Context-awareness, Physiological Monitoring, and Machine Learning in Migraine and Cluster Headache

Contextuele Analyse, Fysiologische Metingen en Machinaal Leren Voor Migraine en Clusterhoofdpijn (COPIMAC Studie)

This is an observational, longitudinal cohort pilot study measuring physiological signals through wearable sensors combined with machine learning algorithms to detect behaviour, stress and headaches in patients with migraine and cluster headache.

Migraine and cluster headache are among the most disabling headache conditions in humans. Both conditions have different phases such as the prodromal/premonitory phase, the aura phase, the headache phase and the postdromal phase. This pilot study examines the potential of wearable sensors combined with machine learning algorithms to investigate the biological changes over time in both conditions. Behaviour such as movement, sleep and activity will be monitored. Stress levels will be estimated through the wearable data combined with input from the patients. Participants will use a wearable device around the wrist and self-developed headache application for 21 days.

Inclusion Criteria:

• migraine or cluster headache diagnosis based on ICHD 3 criteria
• at least 2 attacks each month
• onset of headache syndrome before the age of 50
• if multiple headache syndromes coexist: attacks are clearly distinguishable
• participant has smartphone that he/she wants to apply for this research

Exclusion Criteria:

• chronic migraine patients
• history of alcohol or illicit drug abuse
• significant medical comorbidity deemed by the investigator to interfere with the study
• use of betablockers
• participating in other academic or commercial trials