<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/NCT03283748</url>
  </required_header>
  <id_info>
    <org_study_id>3596</org_study_id>
    <nct_id>NCT03283748</nct_id>
  </id_info>
  <brief_title>Detection of Motor Seizures Using WBAN</brief_title>
  <acronym>DMS-WBAN</acronym>
  <official_title>Detection of Motor Seizures Using Wireless Body Area Network</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Mohawk College</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Hamilton Health Sciences Corporation</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Toronto Metropolitan University</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Mohawk College</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
    <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 aims to collect the motor movement data using sensors to detect Generalized Tonic&#xD;
      Clonic Seizures . Wearable sensors similar to smart watches will be used to detect seizures.&#xD;
      The proposed system will consist of 3-4 wearable wireless sensor worn on the hands and legs.&#xD;
      The data from these sensors will be send to the clod and collected to a central hub for&#xD;
      analysis and detection of GTC Seizures.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The key of the project is digital signal processing of the movement data collected. The&#xD;
      medical application sensors from Analog Devices will be worn around the wrist and legs of the&#xD;
      participants. These sensors will continuously collect the motor movement data. The data will&#xD;
      be send to the cloud from where it will be collected at a central hub for digital signal&#xD;
      processing and detection. The data analysis results will be compared with the standard EEG&#xD;
      results for Tonic Clonic seizures and results will be verified.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">November 1, 2017</start_date>
  <completion_date type="Actual">January 30, 2019</completion_date>
  <primary_completion_date type="Actual">February 25, 2018</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>N/A</allocation>
    <intervention_model>Single Group Assignment</intervention_model>
    <primary_purpose>Diagnostic</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Measurement of Acceleration</measure>
    <time_frame>3 months</time_frame>
    <description>Motor movements will cause changes in acceleration. Accelerometer sensors will be used to measure the acceleration as a first step towards detection of Tonic Clonic Seizures</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Digital Signal processing of the data</measure>
    <time_frame>3 months</time_frame>
    <description>The raw acceleration data collected will be processed in a computer with MATLAB software using Digital Signal processing techniques. These techniques will help identify the data and differentiate the seizure movements from normal movements thereby helping to detect seizures data</description>
  </secondary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">5</enrollment>
  <condition>Seizures, Tonic-Clonic</condition>
  <arm_group>
    <arm_group_label>Measurement of Motor Movements</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Wearable Accelerometer Sensors manufactured by leading manufacturers will be given to the participants to be worn around hands and legs. These sensors will be used to measure accelerations which will be impacted by the motor movements.</description>
  </arm_group>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>Wearable sensors</intervention_name>
    <description>Wearable sensors will be given to the participants to be worn and movement data will be collected</description>
    <arm_group_label>Measurement of Motor Movements</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  subject has seizures or symptoms of seizures&#xD;
&#xD;
        Exclusion Criteria:&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Mini Thomas, M.Eng.</last_name>
    <role>Principal Investigator</role>
    <affiliation>Mohawk College</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Mini Thomas</name>
      <address>
        <city>Hamilton</city>
        <state>Ontario</state>
        <zip>L9C 0E5</zip>
        <country>Canada</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Canada</country>
  </location_countries>
  <link>
    <url>https://www.ncbi.nlm.nih.gov/pubmed/26926071</url>
    <description>Non-EEG based ambulatory seizure detection designed for home use: What is available and how will it influence epilepsy care?</description>
  </link>
  <link>
    <url>https://www.ncbi.nlm.nih.gov/pubmed/26190150</url>
    <description>Electromyography-based seizure detector: Preliminary results comparing a generalized tonic-clonic seizure detection algorithm to video-EEG recordings</description>
  </link>
  <link>
    <url>https://www.ncbi.nlm.nih.gov/pubmed/26859097</url>
    <description>Safe and sound? A systematic literature review of seizure detection methods for personal useSafe and sound? A systematic literature review of seizure detection methods for personal use</description>
  </link>
  <verification_date>March 2018</verification_date>
  <study_first_submitted>September 8, 2017</study_first_submitted>
  <study_first_submitted_qc>September 13, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">September 14, 2017</study_first_posted>
  <last_update_submitted>February 23, 2021</last_update_submitted>
  <last_update_submitted_qc>February 23, 2021</last_update_submitted_qc>
  <last_update_posted type="Actual">February 24, 2021</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Seizures</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Undecided</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/NCT03283748
org study id: 3596
nct id: NCT03283748
lead sponsor: 
collaborator: 
collaborator: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
This study aims to collect the motor movement data using sensors to detect Generalized Tonic
      Clonic Seizures . Wearable sensors similar to smart watches will be used to detect seizures.
      The proposed system will consist of 3-4 wearable wireless sensor worn on the hands and legs.
      The data from these sensors will be send to the clod and collected to a central hub for
      analysis and detection of GTC Seizures.
The key of the project is digital signal processing of the movement data collected. The
      medical application sensors from Analog Devices will be worn around the wrist and legs of the
      participants. These sensors will continuously collect the motor movement data. The data will
      be send to the cloud from where it will be collected at a central hub for digital signal
      processing and detection. The data analysis results will be compared with the standard EEG
      results for Tonic Clonic seizures and results will be verified.
allocation: N/A
intervention model: Single Group Assignment
primary purpose: Diagnostic
masking: None (Open Label)
measure: Measurement of Acceleration
time frame: 3 months
description: Motor movements will cause changes in acceleration. Accelerometer sensors will be used to measure the acceleration as a first step towards detection of Tonic Clonic Seizures
measure: Digital Signal processing of the data
time frame: 3 months
description: The raw acceleration data collected will be processed in a computer with MATLAB software using Digital Signal processing techniques. These techniques will help identify the data and differentiate the seizure movements from normal movements thereby helping to detect seizures data
arm group label: Measurement of Motor Movements
arm group type: Experimental
description: Wearable Accelerometer Sensors manufactured by leading manufacturers will be given to the participants to be worn around hands and legs. These sensors will be used to measure accelerations which will be impacted by the motor movements.
intervention type: Device
intervention name: Wearable sensors
description: Wearable sensors will be given to the participants to be worn and movement data will be collected
arm group label: Measurement of Motor Movements
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
last name: Mini Thomas, M.Eng.
role: Principal Investigator
affiliation: Mohawk College
facility: 
country: Canada
url: https://www.ncbi.nlm.nih.gov/pubmed/26926071
description: Non-EEG based ambulatory seizure detection designed for home use: What is available and how will it influence epilepsy care?
url: https://www.ncbi.nlm.nih.gov/pubmed/26190150
description: Electromyography-based seizure detector: Preliminary results comparing a generalized tonic-clonic seizure detection algorithm to video-EEG recordings
url: https://www.ncbi.nlm.nih.gov/pubmed/26859097
description: Safe and sound? A systematic literature review of seizure detection methods for personal useSafe and sound? A systematic literature review of seizure detection methods for personal use
responsible party type: Sponsor
mesh term: Seizures
sharing ipd: Undecided