Diversity-based combination of non-parametric classifiers for EMG signal decomposition

Pattern Analysis and Applications

Volumn 11, Issue 3-4, 2008, Pages 385-408

  Rasheed, Sarbast ^a,b   Stashuk, Daniel W ^a,b   Kamel, Mohamed S ^a,b  

^a UNIVERSITY OF WATERLOO   (Canada)

^b UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Classifier agreement; Classifier fusion; Diversity measure; EMG signal decomposition; Motor unit potential classification; Non parametric base classifiers

Indexed keywords

EID: 50549085162     PISSN: 14337541     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10044-008-0103-4     Document Type: Article

References (66)

1. Alexandre LA, Campilho AC, Kamel M (2001) On combining classifiers using sum and product rules. Pattern Recogn Lett 22:1283-1289
2. Atiya AF (1992) Recognition of multiunit neural signals. IEEE Trans Biomed Eng 39(7):723-729
3. Chauvet E, Fokapu O, Hogrel J-Y, Gamet D, Duchêne J (2003) Automatic identification of motor unit action potential trains from electromyographic signals using fuzzy techniques. Med Biol Eng Comput 41:646-653
4. Chi Z, Yan H, Pham T (1996) Fuzzy algorithms: with applications to image processing and pattern recognition, World Scientific, Singapore
5. Sung-Bae Cho (1997) Neural-network classifiers for recognizing totally unconstrained handwritten numerals. IEEE Trans Neural Netw 8(1):43-53
6. Cho SB, Kim JH (1995) Combining multiple neural networks by fuzzy integral for robust classification. IEEE Trans Syst Man Cybern 25(2):380-384
7. Sung-Bae Cho, Kim JH (1995) Multiple network fusion using fuzzy logic. IEEE Trans Neural Netw 6(2):497-501
8. Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20(2):37-46
9. Duda RO, Hart PE, Stork DG (2001) Pattern classification, 2nd edn. Wiley, New York
10. Duin RPW (2002) The combining classifier: to train or not to train? In: Proceedings of the 16th international conference on pattern recognition, vol 2, pp 765-770
11. Duin RPW, Taz DMJ (2000) Experiments with classifier combining rules. In: Kittler J, Roli F (eds) Multiple classifier systems. Lecture Notes in Computer Science, vol 1857. Springer, Gagliari, pp 16-29
12. Fang J, Agarwal GC, Shahani BT (1997) Decomposition of EMG signal by wavelet spectrum matching. In: Proceedings of the 19th annual international conference of the IEEE engineering in medicine and biology society, pp 1253-1256
13. Fang J, Agarwal GC, Shahani BT (1999) Decomposition of multiunit electromyogram signals. IEEE Trans Biomed Eng 46(6):685-697
14. Farina D, Colombo RA, Merletti R, Olsen HB (2001) Evaluation of intra-muscular EMG signal decomposition algorithms. J Electromyogr Kinesiol 11:175-187
15. Farina D, Crosetti A, Merletti R (2001) A model for the generation of synthetic intramuscular EMG signals to test decomposition algorithms. IEEE Trans Biomed Eng 48(1):66-77
16. Fleiss JL, Levin B, Paik MC (2003) Statistical methods for rates and proportions, 3rd edn. Wiley, New York
17. Giacinto G, Roli F (2001) An approach to the automatic design of multiple classifier systems. Pattern Recogn Lett 22:25-33
18. Gut R, Moschytz GS (2000) High-precision EMG signal decomposition using communication techniques. IEEE Trans Signal Process 48(9):2487-2494
19. Hamilton-Wright A, Stashuk DW (2005) Physiologically based simulation of clinical EMG signals. IEEE Trans Biomed Eng 52(2):171-183
20. Hassoun MH, Wang C, Spitzer R (1994) NNERVE: Neural network extraction of repetitive vectors for electromyography-part i: algorithm. IEEE Trans Biomed Eng 41(11):1039-1052
21. Hassoun MH, Wang C, Spitzer R (1994) NNERVE: neural network extraction of repetitive vectors for electromyography-part ii: performance analysis. IEEE Trans Biomed Eng 41(11):1053-1061
22. Ho TK, Hull JJ, Srihari SN (1994) Decision combination in multiple classifier systems. IEEE Trans Pattern Anal Mach Intell 16(1):66-75
23. Keller JM, Gader P, Tahani H, Chiang J-H,Mohamed M (1994) Advances in fuzzy integration for pattern recognition. Fuzzy Sets Syst 65:273-283
24. Keller JM, Gray MR, JA Givens JR (1985) A fuzzy k-nearest neighbor algorithm. IEEE Trans Syst Man Cybern 15(4):580-585
25. Keller JM, Osborn J (1996) Advances in fuzzy integration for pattern recognition. Int J Approxim Reason 15(1):1-24
26. Kittler JM, Hatef M, Duin RPV, Matas J (1998) On combining classifiers. IEEE Trans Pattern Anal Mach Intell 20(3):955-966
27. Kuncheva LI, Whitacker CJ (2003) Measure of divesity in classifier ensembles and their relationship with the ensemble accuracy. Mach Learn 51:181-207
28. Kuncheva LI, Whitaker CJ, Shipp CA, Duin RPW (2001) Is independence good for combining classifiers? In: Proceedings of the 15th international conference on pattern recognition, vol 2, pp 168-171
29. Lam L (2000) Classifier combinations: implementations and theoretical issues. In: Kittler J, Roli F (eds) Multiple classifier systems. Lecture Notes in Computer Science, vol 1857. Springer, Cagliari, pp 77-86
30. Lam L, Suen CY (1997) Application of majority voting to pattern recognition: an analysis of its behavior and performance. IEEE Trans Syst Man Cybern Part A Syst Hum 27(5):553-568
31. LeFever RS, De Luca CJ (1982) A procedure for decomposing the myoelectric signal into its constituent action potentials-part i: technique, theory, and implementation. IEEE Trans Biomed Eng 29(3):149-157
32. Loudon GH, Jones NB, Sehmi AS (1992) New signal processing techniques for the decompositon of EMG signals. Med Biol Eng Comput 30(11):591-599
33. De Luca CJ (1989) Reflections on EMG signal decomposition. In: Desmedt JE (ed) Computer-aided electromyography and expert systems. Elsevier, Amesterdam, pp 33-37
34. McGill KC (1984) A method for quantitating the clinical electromyogram. PhD Dissertation, Stanford University, Stanford
35. McGill KC, Cummins K, Dorfman LJ (1985) Automatic decomposition of the clinical electromyogram. IEEE Trans Biomed Eng 32(7):470-477
36. Mikenina L, Zimmermann H-J (1999) Improved feature selectin and classification by the 2-additive fuzzy measure. Fuzzy Sets Syst 107:197-218
37. Mirfakhraei K, Horch K (1997) Recognition of temporally changing action potentials in multiunit neural recordings. IEEE Trans Biomed Eng 44(2):123-131
38. Hamid Nawab S, Wotiz R, De Luca CJ (2004) Improved resolution of pulse superpositions in a knowledge-based system EMG decomposition. In: Proceedings of the 26th annual international conference of the IEEE engineering in medicine and biology society, vol 1, pp 69-71
39. Nikolic M, Sørensen JA, Dahl K, Krarup C (1997) Detailed analysis of motor unit activity. In: Proceedings of the 19th annual international conference of the IEEE engineering in medicine and biology society conference, pp 1257-1260
40. Paoli GM (1993) Estimating certainty in classification of motor unit action potentials. Master's Thesis, University of Waterloo, Waterloo
41. Partridge D, Griffith N (2002) Multiple classifier systems: software engineered, automatically modular leading to a taxonomic overview. Pattern Anal Appl 5:180-188
42. Perrone MP (1995) Averaging/modular techniques for neural networks. In: Arbib MA (ed) The handbook of brain theory and neural networks. MIT Press, Cambridge, pp 126-129
43. Pham TD (2002) Combination of multiple classifiers using adaptive fuzzy integral. In: Proceedings of the 6th IEEE international conference on electronics, circuits and systems ICECS '99, pp 50-55
44. Pham TD, Yan H (1997) Fusion of handwritten numeral classifiers based on fuzzy and genetic algorithms. In: Proceedings of the 1997 annual meeting of the north american fuzzy information processing society NAFIPS'97, pp 257-262
45. Qu Y (1993) Automatic clustering of motor unit action potentials using shape and time information. Master's Thesis, University of Waterloo, Waterloo
46. Rasheed S (2006) A multiclassifier approach to motor unit potential classification for EMG signal decomposition. PhD Dissertation, URL: http://www.etd.uwaterloo.ca/etd/srasheed2006.pdf, University of Waterloo, Waterloo
47. Rasheed S, Stashuk D, Kamel M (2004) Multi-classification techniques applied to EMG signal decomposition. In: Proceedings of the 2004 IEEE international conference on systems, man and cybernetics, SMC 04, vol 2, The Hugue, pp 1226-1231
48. Rasheed S, Stashuk D, Kamel M (2006) Adaptive certainty-based classification for decomposition of EMG signals. Med Biol Eng Comput 44(4):298-310
49. Rasheed S, Stashuk D, Kamel M (2006) Adaptive fuzzy k-NN classifier for EMG signal decomposition. Med Eng Phys J 28(7):694-709
50. Roli F, Giacinto G, Vernazza G (2001) Methods for designing multiple classifier systems. In: Kittler J, Roli F (eds) Proceedings of the 2nd international workshop on multiple classifier systems. Lecture Notes in Computer Science, vol 2096. Springer, Heidelberg, pp 78-87
51. Shipp CA, Kuncheva LI (2002) Relationships between combination methods and measures of diversity in combining classifiers. Inf Fus 3:135-148
52. Spitzer R, Hassoun MH (1993) NNERVE: neural network extraction of repetitive vectors for electrodiagnosis. In: Proceedings of 6th annual ieee symposium on computer-based medical systems, pp 171-176
53. Stashuk DW (1999) Decomposition and quantitative analysis of clinical electromyographic signals. Med Eng Phys 21:389-404
54. Stashuk DW (2001) EMG signal decomposition: how can it be accomplished and used? J Electromyogr Kinesiol 11:151-173
55. Stashuk DW, de Bruin H (1988) Automatic decomposition of selective needle-detected myoelectric signals. IEEE Trans Biomed Eng 35(1):1-10
56. Stashuk DW, Paoli GM (1998) Robust supervised classification of motor unit action potentials. Med Biol Eng Comput 36(1):75-82
57. Stashuk DW, Qu Y (1996) Adaptive motor unit action potential clustering using shape and time information. Med Biol Eng Comput 34(1):41-49
58. Stashuk DW, Qu Y (1996) Robust method for estimating motor unit firing-pattern statistics. Med Biol Eng Comput 34(1):50-57
59. Sugeno M (1974) Theory of fuzzy integrals and its applications. PhD Dissertation, Tokyo Institute of Technology, Tokyo
60. Sugeno M (1977) Fuzzy measures and fuzzy integrals-a survey. In: Fuzzy Automata and Decision Processes. North-Holland, Amsterdam, pp 89-102
61. Tahani H, Keller JM (1990) Information fusion in computer vision using the fuzzy integral. IEEE Trans Syst Man Cybern 20(3):733-741
62. Usaui S, Amidror I (1982) Digital low-pass differentiation for biological signal processing. IEEE Trans Biomed Eng 29(10):686-693
63. Wanas N (2003) Feature based architecture for decision fusion. PhD Dissertation, University of Waterloo, Waterloo
64. Wang D, Wang X, Keller JM (1997) Determining fuzzy integral densities using a genetic algorithm for pattern recognition. In: Proceedings of the 1997 Annual Meeting of the North American Fuzzy Information Processing Society NAFIPS '97, pp 21-24
65. Zennaro D, Wellig P, Koch VM, Moschytz GS, Läubli T (2003) A software package for the decomposition of long-term multi-channel EMG signals using wavelet coefficients. IEEE Trans Biomed Eng 50(1):58-69
66. Zennaro D, Wellig P, Moschytz GS, Läubli T, Krueger H (2001) A decomposition software package for the decomposition of long-term multi-channel electromyographic signals. In: Proceedings of the 23th annual international conference of the IEEE engineering in medicine and biology society, Turkey, pp 1070-1073