Sample entropy analysis of surface EMG for improved muscle activity onset detection against spurious background spikes

Journal of Electromyography and Kinesiology

Volumn 22, Issue 6, 2012, Pages 901-907

  Zhang, Xu ^a   Zhou, Ping ^a,b,c  

^a REHABILITATION INSTITUTE OF CHICAGO   (United States)

^b NORTHWESTERN UNIVERSITY   (United States)

^c UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

EMG onset; Sample entropy; Stroke

Indexed keywords

ARTICLE; CONTROLLED STUDY; ELECTROMYOGRAPHY; ENTROPY; ERROR; HUMAN; INTERMETHOD COMPARISON; MUSCLE CONTRACTION; NOISE; PRIORITY JOURNAL; PROCESS OPTIMIZATION; SAMPLE ENTROPY; SIGNAL DETECTION; SPIKE; STATISTICAL ANALYSIS;

ELECTROMYOGRAPHY; ENTROPY; HUMANS; MUSCLE CONTRACTION; MUSCLE, SKELETAL; SIGNAL PROCESSING, COMPUTER-ASSISTED; SIGNAL-TO-NOISE RATIO; STROKE;

EID: 84868213819     PISSN: 10506411     EISSN: 18735711     Source Type: Journal    
DOI: 10.1016/j.jelekin.2012.06.005     Document Type: Article

References (20)

1. Allison G.T. Trunk muscle onset detection technique for EMG signals with ECG artefact. J Electromyogr Kinesiol 2003, 13(3):209-216.
2. Chang G.C., Kang W.J., Luh J.J., Cheng C.K., Lai J.S., Chen J.J., et al. Real-time implementation of electromyogram pattern recognition as a control command of man-machine interface. Med Eng Phys 1996, 18(7):529-537.
3. Costa M., Healey J.A. Multiscale entropy analysis of complex heart rate dynamics: discrimination of age and heart failure effects. Comput Cardiol 2003, 2003:705-708.
4. Costa M., Goldberger A.L., Peng C.-K. Multiscale entropy analysis of complex physiologic time series. Phys Rev Lett 2002, 89(6):068102.
5. Dalley S., Varol H., Goldfarb M. A method for the control of multigrasp myoelectric prosthetic hands. IEEE Trans Neural Syst Rehabil Eng 2011.
6. Hodges P.W., Bui B.H. A comparison of computer-based methods for the determination of onset of muscle contraction using electromyography. Electroencephalogr Clin Neurophysiol 1996, 101(6):511-519.
7. Lauer R.T., Prosser L.A. Use of the Teager-Kaiser Energy operator for muscle activity detection in children. Ann Biomed Eng 2009 Aug, 37(8):1584-1593.
8. Li X., Zhou P., Aruin A.S. Teager-Kaiser energy operation of surface EMG improves muscle activity onset detection. Ann Biomed Eng 2007, 35(9):1532-1538.
9. Merlo A., Farina D., Merletti R. A fast and reliable technique for muscle activity detection from surface EMG signals. IEEE Trans Biomed Eng 2003, 50(3):316-323.
10. Micera S., Sabatini A.M., Dario P. An algorithm for detecting the onset of muscle contraction by EMG signal processing. Med Eng Phys 1998, 20(3):211-215.
11. Micera S., Vannozzi G., Sabatini A.M., Dario P. Improving detection of muscle activation intervals. IEEE Eng Med Biol Mag 2001, 20(6):38-46.
12. Oskoei M.A., Hu H. Myoelectric control systems-a survey. Biomed Signal Process Control 2007, 2(4):275-294.
13. Pincus S.M. Approximate entropy as a measure of system complexity. Proc Natl Acad Sci U S A 1991, 88:2297-2301.
14. Richman J.S., Moorman J.R. Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol 2000, 278(6):H2039-H2049.
15. Solnik S., DeVita P., Rider P., Long B., Hortobágyi T. Teager-Kaiser Operator improves the accuracy of EMG onset detection independent of signal-to-noise ratio. Acta Bioeng Biomech 2008, 10(2):65-68.
16. Staude G., Wolf W. Objective motor response onset detection in surface myoelectric signals. Med Eng Phys 1999, 21(6-7):449-467.
17. Vannozzi G., Conforto S., D'Alessio T. Automatic detection of surface EMG activation timing using a wavelet transform based method. J Electromyogr Kinesiol 2010, 20(4):767-772.
18. Watkins C.L., Leathley M.J., Gregson J.M., Moore A.P., Smith T.L., Sharma A.K. Prevalence of spasticity post stroke. Clin Rehabil 2002, 16(5):515-522.
19. Zhou P., Lowery M.M., Englehart K.B., Huang H., Li G., Hargrove L., et al. Decoding a new neural machine interface for control of artificial limbs. J Neurophysiol 2007, 98(5):2974-2982.
20. Zhou P., Barkhaus P.E., Zhang X., Rymer W.Z. Characterizing the complexity of spontaneous motor unit patterns of amyotrophic lateral sclerosis using approximate entropy. J Neural Eng 2011, 8(6). 10.1088/1741-2560/8/6/066010.