Abstract
Recording an Electromyogram (EMG) signal is essential for diagnostic procedures like muscle health assessment and motor neurons control. The EMG signals have been used as a source of control for powered prosthetics to support people to accomplish their activities of daily living (ADLs). This work deals with studying different types of hand grips and finding their relationship with EMG activity. Five subjects carried out four functional movements (fine pinch, tripod grip and grip with the middle and thumb finger, as well as the power grip). Hand dynamometer has been used to record the EMG activity from three muscles namely; Flexor Carpi Radialis (FCR), Flexor Digitorum Superficialis (FDS), and Abductor Pollicis Brevis (ABP) with different levels of Maximum Voluntary Contraction (MVC) (10-100%). In order to analyze the collected EMG and force data, the mean absolute value of each trial is calculated followed by a calculation of the average of the 3 trials for each grip for each subject across the different MVC levels utilized in the study. Then, the mean and the standard deviation (SD) across all participants (3 males and 2 females) are calculated for FCR, FDS and APB muscles with multiple % MVC, i.e 10, 30, 50, 70 % MVC for each gesture. The results showed that APB muscle has the highest mean EMG activity across all grips, followed by FCR muscle. Furthermore, the grip with the thumb and middle fingers is the grip with the highest EMG activity for 10-70% MVC than the power grip. As for the 100% MVC, thumb and middle fingers grip achieved the highest EMG activity for APB muscle, while the power grip has the highest EMG activity for both FCR and FDS muscles.
Highlights
Electromyogram (EMG) signals from the skin surface are considered as a source of neural control information and are traditionally employed as inputs to the controller of upper-limb prosthetic hands [1], helping disabled people to use the remaining parts of their own forearm/hand to accomplish the activities of daily livings (ADLs) [2]
In the last part of the data analysis, we evaluate the statistical significance of the achieved results using an N-way analysis of variance (ANOVA) with three grouping variables: the different Maximum Voluntary Contraction (MVC) levels (10, 30, 50, 70 and 100%), the different types of grips (Fine Pinch, Tripod Grip, Grip with Thumb+Middle, and Power Grip), and the different muscles considered (APB, Flexor Digitorum Superficialis (FDS), and Flexor Carpi Radialis (FCR))
The grip with the thumb and middle fingers has the highest activity for abductor pollicis brevis (APB) muscle, while the power grip has the highest activity in both the FCR and FDS muscles
Summary
Electromyogram (EMG) signals from the skin surface are considered as a source of neural control information and are traditionally employed as inputs to the controller of upper-limb prosthetic hands [1], helping disabled people to use the remaining parts of their own forearm/hand to accomplish the activities of daily livings (ADLs) [2]. The term EMG has been associated with the process of detecting, recording, and evaluating the action potential produced by the muscles of the body [3], denoted as Electromyography. The central nervous system (CNS) is the origin of EMG action potential by which the motor neurons carry the information transferred along the nerve in pulse repetition or known as frequency [3]. Interfacing tissues to reach the electrode detection surface placed on the skin [1]. Surface EMG electrodes are placed on the skin above the muscle of interest to measure the EMG signal
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