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Updated: Jan 3, 2026

Assessment of Sensorimotor Function in Mouse Models of Parkinson's Disease
Published on: June 17, 2013
Computer mouse use captures ataxia and parkinsonism, enabling accurate measurement and detection
Krzysztof Z Gajos1, Katharina Reinecke2, Mary Donovan3
1Harvard John A. Paulson School of Engineering and Applied Sciences, Cambridge, Massachusetts, USA.
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.

