Optimum gravity vector and vertical acceleration estimation using a tri-axial accelerometer for falls and normal activities

This study aims to determine an optimum estimate for the gravitational vector and vertical acceleration profiles using a body-worn tri-axial accelerometer during falls and normal activities of daily living (ADL), validated using a camera based motion analysis system. Five young healthy subjects performed a number of simulated falls and normal ADL while trunk kinematics were measured by both an optical motion analysis system and a tri-axial accelerometer. Through low-pass filtering of the trunk tri-axial accelerometer signal between 1Hz and 2.7Hz using a 1^st order or higher, Butterworth IIR filter, accurate gravity vector profile can be obtained using the method described here. Results: a high mean correlation (≥0.83: Coefficient of Multiple Correlations) and low mean percentage error (≤2.06m/s²) were found between the vertical acceleration profile generated from the tri-axial accelerometer based sensor to those from the optical motion capture system. This proposed system enables optimum gravity vector and vertical acceleration profiles to be measured from the trunk during falls and normal ADL.