Title :
Time-frequency analysis of SEMG with special consideration to the interelectrode spacing
Author :
Alemu, M. ; Kumar, Dinesh Kant ; Bradley, Alan
Author_Institution :
Sch. of Electr. & Comput. Syst. Eng., R. Melbourne Inst. of Technol., Vic., Australia
Abstract :
The surface electromyogram (SEMG) is a complex, nonstationary signal. The spectrum of the SEMG is dependent on the force of contraction being generated and other factors like muscle fatigue and interelectrode distance (IED). The spectrum of the signal is time variant. This paper reports the experimental research conducted to study the influence of force of muscle contraction and IED on the SEMG signal using time-frequency (T-F) analysis. Two T-F techniques have been used: Wigner-Ville distribution (WVD) and Choi-Williams distribution (CWD). The experiment was conducted with the help of ten healthy volunteers (five males and five females) who performed isometric elbow flexions of the active right arm at 20%, 50%, and 80% of their maximal voluntary contraction. The SEMG signal was recorded using surface electrodes placed at a distance of 18 and 36 mm over biceps brachii muscle. The results indicate that the two distributions were spread out across the frequency range at smaller IED. Further, regardless of the spacing, both distributions displayed increased spectral compression with time at higher contraction level.
Keywords :
biomedical electrodes; electromyography; medical signal processing; spectral analysis; time-frequency analysis; 18 mm; 36 mm; Choi-Williams distribution; SEMG; Wigner-Ville distribution; biceps brachii muscle; contraction; interelectrode spacing; isometric elbow flexions; muscle fatigue; spectral compression; surface electromyogram; time-frequency analysis; Amplitude estimation; Fatigue; Frequency estimation; Life estimation; Muscles; Signal analysis; Spectral analysis; Stochastic processes; Systems engineering and theory; Time frequency analysis; Adult; Algorithms; Electrodes; Electromyography; Exertion; Female; Humans; Isometric Contraction; Male; Muscle, Skeletal; Reproducibility of Results; Sensitivity and Specificity; Statistics as Topic; Stress, Mechanical;
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
DOI :
10.1109/TNSRE.2003.819903