Psychomotor Impairment Detection via Finger Interactions with a Computer Keyboard During Natural Typing
Name
Giancardo-2015-Psychomotor impairment.pdf
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Author(s)
Giancardo, Luca
Sanchez Ferro, Alvaro
Butterworth, Ian Richard
Sanchez Mendoza, Carlos
Hooker, Jacob M.
Date Issued
April 2015
Journal
Scientific Reports
Publisher
Nature Publishing Group
Citation
Giancardo, L., A. Sanchez-Ferro, I. Butterworth, C. S. Mendoza, and J. M. Hooker. “Psychomotor Impairment Detection via Finger Interactions with a Computer Keyboard During Natural Typing.” Sci. Rep. 5 (April 16, 2015): 9678.
Version
Final published version
Abstract
Modern digital devices and appliances are capable of monitoring the timing of button presses, or finger interactions in general, with a sub-millisecond accuracy. However, the massive amount of high resolution temporal information that these devices could collect is currently being discarded. Multiple studies have shown that the act of pressing a button triggers well defined brain areas which are known to be affected by motor-compromised conditions. In this study, we demonstrate that the daily interaction with a computer keyboard can be employed as means to observe and potentially quantify psychomotor impairment. We induced a psychomotor impairment via a sleep inertia paradigm in 14 healthy subjects, which is detected by our classifier with an Area Under the ROC Curve (AUC) of 0.93/0.91. The detection relies on novel features derived from key-hold times acquired on standard computer keyboards during an uncontrolled typing task. These features correlate with the progression to psychomotor impairment (p < 0.001) regardless of the content and language of the text typed, and perform consistently with different keyboards. The ability to acquire longitudinal measurements of subtle motor changes from a digital device without altering its functionality may allow for early screening and follow-up of motor-compromised neurodegenerative conditions, psychological disorders or intoxication at a negligible cost in the general population.
MIT Department
Massachusetts Institute of Technology. Research Laboratory of Electronics
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DOI of Published Version
https://doi.org/10.1038/srep09678
