Finger Tapping and Typing Kinematics as a Digital Biomarker

Finger tapping kinematics describe the speed, amplitude, rhythm and decay of repetitive finger movement. Typing kinematics describe the same underlying motor control derived from ordinary keyboard interaction, chiefly the time a key is held down and the interval between keystrokes.

The distinction between the two matters. A tapping task is an active assessment: the person is asked to perform, and the result depends on their effort and attention. Typing kinematics are passive: the data comes from typing the person was doing anyway, with no task, no prompt and no awareness of being measured. That makes it one of very few motor measures in this library that can be collected without asking anything of the participant, which removes both burden and the performance effect that active testing introduces.

Tap based measurement uses a touchscreen or a sensor on the finger and derives inter tap interval, tap amplitude, variability and the decrement across repetitions. Smartphone based test batteries designed for Parkinson's disease have included tapping tasks and have been evaluated in early phase trials.

Typing based measurement records keystroke timing during natural use. The key quantity is hold time, meaning how long a key stays pressed, and its variability. Analyses of natural typing have distinguished people with early Parkinson's disease from controls using these features alone, and large scale smartphone research platforms have collected tapping and related motor data from tens of thousands of participants.

Both approaches produce composite scores rather than a single physical quantity, and the composition differs between systems.

The research interest is concentrated in early detection and in remote monitoring of Parkinson's disease, where fine motor change appears before it is obvious clinically. Passive typing analysis is attractive precisely because it can run continuously without adding assessment burden, and because it produces many observations per day rather than one per visit.

Tapping tasks are used in smartphone based trial batteries as a repeatable motor measure between site visits. Both are reported alongside clinic dexterity tests such as the Nine Hole Peg Test and the Pinch Gauge Test, which measure the same function under supervision, and alongside hand function questionnaires that describe what the impairment costs in daily activity.

Passive typing analysis is a substantial privacy undertaking. Keystroke timing can be collected without recording content, but participants are consenting to software observing their typing, and protocols must state clearly that content is not captured and how that is enforced.

Both approaches are confounded by device. Screen size, keyboard type, touch sensitivity and operating system change the measurement, and people switch devices. Typing behaviour also depends on context, posture, mood and what is being typed.

Evidence remains early. Most studies are cross sectional comparisons between patients and controls rather than longitudinal demonstrations that the measure tracks progression or responds to treatment, which is the step that would make it an endpoint rather than a signal.

• Lipsmeier F, et al. Evaluation of smartphone-based testing to generate exploratory outcome measures in a phase 1 Parkinson's disease clinical trial. Mov Disord. 2018. pubmed.ncbi.nlm.nih.gov
• Arroyo-Gallego T, et al. Detecting motor impairment in early Parkinson's disease via natural typing interaction with keyboards. J Med Internet Res. 2018. pubmed.ncbi.nlm.nih.gov
• Bot BM, et al. The mPower study, Parkinson disease mobile data collected using ResearchKit. Sci Data. 2016. pubmed.ncbi.nlm.nih.gov
• Hasan H, et al. The BRadykinesia Akinesia INcoordination (BRAIN) tap test: capturing the sequence effect. Mov Disord Clin Pract. 2019. pubmed.ncbi.nlm.nih.gov