Spectral Characteristics Analysis of Electromyography Signals Recorded During Dynamic Contractions

Signal processing can be applied in the biomedical field, using electromyography (EMG) signals to analyze muscle fatigue, which can be defined as the evidence of loss of muscle strength during muscle contraction. Besides many works of muscle fatigue, there is still a need to know which are the best techniques, especially in dynamic contractions. This contraction is more complex than isometric because it includes body movement, contraction, and muscle rest. The main contribution of this paper is the analysis of the spectral features from EMG signals recorded during dynamic contractions. The features from the frequency domain were extracted from the EMG signal and were made the classification between “fatigue” and “no fatigue”. The database contains signals from three muscles of the quadriceps femoris muscles of the right leg of 17 volunteers, totaling 51 signals with 30 seconds captured during a pedaling activity. After the classification, was observed the use or not of all proposed features, and were made a local analysis of the impact of each feature in the classification. From the initially considered 17 features, 12 were used for classification, obtaining an 89% accuracy rate.