Abstract
The study of hand and finger movement is an important topic with applications in prosthetics, rehabilitation, and ergonomics. Surface electromyography (sEMG) is the gold standard for the analysis of muscle activation. Previous studies investigated the optimal electrode number and positioning on the forearm to obtain information representative of muscle activation and robust to movements. However, the sEMG spatial distribution on the forearm during hand and finger movements and its changes due to different hand positions has never been quantified. The aim of this work is to quantify 1) the spatial localization of surface EMG activity of distinct forearm muscles during dynamic free movements of wrist and single fingers and 2) the effect of hand position on sEMG activity distribution. The subjects performed cyclic dynamic tasks involving the wrist and the fingers. The wrist tasks and the hand opening/closing task were performed with the hand in prone and neutral positions. A sensorized glove was used for kinematics recording. sEMG signals were acquired from the forearm muscles using a grid of 112 electrodes integrated into a stretchable textile sleeve. The areas of sEMG activity have been identified by a segmentation technique after a data dimensionality reduction step based on Non Negative Matrix Factorization applied to the EMG envelopes. The results show that 1) it is possible to identify distinct areas of sEMG activity on the forearm for different fingers; 2) hand position influences sEMG activity level and spatial distribution. This work gives new quantitative information about sEMG activity distribution on the forearm in healthy subjects and provides a basis for future works on the identification of optimal electrode configuration for sEMG based control of prostheses, exoskeletons, or orthoses. An example of use of this information for the optimization of the detection system for the estimation of joint kinematics from sEMG is reported.
Highlights
The human hand shows highly complex motor skills, which are essential for many daily activities
The aim of this work was to quantify, by means of a Surface EMG (sEMG) multi-channel detection system, 1) whether it is possible to spatially localize the sEMG activity related to the activation of distinct forearm muscles during dynamic free movements of the wrist and single fingers, and 2) the effect of hand position on the sEMG activity in terms of changes in amplitude and spatial distribution
The tasks for each single finger consisted in the flexion/extension of the metacarpophalangeal (MCP) and of the proximal interphalangeal (PIP) joint performed with the hand in neutral position (Figure 1d)
Summary
The human hand shows highly complex motor skills, which are essential for many daily activities. Surface EMG (sEMG) signal detected with up to eight bipolar detection systems is commonly used to control multifunction prosthesis [1] [3] [4] [5] [6]. The recent development of sophisticated hand prostheses mimicking the high number of degrees of freedom (DOF) of the human wrist/hand complex push forward the development of more advanced control systems. The use of multi-channel detection systems has been recently proposed in order to increase the informative content of the detected sEMG [7] [8] [9] [10] [11]. Signals detected with multi-channel systems show a certain degree of redundancy and, in practical application, the number of electrodes must be limited as much as possible [12]
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