title: Psychomotor impairment detection via finger interactions with a computer keyboard during natural typing.
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.
authors.affiliation: Madrid-MIT M+Visión Consortium, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139.
authors.forename: L
authors.initials: L
authors.lastname: Giancardo
authors.affiliation: Madrid-MIT M+Visión Consortium, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139.
authors.forename: A
authors.initials: A
authors.lastname: Sánchez-Ferro
authors.affiliation: Madrid-MIT M+Visión Consortium, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139.
authors.forename: I
authors.initials: I
authors.lastname: Butterworth
authors.affiliation: Madrid-MIT M+Visión Consortium, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139.
authors.forename: C S
authors.initials: CS
authors.lastname: Mendoza
authors.affiliation: 1] Madrid-MIT M+Visión Consortium, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139 [2] Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129.
authors.forename: J M
authors.initials: JM
authors.lastname: Hooker
mesh_terms: D000328:Adult; D000465:Algorithms; D019540:Area Under Curve; D003201:Computers; D005260:Female; D005385:Fingers / Q000502:physiology*; D064368:Healthy Volunteers; D006801:Humans; D008297:Male; D011596:Psychomotor Disorders / Q000175:diagnosis*; D012372:ROC Curve; D055815:Young Adult