Identification of forearm skin zones with similar muscle activation patterns during activities of daily living

Abstract

Background: A deeper knowledge of the activity of the forearm muscles during activities of daily living (ADL) could help to better understand the role of those muscles and allow clinicians to treat motor dysfunctions more effectively and thus improve patients' ability to perform activities of daily living.

Methods: In this work, we recorded sEMG activity from 30 spots distributed over the skin of the whole forearm of six subjects during the performance of 21 representative simulated ADL from the Sollerman Hand Function Test. Functional principal component analysis and hierarchical cluster analysis (HCA) were used to identify forearm spots with similar muscle activation patterns.

Results: The best classification of spots with similar activity in simulated ADL consisted in seven muscular-anatomically coherent groups: (1) wrist flexion and ulnar deviation; (2) wrist flexion and radial deviation; (3) digit flexion; (4) thumb extension and abduction/adduction; (5) finger extension; (6) wrist extension and ulnar deviation; and (7) wrist extension and radial deviation.

Conclusion: The number of sEMG sensors could be reduced from 30 to 7 without losing any relevant information, using them as representative spots of the muscular activity of the forearm in simulated ADL. This may help to assess muscle function in rehabilitation while also simplifying the complexity of prosthesis control.

Keywords: Activities of daily living; Clustering analysis; Electrode placement; Electromyography; Forearm muscles; Functional principal component analysis; Myoelectric prostheses; Rehabilitation; Sollerman hand function test.

Fig. 1

Sollerman Hand Function Test configuration

Fig. 2

Grid with the 30 spots for sEMG recording, and anatomical landmarks used

Fig. 3

sEMG Electrodes (SX230) used: integral dry reusable electrodes with a gain of 1000, bandwidth between 20 Hz – 460 Hz and noise less than 5 μV

Fig. 4

Values of the 17 RVs for each of the 30 spots. Positives values are displayed in red and negative values in blue

Fig. 5

Dendrogram obtained from the hierarchical clustering. The seven groups chosen are displayed in different colours

Fig. 6

Resulting groups of spots with similar activation patterns

Fig. 7

RMS of the muscular activity values of each spot. The bars are colored according to the resulting groups