Sensor Network for Bipolar sEMG Detection and Angular Measurement for the Characterization of Foot Drop Pathology

Abstract. The aim of this research work was to develop an embedded electronic sensing system, portable, wireless and wearable prototype that allowed to perform bipolar surface electromyography (sEMG) detection for the Tibialis Anterior (TA) and Peroneus Longus (PL) muscles and measure the angular di...

Full description

Autores:
Murrugarra, Cecilia
Noriega Alvarez, Santiago
Tipo de recurso:
Article of journal
Fecha de publicación:
2020
Institución:
Universidad El Bosque
Repositorio:
Repositorio U. El Bosque
Idioma:
eng
OAI Identifier:
oai:repositorio.unbosque.edu.co:20.500.12495/5526
Acceso en línea:
http://hdl.handle.net/20.500.12495/5526
https://doi.org/10.1007/978-3-030-61834-6_27
Palabra clave:
Wearable sensors
Wireless transmission
sEMG
Foot drop
Sensing system
Rights
openAccess
License
Acceso abierto
Description
Summary:Abstract. The aim of this research work was to develop an embedded electronic sensing system, portable, wireless and wearable prototype that allowed to perform bipolar surface electromyography (sEMG) detection for the Tibialis Anterior (TA) and Peroneus Longus (PL) muscles and measure the angular displacement of the ankle-foot joint for the characterization of Foot Drop (FD) pathology through the establishment of a sensor network. Two Sensor Units were developed around a CPU responsible for receiving the sensors measurements in order to assemble data packets for transmission. The bipolar sEMG detection is carried out through an analogous conditioning module. The sEMG architecture allows to obtain the raw, rectified, and the envelope of the muscular signals. The angular displacement measurement consists in an inertial measurement system. A statistical analysis to validate the precision of the measurements regard to commercial instruments, showing a MSE of 5, 27% for the sEMG and a mean error ≤ }1.5 ◦for angular displacement measurements. Likewise, an analysis was implemented both in the time and frequency domain for bipolar sEMG detection, to assess the energetic distribution of the TA and PL muscle contractions, showing that the spectral information in the 10–300 Hz range and PSD oscillates in the 0-7e-3 dB/Hz for a subject without FD pathology. The sensor network was implemented on the TA and PL in order to compare the transmitted and received information. The data collected and the experimental platform show the potential of the electronic prototype to measure physiological variables in real-time.