Fatigue detection in the vastus lateralis muscle based on sEMG signal analysis

Electromyography (EMG) captures the electrical signals produced by skeletal muscle contraction. Surface electromyography (sEMG) analysis is the main method for identifying muscle exhaustion. Identifying fatigue allows for the creation of supportive techniques and aids in both clinical rehabilitation and injury prevention, as muscle exhaustion increases the risk of sports injuries. Therefore, the main objective of the present work is the analysis of sEMG signals in the vastus lateralis muscle for the detection of muscle fatigue after physical activities involving the inferior extremities. For this purpose, the Wavelet Transform was applied to the sEMG signals acquired before and after gymnastic exercises. The study uses a sEMG signal amplifier, an NI USB 6212 card, and the MATLAB platform for signal acquisition, processing, and analysis. The decomposition of the signals using the wavelet transform with the biorthogonal basis function 3.5 and a 4th level of decomposition made it possible to analyze the variations in muscle activity and characterize them through the calculation of the parameters mean absolute value (MAV), root mean square value (RMS), and mean frequency (MNF) of the sEMG signals, improving the ability to identify patterns associated with muscle fatigue. Finally, it was concluded that the amplitude of the parameters of the sEMG signals in the time domain increases and the parameters in the frequency domain decrease in the fatigue state.

• Egile nagusia: Figueroa Guayllas, Marilyn Elizabeth (author)
• Formatua: bachelorThesis
• Hizkuntza: eng
• Argitaratua: 2024
• Gaiak: Señales electromiográficas; Transformada wavelet; Extracción de características; Electromyographic signals; Wavelet transform; Feature extraction
• Sarrera elektronikoa: http://repositorio.yachaytech.edu.ec/handle/123456789/752