Fourier and Wavelet Spectral Analysis of EMG signals in Supramaximal Constant Load Dynamic Exercise

被引:14
作者
Camata, Thiago V. [1 ]
Dantas, Jose L. [1 ]
Abrao, Taufik [4 ]
Brunetto, Maria A. O. C. [2 ]
Moraes, Antonio C. [3 ]
Altimari, Leandro R. [1 ]
机构
[1] CEFE State Univ Londrina UEL, Grp Study & Res Neuromuscular Syst & Exercise, Londrina, PR, Brazil
[2] Univ Estadual Londrina, Dept Comp CSE, Londrina, Brazil
[3] Univ Estadual Campinas, UNICAMP, Campinas, Brazil
[4] Univ Estadual Londrina, Dept Elect Engn, CTU, Londrina, Brazil
来源
2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2010年
基金
巴西圣保罗研究基金会;
关键词
MUSCLE FATIGUE; BICEPS-BRACHII; CONTRACTIONS; ELECTROMYOGRAPHY; TRANSFORM;
D O I
10.1109/IEMBS.2010.5626743
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Frequency domain analyses of changes in electromyographic (EMG) signals over time are frequently used to assess muscle fatigue. Fourier based approaches are typically used in these analyses, yet Fourier analysis assumes signal stationarity, which is unlikely during dynamic contractions. Wavelet based methods of signal analysis do not assume stationarity and may be more appropriate for joint time-frequency domain analysis. The purpose of this study was to compare Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) in assessing muscle fatigue in supramaximal constant load dynamic exercise (110% VO2peak). The results of this study indicate that CWT and STFT analyses give similar fatigue estimates (slope of median frequency) in supramaximal constant load dynamic exercise (P > 0.05). However, the results of the variance was significantly lower for at least one of the muscles studied in CWT compared to STFT (P < 0.05) indicating more variability in the EMG signal analysis using STFT. Thus, the stationarity assumption may not be the sole factor responsible for affecting the Fourier based estimates.
引用
收藏
页码:1364 / 1367
页数:4
相关论文
共 18 条
[1]   Models to explain fatigue during prolonged endurance cycling [J].
Abbiss, CR ;
Laursen, PB .
SPORTS MEDICINE, 2005, 35 (10) :865-898
[2]   Skeletal muscle fatigue: Cellular mechanisms [J].
Allen, D. G. ;
Lamb, G. D. ;
Westerblad, H. .
PHYSIOLOGICAL REVIEWS, 2008, 88 (01) :287-332
[3]  
Barria E. A., 1994, Proceedings of the SPIE - The International Society for Optical Engineering, V2303, P542, DOI 10.1117/12.188803
[4]   Comparison of Fourier and wavelet transform procedures for examining the mechanomyographic and electromyographic frequency domain responses during fatiguing isokinetic muscle actions of the biceps brachii [J].
Beck, TW ;
Housh, TJ ;
Johnson, GO ;
Weir, JP ;
Cramer, JT ;
Coburn, JW ;
Malek, MH .
JOURNAL OF ELECTROMYOGRAPHY AND KINESIOLOGY, 2005, 15 (02) :190-199
[5]   Time-frequency parameters of the surface myoelectric signal for assessing muscle fatigue during cyclic dynamic contractions [J].
Bonato, P ;
Roy, SH ;
Knaflitz, M ;
De Luca, CJ .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2001, 48 (07) :745-753
[6]  
da Silva R A, 2008, Electromyogr Clin Neurophysiol, V48, P147
[7]   Decomposition of surface EMG signals [J].
De Luca, Carlo J. ;
Adam, Alexander ;
Wotiz, Robert ;
Gilmore, L. Donald ;
Nawab, S. Hamid .
JOURNAL OF NEUROPHYSIOLOGY, 2006, 96 (03) :1646-1657
[8]   The use of surface electromyography in biomechanics [J].
De Luca, CJ .
JOURNAL OF APPLIED BIOMECHANICS, 1997, 13 (02) :135-163
[9]   Spinal and supraspinal factors in human muscle fatigue [J].
Gandevia, SC .
PHYSIOLOGICAL REVIEWS, 2001, 81 (04) :1725-1789
[10]   Development of recommendations for SEMG sensors and sensor placement procedures [J].
Hermens, HJ ;
Freriks, B ;
Disselhorst-Klug, C ;
Rau, G .
JOURNAL OF ELECTROMYOGRAPHY AND KINESIOLOGY, 2000, 10 (05) :361-374