Inertial characteristics of upper extremity motions in upper extremity stroke rehabilitation based tasks

Abstract

Activity counting has demonstrated strong correlations to recovery before and after stroke rehabilitation. However, there are only moderate to poor correlations with movement specific features (such as timing and repetition) that are significant to stroke rehabilitation, allowing room for improvement. This paper explores the physical meaning of an accelerometric based activity count, by using a precise tri-axial accelerometer and tri-axial gyroscope during tasks based on selected activities of daily living (ADLs). The impact of processing algorithms and sensor choice were also considered. Nine healthy participants performed a series of free-world upper extremity movement tasks modelled after ADLs as well as tasks constrained by speed and direction. Raw gyroscope and accelerometer data were linearly regressed with medically graded actigraphy bands for comparison. The results demonstrated that wrist motion during upper extremity tasks had similar distributions of data across all planes and axes of motion. The results also highlighted that processing algorithms based on mean and median epoched data were more sensitive (p <; 0.05) to differences in planes and axes of motion, but that variance based methods presented lower root-mean-square-errors (RMSE) errors when linearly regressed with medically graded technology. The findings from this study help to better understand inertial patterns of upper extremity rehabilitation based tasks and physical interpretations of activity count measures.