A metric for upper extremity functional range of motion analysis in long-term stroke recovery using wearable motion sensors and posture cubics

Abstract

We investigate an approach to analyse and represent the functional range of motion (fROM) in patients after stroke during long-term rehabilitation in a day-care centre. Movement data of patients after stroke were recorded during free activities of living (ADL) and one-to-one (OTO) therapies using wearable inertial motion sensors. Using a gradient descent sensor fusion algorithm, we estimated orientation of upper body extremities and described extremity positions as frequency statistics in spatial posture cubics. We visualised the fROM and compared sensor-based posture representation with video reference during OTO. To illustrate our approach, we analysed differences in affected and non-affected arm use in three typical patients after stroke across multiple weeks. Our analysis revealed differences in body sides as well as between ADL and OTO. Posture cubics may provide clinicians with an intuitive tool for longitudinal fROM analysis.