<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03762902</url>
  </required_header>
  <id_info>
    <org_study_id>LifegraphMigrainePrediction</org_study_id>
    <nct_id>NCT03762902</nct_id>
  </id_info>
  <brief_title>Predicting Migraine Attacks Based on Environmental and Behavioral Changes as Detected From the Smartphone</brief_title>
  <acronym>Migraine</acronym>
  <official_title>The Relation Between Analyzed Sensory Data of the Smartphone and Migraine Attacks, Recorded by Individuals Who Suffer From Episodic Migraine</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Lifegraph Ltd.</agency>
      <agency_class>Industry</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Henry Ford Health System</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Lifegraph Ltd.</source>
  <oversight_info>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      This study is conducted at the Henry Ford Health System with Lifegraph's behavioral&#xD;
      monitoring technology, to examine the relation between migraine attacks and behavioral and&#xD;
      environmental changes as detected from the smartphone sensors. The investigators hypothesize&#xD;
      that Lifegraph's technology can predict the occurrence of migraine attacks with high&#xD;
      precision.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Migraine attacks can damage quality of life and lead to missed work days if not treated in&#xD;
      time. These attacks last for about 4-72 hours, accompanied by headache and other symptoms.&#xD;
      The time window for early intervention, which can potentially reduce the severity of an&#xD;
      attack, lasts 2-48 hours before symptoms are starting to appear (10 hours on average). This&#xD;
      time window is defined in the literature as the prodromal phase, when intervention during&#xD;
      this phase can allow early treatment to improve the patient's condition and reduce the&#xD;
      intensity and duration of the attack.&#xD;
&#xD;
      Migraine attacks and the prodromal phase can be characterized by one or more behavioral or&#xD;
      environmental symptoms, either causal or resultant. Some of them can be passively measured by&#xD;
      the smartphone usage, such as changes in sleep, physical activity and weather.&#xD;
&#xD;
      Lifegraph's smartphone application runs in the background of the subjects' personal&#xD;
      smartphone, collects data passively and automatically, while rigorously maintaining privacy&#xD;
      and with no effect to the daily use. Proprietary machine-learning algorithms analyze the&#xD;
      collected data and turn it into behavioral channels, such as activity, sleep and mobility.&#xD;
      The technology learns the personal routine of each user and detects changes in his/her&#xD;
      behavioral patterns that can indicate an upcoming migraine.&#xD;
&#xD;
      Eligible subjects will meet a neurologist, sign an informed consent, fill an initial&#xD;
      questionnaire and install the Lifegraph application on their smartphone. The application&#xD;
      requires a one-time registration process.&#xD;
&#xD;
      During the study, subjects will self-report migraine attacks they experience through the&#xD;
      smartphone application. Each report will include start time, end time and pain intensity.&#xD;
      Data will be analyzed during the study in order to learn each subject's behavior and his/her&#xD;
      migraine attacks. Subjects will be blinded to the app's migraine predictions to avoid&#xD;
      expectancy bias.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Terminated</overall_status>
  <why_stopped>
    Sufficient data was collected through the app to achieve initial results&#xD;
  </why_stopped>
  <start_date type="Actual">April 30, 2019</start_date>
  <completion_date type="Actual">September 1, 2019</completion_date>
  <primary_completion_date type="Actual">August 1, 2019</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Assessing Lifegraph's predictive ability of migraine attacks before subjects report they experience an attack.</measure>
    <time_frame>3 months</time_frame>
    <description>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</description>
  </primary_outcome>
  <enrollment type="Actual">10</enrollment>
  <condition>Migraine Disorders</condition>
  <condition>Headache Disorders</condition>
  <condition>Headache Disorders, Primary</condition>
  <condition>Brain Diseases</condition>
  <condition>Central Nervous System Diseases</condition>
  <condition>Nervous System Diseases</condition>
  <eligibility>
    <study_pop>
      <textblock>
        Individuals who suffer from episodic migraine&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Individuals who suffer from episodic migraine with 4-14 days of migraine per month&#xD;
             (ICHD-3 patients).&#xD;
&#xD;
          -  Individuals who possess a smartphone - Android version 5.0 and above or iOS version&#xD;
             10.0 and above.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Individuals who are unable to sign the consent form.&#xD;
&#xD;
          -  Pregnant women.&#xD;
&#xD;
          -  Individuals suffering from headaches that do not meet the IHS migraine criteria or&#xD;
             don't have moderate to severe chronic pain of VAS chronic grade 4 and above.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>75 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Ashhar Ali, DO</last_name>
    <role>Principal Investigator</role>
    <affiliation>Senior Staff Physician, Department of Neurology</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Henry Ford Health System Main Campus</name>
      <address>
        <city>Detroit</city>
        <state>Michigan</state>
        <zip>48202</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Henry Ford Health System</name>
      <address>
        <city>West Bloomfield</city>
        <state>Michigan</state>
        <zip>48322</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>May 2019</verification_date>
  <study_first_submitted>November 30, 2018</study_first_submitted>
  <study_first_submitted_qc>November 30, 2018</study_first_submitted_qc>
  <study_first_posted type="Actual">December 4, 2018</study_first_posted>
  <last_update_submitted>September 11, 2019</last_update_submitted>
  <last_update_submitted_qc>September 11, 2019</last_update_submitted_qc>
  <last_update_posted type="Actual">September 13, 2019</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>Migraine</keyword>
  <keyword>Smartphone</keyword>
  <keyword>App</keyword>
  <keyword>Prediction</keyword>
  <keyword>Forecast</keyword>
  <keyword>Detection</keyword>
  <keyword>Individual</keyword>
  <keyword>Machine Learning</keyword>
  <keyword>Data Science</keyword>
  <keyword>Algorithm</keyword>
  <keyword>Behavior</keyword>
  <keyword>Henry Ford Health System</keyword>
  <keyword>HFHS</keyword>
  <keyword>Lifegraph</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Migraine Disorders</mesh_term>
    <mesh_term>Nervous System Diseases</mesh_term>
    <mesh_term>Brain Diseases</mesh_term>
    <mesh_term>Central Nervous System Diseases</mesh_term>
    <mesh_term>Headache Disorders</mesh_term>
    <mesh_term>Headache Disorders, Primary</mesh_term>
    <mesh_term>Headache</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03762902
org study id: LifegraphMigrainePrediction
nct id: NCT03762902
lead sponsor: 
collaborator: 
is fda regulated drug: No
is fda regulated device: No
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.
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.
observational model: Cohort
time perspective: Prospective
measure: Assessing Lifegraph's predictive ability of migraine attacks before subjects report they experience an attack.
time frame: 3 months
description: 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
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: 75 Years
healthy volunteers: No
last name: Ashhar Ali, DO
role: Principal Investigator
affiliation: Senior Staff Physician, Department of Neurology
facility: 
facility: 
country: United States
responsible party type: Sponsor
mesh term: Migraine Disorders
mesh term: Nervous System Diseases
mesh term: Brain Diseases
mesh term: Central Nervous System Diseases
mesh term: Headache Disorders
mesh term: Headache Disorders, Primary
mesh term: Headache
sharing ipd: No