Computational Intelligence for Movement Sciences: Neural Networks and Other Emerging Techniques

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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.

About the Author:
Dr. Rezaul Begg received his B.Sc. and M.Sc. Eng degrees in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology, Bangladesh, and his Ph.D. degree in Biomedical Engineering from the University of Aberdeen, U.K. Currently, he is a Faculty member within the Centre for Ageing, Rehabilitation, Exercise & Sport at Victoria University, Melbourne, Australia. He researches in Biomedical Engineering, Biomechanics and Machine Learning areas.

Bio2 - Dr. Marimuthu Palaniswami received his BE(Hons) from the University of Madras, ME from the Indian Institute of science, India, MEngSc from the University of Melbourne and Ph.D from the University of Newcastle, Australia before rejoining theUniversity of Melbourne. He has been serving the University of Melbourne for over 16 years. He has published more than 180 refereed papers. He was given a Foreign Specialist Award by the Ministry of Education, Japan in recognition of his contributions to the field of Machine Learning. He served as associate editor for Journals/transactions including IEEE Transactions on neural Networks and Computational Intelligence for Finance. His research interests include SVMs, Sensors and Sensor Networks, Machine Learning, Neural Network, Pattern Recognition, Signal Processing and Control. He is the convener for Australian Research Network on Sensor Network.

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Product Details

Table of Contents

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