The purpose of this research is to determine if data from smart devices, including heart rate and movement during sleep and wake times, will be able to track headaches and predict recurrence and exacerbations (make worse). This use of this information may in the future allow patients earlier and more effective treatments if these devices can help predict when the headaches may occur.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
PREVENTION
Masking
NONE
Enrollment
20
Custom phone application that integrates data from smart watch. Subjects will complete daily "To-Do-Lists" where data will be collected on if they had a headache in the past 24 hours, severity of headache, and any analgesics used to treat the headache.
Mayo Clinic Minnesota
Rochester, Minnesota, United States
Percentage accuracy of fit with AUC of the ROC (receiver operating characteristics) curve (%) for headache tracking.
Percentage accuracy of fit with AUC of the ROC curve for factors from data collected from custom phone app integrated with smart devices to track headache frequency and severity.
Time frame: 6 months
Percentage accuracy of fit with AUC of the ROC curve (%) for headache forecasting.
Percentage accuracy of fit with AUC of the ROC curve for data from custom phone app integrated with smart devices to forecast periods of increased headache likelihood.
Time frame: 6 months
Correlation coefficients of wearable sensor data to headache frequency and severity.
Correlation of novel physiological clinical outcome data (e.g., time in bed, average sleep time, stand time, exercise time, move time, walking distance, running distance, estimated six-minute walk, steps per day, heart rate, heart rate variability) to monthly headache days, moderate to severe monthly headache days, analgesic use, MIDAS, and HIT-6.
Time frame: 6 months
uMARS app quality mean score
Quality of the custom phone app integrated with smart watches as assessed by the validated uMARS.
Time frame: 6 months
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