High-accuracy detection of early Parkinson's Disease using multiple characteristics of finger movement while typing

Warwick R. Adams

doi:10.1371/journal.pone.0188226

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Open Access

Peer-reviewed

Research Article

High-accuracy detection of early Parkinson's Disease using multiple characteristics of finger movement while typing

Warwick R. Adams

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: warwick@harvest.com.au

Affiliation School of Computing & Mathematics, Charles Sturt University, N.S.W., Australia

http://orcid.org/0000-0003-1533-0961

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High-accuracy detection of early Parkinson's Disease using multiple characteristics of finger movement while typing

Warwick R. Adams

Published: November 30, 2017
https://doi.org/10.1371/journal.pone.0188226

About the Authors

Warwick R. Adams

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: warwick@harvest.com.au

Affiliation School of Computing & Mathematics, Charles Sturt University, N.S.W., Australia

http://orcid.org/0000-0003-1533-0961

Competing Interests

The author has declared that no competing interests exist.

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Parkinson disease
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Machine learning
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Myoclonus
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Fingers
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Diagnostic medicine
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Hands
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Statistical data
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Motor neuron diseases
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