Assessment of human locomotion by using an insole measurement system and artificial neural networks

A new method for measuring and characterizing free-living human locomotion is presented. A portable device was developed to objectively record and measure foot-ground contact information in every step for up to 24 h. An artificial neural network (ANN) was developed to identify the type and intensity...

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Bibliographic Details
Published in:Journal of biomechanics 2005-11, Vol.38 (11), p.2276-2287
Main Authors: Zhang, Kuan, Sun, Ming, Kevin Lester, D., Xavier Pi-Sunyer, F., Boozer, Carol N., Longman, Richard W.
Format: Article
Language:English
Subjects:
Adolescent
Adult
Aged
Artificial neural networks
Biomechanical Phenomena - instrumentation
Biomechanical Phenomena - statistics & numerical data
Equipment Design
Exercise
Female
Foot
Gait
Ground reaction force
Humans
Insole
Locomotion
Locomotion - physiology
Male
Measurement techniques
Mechanical work
Middle Aged
Models, Biological
Neural networks
Neural Networks (Computer)
Running - physiology
Walking - physiology
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Summary:A new method for measuring and characterizing free-living human locomotion is presented. A portable device was developed to objectively record and measure foot-ground contact information in every step for up to 24 h. An artificial neural network (ANN) was developed to identify the type and intensity of locomotion. Forty subjects participated in the study. The subjects performed level walking, running, ascending and descending stairs at slow, normal and fast speeds determined by each subject, respectively. The device correctly identified walking, running, ascending and descending stairs (accuracy 98.78%, 98.33%, 97.33%, and 97.29% respectively) among different types of activities. It was also able to determine the speed of walking and running. The correlation between actual speed and estimated speed is 0.98, p
ISSN:0021-9290
1873-2380
DOI:10.1016/j.jbiomech.2004.07.036