Posts Tagged Muscles

[Abstract] Biofeedback Signals for Robotic Rehabilitation: Assessment of Wrist Muscle Activation Patterns in Healthy Humans


Electrophysiological recordings from human muscles can serve as control signals for robotic rehabilitation devices. Given that many diseases affecting the human sensorimotor system are associated with abnormal patterns of muscle activation, such biofeedback can optimize human-robot interaction and ultimately enhance motor recovery. To understand how mechanical constraints and forces imposed by a robot affect muscle synergies, we mapped the muscle activity of 7 major arm muscles in healthy individuals performing goal-directed discrete wrist movements constrained by a wrist robot. We tested 6 movement directions and 4 force conditions typically experienced during robotic rehabilitation. We analyzed electromyographic (EMG) signals using a space-by-time decomposition and we identified a set of spatial and temporal modules that compactly described the EMG activity and were robust across subjects. For each trial, coefficients expressing the strength of each combination of modules and representing the underlying muscle recruitment, allowed for a highly reliable decoding of all experimental conditions. The decomposition provides compact representations of the observable muscle activation constrained by a robotic device. Results indicate that a low-dimensional control scheme incorporating EMG biofeedback could be an effective add-on for robotic rehabilitative protocols seeking to improve impaired motor function in humans.

Source: Biofeedback Signals for Robotic Rehabilitation: Assessment of Wrist Muscle Activation Patterns in Healthy Humans – IEEE Xplore Document

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[Abstract] Combining a hybrid robotic system with a bain-machine interface for the rehabilitation of reaching movements: A case study with a stroke patient


Reaching and grasping are two of the most affected functions after stroke. Hybrid rehabilitation systems combining Functional Electrical Stimulation with Robotic devices have been proposed in the literature to improve rehabilitation outcomes. In this work, we present the combined use of a hybrid robotic system with an EEG-based Brain-Machine Interface to detect the user’s movement intentions to trigger the assistance. The platform has been tested in a single session with a stroke patient. The results show how the patient could successfully interact with the BMI and command the assistance of the hybrid system with low latencies. Also, the Feedback Error Learning controller implemented in this system could adjust the required FES intensity to perform the task.

I. Introduction

Stroke is a leading cause of adult disability around the world. A large number of stroke survivors are left with a unilateral arm or leg paralysis. After completing conventional rehabilitation therapy, a significant number of stroke survivors are left with limited reaching and grasping capabilities [1].

Source: Combining a hybrid robotic system with a bain-machine interface for the rehabilitation of reaching movements: A case study with a stroke patient – IEEE Xplore Document

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[Abstract] Fatigue detection and estimation using auto-regression analysis in EEG


Estimation of fatigue is a required criteria in the field of physiology. The estimation of muscle fatigue and its development in the brain signals can provide a level of endurance among athletes and limits of a persons in doing physical tasks. In this paper a technique for detecting and estimating the fatigue development using regression parameters for EEG signals is discussed. The study of 14 subjects was undertaken and analysed for the fatigue development using Auto-Regression(AR) model. The behaviour of the error function obtained is analysed for the prediction of the stages and limits of muscle fatigue development.

I. Introduction

Muscle fatigue is a phenomenon associated with the muscle contraction. It is understood as the reduction in the ability of maximal force generation by the muscle with time, during its stressing, as the muscle contraction keeps on increasing. The nervous system’s limitation to generate sustainable signals and the reduction of ability of muscle fiber to contract are two major factors contributing to fatigue development [1]. Fatigue development limits the performance and capability of the individual in sports, long stretch driving conditions and in rigourous day to day activities. Hence a parameter that can estimate the fatigue levels and provide a break point for maximum fatigue can be useful for physiology and in other areas such as labour. People working under mines can be monitored for the fatigue break point and the overall productivity of such areas can be increased by proper analysis. The fatigue development in a person can be analysed via number of methods based on physiological changes. These include Electroencephalogram (EEG), Elec-tromyography(EMG), and Heart Rate Variability(HRV). Zadry [2] reported the increase in alpha band power level of EEG with time for fatigue development [3]. Ali also reported increase in RMS values of different bands in EEG [4]. Few studies measure brain activity in light repetitive task using EEG [5] to measure drowsiness or fatigue on drivers [6] [7] and night work [8] [9]. The EEG analysis for overall fatigue has been the focus of research, but research for specific muscle fatigue detection has been limited. The EEG based detection of fatigue has the advantage of quantitative based assessment. But, for real time application perspective faster computational power and signal processing methods are required. One of the challenges based on EEG based approach is the disturbances and contamination of the signal from eyes blinking action, muscle noise by movements and instrumental noises like line noise, electronic interferences [10]. Another problem is imposed by the inter-variability and intra-variability in EEG dynamics accompanying loss of alertness [11].

Source: Fatigue detection and estimation using auto-regression analysis in EEG – IEEE Xplore Document

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[Abstract] Impairment of muscle force transmission in spastic-paretic muscles of stroke survivors


Hemispheric stroke survivors tend to have persistent motor impairments, with muscle weakness and muscle spasticity observed concurrently in the affected muscles.
The objective of this preliminary study was to identify whether impairment of muscle force transmission could contribute to weakness in spastic-paretic muscles of chronic stroke survivors. To characterize the efficiency of the transmission of muscle forces to the tendon, we activated biceps brachii muscle electrically by stimulating the musculocutaneous nerve with maximum current. The ratio between the elicited maximum twitch force amplitude and the maximum M-wave peak-peak amplitude was calculated as a measure of the efficiency of force transmission.
Based on the preliminary results of two stroke survivors, we show that the Force/M-wave ratio was reduced in the affected biceps brachii muscles in comparison with the contralateral muscles, indicating a potential impairment in the muscle force transmission in the affected muscles.
Our findings suggest that disrupted muscle force transmission to the tendon could contribute to weakness in spastic muscles of chronic stroke survivors.

Source: IEEE Xplore Document – Impairment of muscle force transmission in spastic-paretic muscles of stroke survivors

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[Abstract] Switching control of functional electrical stimulation and motor assist for muscle fatigue compensation.

The torque generation capability of muscles often reduces during a functional electrical stimulation (FES) session due to the rapid onset of muscle fatigue. Hybrid rehabilitation systems that use FES and electric motor assist may overcome this issue.

The primary control challenge in such a system is how to allocate control inputs between electric motor and FES during muscle fatigue and muscle recovery. One strategy is to switch between FES and the electric motor by using an estimate of the muscle fatigue. This would allow the system to switch from using FES to using the electric motor when the muscle torque output has significantly decreased, then switch back to FES once the muscles have sufficiently recovered.

This paper uses a second order sliding mode controller cascaded with a feedback linearization controller for a switched, FES and electric motor, system. The second order sliding mode is achieved through the use of a variable-gain super-twisting algorithm. A Lyapunov stability analysis was used to prove asymptotic stability of the switched control system. Simulations of the developed controller on a hybrid knee extension model illustrate that prolonged knee movements can be elicited through the switched system.

Source: IEEE Xplore Abstract (Abstract) – Switching control of functional electrical stimulation and motor assist for muscle fatigue compensat…

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[Abstract] Benefits of using a voice and EMG-driven actuated glove to support occupational therapy for stroke survivors.

Many mechatronic devices exist to facilitate hand rehabilitation, however few directly address deficits in muscle activation patterns while also enabling functional task practice.

We developed an innovative voice and electromyography-driven actuated (VAEDA) glove, which is sufficiently flexible/portable for incorporation into hand-focused therapy post-stroke. The therapeutic benefits of this device were examined in a longitudinal intervention study. Twenty-two participants with chronic, moderate hand impairment (Chedoke-McMaster Stroke Assessment Stage of Hand (CMSA-H=4)) enrolled >8 months post-stroke for 18 one-hour training sessions (3x/week) employing a novel hand-focused occupational therapy paradigm, either with (VAEDA) or without (No-VAEDA) actuated assistance.

Outcome measures included CMSA-H, Wolf Motor Function Test (WMFT), Action Research Arm Test, Fugl-Meyer Upper Extremity Motor Assessment (FMUE), grip and pinch strength and hand kinematics. All outcomes were recorded at baseline and endpoint (immediately after and 4 weeks post-training).

Significant improvement was observed following training for some measures for the VAEDA group (n=11) but for none of the measures for the No-VAEDA group (n=11). Specifically, statistically significant gains were observed for CMSA-H (p=0.038) and WMFT (p=0.012) as well as maximum digit aperture subset (p=0.003, n=7), but not for the FMUE or grip or pinch strengths.

In conclusion, therapy effectiveness appeared to be increased by employment of the VAEDA glove, which directly targets deficits in muscle activation patterns.

Source: IEEE Xplore Abstract (Abstract) – Benefits of using a voice and EMG-driven actuated glove to support occupational therapy for stroke s…

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[ARTICLE] Integrated Rehabilitation Treatment of Focal Spasticity after Botulinum Toxin Type-A Injection – Full Text PDF


Several treatments have been proposed for the management of spasticity. The injection of botulinum toxin type A is considered the gold standard treatment and appears to be safe and effective. The combination between botulinum toxin type A (BTX-A) and physiotherapy (FKT) is thought to be able to enhance the effects. The aim of this study was to assess the effectiveness of the administration of botulinum toxin type A when combined with a specific rehabilitation protocol in subjects with focal spasticity. 44 subjects were randomly divided into two groups (A and B).

All subjects underwent ECO and EMG guided BTX-A injection. After the injection group A underwent a complex rehabilitation protocol with functional electrical stimulation, functional bandaging, manual therapy, cognitive sensory motor training and focal vibration on the treated muscle; group B made functional rehabilitation at home.

Both groups improved spasticity, pain and function in the first month after the inoculation (T1) but only in group A an improvement at the follow up performed in the subsequent 9 months was observed.

According to the results, it may be suggested that the inoculation of Botulinum toxin A should be properly placed within a specific rehabilitation program

Full Text PDF


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[STUDY] – Design of a physiologically informed virtual reality based interactive platform for individuals with upper limb impairment

A large number of stroke-surviving individuals exhibit deficits related to upper limb movement, thereby making post stroke rehabilitation a critical part of patients’ health care system. The patients are typically treated with conventional occupational therapy at the hospital after stroke. However, due to economic pressures and limited health care resources often the patients receive less therapy than required causing them to be deprived of the potential therapeutic benefits. Thus implementing a cost-effective home based technology-assisted rehabilitation system which is capable of providing intensive, adaptive and individualized rehabilitation service is critical. Virtual reality (VR) based rehabilitation system seems to address this challenge effectively. VR technology for rehabilitation allows us to create an interactive environment with precise control over intensity of practice that influence one’s motor control in an individualized manner. In this study we developed an interactive VR-based platform which challenges the coordination skill of individuals with upper limb impairment. Additionally, we used patient’s physiological indices to understand their stress level while they interact with the VR-based rehabilitation environment. The system developed in this work is a first step to understand its potential to provide individualized home-based rehabilitative service with minimal dependency on physiotherapist. In our initial study designed as a proof-of-concept application, one stroke-surviving patient participated in the interactive VR-based task. The preliminary results obtained from this initial study indicate the potential of mapping one’s stress level to his physiological indices. Thus these results indicate the potential applicability of such a system for various stroke-rehabilitation applications

via IEEE Xplore Abstract (Abstract) – Design of a physiologically informed virtual reality based interactive platform for individuals with….

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