Computer mouse use captures ataxia and parkinsonism, enabling accurate measurement and detection

• Published in: Movement disorders Vol. 35; no. 2; pp. 354 - 358
• Main Authors: Gajos, Krzysztof Z., Reinecke, Katharina, Donovan, Mary, Stephen, Christopher D., Hung, Albert Y., Schmahmann, Jeremy D., Gupta, Anoopum S.
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.02.2020; Wiley Subscription Services, Inc
• Subjects: Adolescent; Adult; Aged; Aged, 80 and over; Ataxia; Ataxia - diagnosis; Ataxia - physiopathology; Basal ganglia; Brain diseases; Brief Report; Brief Reports; Central nervous system diseases; Child; Child, Preschool; Clinical trials; Computers; Disease Progression; Female; Hevelius; Humans; Learning algorithms; machine learning; Male; Middle Aged; Movement disorders; outcome measures; Parkinson Disease - diagnosis; Parkinson Disease - drug therapy; Parkinsonian Disorders - diagnosis; Parkinsonian Disorders - drug therapy; parkinsonism; Phenotypes; Young Adult; clinical trials; ataxia; parkinsonism; machine learning; outcome measures
• ISSN: 0885-3185; 1531-8257
• DOI: 10.1002/mds.27915

Background Objective assessments of movement impairment are needed to support clinical trials and facilitate diagnosis. The objective of the current study was to determine if a rapid web‐based computer mouse test (Hevelius) could detect and accurately measure ataxia and parkinsonism. Methods Ninety‐five ataxia, 46 parkinsonism, and 29 control participants and 229,017 online participants completed Hevelius. We trained machine‐learning models on age‐normalized Hevelius features to (1) measure severity and disease progression and (2) distinguish phenotypes from controls and from each other. Results Regression model estimates correlated strongly with clinical scores (from r = 0.66 for UPDRS dominant arm total to r = 0.83 for the Brief Ataxia Rating Scale). A disease change model identified ataxia progression with high sensitivity. Classification models distinguished ataxia or parkinsonism from healthy controls with high sensitivity (≥0.91) and specificity (≥0.90). Conclusions Hevelius produces a granular and accurate motor assessment in a few minutes of mouse use and may be useful as an outcome measure and screening tool. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.