Computational Intelligence for Movement Sciences

Neural Networks and Other Emerging Techniques

By: Rezaul Begg (Editor), Marimuthu Palaniswami (Editor)

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Hardcover | 28 February 2006

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412 Pages

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Recent years have seen many new developments in computational intelligence (CI) techniques and, consequently, this has led to an exponential increase in the number of applications in a variety of areas, including: engineering, finance, social and biomedical. In particular, CI techniques are increasingly being used in biomedical and human movement areas because of the complexity of the biological systems as well as the limitations of the existing quantitative techniques in modelling. Computational Intelligence for Movement Sciences: Neural Networks and Other Emerging Techniques contains information regarding state-of-the-art research outcomes and cutting-edge technology from leading scientists and researchers working on various aspects of the human movement. Readers of this book will gain an insight into this field as well as access to pertinent information, which they will be able to use for continuing research in this area. This book is a part of the Computational Intelligence and its Applications Series.

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You Can Find This Book In

Non-Fiction Science Biology, Life Sciences Science in General Computing & I.T.Computer Science Artificial Intelligence Neural Networks & Fuzzy Systems Physics Applied Physics Biophysics Medicine

Pre-Clinical Medicine & Basic Sciences Physiology Systems Analysis & Design

Overview of movement analysis and gait features	p. 1
Inertial sensing in biomechanics : a survey of computational techniques bridging motion analysis and personal navigation	p. 70
Monitoring human movement with body-fixed sensors and its clinical applications	p. 101
Computational intelligence techniques	p. 139
Modelling of some aspects of skilled locomotor behaviour using artificial neural networks	p. 172
Visualisation of clinical gait data using a self-organising artificial neural network	p. 197
Neural network models for estimation of balance control, detection of imbalance, and estimation of falls risk	p. 217
Recognition of gait patterns using support vector machines	p. 243
Control of man-machine FES systems	p. 263
Evolutionary methods for analysis of human movement	p. 281
Dynamic pattern recognition in sport by means of artificial neural networks	p. 299
Estimation of muscle forces about the ankle during gait in healthy and neurologically impaired subjects	p. 320
Computational modelling in shoulder biomechanics	p. 348
Table of Contents provided by Blackwell. All Rights Reserved.

Computational Intelligence for Movement Sciences

Neural Networks and Other Emerging Techniques

At a Glance

Hardcover

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