Recognition of Gait Patterns Using Support Vector Machines

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Author(s): Rezaul Begg (Victoria University, Australia)and Marimuthu Palaniswami (The University of Melbourne, Australia)
Copyright: 2006
Pages: 20
Source title: Computational Intelligence for Movement Sciences: Neural Networks and Other Emerging Techniques
Source Author(s)/Editor(s): Rezaul Begg (Victoria University, Australia)and Marimuthu Palaniswami (The University of Melbourne, Australia)
DOI: 10.4018/978-1-59140-836-9.ch008

Keywords: Bioinformatics / Biometrics / Medical Information Science Reference / Medicine & Healthcare

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Abstract

Automated gait pattern recognition capability has many advantages. For example, it can be used for the detection of at-risk or faulty gait, or for monitoring the progress of treatment effects. In this chapter, we first provide an overview of the major automated techniques for detecting gait patterns. This is followed by a description of a gait pattern recognition technique based on a relatively new machine-learning tool, support vector machines (SVM). Finally, we show how SVM technique can be applied to detect changes in the gait characteristics as a result of the ageing process and discuss their suitability as an automated gait classifier.

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Recognition of Gait Patterns Using Support Vector Machines

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