Estimation of walking energy expenditure by using support vector regression.
This paper develops a new predictor of walking energy expenditure from wireless measurements of body movements using triaxial accelerometers. Reliable data were collected from repeated walking experiments in different conditions on a treadmill with simultaneous measurement of expired oxygen and carbon dioxide. Support vector regression, a powerful non-linear regression method, was used to process and model the data. This novel processing method sets this investigation apart from existing papers. Good results were achieved in the robust estimation of walking related energy expenditure from a number of variables derived from triaxial accelerometer and treadmill speed.
Su
S
S
Human Performance Lab, School of Electrical Engineering & Telecommunications, University of New South Wales, UNSW Sydney N.S.W. 2052 Australia. Email addresses: steven.su@unsw.edu.au.
Wang
L
L
Celler
B
B
Ambikairajah
E
E
Savkin
A
A