MFC Histogram and Poincaré Plot Images for Automated Gait Detection

Proceedings of International Conference on Intelligent Sensing and Information Processing, ICISIP 2004

Volumn , Issue , 2004, Pages 368-372

  Begg, R ^a   Palaniswami, M ^b   Owen, B ^b   Taylor, S ^a   Dell'Oro, L ^a  

^a VICTORIA UNIVERSITY   (Australia)

^b UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

Gait; Minimum foot clearance; Poincar plots; Support vector machines

Indexed keywords

ALGORITHMS; AUTOMATION; CLASSIFICATION (OF INFORMATION); GAIT ANALYSIS; MATHEMATICAL MODELS; NEURAL NETWORKS; PROBLEM SOLVING; REGRESSION ANALYSIS; SET THEORY;

GAIT PATTERNS; MINIMUM FOOT CLEARANCE (MFC); RADIAL BASIS FUNCTION (RBF); SUPPORT VECTOR MACHINES (SVM);

PATTERN RECOGNITION;

EID: 1942535775     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. Barton, J.G. and Lees, A. "An application of neural networks for distinguishing gait patterns on the basis of hip-knee joint angle diagrams," Gait Posture, vol. 5, pp. 28-33, (1997).
2. Best, R.J., Begg, R.K.and Dell'Oro, L. "The probability of tripping during gait," in proc. Int. Soc. Biomech. Conf., Calgary, (1999).
3. Brennan, M., Palaniswami, M. and Kamen, P.W. "Do existing measures of Poincare plot geometry reflect nonlinear features of heart rate variability?" IEEE Trans. Biomed. Eng., vol. 48, pp. 1342-1347. (2001).
4. Chan, K., Lee, T.-W., Sample, P.A., Goldbaum, Weinreb, R.N. and Sejnowski, T.J. "Comparison of machine learning and traditional classifiers in glaucoma diagnosis," IEEE Trans. Biomed. Eng., vol. 49, no. 9, pp. 963-974, (2002).
5. Gunn, S. Support vector machines for classification and regression. ISIS Technical Report. University of Southampton, UK, (1998).
6. Holzreiter, S.H. and Kohle, M.E. "Assessment of gait pattern using neural networks," J. Biomech., vol. 26, pp. 645-651, (1993).
7. Kecman, V. Learning and soft computing: support vector machines, neural networks and fuzzy logic models. New Jersey: IEEE MIT Press, (2002).
8. Lee, L. and Grimson, W.E.L. "Gait analysis for recognition and classification," in proc. fifth Int. Conf. Automatic Face Gesture Recognition (FGR'02), IEEE Computer Society, pp. 1-8, (2002).
9. O'Malley, M.J., Abel, M.F., Damiano, D.L.and Vaughan, C.L. "Fuzzy clustering of children with cerebral palsy based on temporal-distance gait parameters," IEEE Trans. Rehab. Eng., vol. 5, pp. 300-309, (1997).
10. Shilton, A. Palaniswami, M. Ralph, D. and Tsoi, A.C. "Incremental training in support vector machines", in proc. Int. Jt. Conf. Neural Networks, Washington, July (2001).
11. Vapnik, V.N. The Nature of Statistical Learning Theory. Springer, New York, (1995).
12. Winter, D. The Biomechanics and Motor Control of Human Gait: Normal, Elderly and Pathological. Waterloo: University of Waterloo Press, (1991).
13. Yom-Tov, E. and Inbar, G.F. "Feature selection for the classification of movements from single movement-related potentials," IEEE Trans. Neural System, vol.10, pp. 170-177, (2002).
14. Zavaljevski, N. Stevens, F.J. and Reifman, J. "Support vector machines with selective kernel scaling for protein classification and identification of key amino acid positions," Bioinformatics, vol. 18, pp. 689-696, (2002).