Re-evaluation of EMG-torque relation in chronic stroke using linear electrode array EMG recordings

Abstract

The objective was to re-evaluate the controversial reports of EMG-torque relation between impaired and non-impaired sides using linear electrode array EMG recordings. Ten subjects with chronic stroke performed a series of submaximal isometric elbow flexion tasks. A 20-channel linear array was used to record surface EMG of the biceps brachii muscles from both impaired and non-impaired sides. M-wave recordings for bilateral biceps brachii muscles were also made. Distribution of the slope of the EMG-torque relations for the individual channels showed a quasi-symmetrical “M” shaped pattern. The lowest value corresponded to the innervation zone (IZ) location. The highest value from the slope curve for each side was selected for comparison to minimize the effect of electrode placement and IZ asymmetry. The slope was greater on the impaired side in 4 of 10 subjects. There were a weak correlation between slope ratio and strength ratio and a moderate to high correlation between slope ratio and M-wave ratio between two sides. These findings suggest that the EMG-torque relations are likely mediated and influenced by multiple factors. Our findings emphasize the importance of electrode placement and suggest the primary role of peripheral adaptive changes in the EMG-torque relations in chronic stroke.

Re-Evaluating Electromyogram–Force Relation in Healthy Biceps Brachii Muscles Using Complexity Measures

“…Although the ANOVA did not report significant main effect of the model on the R-square, the exponential model truly outperformed the linear model in characterizing EMG RMS-torque relation, with statistical significance reported by the pairwise comparisons. This confirmed previous finding that the EMG RMS amplitude of the BB muscle increased faster with the increment of muscle force, and represented a nonlinear EMG RMS-torque relation [8,[15][16][17].…”

“…Therefore, the relation between EMG and muscle contraction level (described as force or torque alternatively) offers a useful tool for examining muscle functions and deficits, with wide biomedical and biomechanical applications [3,[5][6][7]. Among them, the EMG signals were usually analyzed with time-domain amplitude-associated and frequency-domain parameters including root mean square (RMS), averaged rectified value (ARV), median frequency (MDF) and mean power frequency (MPF) of EMG signal [8][9][10][11][12][13][14][15][16][17]. Sbriccoli et al [8] reported that the RMS of the Subjects completed a series of isometric elbow flexion tasks while the forearm of the dominant side was positioned on an equipment with the elbow joint at 90 • , the shoulder abducted at 45 • and flexed at approximately 30 • .…”

A Portable Elbow Exoskeleton for Three Stages of Rehabilitation

“…Because of the reliance on biosignals, those systems are inoperable without sensors. Movement based on EMG data extraction from stroke patients is difficult because of abnormal EMG-torque relationship [13]. The adaptive control algorithm used in exoskeleton results in constant draining of energy for controlling the variable joint torque and active range of motion.…”

Design of a Game-Based Rehabilitation System Using Kinect Sensor

“…However, the issues such as cost, compatibility with user, efficiency, accuracy and acceptability restrict the use. Fine EMG signal extraction from stroke patients is troublesome due to irregular EMG-torque relations in stroke [4]. IMU and accelerometer are attached to the human body which restricts motion of the users and they feel captive wearing them [5].…”