By Topic

Estimation of speed and incline of walking using neural network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Aminian, K. ; Lab. de Metrol., Swiss Federal Inst. of Technol., Lausanne, Switzerland ; Robert, P. ; Jequier, E. ; Schutz, Y.

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

Published in:

Instrumentation and Measurement, IEEE Transactions on  (Volume:44 ,  Issue: 3 )