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Force and position detection for elbow flexion and extension movements from EMG signals
Detección de fuerza y posición para los movimientos de flexión-extensión de codo a partir de señales de EMG
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Force and position detection for elbow flexion and extension movements from EMG signals . (2023). Revista EIA, 20(39), 3924 pp. 1-20. https://doi.org/10.24050/reia.v20i39.1595
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Objective: Assessment of force and angular position based on the analysis of electromyographic signals acquired from the biceps and triceps during the elbow flexion-extension. The idea is to compare the computational algorithms V − Order, WaveLength, Mean Absolute Value, Wavelength, and the Q1 value.
Materials and Methods: An experiment with 15 volunteers was carried out. We used weights of 0, 0.5, y 1 kg. We extracted the signal characteristics using the algorithms mentioned above to measure the force. After, we calculated the angular position using a low-pass filter applied to the force signal. We measured the angular position with a NOTCH commercial sensor to validate the algorithms. Then, we evaluated the correlation coefficient and compared the results with those of the algorithm that behaves better.
Results: The acquired signals show that the biceps’ signal has a greater amplitude compared to the triceps’ signal. Furthermore, the Q1 algorithm has lower noise levels. Therefore, it is employed to acquire the force and the angular position. As main results, we found a mean correlation coefficient of 72,3% for 1 kg and 60,9% for 0 kg, comparing the angular position calculated with the angular position from the NOTCH sensors.
Conclusion: The measurement of force and angular position allows the development of control systems for biomechatronic devices intended to support rehabilitation processes and evaluation of the evolution of a patient. The algorithm behaves better with higher loads, because it implies a greater muscular activation.
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