Characterization and differentiation of electromyographic signals acquired with the BITalino platform in Peruvian university students

Guevara Remon F.J.; Espinosa L.E.B.; Reyes D.M.S.; Aguinaga C.A.P.; Shishco S.G.M.; Bocanegra C.A.S. · Proceedings of the 2023 IEEE 30th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2023 (2023) · DOI: 10.1109/intercon59652.2023.10326037

Resumen

This study aims to characterize and differentiate electromyographic (EMG) signals acquired using the BITalino platform in Peruvian university females. Electromyography (EMG) is a diagnostic procedure that records the electrical activity of motor units near the electrode placement area. EMG has various applications, from assessing neuromuscular health in pathologies to controlling prosthetics and exoskeletons. The study focuses on the BITalino (r)evolution kit, a user-friendly option that facilitates rapid data processing. Despite its numerous applications for surface EMG (sEMG), consistent processing criteria are lacking, especially when comparing pathological and healthy cases. The research aims to evaluate and characterize the electromyographic response using the BITalino kit to measure muscle action potential in university females during an exertion exercise. The study follows an experimental design, considering various aspects such as subject selection, comparison groups, measurement procedures, and data analysis.

Instituciones: Universidad Peruana Cayetano Heredia