Abstract

In the article comparison of time-frequency spectra of EMG signals obtained by the following methods: Fast Fourier Transform, predictive analysis and wavelet analysis is presented. The EMG spectra of biceps and triceps while an adult man was flexing his arm were analysed. The advantages of the predictive analysis were shown as far as averaging of the spectra and determining the main maxima are concerned. The Continuous Wavelet Transform method was applied, which allows for the proper distribution of the scales, aiming at an accurate analysis and localisation of frequency maxima as well as the identification of impulses which are characteristic of such signals (bursts) in the scale of time. The modified Morlet wavelet was suggested as the mother wavelet. The wavelet analysis allows for the examination of the changes in the frequency spectrum in particular stages of the muscle contraction. Predictive analysis may also be very useful while smoothing and averaging the EMG signal spectrum in time.

Highlights

  • Human movement is the result of skeletal muscle contractions under the influence of nerve impulses which come from the central nervous system (CNS)

  • The EMG signal analysis is of great importance for the evaluation of the condition and functioning of the human musculoskeletal apparatus

  • The limitations of the ShortTime Fourier Transform method, commonly used in such research, are a motivation to search for better methods

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Summary

Introduction

Human movement is the result of skeletal muscle contractions under the influence of nerve impulses which come from the central nervous system (CNS). In the research the average or median of the Fourier spectrum is established [5, 6]. S for the analysis of the signals and suggests the linear prediction method for the generalization of the spectral courses, as well as the wavelet method to obtain spectra of. Electromyographic signals were registered during the contraction of the muscles: biceps and triceps when an adult man was folding his arm. They were performed with the use of surface electrodes in the Department of Biomechanics and Computer Science in Biała Podlaska. U for latitude in scaling thereof and for the presentation of a wavelet spectrum

Short-Time Fourier Spectrum
LPC Spectrum
Wavelet analysis
Conclusions

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