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Cited by 17Migraine and Headache StudiesArtificial Intelligence in HealthcareMobile Health and mHealth Applications

mBrain: towards the continuous follow-up and headache classification of primary headache disorder patients

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De Brouwer, Mathias, Vandenbussche, Nicolas, Steenwinckel, Bram, Stojchevska, Marija, Van Der Donckt, Jonas, Degraeve, Vic, Vaneessen, Jasper, De Turck, Filip +5 more·2022·BMC Medical Informatics and Decision Making
DOI 10.1186/s12911-022-01813-wPMC PMC8969243
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Abstract

Background: The diagnosis of headache disorders relies on the correct classification of individual headache attacks. Currently, this is mainly done by clinicians in a clinical setting, which is dependent on subjective self-reported input from patients. Existing classification apps also rely on self-reported information and lack validation. Therefore, the exploratory mBrain study investigates moving to continuous, semi-autonomous and objective follow-up and classification based on both self-reported and objective physiological and contextual data. Methods: The data collection set-up of the observational, longitudinal mBrain study involved physiological data from the Empatica E4 wearable, data-driven machine learning (ML) algorithms detecting activity, stress and sleep events from the wearables’ data modalities, and a custom-made application to interact with these events and keep a diary of contextual and headache-specific data. A knowledge-based classification system for individual headache attacks was designed, focusing on migraine, cluster headache (CH) and tension-type headache (TTH) attacks, by using the classification criteria of ICHD-3. To show how headache and physiological data can be linked, a basic knowledge-based system for headache trigger detection is presented. Results: In two waves, 14 migraine and 4 CH patients participated (mean duration 22.3 days). 133 headache attacks were registered (98 by migraine, 35 by CH patients). Strictly applying ICHD-3 criteria leads to 8/98 migraine without aura and 0/35 CH classifications. Adapted versions yield 28/98 migraine without aura and 17/35 CH classifications, with 12/18 participants having mostly diagnosis classifications when episodic TTH classifications (57/98 and 32/35) are ignored. Conclusions: Strictly applying the ICHD-3 criteria on individual attacks does not yield good classification results. Adapted versions yield better results, with the mostly classified phenotype (migraine without aura vs. CH) matching the diagnosis for 12/18 patients. The absolute number of migraine without aura and CH classifications is, however, rather low. Example cases can be identified where activity and stress events explain patient-reported headache triggers. Continuous improvement of the data collection protocol, ML algorithms, and headache classification criteria (including the investigation of integrating physiological data), will further improve future headache follow-up, classification and trigger detection. Trial registration This trial was retrospectively registered with number NCT04949204 on 24 June 2021 at www.clinicaltrials.gov.

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  • The device memory mode is very reliable and data loss only occurs whenever the device is switched off to swap it or when using the shower.

    “The device memory mode is very reliable and data loss only occurs whenever the device is switched off to swap it or when using the shower, as seen in previous studies20,21,54.”

    From Data quality evaluation in wearable monitoring (2022) · cites this paper as [54]

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Authors
De Brouwer, M., Vandenbussche, N., Steenwinckel, B., Stojchevska, M., Van Der Donckt, J., Degraeve, V., Vaneessen, J., De Turck, F., Volckaert, B., Boon, P., Paemeleire, K., Van Hoecke, S., & Ongenae, F.
Affiliations
  • Ghent University Hospital (BE)
  • Ghent University (BE)
ORCID
Venue
BMC Medical Informatics and Decision Making
Publisher
Springer Science and Business Media LLC
Published
2022-03-31
Volume
22
Issue
1
Pages
87-87
ISSN
1472-6947 (ISSN-L)
DOI
10.1186/s12911-022-01813-w
PMC
PMC8969243
OpenAlex
W4221070291
Cited by
17
References
55
Citations by year
2026: 3 · 2025: 8 · 2024: 4 · 2023: 1 · 2022: 1
FWCI
2.28
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Medical Informatics and Decision Making (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Ghent University Academic Bibliography (Ghent University) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Fonds Wetenschappelijk Onderzoek (1S56322N, 1SA0219N)
  • Universitair Ziekenhuis Gent
  • Universiteit Gent
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Migraine and Headache Studies
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Keywords
primary headache, migraine without aura, cluster headache, tension-type headache, ICHD-3 criteria, headache triggers, wearable sensors, Empatica E4, physiological signals, activity detection, stress detection, sleep detection, mobile health
MeSH terms
Follow-Up Studies, Headache, Humans, Migraine Disorders, Headache Disorders, Self Report

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