Key result
Multitasking stress alters individual typing rhythms, enabling machine learning to accurately classify stressed states.
Why the study?
Stress induces changes in muscle tone and motor control, but whether typing rhythms can identify stressed individuals or universal keystroke markers of stress remains unknown.
Does socially evaluated multitasking stress alter typing rhythms in individuals?
Observational (n=116)
Does socially evaluated multitasking stress alter typing rhythms in individuals?
Typing rhythms can be used to identify individual stress states, offering a potential non-invasive method for stress monitoring.
Typing rhythms may enable passive stress monitoring in daily computing; leaves open generalizability and links to cardiovascular outcomes.
Individuals have unique typing rhythms characterized by specific keystroke dynamics. Changes in state and cardiovascular responding are well documented manifestations of the fight-flight response to stress. However, as stress also leads to changes in muscle tone and motor control, typing rhythms may also be impacted. We aim to determine which individuals are experiencing stress through their typing rhythms and identify universal keystroke markers of stress. Participants (N = 116) typed 80 repetitions of a 6-word, 30-character phrase before and after 15 min of critically evaluated multitasking stress. Cardiovascular, hemodynamic, and state variables were compared across baseline, stress, and recovery periods and measures of typing rhythm were derived for each period and classified using machine-learning algorithms. Critically evaluated multitasking led to significant changes in all stress measures, demonstrating highly robust stress reactivity. Machine learning algorithms accurately classified stressed typing for each individual based on their typing rhythms; however, no universal keystroke markers of stress were identified. Using typing rhythms. We were able to determine whether an individual was stressed or not, but the markers used for classification differed between individuals. These individual changes may provide opportunities for identifying stressful periods through keystroke monitoring, as well as the potential for early identification of disorders which may impact fine motor control. Typing rhythms could therefore be used to monitor health and well-being in individuals who use keyboards in various situations. This is the first rigorous assessment of stress and typing rhythms and has led to the development of a feasible and highly reproducible research protocol.
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Wetherell et al. (2023) conducted an observational in Stress (n=116). Critically evaluated multitasking stress vs. Baseline (pre-stress) was evaluated on Classification of stressed typing using machine-learning algorithms based on typing rhythms. Critically evaluated multitasking stress significantly altered individual typing rhythms, allowing machine learning algorithms to accurately classify stressed states without universal keystroke markers.
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