Estimation of speed and incline of walking using neural network

Author

Aminian, Kamiar ; Robert, Philippe ; Jequier, E. ; Schutz, Yves

Author_Institution

Lab. de Metrol., Swiss Federal Inst. of Technol., Lausanne, Switzerland

Volume

44

Issue

3

fYear

1995

fDate

6/1/1995 12:00:00 AM

Firstpage

743

Lastpage

746

Abstract

A portable data logger is designed to record body accelerations during human walking. Five subjects walk first on a treadmill at various speeds on the level, and at positive and negative inclines. Then, the subjects performed a self-pace walking on an outdoor test circuit involving roads of various inclines. The recorded signals are parameterized, and the pattern of walking at each gait cycle is found. These patterns are presented to two neural networks which estimate the incline and the speed of walking. The results show a good estimation of the incline and the speed for all of the subjects. The correlation between predicted and actual inclines is r=0.98, and the maximum of speed-predicted error is 16%. To the best of our knowledge these results constitute the first speed and incline estimation of level and slope-unconstrained walking

Keywords

biological techniques; biomechanics; computerised instrumentation; data acquisition; data loggers; neural nets; portable instruments; body accelerations; correlation; gait cycle; human walking; incline estimation; negative inclines; neural network; outdoor test circuit; piezoresistive accelerometers; portable data logger; positive inclines; recorded signals ar; self-pace walking; slope-unconstrained walking; speed-predicted error; treadmill; walking; Acceleration; Accelerometers; Automatic testing; Belts; Circuit testing; Humans; Legged locomotion; Neural networks; Performance evaluation; Random access memory;

fLanguage

English

Journal_Title

Instrumentation and Measurement, IEEE Transactions on

Publisher

ieee

ISSN

0018-9456

Type

jour

DOI

10.1109/19.387322

Filename

387322