Title :
Estimation of Walking Energy Expenditure by Using Support Vector Regression
Author :
Su, S.W. ; Wang, L. ; Celler, B.G. ; Ambikairajah, E. ; Savkin, A.V.
Author_Institution :
Sch. of Electr. Eng. & Telecommun., New South Wales Univ., Sydney, NSW
fDate :
6/27/1905 12:00:00 AM
Abstract :
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
Keywords :
accelerometers; gait analysis; medical signal processing; regression analysis; CO2; O2; body movements; nonlinear regression method; support vector regression; treadmill speed; triaxial accelerometers; walking energy expenditure estimation; Accelerometers; Carbon dioxide; Diabetes; Energy measurement; Equations; Insulin; Legged locomotion; Linear regression; Motion measurement; Robustness;
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
DOI :
10.1109/IEMBS.2005.1617240