Classification of the mechanomyogram signal using a wavelet packet transform and singular value decomposition for multifunction prosthesis control

Physiological Measurement

Volumn 30, Issue 5, 2009, Pages 441-457

  Xie, Hong Bo ^a,b   Zheng, Yong Ping ^a   Guo, Jing Yi ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b JIANGSU UNIVERSITY   (China)

Author keywords

Electromyogram; Mechanomyogram; Muscle activity classification; Prosthetic control; Singular value decomposition; Wavelet packet transform

Indexed keywords

BIOMEDICAL SIGNAL PROCESSING; CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION; MUSCLE; WAVELET ANALYSIS; WAVELET DECOMPOSITION;

CLASSIFICATION ACCURACY; ELECTROMYO GRAMS; HAND MOTION; MECHANOMYOGRAM; MULTI-FUNCTIONS; MUSCLE ACTIVITY CLASSIFICATION; PROSTHESIS CONTROL; PROSTHETIC CONTROLS; TIME-FREQUENCY REPRESENTATIONS; WAVELET PACKET TRANSFORMS;

SINGULAR VALUE DECOMPOSITION;

ACCURACY; ADULT; ARTICLE; CLINICAL EVALUATION; CONTROLLED STUDY; DECOMPOSITION; DIAGNOSTIC PROCEDURE; FEMALE; FOREARM; FOURIER TRANSFORMATION; HAND; HUMAN; MALE; MECHANOMYOGRAM; MUSCLE CONTRACTION; NOISE; OSCILLATION; PRIORITY JOURNAL; PROSTHESIS; RELIABILITY; SIGNAL TRANSDUCTION; ALGORITHM; CLASSIFICATION; LIMB PROSTHESIS; MYOGRAPHY; PHYSIOLOGY; SKELETAL MUSCLE;

ADULT; ALGORITHMS; ARTIFICIAL LIMBS; FEMALE; FOREARM; HAND; HUMANS; MALE; MUSCLE, SKELETAL; MYOGRAPHY; YOUNG ADULT;

EID: 67651166904     PISSN: 09673334     EISSN: 13616579     Source Type: Journal    
DOI: 10.1088/0967-3334/30/5/002     Document Type: Article

References (50)

1. Addison P S 2005 Wavelet transforms and the ECG: a review Physiol. Meas. 26 R155-99
2. Akataki K, Mita K, Itoh K, Suzuki N and Watakabe M 1996 Acoustic and electrical activities during voluntary isometric contraction of biceps brachii muscle in patients with spastic cerebral palsy Muscle Nerve 19 1252-7
3. Akataki K, Mita K, Watakabe M and Itoh K 2001 Mechanomyogram and force relationship during voluntary isometric ramp contractions of the biceps brachii muscle Eur. J. Appl. Physiol. 84 19-25
4. Alves N and Chau T 2008 Stationarity distributions of mechanomyogram signals from isometric contractions of extrinsic hand muscles during functional grasping J. Electromyogr. Kinesiol. 18 509-15
5. Assous S, Humeau A and L'huillier J P 2006 S transform time-frequency feature extraction of laser Doppler flowmetry signal using SVD decomposition Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing vol 3 pp 157-60
6. Barry D T and Cole N M 1990 Muscle sounds are emitted at the resonant frequencies of skeletal muscle IEEE Trans. Biomed. Eng. 37 525-31
7. Barry D T, Leonard J A, Gitter A J and Ball R D 1986 Acoustic myography as a control signal for an externally powered prosthesis Arch. Phys. Med. Rehabil. 67 267-9
8. Beck T, Housh T, Johnson G, Weir J, Cramer J, Coburn J and Malek M 2004 Mechanomyographic amplitude and mean power frequency versus torque relationships during isokinetic and isometric muscle actions of the biceps brachii J. Electromyogr. Kinesiol. 14 555-64 (Pubitemid 39061147)
9. Beck T W, Housh T J, Cramer J T, Weir J P, Johnson G O, Coburn J W, Malek M H and Mielke M 2005 Mechanomyographic amplitude and frequency responses during dynamic muscle actions: a comprehensive review Biomed. Eng. Online 4 67-93
10. Beck T W, Tscharner V V, Housh T J, Cramer J T, Weir J P, Malek M H and Mielke M 2008 Time/frequency events of surface mechanomyographic signals resolved by nonlinearly scaled wavelets Biomed. Signal Process. Control 3 255-66
11. Behroozmand R and Almasganj F 2007 Optimal selection of wavelet-packet-based features using genetic algorithm in pathological assessment of patients' speech signal with unilateral vocal fold paralysis Comput. Med. Biol. 37 474-85
12. Brochier T, Spinks R L, Umilta M A and Lemon R N 2004 Patterns of muscle activity underlying object-specific grasp by the macaque monkey J. Neurophysiol. 92 1770-82
13. Cai L, Wang Z and Zhang H 1999 Classification EMG signals using T-F representation and SVD Proc. 21st Ann. Conf. 1999 Ann. Fall Meeting of the Biomed. Eng. Soc. vol 1 p 575
14. Castillo-Valdivieso P A, Merelo J J, Prieto A, Rojas I and Romero G 2002 Statistical analysis of the parameters of a neuro-genetic algorithm IEEE Trans. Neural Netw. 13 1374-94
15. Chendeb M, Khalil M and Duchne J 2006 Methodology of wavelet packet selection for event detection Signal Process 86 3826-41
16. Daubechies I 1992 Ten lectures on wavelets Proc. CBMS-NSF Regional Conf. Series in Applied Mathematic p 61
17. Duda R O, Hart P E and Stork D G 2001 Pattern Classification 2nd edn (New York: Wiley)
18. Englehart K, Hudgins B, Parker P and Stevenson M 1999 Classification of the myoelectric signal using time-frequency based representations Med. Eng. Phys 21 431-8 (Pubitemid 29537720)
19. Gu S, Ni J and Yuan J 2002 Non-stationary signal analysis and transient machining process condition monitoring Int. J. Mach. Tools Manuf. 42 41-51
20. Hardalac F, Yildirim H and Serhatlioglu S 2007 Determination of carotid disease with the application of STFT and CWT methods Comput. Med. Biol. 37 785-92
21. Hassanpour H, Mesbah M and Boashash B 2004 Time-frequency feature extraction of newborn EEG seizure using SVD-based techniques EURASIP J. Appl. Sig. Process. 16 2544-54 (Pubitemid 40297533)
22. Housh T J, Perry S R, Bull A J, Johnson G O, Ebersole K T, Housh D J and deVries H A 2000 Mechano-myographic and electromyographic responses during submaximal cycle ergometry Eur. J. Appl. Physiol. 83 381-7
23. Huang Y, Englehart K, Hudgins B and Chan A D C 2005 A Gaussian mixture model based classification scheme for myoelectric control of powered upper limb prostheses IEEE Trans. Biomed. Eng. 52 1801-11
24. Hudgins B, Parker P and Scott R N 1993 A new strategy for multifunction myoelectric control IEEE Trans. Biomed. Eng. 40 82-94
25. Leman H and Marque C 2000 Rejection of the maternal electrocardiogram in the electrohysterogram signal IEEE Trans. Biomed. Eng. 47 1010-7
26. L'Estrange P R, Rowell J and Stokes M J 1993 Acoustic myography in the assessment of human masseter muscle J. Oral. Rehabil. 20 353-62
27. Lukasik E 2005 Wavelet packets features extraction and selection for discriminating plucked sounds of violins Adv. Soft Comput. 30 867-75
28. Madeleine P, Cescon C and Farina D 2006 Spatial and force dependency of mechanomyographic signal features J. Neurosci. Methods 158 89-99
29. Mamaghani N K, Shimomura Y, Iwanaga K and Katsuura T 2002 Mechanomyogram and electromyogram responses of upper limb during sustained isometric fatigue with varying shoulder and elbow Postures J. Physiol. Anthropol. Appl. Human Sci. 21 29-43
30. Marinovic N M and Eichmann G 1985 Feature extraction and pattern classification in space-spatial frequency domain Proc. SPIE Intell. Robots Comput. Vis. 579 19-25
31. Martinez-Alajarin J and Ruiz-Merino R 2004 Wavelet and wavelet packet compression of phonocardiograms Electron. Lett. 40 1040-1
32. Monfared E S and Setarehdan S K 2006 A new classification method applied to EMG-control of hand prosthesis Proc. 2nd Int. Symp. on Biomedical Engineering pp 1-2
33. Orizio C 1993 Muscle sound: bases for the introduction of a mechanomyographic signal in muscle studies Crit. Rev. Biomed. Eng. 21 201-43
34. Orizio C 2004 Surface Mechanomyogram Electromyography: Physiology, Engineering, and Noninvasive Applications ed R Merletti and P Parker (Hoboken, NJ: IEEE) pp 305-22
35. Orizio C, Esposito F, Sansone V, Parrinello G, Meola G and Veicsteinas A 1997 Muscle surface mechanical and electrical activities in myotonic dystrophy Electromyogr. Clin. Neurophysiol. 37 231-9
36. Orizio C, Gobbo M, Diemont B, Esposito F and Veicsteinas A 2003 The surface mechanomyogram as a tool to describe the influence of fatigue on biceps brachii motor unit activation strategy historical basis and novel evidence Eur. J. Appl. Physiol. 90 326-36
37. Parker P, Englehart K and Hudgins B 2006 Myoelectric signal processing for control of powered limb prostheses J. Electromyogr. Kinesiol. 16 541-8
38. Perry S R, Housh T J, Weir J P, Johnson G O, Bull A J and Ebersole K T 2001 Mean power frequency and amplitude of the mechanomyographic and electromyographic signals during incremental cycle ergometry J. Electromyogr. Kinesiol. 11 299-305
39. Petitjean M and Bellemare F 1994 Phonomyogram of the diaphragm during unilateral and bilateral phrenic nerve stimulation and changes with fatigue Muscle Nerve 17 1201-9
40. Rhatigan B A, Mylrea K C, Lonsdale E and Stern L Z 1986 Investigation of sounds produced by healthy and diseased human muscular contraction IEEE Trans. Biomed. Eng. 33 967-71
41. Saito N and Coifman R R 1995 Local discriminant bases and their applications J. Math. Imaging Vis. 5 331-58
42. Shinohara M, Kouzaki M, Yoshihisa T and Fukunaga T 1997 Mechanomyography of the human quadriceps muscle during incremental cycle ergometry Eur. J. Appl. Physiol. 76 314-9
43. Silva J, Heim W and Chau T 2004 MMG-based classification of muscle activity for prosthesis control Proc. 26th Ann. Int. Conf. IEEE-EMBS vol 2 pp 968-71
44. Silva J, Heim W and Chau T 2005 A self-contained, mechanomyography-driven externally powered prosthesis Arch. Phys. Med. Rehabil. 86 2066-70
45. Stockwell R G, Mansinha L and Lowe R P 1996 Localization of the complex spectrum: the S transform IEEE Trans. Signal Process. 44 998-1001
46. Torres A, Fiz J A, Galdiz B, Gea J, Morera J and Jane R A 2005 Wavelet multiscale based method to separate the high and low frequency components of mechanomyographic signals Proc. 27th Ann. Int. Conf. IEEE-EMBS pp 7262-5
47. Widodo A, Yang B S and Han T 2007 Combination of independent component analysis and support vector machines for intelligent faults diagnosis of induction motors Expert. Syst. Appl. 32 299-312
48. Yang B S, Han T and An J L 2004 Art-Kohonen neural network for fault diagnosis of rotating machinery Mech. Syst. Signal Process. 18 645-57
49. Yoshitake Y, Shinohara M, Ue H and Moritani T 2002 Characteristics of surface mechanomyogram are dependent on development of fusion of motor units in humans J. Appl. Physiol. 93 1744-52
50. Yoshitake Y, Ue H, Myazaki M and Moritani T 2001 Assessment of lower-back muscle fatigue using electromyography, mechanomyography, and near-infrared spectroscopy Eur. J. Appl. Physiol. 84 174-9