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Evolutionary Methods for Analysis of Human Movement

Evolutionary Methods for Analysis of Human Movement
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Author(s): Rahman Davoodi (University of Southern California, USA)and Gerald E. Loeb (University of Southern California, USA)
Copyright: 2006
Pages: 18
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.ch010

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Abstract

A movement rehabilitation therapist must first diagnose the cause of disability and then prescribe therapies that specifically target the dysfunctional unit of the movement system. Objective diagnosis and prescription are difficult, however, because human movement is the result of complicated interactions among complex and highly nonlinear elements. Treatment based on limited observations may target the wrong element of the movement system. Researchers in central nervous system (CNS) control of human movement and functional electrical stimulation (FES) restoration of movement to paralyzed limbs face similar challenges in objective analysis of the integrated movement system. In this chapter, we will present evolutionary methods as powerful new tools for analysis and rehabilitation of human movement. These methods have been modeled after the same biological processes that have been optimized for the control of human movement in the process of biological evolution. Therefore, it is logical to think that these methods, if applied properly, could help us understand the control of human movement and repair it when it is disabled. A case study demonstrates the potential of evolutionary methods in movement analysis and rehabilitation.

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