthy subjects (19 subjects; 22 to 70 years), identifying a reduced muscle activity of the lower limbs (gluteus medius and maximus, rectus femoris, semitendinosus, tibialis anterior and gastrocnemius) caused by the weight bearing imposed on the walker.

Most stroke individuals need rehabilitation, whose main goal is the movement recovery to allow them to carry out daily tasks independently (Dohring and Daly, 2008Roger et al., 2011). This rehabilitation depends on many factors: lesion severity, age, type of therapeutic intervention, and how complex the stroke was. However, in many cases, rehabilitation does not provide an efficient recovery, and sometimes worsening the clinical status and the damage in the non-paretic limb. In such cases, those therapeutic interventions may provoke decreased mobility and secondary complications (Allen et al., 2011). On the other hand, conventional gait training and rehabilitation, commonly used nowadays, may not provide a total restoration for most patients (Dohring and Daly, 2008Suica et al., 2016).

Many studies (Cifuentes et al., 2014Dohring and Daly, 2008Tan et al., 2013) used robotic devices for motor rehabilitation, to recover important features of the gait and maintain muscle integrity. However, to the extent of our knowledge, no neuromuscular analysis was performed using robotic walkers applied for stroke rehabilitation. The main goal of this paper is to analyze changes in the muscle pattern on paretic limb during free and walker-assisted gaits in stroke individuals, through accelerometry and surface electromyography (sEMG). Another important goal is to verify the volunteer adaptation to a smart walker in the first contact. Therefore, this study is focused on the pattern-variation analysis of the paretic limb muscles and the swing and stance phase duration, in addition to the walking speed during the use of robotic walker and in free gait.

METHODS

Volunteers

Eight ischemic stroke individuals (4 males and 4 females; 65.75 ± 6.27 years old), from a rehabilitation institution of Espirito Santo state (Brazil), volunteered for the experiments. The number of volunteers generated a sample size for this study that has an effect size of 0.8, with statistical power of 50% and alpha equals 0.05. The research was previously approved by the Ethical Committee of Federal University of Espírito Santo (UFES/Brazil) and all volunteers signed the informed consent.

Eligibility criteria for inclusion in this study were: only one stroke that happened at least from 6 months up to 5 years before the tests; hemiparetic gait; Functional Ambulation Classification – FAC (Holden et al., 1984) in stage 2 or higher; ability to remain erect and with elbows at 90º while using the smart walker; age range from 50 to 80 years; enough cognitive skills and language to follow the experiment instructions. Individuals were excluded if they could not walk independently, had any musculoskeletal or neurological disorder limiting ambulation unrelated to the stroke, and if they had cardiorespiratory impairment, conditions that may prevent them from performing walking tests. Each volunteer was classified through a functional walking test (FAC) by the same physiotherapist, who has more than 20 years of experience.

sEMG and accelerometer data

All procedures for sEMG data acquisition and processing were based on recommendations of the “Standards for reporting EMG data” (Merletti and Torino, 2015). The kind of electrodes used was Ag/AgCl discoid shape, with 10 mm diameter, pre-gelled and with inter-electrode distance of 20 mm. Before the electrode placement, the skin was cleaned (alcohol 70%) and shaved to reduce impedance. Signals from four muscles of lower limb — vastus medialis (VM), biceps femoris (BF), tibialis anterior (TA) and gastrocnemius medialis (GM) — were acquired and analyzed. In addition, a reference electrode was placed on the medial malleolus. In all cases, the analyzed limb was the contralateral to the brain lesion. For better accuracy in electrode placement, two experts checked the electrode position placed on the muscles. Cables from the sEMG acquisition equipment were fixed on the limb using adhesive tape to minimize motion artifacts. In addition, a biaxial accelerometer was fixed using adhesive tape on the ankle of the contralateral limb, with the y-axis pointing cranially and x-axis pointing anteriorly.

Both sEMG and accelerometer data were recorded simultaneously using an acquisition equipment EMG 830C (EMG System do Brasil Ltda®) with 16-bit analog/digital conversion resolution, amplifier gain up to 2000V/V, common mode rejection > 100dB, input impedance of 109Ω, and maximum sampling frequency of 2 kHz. The measurement capacity ranged from -2000 to 2000 μV with sensitivity of 0.061 μV.

Smart walker

A smart walker from UFES/Brazil (Valadão et al., 2016) (Figure 1) was used in the experiments, which was built from a conventional four-legged walker adapted to a robotic mobile platform. The smart walker structure has forearm bars to provide weight support and comfort during its use, also allowing the user to guide it. The smart walker has also a height adjustment, which allows the user to stay in an upright posture. An onboard laser sensor is used to provide information about the distance from the walker to the user’s leg. By using the information provided by the laser sensor, the walker can adjust its speed through a proportional–integral–derivative controller (PID), with the goal of keeping the user at a predefined distance and angle, thus aiding him/her to maintain right posture (position and orientation) while using the device. […]

Figure 1 Smart Walker scheme: side view (left) and top view (middle). Stroke subject using the walker (right) in an experiment. Structure changes in the walker: (a) Handlebar; (b) Forearm support; (c) Stabilizer bars; (d) Laser sensor; (e) Pioneer 3-DX robot; (f) Free wheels; (g) Fixed distance (70 cm) from the user to laser sensor. 

 

Continue —> Adaptation of a smart walker for stroke individuals: a study on sEMG and accelerometer signals

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[Abstract] The eWrist — A wearable wrist exoskeleton with sEMG-based force control for stroke rehabilitation.

Abstract:

Chronic wrist impairment is frequent following stroke and negatively impacts everyday life. Rehabilitation of the dysfunctional limb is possible but requires extensive training and motivation. Wearable training devices might offer new opportunities for rehabilitation. However, few devices are available to train wrist extension even though this movement is highly relevant for many upper limb activities of daily living. As a proof of concept, we developed the eWrist, a wearable one degree-of-freedom powered exoskeleton which supports wrist extension training. Conceptually one might think of an electric bike which provides mechanical support only when the rider moves the pedals, i.e. it enhances motor activity but does not replace it. Stroke patients may not have the ability to produce overt movements, but they might still be able to produce weak muscle activation that can be measured via surface electromyography (sEMG). By combining force and sEMG-based control in an assist-as-needed support strategy, we aim at providing a training device which enhances activity of the wrist extensor muscles in the context of daily life activities, thereby, driving cortical reorganization and recovery. Preliminary results show that the integration of sEMG signals in the control strategy allow for adjustable assistance with respect to a proxy measurement of corticomotor drive.

Source: The eWrist — A wearable wrist exoskeleton with sEMG-based force control for stroke rehabilitation – IEEE Xplore Document

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[ARTICLE] Late physiotherapy rehabilitation changes gait patterns in post-stroke patients – Full Text PDF

Summary
Study aim: To determine whether a physiotherapy protocol improves the electromyographic activation (EA) during the hemiparetic gait in patients with delayed access to rehabilitation. Material and methods: 40 post-stroke patients underwent clinical evaluation and gait assessment at the time of admission and at the end of treatment.

Results: The anterior leg muscles tibialis anterior and rectus femoris had earlier onset (p = 0.0001).

Conclusion: Electromyographic findings showed altered patterns during the hemiparetic gait cycle, even in patients with delayed access to treatment.

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[ARTICLE] Electromyographic Activity of the Upper Limb in Three Hand Function Tests – Full Text

Summary

Objective/Background

Occupational therapists usually assess hand function through standardised tests, however, there is no consensus on how the scores assigned to hand dexterity can accurately measure hand function required for daily activities and few studies evaluate the movement patterns of the upper limbs during hand function tests. This study aimed to evaluate the differences in muscle activation patterns during the performance of three hand dexterity tests.

Methods

Twenty university students underwent a surface electromyographic (sEMG) assessment of eight upper limb muscles during the performance of the box and blocks test (BBT), nine-hole peg test (9HPT), and functional dexterity test (FDT). The description and comparison of each muscle activity during the test performance, gender differences, and the correlation between individual muscles’ sEMG activity were analysed through appropriate statistics.

Results

Increased activity of proximal muscles was found during the performance of BBT (p < .001). While a higher activation of the distal muscles occurred during the FDT and 9HPT performance, no differences were found between them. Comparisons of the sEMG activity revealed a significant increase in the muscle activation among women (p = .05). Strong and positive correlations (r > .5; p < .05) were observed between proximal and distal sEMG activities, suggesting a coordinate pattern of muscle activation during hand function tests.

Conclusion

The results suggested the existence of differences in the muscle activation pattern during the performance of hand function evaluations. Occupational therapists should be aware of unique muscle requirements and its impact on the results of dexterity tests during hand function evaluation.

Introduction

Hand and upper extremity function is essential to humans as it allows for the performance of a wide range of self-care, productive, and leisure activities (Chan & Spencer, 2004). Due to its importance, impairments in the upper extremities lead to restrictions on activity performance and impacts participation in social activities and engagements in meaningful occupations, ultimately affecting overall wellbeing and quality of life (van de Ven-Stevens et al., 2016).

Treating patients with hand and upper limb injuries is a common situation for occupational therapists; hand and wrist lesions account for approximately 20% of all cases seen in hospital emergency departments (Dias & Garcia-Elias, 2006), with most patients presenting further limitations to upper extremity function due to a restricted range of motion, pain, oedema, and muscle weakness caused by the trauma (Ydreborg, Engstrand, Steinvall, & Larsson, 2015). In addition to acute situations, restricted hand function also represents one of the leading causes of limited participation in daily activities by patients with chronic diseases, such as rheumatoid arthritis (Andrade, Brandão, Pinto, & Lanna, 2016) and stroke (Dawson, Binns, Hunt, Lemsky, & Polatajko, 2013).

Although the cause of injury varies in different countries (Che Daud, Yau, Barnett, Judd, Jones, & Muhammad Nawawi, 2016), the majority of the upper limb trauma affects working adults aged between 20 years and 64 years (de Putter et al., 2016), thereby causing a significant economic impact. Studies completed in the past decade have estimated the healthcare and productivity costs of upper limb lesions to be US$ 410–740 million per year (de Putter et al., 2012 ;  de Putter et al., 2016), with increased absenteeism and early retirement age observed among patients (Shi et al., 2014 ;  Tiippana-Kinnunen et al., 2013).

Assessment procedures that allow occupational therapists to obtain accurate and reliable information regarding patients’ hand function are essential for setting realistic goals and measuring patients’ progression during the rehabilitation of upper limb injuries (Carrasco-Lopez et al., 2016). Amongst the several resources available, standardised manual tests are extensively used during the evaluations of hand function to assess the upper limb coordination and skill through a series of tasks involving the manipulation of objects in established patterns (Ekstrand et al., 2016; Srikesavan et al., 2015 ;  van de Ven-Stevens et al., 2016).

Despite focusing on the measurements of body functions and structures, standardised dexterity tests provide valid and reliable data that aids therapists in understanding the impact of hand injuries on patients’ activities of daily life. Commonly used standardised tests have high inter-rater and test-retest reliability, usually with an intraclass correlation coefficient (ICC) greater than 0.85 (Aaron and Jansen, 2003; Desrosiers et al., 1994 ;  Earhart et al., 2011).

However, given the existence of multiple standardised dexterity tests and an even greater variety of structured tasks involved in each assessment, there is no consensus on which test is more suitable for evaluating the entire function of upper extremities (van de Ven-Stevens et al., 2016). Moreover, there is an increasing concern regarding the way by which the scores assigned to hand dexterity can accurately measure hand function required for daily activities (Rallon and Chen, 2008; Rand and Eng, 2010 ;  van de Ven-Stevens et al., 2016).

The study of muscle activation through surface electromyography (sEMG) allows a real-time, noninvasive assessment of the activation pattern of muscles during the activity performance (Gurney et al., 2016). Although sEMG has been used to evaluate the muscle activation patterns in several self-care (Meijer et al., 2014), productivity (Almeida et al., 2013 ;  Ferrigno et al., 2009), and leisure activities (Donoso Brown, McCoy, Fechko, Price, Gilbertson, & Moritz, 2014), few studies have analysed the different recruitment of muscle fibres during the performances of different hand function tests (Brorsson et al., 2014 ;  Calder et al., 2011).

Considering the lack of studies describing the muscle activities of the upper extremities in standardised hand assessments, this study aimed to evaluate and compare the differences in muscle activation patterns during the performance of the box and blocks test (BBT), nine-hole peg test (9HPT), and functional dexterity test (FDT)—the three hand dexterity tests used by occupational therapists during hand function evaluation.

Continue —> Electromyographic Activity of the Upper Limb in Three Hand Function Tests

Experimental setting. (A) Box and blocks test; (B) Nine-hole peg test; (C) ...

Figure 1. Experimental setting. (A) Box and blocks test; (B) Nine-hole peg test; (C) functional dexterity test.

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[BOOK CHAPTER] Toward an Upper-Limb Neurorehabilitation Platform Based on FES-Assisted Bilateral Movement: Decoding User’s Intentionality

Abstract

In the last years there has been a noticeable progress in motor learning, neuroplasticity and functional recovery after the occurrence of brain lesion. Rehabilitation of motor function has been associated to motor learning that occurs during repetitive, frequent and intensive training. Neuro-rehabilitation is based on the assumption that motor learning principles can be applied to motor recovery after injury, and that training can lead to permanent improvements of motor functions in patients with muscle deficits. The emergent research field of Rehabilitation Engineering may provide promise technologies for neuro-rehabilitation therapies, exploiting the motor learning and neural plasticity concepts. Among those technologies, the FES-assisted systems could provide repetitive training-based therapies and have been developed to aid or control the upper and lower limbs movements in response to user’s intentionality. Surface electromyography (SEMG) reflects directly the human motion intention, so it can be used as input information to control an active FES-assisted system. The present work describes a neurorehabilitation platform at the upper-limb level, based on bilateral coordination training (i.e. mirror movements with the unaffected arm) using a close-loop active FES system controlled by user. In this way, this work presents a novel myoelectric controller for decoding movements of user to be employed in a neurorehabilitation platform. It was carried out a set of experiments to validate the myoelectric controller in classification of seven human upper-limb movements, obtaining an average classification error of 4.3%. The results suggest that the proposed myoelectric pattern recognition method may be applied to control close-loop FES system.

more —>  Toward an Upper-Limb Neurorehabilitation Platform Based on FES-Assisted Bilateral Movement: Decoding User’s Intentionality – Springer.

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[ARTICLE] A novel functional electrical stimulation-control system for restoring motor function of post-stroke hemiplegic patients – Full Text HTML/PDF

 Abstract  

Hemiparesis is one of the most common consequences of stroke. Advanced rehabilitation techniques are essential for restoring motor function in hemiplegic patients. Functional electrical stimulation applied to the affected limb based on myoelectric signal from the unaffected limb is a promising therapy for hemiplegia. In this study, we developed a prototype system for evaluating this novel functional electrical stimulation-control strategy. Based on surface electromyography and a vector machine model, a self-administered, multi-movement, force-modulation functional electrical stimulation-prototype system for hemiplegia was implemented. This paper discusses the hardware design, the algorithm of the system, and key points of the self-oscillation-prone system. The experimental results demonstrate the feasibility of the prototype system for further clinical trials, which is being conducted to evaluate the efficacy of the proposed rehabilitation technique.

Full Text HTML –> A novel functional electrical stimulation-control system for restoring motor function of post-stroke hemiplegic patients Huang Z, Wang Z, Lv X, Zhou Y, Wang H, Zong S – Neural Regen Res.

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[ARTICLE] REAL TIME BIOSIGNAL-DRIVEN ILLUSION SYSTEM FOR UPPER LIMB REHABILITATION

Abstract

This paper presents design and development of real time biosignal-driven illusion system: Augmented Reality based Illusion System (ARIS) for upper limb motor rehabilitation. ARIS is a hospital / home based self- motivated whole arm rehabilitation system that aims to improve and restore the lost upper limb functions due to Cerebrovascular Accident (CVA) or stroke.

Taking the advantage of human brain plasticity nature, the system incorporates with number of technologies to provide fast recovery by re-establishing the neural pathways and synapses that able to control the mobility. These technologies include Augmented Reality (AR) where illusion environment is developed, computer vision technology to track multiple colors in real time, EMG acquisition system to detect the user intention in real time and 3D modelling library to develop Virtual Arm (VA) model where human biomechanics are applied to mimic the movement of real arm. The system operates according to the user intention via surface electromyography (sEMG) threshold level. In the case of real arm cannot reach to the desired position, VA will take over the job of real arm to complete the exercise.

The effectiveness of the developed ARIS has evaluated via questionnaire, graphical and analytical measurements which provided with positive results.

via [Abstract] REAL TIME BIOSIGNAL-DRIVEN ILLUSION SYSTEM FOR UPPER LIMB REHABILITATION.

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