Uncovering the potential of smartphones for behavior monitoring during migraine follow-up
Abstract
BACKGROUND: Migraine is a neurological disorder that affects millions of people worldwide. It is one of the most debilitating disorders which leads to many disability-adjusted life years. Conventional methods for investigating migraines, like patient interviews and diaries, suffer from self-reporting biases and intermittent tracking.
METHODS: This study aims to leverage smartphone-derived data as an objective tool for examining the relationship between migraines and various human behavior aspects. By utilizing built-in sensors and monitoring phone interactions, we gather data from which we derive metrics such as keyboard usage, application interaction, physical activity levels, ambient light conditions, and sleep patterns. We perform statistical analysis testing to investigate whether there is a difference in user behavioral aspects during headache and non-headache periods.
RESULTS: Our analysis of 362 headaches reveals differences in behavioral aspects such as ambient light, use of leisure apps, and number of keystrokes during headache periods and non-headache periods.
CONCLUSIONS: This exploratory study shows on the one hand that it is possible to monitor various human behavioral aspects using the smartphone sensors and interaction data only. On the other hand it shows that we can observe difference in human behavior between headache and non-headache periods. Our work is a step towards objectively measure the effects that migraine has on people's lives.
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence.
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