Affiliation:
1. John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, USA
2. Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
Abstract
Methods for obtaining accurate quantitative assessments of motor impairments are essential in accessibility research, design of adaptive ability-based assistive technologies, as well as in clinical care and medical research. Currently, such assessments are typically performed in controlled laboratory or clinical settings under professional supervision. Emerging approaches for collecting data in unsupervised settings have been shown to produce valid data when aggregated over large populations, but it is not yet established whether in unsupervised settings measures of research or clinical significance can be collected accurately and reliably for individuals. We conducted a study with 13 children with ataxia-telangiectasia and 9 healthy children to analyze the validity, test-retest reliability, and acceptability of at-home use of a recent active digital phenotyping system, called Hevelius. Hevelius produces 32 measures derived from the movement trajectories of the mouse cursor and then generates a quantitative estimate of motor impairment in the dominant arm using the dominant arm component of the Brief Ataxia Rating Scale (BARS). The severity score estimates generated by Hevelius from single at-home sessions deviated from clinician-assigned BARS scores more than the severity score estimates generated from single sessions conducted under researcher supervision. However, taking a median of as few as 2 consecutive sessions produced severity score estimates that were as accurate or better than the estimates produced from single supervised sessions. Further, aggregating as few as 2 consecutive sessions resulted in good test-retest reliability (ICC = 0.81 for A-T participants). This work demonstrated the feasibility of performing accurate and reliable quantitative assessments of individual motor impairments in the dominant arm through tasks performed at home without supervision by the researchers. Further work is needed, however, to assess how broadly these results generalize.
Funder
Sony Group Corporation
Ataxia-Telangiectasia Children’s Project, Biogen, and NIH
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Science Applications,Human-Computer Interaction
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Bibliography;Human-Computer Interaction;2024
2. The human factor;Human-Computer Interaction;2024