Real time patient's gait monitoring through wireless accelerometers with the wavelet transform

Abstract

Gait analysis through on-body wireless accelerometers can provide valuable information for multiple health-related applications. The dynamic nature of human body acceleration signals makes their analysis with the wavelet transform optimum. Nevertheless, one of the main issues for the practical development of this signal processing tool in real time is the difficulty in the selection of the appropriate scale and mother wavelet for each particular gait. In this paper we show how these problems can be solved, resulting in a system that can accurately monitor patients' gait in real time without the need for calibration.