A study on the effect of age, gender and paralysis on sEMG signals

TL;DR

This study explores how age, gender, and paralysis influence sEMG signals using a cost-effective sensor setup and data analysis from diverse individuals.

Contribution

It introduces a simple, low-cost sEMG sensor and analyzes its effectiveness across different demographic and health groups.

Findings

Differences in sEMG signals across age groups

Gender-related variations in EMG patterns

Impact of paralysis on electromyography signals

Abstract

Surface Electromyography (sEMG) is a technology to measure the bio-potentials across the muscles. The true prospective of this technology is yet to be explored. In this paper, a simple and economic construction of a sEMG sensor is proposed. These sensors are used to determine the differences in the Electromyography (EMG) signal patterns of different individuals. Signals of several volunteers from different age groups, gender and individual having paralysis have been obtained. The sEMG data acquisition is done using the soundcard of a computer, hence reducing the need of additional hardware. Finally, the data is used to analyse the relationship between electromyography and factors like age, gender and health condition i.e. paralysis.