Ignite Creation Date:
2025-12-25 @ 3:53 AM
Ignite Modification Date:
2025-12-26 @ 2:42 AM
Study NCT ID:
NCT03762902
Status:
TERMINATED
Last Update Posted:
2019-09-13
First Post:
2018-11-30
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Predicting Migraine Attacks Based on Environmental and Behavioral Changes as Detected From the Smartphone
Sponsor:
Lifegraph Ltd.
Organization:
Study Overview
Official Title:
The Relation Between Analyzed Sensory Data of the Smartphone and Migraine Attacks, Recorded by Individuals Who Suffer From Episodic Migraine
Status:
TERMINATED
Status Verified Date:
2019-05
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Sufficient data was collected through the app to achieve initial results
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
Migraine
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.
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.
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.
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: