Human gait modeling using a genetic fuzzy finite state machine

IEEE Transactions on Fuzzy Systems

Volumn 20, Issue 2, 2012, Pages 205-223

  Alvarez Alvarez, Alberto ^a   Trivino, Gracian ^a   Cordón, Oscar ^a,b  

^a EUROPEAN CENTRE FOR SOFT COMPUTING   (Spain)

^b UNIVERSITY OF GRANADA   (Spain)

Author keywords

Fuzzy finite state machines; fuzzy systems; genetic algorithms (GAs); genetic fuzzy systems; human gait modeling

Indexed keywords

AUTOMATIC METHOD; COMPLEX TASK; COMPUTATIONAL INTELLIGENCE TECHNIQUES; DATA SETS; GENETIC FUZZY SYSTEMS; GENETIC-FUZZY; HUMAN GAIT MODELING; HUMAN MOVEMENTS; HUMAN-FRIENDLY; LINGUISTIC DESCRIPTIONS; MODEL PARAMETERS; MOVEMENT DISORDERS; REHABILITATION PROGRAMS; TEMPORAL EVOLUTION;

ARTIFICIAL INTELLIGENCE; BIOMECHANICS; DIAGNOSIS; FINITE AUTOMATA; FUZZY SYSTEMS; PROGRAM DIAGNOSTICS;

GENETIC ALGORITHMS;

EID: 84859705290     PISSN: 10636706     EISSN: None     Source Type: Journal    
DOI: 10.1109/TFUZZ.2011.2171973     Document Type: Article

References (83)

1. D. T. H. Lai, R. K. Begg, and M. Palaniswami, "Computational intelligence in gait research: A perspective on current applications and future challenges," IEEE Trans. Inf. Technol. Biomed., vol. 13, no. 5, pp. 687-702, Sep. 2009.
2. K. Ogata, State Space Analysis of Control Systems. Englewood Cliffs, NJ: Prentice-Hall, 1967.
3. L. Ljung, System Identification: Theory for the User. Upper Saddle River, NJ: Prentice-Hall, 1986.
4. O. Nelles, Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models, 1st ed. NewYork: Springer-Verlag, Dec. 2000.
5. R. Isermann and M. Munchhof, Identification of Dynamical Systems. Berlin, Heidelberg, Germany: Springer-Verlag, 2009.
6. L. A. Zadeh, "Outline of a new approach to the analysis of complex systems and decision processes," IEEE Trans. Syst.,Man, Cybern., vol. SMC-3, no. 1, pp. 28-44, Jan. 1973.
7. D. Driankov, H. Hellendoorn, andM. Reinfrank, An Introduction to Fuzzy Control. New York: Springer-Verlag, 1993.
8. A. Bardossy and L. Duckstein, Fuzzy Rule-Based Modeling with Applications to Geophysical, Biological, and Engineering Systems. Boca Raton, FL: CRC, 1995.
9. H. Hellendoorn and D. Driankov, Eds., Fuzzy Model Identification: Selected Approaches. London, U.K.: Springer-Verlag, 1997.
10. L. A. Zadeh, "The concept of a linguistic variable and its application to approximate reasoning-Part I," Inf. Sci., vol. 8, pp. 199-249, 1975.
11. L. A. Zadeh, "The concept of a linguistic variable and its application to approximate reasoning-Part II," Inf. Sci., vol. 8, pp. 301-357, 1975.
12. L. A. Zadeh, "The concept of a linguistic variable and its application to approximate reasoning-Part III," Inf. Sci., vol. 9, pp. 43-80, 1975.
13. E. H. Mamdani, "Application of fuzzy logic to approximate reasoning using linguistic systems," IEEE Trans.Comput., vol.C-26, no. 12, pp. 1182-1191, Dec. 1977.
14. J. L. Castro, "Fuzzy logic controllers are universal approximators," IEEE Trans. Syst., Man Cybern., vol. 25, no. 4, pp. 629-635, Apr. 1995.
15. L. I. Kuncheva, Fuzzy Classifier Design. London, U.K.: Springer-Verlag, 2000.
16. H. Ishibuchi, T. Nakashima, and M. Nii, Classification and Modeling with Linguistic Information Granules: Advanced Approaches to Linguistic Data Mining (Advanced Information Processing). Secaucus, NJ: Springer-Verlag, 2005.
17. J. Kacprzyk andM. Fedrizzi, Fuzzy Regression Analysis (Studies in Fuzziness and Soft Computing). New York: Physica-Verlag, 1992.
18. P. Pulkkinen and H. Koivisto, "A dynamically constrained multiobjective genetic fuzzy system for regression problems," IEEE Trans. Fuzzy Syst., vol. 18, no. 1, pp. 161-177, Feb. 2010.
19. H. Lee, "Robust adaptive fuzzy control by backstepping for a class of MIMO nonlinear systems," IEEE Trans. Fuzzy Syst., vol. 19, no. 2, pp. 265-275, Apr. 2011.
20. J. Zhang, P. Shi, and Y. Xia, "Robust adaptive sliding-mode control for fuzzy systems with mismatched uncertainties," IEEE Trans. Fuzzy Syst., vol. 18, no. 4, pp. 700-711, Aug. 2010.
21. M. V. Lawson, Finite Automata. London, U.K.: Chapman & Hall, Sep. 2003.
22. J. Davis, Finite State Machine Datapath Design, Optimization, and Implementation (Synthesis Lectures on Digital Circuits and Systems). San Rafael, CA: Morgan & Claypool, Feb. 2008.
23. E. S. Santos, "Maxmin automata," Inf. Control, vol. 13, pp. 363-377, 1968.
24. J. N. Mordeson and D. S. Malik, Fuzzy Automata and Languages: Theory and Applications (Computational Mathematics). London, U.K.: Chapman & Hall, Mar. 2002.
25. M. Ying, "A formal model of computing with words," IEEE Trans. Fuzzy Syst., vol. 10, no. 5, pp. 640-652, Oct. 2002. (Pubitemid 35274825)
26. Y. Cao, M. Ying, and G. Chen, "Retraction and generalized extension of computing with words," IEEE Trans. Fuzzy Syst., vol. 15, no. 6, pp. 1238-1250, Dec. 2007. (Pubitemid 350268653)
27. G. Trivino and A. van der Heide, "Linguistic summarization of the human activity using skin conductivity and accelerometers," in Proc. Conf. Inf. Process. Manag. Uncertainty Knowl. Based Syst., 2008, pp. 1583-1589.
28. A. Alvarez-Alvarez and G. Trivino, "Comprehensible model of a quasiperiodic signal," in Proc. 9th Int. Conf. Intell. Syst.Design Applicat., 2009, pp. 450-455.
29. G. Trivino, A. Alvarez-Alvarez, and G. Bailador, "Application of the computational theory of perceptions to human gait pattern recognition," Pattern Recognit., vol. 43, no. 7, pp. 2572-2581, 2010.
30. G. Bailador and G. Trivino, "Pattern recognition using temporal fuzzy automata," Fuzzy Sets Syst., vol. 161, no. 1, pp. 37-55, 2010.
31. A. Alvarez-Alvarez, J. M. Alonso, G. Trivino, N. Herńandez, F. Herranz, A. Llamazares, and M. Ocaña, "Human activity recognition applying computational intelligence techniques for fusing information related to WiFi positioning and body posture," in Proc. IEEE Int. Conf. Fuzzy Syst., Barcelona, Spain, Jul. 18-23, 2010, pp. 1881-1885.
32. P. Bahl and V. Padmanabhan, "RADAR: An in-building RF-based user location and tracking system," in Proc. 19th Annu. Joint Conf. IEEE Comput. Commun. Soc., 2000, pp. 775-784. (Pubitemid 30584527)
33. A. E. Eiben and J. E. Smith, Introduction to Evolutionary Computing. New York: Springer-Verlag, 2003.
34. O. Cord́on, F. Herrera, F. Hoffmann, and L. Magdalena, Genetic Fuzzy Systems. Evolutionary Tuning and Learning of Fuzzy Knowledge Bases (Advances in Fuzzy Systems Applications and Theory). Singapore: World Scientific, 2001.
35. O. Cord́on, F. Gomide, F. Herrera, F. Hoffmann, and L. Magdalena, "Ten years of genetic fuzzy systems: Current framework and newtrends," Fuzzy Sets Syst., vol. 141, no. 1, pp. 5-31, 2004.
36. F. Herrera, "Genetic fuzzy systems: Status, critical considerations and future directions," Int. J. Comput. Intell. Res., vol. 1, no. 1, pp. 59-67, 2005.
37. F. Herrera, "Genetic fuzzy systems: Taxonomy, current research trends and prospects," Evol. Intell., vol. 1, no. 1, pp. 27-46, Mar. 2008.
38. O. Cord́on, "A historical review of evolutionary learning methods for Mamdani-type fuzzy rule-based systems: Designing interpretable genetic fuzzy systems," Int. J. Approx. Reason., vol. 52, no. 6, pp. 894-913, 2011.
39. J. C. R. Licklider, "Man-computer symbiosis," in Conversational Computers, W. D. Orr, Ed. New York: Wiley, 1968, pp. 3-5.
40. D. A. Winter, Biomechanics and Motor Control of Human Movement. New York: Wiley-Interscience, 1990.
41. S. P. Moustakidis, J. B. Theocharis, and G. Giakas, "A fuzzy decision treebased SVM classifier for assessing osteoarthritis severity using ground reaction force measurements," Med. Eng. Phys., vol. 32, no. 10, pp. 1145-1160, 2010.
42. R. Begg, D. T. H. Lai, and M. Palaniswami, Computational Intelligence in Biomedical Engineering. Boca Raton, FL: CRC, 2007.
43. J. Perry, Gait Analysis: Normal and Pathological Function. Thorofare, NJ: Slack, Feb. 1992.
44. L. A. Zadeh, "Towards a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic," Fuzzy Sets Syst., vol. 90, pp. 111-127, 1997. (Pubitemid 127683681)
45. J. Casillas, O. Cord́on, F. Herrera, and L. Magdalena, Interpretability Issues in Fuzzy Modelin (ser. Studies in Fuzziness and Soft Computing vol. 128). New York: Springer-Verlag, 2003.
46. J. Casillas, O. Cord́on, F. Herrera, and L. Magdalena, Accuracy Improvements in Linguistic Fuzzy Modelin (ser. Studies in Fuzziness and Soft Computing vol. 129). New York: Springer-Verlag, 2003.
47. J. M. Alonso, L. Magdalena, and S. Guillaume, "HILK: A new methodology for designing highly interpretable linguistic knowledge bases using the fuzzy logic formalism," Int. J. Intell. Syst., vol. 23, no. 7, pp. 761-794, 2008.
48. M. J. Gacto, R. Alcaĺa, and F. Herrera, "Integration of an index to preserve the semantic interpretability in the multiobjective evolutionary rule selection and tuning of linguistic fuzzy systems," IEEE Trans. Fuzzy Syst., vol. 18, no. 3, pp. 515-531, Jun. 2010.
49. M. J. Gacto, R. Alcaĺa, and F. Herrera, "Interpretability of linguistic fuzzy rule-based systems: An overview of interpretability measures," Inf. Sci., vol. 181, no. 20, pp. 4340-4360, 2011.
50. L. A. Zadeh, "From computing with numbers to computing with words-From manipulation of measurements to manipulation of perceptions," IEEE Trans. Circuits Syst.-I: Fund. Theory Appl., vol. 45, no. 1, pp. 105-119, Jan. 1999.
51. L. A. Zadeh, "From circuit theory to system theory," Proc. Inst. Radio Eng., vol. 50, pp. 856-865, 1962.
52. L. A. Zadeh, "Towards a theory of fuzzy systems," in Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers by Lotfi A. Zadeh, B. Yuan and G. J. Klir, Eds. River Edge, NJ:World Scientific, 1996, pp. 83-104.
53. R. R. Yager and D. P. Filev, Essentials of Fuzzy Modeling and Control. New York: Wiley-Interscience, 1994.
54. E. H. Ruspini, "A new approach to clustering," Inf. Control, vol. 15, pp. 22-32, 1969.
55. J. C. Bezdek and J. D. Harris, "Fuzzy partitions and relations: An axiomatic basis for clustering," Fuzzy Sets Syst., vol. 1, no. 2, pp. 111-127, 1978.
56. M. Valenzuela-Rend́on, "The fuzzy classifier system: Motivations and first results," in Proc. 1st Workshop on Parallel Problem Solving from Nature. Berlin, Germany: Springer-Verlag, 1991, pp. 330-334.
57. F. Hoffmann and G. Pfister, "Evolutionary design of a fuzzy knowledge base for a mobile robot," Int. J. Approx. Reason., vol. 17, pp. 447-469, 1997. (Pubitemid 127403034)
58. L. Magdalena and F. Monasterio Huelin, "A fuzzy logic controller with learning through the evolution of its knowledge base," Int. J. Approx. Reason., vol. 16, no. 3-4, pp. 335-358, 1997. (Pubitemid 127418357)
59. A. Gonzalez and R. Perez, "SLAVE: A genetic learning system based on an iterative approach," IEEE Trans. Fuzzy Syst., vol. 7, no. 2, pp. 176-191, Apr. 1999.
60. C. Alsina, M. J. Frank, and B. Schweizer, Associative Functions: Triangular Norms and Copulas. Singapore: World Scientific, 2006.
61. O. Cord́on, M. J. del Jesus, and F. Herrera, "Aproposal on reasoning methods in fuzzy rule-based classification systems," Int. J. Approx. Reason., vol. 20, no. 1, pp. 21-45, 1999.
62. F. Hayes-Roth,D.A.Waterman, andD.B. Lenat, Building Expert Systems. New York: Addison-Wesley, 1983.
63. M. J. Vlaanderen, "Automated knowledge acquisition for expert systems: An overview." Faculty Philosophy, Erarmus Univ. Rotterdam, Rotterdam, the Netherlands, 1990.
64. S. Haykin, Neural Networks: A Comprehensive Foundation. NewYork: Macmillan, 1994.
65. D. Nauck, F. Klawonn, and R. Kruse, Foundations of Neuro-Fuzzy Systems. New York: Wiley, 1997.
66. J.-S. R. Jang and C.-T. Sun, Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence. Upper Saddle River, NJ: Prentice-Hall, 1997.
67. K. De Jong, "Learning with genetic algorithms: An overview," Mach. Learn., vol. 3, pp. 121-138, 1988.
68. M. Antonelli, P. Ducange, B. Lazzerini, and F.Marcelloni, "Learning concurrently partition granularities and rule bases of Mamdani fuzzy systems in a multi-objective evolutionary framework," Int. J. Approx. Reason., vol. 50, no. 7, pp. 1066-1080, 2009.
69. R. Alcaĺa, J. Alcaĺa-Fdez, J. Casillas, O. Cord́on, and F. Herrera, "Hybrid learning models to get the interpretability- accuracy trade off in fuzzy modeling," Soft Comput., vol. 10, no. 9, pp. 717-734, 2006. (Pubitemid 43615677)
70. K. De Jong, W. M. Spears, and D. F. Gordon, "Using genetic algorithms for concept learning," Mach. Learn., vol. 13, no. 2-3, pp. 161-188, 1993.
71. A. Homaifar and E. McCormick, "Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithms," IEEE Trans. Fuzzy Syst., vol. 3, no. 2, pp. 129-139, May 1995.
72. F. Hoffmann, "Evolutionary algorithms for fuzzy control system design," in Proc. IEEE, Spec. Issue Ind. Appl. Soft Comput., 2001, vol. 89, no. 9, pp. 1318-1333. (Pubitemid 33766625)
73. F. Hoffmann, D. Schauten, and S. Holemann, "Incremental evolutionary design of TSK fuzzy controllers," IEEE Trans. Fuzzy Syst., vol. 15, no. 4, pp. 563-577, Aug. 2007. (Pubitemid 47316710)
74. N. Mijailovíc, M. Gavrilovíc, and S. Rafajlovíc, "Gait phases recognition from accelerations and ground reaction forces: Application of neural networks," Telfor J., vol. 1, no. 1, pp. 34-36, 2009.
75. L. J. Eshelman and J. D. Schaffer, "Real-coded genetic algorithms and interval-schemata," in Proc. 2nd Workshop Foundations Genetic Algorithms, 1993, pp. 187-202.
76. O. Cord́on and F. Herrera, "Hybridizing genetic algorithms with sharing scheme and evolution strategies for designing approximate fuzzy rulebased systems," Fuzzy Sets Syst., vol. 118, no. 2, pp. 235-255, 2001. (Pubitemid 32028655)
77. O. Cord́on, F. Herrera, and P. Villar, "Generating the knowledge base of a fuzzy rule-based system by the genetic learning of data base," IEEE Trans. Fuzzy Syst., vol. 9, no. 4, pp. 667-674, Aug. 2001. (Pubitemid 32933051)
78. W. Stuetzle, Cross-Validation. Encyclopedia of Statistics in Behavioral Science. New York: Wiley, 2005.
79. F. Wilcoxon, "Individual Comparisons by Ranking Methods," Biometr. Bull., vol. 1, no. 6, pp. 80-83, 1945.
80. S. García and F. Herrera, "An extension on "statistical comparisons of classifiers overmultiple data sets" for all pairwise comparisons," J.Mach. Learn. Res., vol. 9, pp. 2677-2694, 2008.
81. S. García, D. Molina, M. Lozano, and F. Herrera, "A study on the use on non-parametric tests for analyzing the evolutionary algorithms' behaviour: A case study on the CEC'2005 Special Session on Real Parameter Optimization," J. Heurist., vol. 15, pp. 617-644, 2009.
82. S. P. Moustakidis, J. B. Theocharis, and G. Giakas, "Subject recognition based on ground reaction force measurements of gait signals," IEEE Trans. Syst., Man, Cybern. B, vol. 28, no. 5, pp. 1476-1485, Dec. 2008.
83. P. Thrift, "Fuzzy logic synthesis with genetic algorithms," in Proc. 4th Int. Conf. Genet. Algorithms, 1991, pp. 509-513.