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Minimization of Number of Gait Trials for Predicting the Stabilized Minimum Toe Clearance During Gait Using Artificial Neural Networks

Cai, Jimmy, Begg, Rezaul, Best, Russell, Karaharju-Huisman, Tuire and Taylor, Simon (2001) Minimization of Number of Gait Trials for Predicting the Stabilized Minimum Toe Clearance During Gait Using Artificial Neural Networks. In: ANZIIS 2001‎: Seventh Australian and New Zealand Intelligent Information Systems Conference. The University of Western Australia, ‬Crawley, W. A., pp. 429-432.

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Abstract

Artificial neural networks (ANN) have been increasingly used in gait analysis. Back-propagation neural network has been widely used because of its good predicting power in supervised training mode for gait data analysis. In this paper an artificial neural network was used to model relationships between minimum toe clearance (MTC) characteristics derived from fewer gait trials and that derived from gait data during a 30-minute continuous treadmill walking. The ANN was separately trained and tested with nine statistics calculated from 10 different data segment lengths as inputs, and the mean and standard deviation of MTC data calculated from 30 minutes gait trials as outputs. The results suggest that a trained ANN is able to accurately predict stabilized MTC data, even a 5-gait cycles’ data predicted with about 80% accuracy and the prediction accuracy was seen to improve with increase in the length of input data segment.

Item Type: Book Section
ISBN: ‬978174052061
Additional Information:

‬"IEEE Catalog Number: OIEX539"--verso of T.p
‬Australian and New Zealand Conference on Intelligent Information Systems‎ ‬(7th :‎ 2001 :‎ ‬Perth, W. A.). Conference date: 18-21 Nov. 2001.

Uncontrolled Keywords: horizontal velocity, gait pattern recognition, treadmill walking, heel contact, two-dimensional calibration, metatarsal head, MH, back-propagation, processing elements, PE, prediction accuracy, neural net
Subjects: FOR Classification > 0801 Artificial Intelligence and Image Processing
FOR Classification > 1106 Human Movement and Sports Science
Faculty/School/Research Centre/Department > School of Sport and Exercise Science
Depositing User: Yimin Zeng
Date Deposited: 18 Jun 2013 01:48
Last Modified: 21 Mar 2019 01:05
URI: http://vuir.vu.edu.au/id/eprint/21413
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Citations in Scopus: 0 - View on Scopus

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