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Fourier and Wavelet Spectral Analysis of EMG Signals in 1-km Cycling Time-Trial

Applied Mathematics 2014年第13期5卷 1878-1886页

作者： Marcelo Bigliassi paulo rogério scalassara Thiago Ferreira Dias Kanthack Taufik Abrao Antonio Carlos de Moraes Leandro Ricardo Altimari Group of Study and Research in Neuromuscular System and Exercise CEFE-State University of LondrinaLondrinaBrazil Department of Electrical Engineering Federal Technological University of ParanaCornélio ProcopioBrazil Department of Electrical Engineering CTU-State University of LondrinaLondrinaBrazil Laboratory of Electromyography Studies FEF-State University of CampinasCampinasBrazil

Frequency domain analyses in electromyographic (EMG) signals are frequently applied to assess muscle fatigue and similar variables. Moreover, Fourier-based approaches are typically used for investigating these procedures. Nonetheless, Fourier analysis assumes the signal as stationary which is unlikely during dynamic contractions. As an alternative method, wavelet-based treatments do not assume this pattern and may be considered as more appropriate for joint time-frequency domain analysis. Based on the previous statements, the purpose of the present study was to compare the application of Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) to assess muscle fatigue in dynamic exercise of a 1-km of cycling (time-trial condition). The results of this study indicated that CWT and STFT analyses have provided similar fatigue estimates (slope) (p> 0.05). However, CWT application represents lesser dispersion (p 0.05) according to different methods, it is important to note that these responses seem to show greater values for CWT compared to STFT for 2 superficial muscles. Thereby, we are capable of considering CWT as a reliable and useful method to take into consideration when non-stationary or oscillating exercise models are evaluated.

关键词： Exercise Dynamic Exercise Wavelet Analysis Fourier Analysis

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