Predicting Migraine Attacks Based on Environmental and Behavioral Changes as Detected From the Smartphone

NCT03762902 | Terminated

• 1 other identifier: LifegraphMigrainePrediction
• Study Type: observational
• Target: 10
• Locations: 1 country
• Sites: 2

Brief Summary

This study is conducted at the Henry Ford Health System with Lifegraph's behavioral monitoring technology, to examine the relation between migraine attacks and behavioral and environmental changes as detected from the smartphone sensors. The investigators hypothesize that Lifegraph's technology can predict the occurrence of migraine attacks with high precision.

Conditions

Migraine Disorders; Headache Disorders; Headache Disorders, Primary; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases

Keywords

Migraine; Smartphone; App; Prediction; Forecast; Detection; Individual; Machine Learning; Data Science; Algorithm; Behavior; Henry Ford Health System; HFHS; Lifegraph

Outcome Measures

Primary Outcomes (1)

• Assessing Lifegraph's predictive ability of migraine attacks before subjects report they experience an attack.

  Lifegraph has created a scalable and dynamic platform to accommodate different conditions, different types of patients with different types of data, concurrently. This platform converts the raw sensor data accumulating in Lifegraph's servers into behavioral and environmental features that have been found to be informative and helpful in generating insights relevant to migraines. The features are fed into machine learning algorithms that search for early signs of change, that may indicate an oncoming attack. These algorithms may be divided into population-based and personalized models. The study will develop a separate predictive model for each subject to predict the probability of experiencing a migraine attack during a particular interval (e.g. the next 12, 24, or 48 hours). Higher precision values of prediction will represent a better outcome. The precision is expected to be 50-70%, depends on the time passed since first installing the app and the number of reported migraine attacks

  3 months

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Individuals who suffer from episodic migraine

You may qualify if:

• Individuals who suffer from episodic migraine with 4-14 days of migraine per month (ICHD-3 patients).
• Individuals who possess a smartphone - Android version 5.0 and above or iOS version 10.0 and above.

You may not qualify if:

• Individuals who are unable to sign the consent form.
• Pregnant women.
• Individuals suffering from headaches that do not meet the IHS migraine criteria or don't have moderate to severe chronic pain of VAS chronic grade 4 and above.

Sponsors & Collaborators

• Lifegraph Ltd.: lead
• Henry Ford Health System: collaborator

Study Sites (2)

Henry Ford Health System Main Campus

Detroit, Michigan, 48202, United States

Location

Henry Ford Health System

West Bloomfield, Michigan, 48322, United States

Location

MeSH Terms

Conditions

Migraine Disorders; Headache Disorders; Headache Disorders, Primary; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Alzheimer Disease; Behavior

Condition Hierarchy (Ancestors)

Dementia; Tauopathies; Neurodegenerative Diseases; Neurocognitive Disorders; Mental Disorders

Study Officials

• Ashhar Ali, DO

  Senior Staff Physician, Department of Neurology

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: November 30, 2018
• First Posted: December 4, 2018
• Study Start: April 30, 2019
• Primary Completion: August 1, 2019
• Study Completion: September 1, 2019
• Last Updated: September 13, 2019

Record last verified: 2019-05

Data Sharing

• IPD Sharing: Will not share

Locations

US (2)