Analysis of Progressive Changes Associated with Muscle Fatigue in Dynamic Contraction of Biceps Brachii Muscle Using Surface EMG Signals and Bispectrum Features

다국어 초록 (Multilingual Abstract)

Purpose In this work, an attempt has been made to analyzesurface electromyography (sEMG) signals in dynamiccontractions using bispectrum features.
Methods Signals are recorded from the biceps brachii muscleof 50 healthy volunteers during curl exercise. Bispectrumand bicoherence are estimated from the recorded sEMGsignals. Sum and variance of bispectrum and bicoherence arecalculated. Further analysis is carried by dividing the entireduration of the exercise into six zones. Results obtained areverified using the subject’s feedback about first musclediscomfort time.
Results Bispectrum is observed with high amplitude peaksat zone where subjects reported first muscle discomfort.
Maximum values for sum and variance of bispectrum areobserved in the same zone. Similar patterns are not seen withbicoherence features. In bicoherence sum and bicoherencevariance, distinctive peaks are observed in the zone whentask failure occurs.
Conclusions First discomfort zone estimated using bispectrumvariance is found to be in agreement with the subject'sfeedback. It appears that, this method is useful in analyzingprogressive changes associated with muscle mechanics infatigue conditions using non-invasive sEMG recordings.

참고문헌 (Reference)

1 Sharma S, "Wavelet analysis based feature extraction for pattern classification from single channel acquired EMG signal" 50 : 10320-10324, 2012

2 Peng ZK, "The parametric characteristic of bispectrum for nonlinear systems subjected to Gaussian input" 36 (36): 456-470, 2013

3 Greb U, "The interpretation of the bispectrum and bicoherence for non-linear interactions of continuous spectra" 30 (30): 537-549, 1998

4 Reaz MBI, "Techniques of EMG signal analysis: detection, processing, classification and applications" 8 (8): 11-35, 2006

5 Cifrek M, "Surface EMG based muscle fatigue evaluation in biomechanics" 24 (24): 327-340, 2009

6 Kaplanis PA, "Surface EMG analysis on normal subjects based on isometric voluntary contraction" 19 (19): 157-171, 2009

7 Wan B, "Study on fatigue feature from forearm SEMG signal based on wavelet analysis" 1229-1232, 2010

8 Gydikov A, "Some features of different motor units in human biceps brachii" 347 (347): 75-88, 1974

9 Allen DG, "Skeletal muscle fatigue: Cellular mechanisms" 88 : 287-332, 2008

10 George T, "Signal denoising using empirical mode decomposition and higher order statistics" 4 (4): 91-106, 2011

11 Hussain MS, "SEMG signal processing and analysis using wavelet transform and higher order statistics to characterize muscle force" 366-379, 2008

12 Song JH, "Robust EMG pattern recognition to muscular fatigue effect for human- machine interaction" 4293 : 1190-1199, 2006

13 Katirji B, "Neuromuscular disorders in clinical practice. 2nd ed" Springer 2014

14 Greig CA, "Muscle physiology" 28 (28): 55-59, 2009

15 Enoka RM, "Muscle fatigue: what, why and how it influences muscle function" 586 (586): 11-23, 2008

16 Pereira GR, "Isometric fatigue patterns in time and time–frequency domains of tricepssurae muscle in different knee positions" 21 (21): 572-578, 2011

17 De Luca CJ, "Filtering the surface EMG signal: movement artifact and baseline noise contamination" 43 (43): 1573-1579, 2010

18 Venugopal G, "Extraction and analysis of multiple time window features associated with muscle fatigue conditions using sEMG signals" 41 (41): 2652-2659, 2014

19 Hussain MS, "Electromyography signal analysis using wavelet transform and higher order statistics to determine muscle contraction" 26 (26): 35-48, 2009

20 González-Izal M, "EMG spectral indices and muscle power fatigue during dynamic contractions" 20 (20): 233-240, 2010

21 Biyouki F, "Differentiation between migraine without aura and chronic tensiontype headache based on HOS analysis of sEMG signals" 1-6, 2013

22 Janssen D, "Diagnosing fatigue in gait patterns by support vector machines and self-organizing maps" 30 (30): 966-975, 2011

23 Soylu AR, "Detection of surface electromyography recording time interval without muscle fatigue effect for biceps brachii muscle during maximum voluntary contraction" 20 (20): 773-776, 2010

24 Marceglia S, "Crossbispectral analysis of local field potentials: An application to essential tremor" 494-497, 2009

25 Mallor F, "Changes in power curve shapes as an indicator of fatigue during dynamic contractions" 43 (43): 1627-1631, 2010

26 Kaplanis PA, "Bispectral analysis of surface EMG" 770-773, 2000

27 Orosco EC, "Bipectrum based, features classification for myoelectric control" 8 (8): 153-168, 2013

28 Simeoni RJ, "Bicoherence analysis of quadriceps electromyogram during isometric knee extension" 26 (26): 12-17, 2003

29 Knaflitz M, "Assessment of muscle fatigue during biking" 11 (11): 17-23, 2003

30 Sigl JC, "An introduction to bispectral analysis for the electroelcephalogram" 10 (10): 392-404, 1994

31 Potvin JR, "A validation of techniques using surface EMG signals from dynamic contractions to quantify muscle fatigue during repetitive tasks" 7 (7): 131-139, 1997

32 Ma L, "A novel approach for determining fatigue resistances of different muscle groups in static cases" 41 (41): 10-18, 2011

33 Chen X, "A discriminant bispectrum feature for surface electromyogram signal classification" 32 (32): 126-135, 2010