Computer mouse use captures ataxia and parkinsonism, enabling accurate measurement and detection.
Mov Disord
; 35(2): 354-358, 2020 02.
Article
em En
| MEDLINE
| ID: mdl-31769069
ABSTRACT
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.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Doença de Parkinson
/
Ataxia
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Progressão da Doença
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Transtornos Parkinsonianos
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Adolescent
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Adult
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Aged
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Aged80
/
Child
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Child, preschool
/
Female
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Humans
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Male
/
Middle aged
Idioma:
En
Revista:
Mov Disord
Assunto da revista:
NEUROLOGIA
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Estados Unidos