Movement Pattern Recognition Using Neural Networks

Movement Pattern Recognition Using Neural Networks

Rezaul Begg (Victoria University, Australia) and Joarder Kamruzzaman (Monash University, Australia, University of New South Wales, Australia)
Copyright: © 2006 |Pages: 21
DOI: 10.4018/978-1-59140-848-2.ch010
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This chapter provides an overview of artificial neural network applications for the detection and classification of various gaits based on their typical characteristics. Gait analysis is routinely used for detecting abnormality in the lower limbs and also for evaluating the progress of various treatments. Neural networks have been shown to perform better compared to statistical techniques in some gait classification tasks. Various studies undertaken in this area are discussed with a particular focus on neural network’s potential in gait diagnostics. Examples are presented to demonstrate the suitability of neural networks for automated recognition of gait changes due to aging from their respective gait patterns and their potential for identification of at-risk or non-functional gait.

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