An Investigation into Keystroke Dynamics and Heart Rate Variability as Indicators of Stress

TL;DR

This study investigates the potential of using keystroke timing and heart rate variability as indicators of emotional stress, highlighting the need for personalized keystroke analysis for accurate stress detection.

Contribution

It explores the relationship between keystroke dynamics and HRV as stress indicators and suggests personalized keystroke analysis for better accuracy.

Findings

Keystroke timing varies with emotional stress and fatigue.

Current top-10 bigram analysis is insufficient for stress detection.

Personalized keystroke models may improve stress monitoring accuracy.

Abstract

Lifelogging has become a prominent research topic in recent years. Wearable sensors like Fitbits and smart watches are now increasingly popular for recording ones activities. Some researchers are also exploring keystroke dynamics for lifelogging. Keystroke dynamics refers to the process of measuring and assessing a persons typing rhythm on digital devices. A digital footprint is created when a user interacts with devices like keyboards, mobile phones or touch screen panels and the timing of the keystrokes is unique to each individual though likely to be affected by factors such as fatigue, distraction or emotional stress. In this work we explore the relationship between keystroke dynamics as measured by the timing for the top-10 most frequently occurring bi-grams in English, and the emotional state and stress of an individual as measured by heart rate variability (HRV). We collected keystroke data using the Loggerman application while HRV was simultaneously gathered. With this data we performed an analysis to determine the relationship between variations in keystroke dynamics and variations in HRV. Our conclusion is that we need to use a more detailed representation of keystroke timing than the top-10 bigrams, probably personalised to each user.