Computer keyboard interaction as an indicator of early Parkinson’s disease
Name
Computer keyboard.pdf
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640.32 KB
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Checksum (MD5)
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Author(s)
Montero, P.
Matarazzo, M.
Obeso, J. A.
Estépar, R. San José
Giancardo, Luca
Sanchez Ferro, Alvaro
Arroyo Gallego, Teresa
Butterworth, Ian Richard
Sanchez Mendoza, Carlos
Gray, Martha L
Date Issued
October 2016
Journal
Scientific Reports
Publisher
Nature Publishing Group
Citation
Giancardo, L. et al. “Computer Keyboard Interaction as an Indicator of Early Parkinson’s Disease.” Scientific Reports 6.1 (2016): n. pag.
Version
Final published version
Abstract
Parkinson’s disease (PD) is a slowly progressing neurodegenerative disease with early manifestation of motor signs. Objective measurements of motor signs are of vital importance for diagnosing, monitoring and developing disease modifying therapies, particularly for the early stages of the disease when putative neuroprotective treatments could stop neurodegeneration. Current medical practice has limited tools to routinely monitor PD motor signs with enough frequency and without undue burden for patients and the healthcare system. In this paper, we present data indicating that the routine interaction with computer keyboards can be used to detect motor signs in the early stages of PD. We explore a solution that measures the key hold times (the time required to press and release a key) during the normal use of a computer without any change in hardware and converts it to a PD motor index. This is achieved by the automatic discovery of patterns in the time series of key hold times using an ensemble regression algorithm. This new approach discriminated early PD groups from controls with an AUC = 0.81 (n = 42/43; mean age = 59.0/60.1; women = 43%/60%;PD/controls). The performance was comparable or better than two other quantitative motor performance tests used clinically: alternating finger tapping (AUC = 0.75) and single key tapping (AUC = 0.61).
MIT Department
Institute for Medical Engineering and Science
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Research Laboratory of Electronics
Terms of Use
Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1038/srep34468
