The precise study of muscle behaviour is essential to multiple fields, from quantifying an athlete’s strength performance to verifying muscle activity and identifying pathologies. In this context, developing and standardising detailed and efficient methodologies for measuring electromyographic signals is necessary. This study aims to present a non-invasive method for collecting surface electromyography data, specifically from the forearms, during the movement associated with hand compression. Accordingly, a pair of muscles was selected: one primarily responsible for finger contraction, and the other for detecting compensatory movements during the task. The acquisition methodology implemented the BITalino® system; electrode placement followed medical standards to ensure reproducibility and signal quality, and was guided by detailed anatomical studies; OpenSignals software was used as signal interface; and MATLAB to analyse muscle patterns and assess symmetry between contralateral muscles. The resulting systematic method ensures safety and reproducible outcomes, supporting its adoption in similar research contexts.
Oliveira et al. (Thu,) studied this question.