TITLE:
Fourier and Wavelet Spectral Analysis of EMG Signals in 1-km Cycling Time-Trial
AUTHORS:
Marcelo Bigliassi, Paulo Rogério Scalassara, Thiago Ferreira Dias Kanthack, Taufik Abrão, Antonio Carlos de Moraes, Leandro Ricardo Altimari
KEYWORDS:
Exercise, Dynamic Exercise, Wavelet Analysis, Fourier Analysis
JOURNAL NAME:
Applied Mathematics,
Vol.5 No.13,
July
8,
2014
ABSTRACT: 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 (pp>
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.