Evaluating functional ability of upper limbs after stroke using video game data

Abstract

The aim of this paper is to develop a validated system for remote monitoring by health professionals of home-based upper limb rehabilitation by utilising action-video games, data analysis algorithms and cloud server technology. Professionally-written action-video games designed specifically for upper limb rehabilitation were used and game controllers provided continuous 3D kinematic data of hand and arm position. Assessments were made in the patient's home when they played a bespoke 'assessment' mini game controlled by 40 representative actions. An occupational therapist also undertook a blinded clinical CAHAI assessment. For each move 8 scalar variables were defined from both limbs, giving 320 covariates. There were entered into a multiple linear regression random effects model which identified 15 covariates derived from 12 movements that explained 80% of the variance in the CAHAI scores. We conclude that remote monitoring by health professionals of home-based upper limb rehabilitation is possible using data collected remotely from video game play. © Springer International Publishing 2013.