Use of infrared sensors for estimation of energy expenditure by elderly people living alone at home.
Tri-axial accelerometers (triax) can estimate energy expenditure with a correlation of approximately 0.9. We explored the idea of developing an alternative non-contact method to estimate energy expenditure. In this paper, we present a statistical analysis of infrared sensor data and tri-axial accelerometer data to investigate a relationship between the infrared sensor outputs and energy expenditure as estimated using a triaxial accelerometer. Parametric regression of triax data and sensor data did not show any global fitting parameters. Non parametric regression method of locally weighted scatter plot smoothing (lowess) using tri-cube kernel weights gives an underlying trend of energy estimate. As it is a non-parametric method, it does not give us any global parameters to estimate measure of energy expenditure. But it gives us a good visual assessment of relationship between motion sensor data and accelerometer data.
Kaushik
Alka R
AR
School of Electrical Engineering & Telecommunications, New South Wales University, Sydney, NSW, Australia. alka@student.unsw.edu.au
Celler
Branko G
BG
D000203:Activities of Daily Living; D000368:Aged; D002153:Calorimetry, Indirect / Q000295:instrumentation; D004734:Energy Metabolism; D016552:Ergometry; D006801:Humans; D007259:Infrared Rays; D016014:Linear Models; D015233:Models, Statistical; D008962:Models, Theoretical; D009043:Motor Activity; D009068:Movement; D017711:Nonlinear Dynamics; D012044:Regression Analysis; D012146:Rest