Aisling Kelliher
Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
Physical rehabilitation typically requires therapists to make judgements about patient movement and functional improvement using subjective observation. This process makes it challenging to quantitatively track, compute and predict long-term patient improvement. We therefore propose a novel methodical approach to the standardized and interpretable quantification of patient movement during rehabilitation. We describe the expert-led development of a movement assessment rubric and an accompanying quantitative rating system. We present our movement capture and annotation computational tools designed to implement the rubric and assist therapists in the quantitative documentation and assessment of rehabilitation. We describe results from a movement capture study of the tool with nine stroke survivors and a movement rating study with four therapists. Findings from these studies highlight potential optimal methodical process paths for individuals engaged in capturing, understanding and predicting human movement performance.
https://doi.org/10.1145/3313831.3376706
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)