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TerminatedNCT03762902MigraineUpdated Sep 13, 2019

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

An observational study in Migraine Disorders, Headache Disorders and Headache Disorders, Primary, sponsored by Lifegraph Ltd.. Terminated at 2 sites in United States. Open to participants aged 18 Years to 75 Years. Per ClinicalTrials.gov, last updated 2019-09-13.

Sponsored by Lifegraph Ltd. · Observational

Why this study was terminated
Sufficient data was collected through the app to achieve initial results
Study type
Observational
Model
Cohort
Time perspective
Prospective
Enrollment
10
Ages
18 Years to 75 Years
Sex
All
01

Study 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.

Read the detailed description

Migraine attacks can damage quality of life and lead to missed work days if not treated in time. These attacks last for about 4-72 hours, accompanied by headache and other symptoms. The time window for early intervention, which can potentially reduce the severity of an attack, lasts 2-48 hours before symptoms are starting to appear (10 hours on average). This time window is defined in the literature as the prodromal phase, when intervention during this phase can allow early treatment to improve the patient's condition and reduce the intensity and duration of the attack.

Migraine attacks and the prodromal phase can be characterized by one or more behavioral or environmental symptoms, either causal or resultant. Some of them can be passively measured by the smartphone usage, such as changes in sleep, physical activity and weather.

Lifegraph's smartphone application runs in the background of the subjects' personal smartphone, collects data passively and automatically, while rigorously maintaining privacy and with no effect to the daily use. Proprietary machine-learning algorithms analyze the collected data and turn it into behavioral channels, such as activity, sleep and mobility. The technology learns the personal routine of each user and detects changes in his/her behavioral patterns that can indicate an upcoming migraine.

Eligible subjects will meet a neurologist, sign an informed consent, fill an initial questionnaire and install the Lifegraph application on their smartphone. The application requires a one-time registration process.

During the study, subjects will self-report migraine attacks they experience through the smartphone application. Each report will include start time, end time and pain intensity. Data will be analyzed during the study in order to learn each subject's behavior and his/her migraine attacks. Subjects will be blinded to the app's migraine predictions to avoid expectancy bias.

02

Conditions studied

  • 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
03

In context

Migraine Disorders

1,657 studies on the registry are indexed under Migraine Disorders; 339 are open to participants now.

This study's enrollment of 10 is below the median of 137 across 331 observational studies indexed under Migraine Disorders.

Browse Migraine Disorders studies →

Lead sponsor

This is the only study on the registry with Lifegraph Ltd. as lead sponsor.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years to 75 Years
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

Individuals who suffer from episodic migraine

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • 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.

Exclusion criteria

Exclusion Criteria:

  • 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.
05

Study design

Observational model
Cohort
Time perspective
Prospective
Enrollment
10 participants (actual)
Patient registry
No
06

What researchers measure

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

    Time frame: 3 months

07

Study locations

2 sites
  • Henry Ford Health System Main Campus
    Detroit, Michigan 48202, United States
  • Henry Ford Health System
    West Bloomfield, Michigan 48322, United States
08

References and documents

Individual participant data

Plan to share: No

No publications or documents are linked to this record.

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Sep 13, 2019, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT03762902
Lead sponsor
Lifegraph Ltd.
Responsible party
Sponsor
First posted
Dec 4, 2018
Start date
Apr 30, 2019
Primary completion
Aug 1, 2019
Completion
Sep 1, 2019
Last update
Sep 13, 2019

Study contacts

Ashhar Ali, DO
principal investigator · Senior Staff Physician, Department of Neurology

Oversight

FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is terminated, as verified in May 2019. You cannot join it, but the record below documents what was studied.

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