Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Migraines are among the most common
neurological disorders, leading to reduced productivity,
poor concentration, and a lower quality of life.
Identifying and managing migraine triggers is
challenging due to their complex and variable nature.
Traditional tracking methods like headache diaries
often suffer from missing data and limited predictive
value. This project presents an AIpowered Migraine
Trigger Tracker that integrates data from self-reports,
wearable sensors (stress levels), environmental factors
(weather, air quality), and lifestyle patterns. Using
machine learning, the system uncovers hidden
correlations, predicts potential migraine attacks, and
provides real-time alerts. The mobile and web-based
platform offers user-friendly interfaces, personalized
insights, and data-driven recommendations, enabling
proactive prevention and improved patient care.
Keywords:
AI in healthcare, Migraine prediction, Machine learning, Trigger detection, Digital health, Preventive healthcare, Wearable sensors, Personalized medicine
Cite Article:
"AI-Powered Migraine Trigger Tracker", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 6, page no.a587-a595, June-2026, Available :http://www.ijrti.org/papers/IJRTI2606059.pdf
Downloads:
000106
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator