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

Marcelo Bigliassi,Taufik Abrão,Leandro Ricardo Altimari,Thiago Ferreira Dias Kanthack,Antonio Carlos De Moraes,Paulo Rogério Scalassara

doi:10.4236/am.2014.513181

Marcelo Bigliassi, Taufik Abrão + Show 4 more

Open Access

https://doi.org/10.4236/am.2014.513181

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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.

Highlights

The use of surface electromyography (EMG) has been applied as a valuable and non-invasive method to study the human movement and its neurophysiological mechanisms of fatigue
Some studies compared the use of Continuous Wavelet Transform (CWT) and Short-Time Fourier Transform (STFT) in different exercises protocols [7] [9] [15] [16]
Our protocol involved a sport activity without possibility of controlling these variables properly, our results suggest that both STFT and CWT may be applied to evaluate muscle fatigue using EMG fatigue indices in a time-trial dynamic exercise

Summary

Introduction

The use of surface electromyography (EMG) has been applied as a valuable and non-invasive method to study the human movement and its neurophysiological mechanisms of fatigue. Fatigue can be defined as a decrease on the capacity of muscle to produce force [2] [3]. EMG technique is applied to measure the excitability of the muscle fibers and signal speed. This provides meaningful information regarding fatigue process [4] [5]. EMG cues may be analyzed in two different domains: time and frequency. Frequency domain provides variables such as median frequency (MDF), variance, and MDF slope. The MDF slope is understood as the decrease rate in median frequency [1] [6]. It is important to highlight that a decrease in median frequency is categorized as the onset of muscle fatigue process [6]

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Results

Conclusion