Muscle contraction can be measured by monitoring electrical or mechanical phenomena. Electromyography (EMG) records electrical muscle activity, Forcemyography (FMG) detects muscle cross-section changes, while Mechanomyography (MMG) captures muscle vibrations. This study aims to evaluate the performance of a dual force sensor in monitoring muscle contraction against the EMG. The new device consists of stacked piezoresistive (FSR) and piezoelectric (PZT) sensors that provides FMG and MMG signals. Four healthy subjects were instructed to perform a sequence of biceps brachii contractions. A reference EMG, FMG and MMG signals were simultaneously recorded. These signals were preprocessed and segmented automatically. The following features were computed: Root Mean Square (RMS) of the EMG; mean and area of the EMG Linear Envelope (EMG-LE); mean of the FMGs; RMS and Averaged Rectified Value (ARV) of the MMGs. Pearson’s correlation coefficients were calculated between EMG and dual force sensor features. The mean FMG-FSR resulted highly correlated (r ≈ 0.83) with both mean EMG-LE and EMG RMS. The ARV MMG-FSR and the RMS EMG scored an r value of 0.82. FSR sensor performed slightly better than PZT. The results suggest that the dual force sensor may offer a viable alternative to EMG.
Evaluation of a Dual Force Sensor to Monitor Muscle Contraction / Muto, Vincenzo; Bifulco, Paolo. - 111 IFMBE:(2024), pp. 444-452. ( 11th International Conference on E-Health and Bioengineering, EHB 2023 rou 2023) [10.1007/978-3-031-62523-7_49].
Evaluation of a Dual Force Sensor to Monitor Muscle Contraction
Muto, Vincenzo;Bifulco, Paolo
2024
Abstract
Muscle contraction can be measured by monitoring electrical or mechanical phenomena. Electromyography (EMG) records electrical muscle activity, Forcemyography (FMG) detects muscle cross-section changes, while Mechanomyography (MMG) captures muscle vibrations. This study aims to evaluate the performance of a dual force sensor in monitoring muscle contraction against the EMG. The new device consists of stacked piezoresistive (FSR) and piezoelectric (PZT) sensors that provides FMG and MMG signals. Four healthy subjects were instructed to perform a sequence of biceps brachii contractions. A reference EMG, FMG and MMG signals were simultaneously recorded. These signals were preprocessed and segmented automatically. The following features were computed: Root Mean Square (RMS) of the EMG; mean and area of the EMG Linear Envelope (EMG-LE); mean of the FMGs; RMS and Averaged Rectified Value (ARV) of the MMGs. Pearson’s correlation coefficients were calculated between EMG and dual force sensor features. The mean FMG-FSR resulted highly correlated (r ≈ 0.83) with both mean EMG-LE and EMG RMS. The ARV MMG-FSR and the RMS EMG scored an r value of 0.82. FSR sensor performed slightly better than PZT. The results suggest that the dual force sensor may offer a viable alternative to EMG.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


