Detection of Motor Seizures Using WBAN (DMS-WBAN)
Primary Purpose
Seizures, Tonic-Clonic
Status
Completed
Phase
Not Applicable
Locations
Canada
Study Type
Interventional
Intervention
Wearable sensors
Sponsored by
About this trial
This is an interventional diagnostic trial for Seizures, Tonic-Clonic
Eligibility Criteria
Inclusion Criteria:
- subject has seizures or symptoms of seizures
Exclusion Criteria:
Sites / Locations
- Mini Thomas
Arms of the Study
Arm 1
Arm Type
Experimental
Arm Label
Measurement of Motor Movements
Arm 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.
Outcomes
Primary Outcome Measures
Measurement of Acceleration
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
Secondary Outcome Measures
Digital Signal processing of the data
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
Full Information
NCT ID
NCT03283748
First Posted
September 8, 2017
Last Updated
February 23, 2021
Sponsor
Mohawk College
Collaborators
Hamilton Health Sciences Corporation, Toronto Metropolitan University
1. Study Identification
Unique Protocol Identification Number
NCT03283748
Brief Title
Detection of Motor Seizures Using WBAN
Acronym
DMS-WBAN
Official Title
Detection of Motor Seizures Using Wireless Body Area Network
Study Type
Interventional
2. Study Status
Record Verification Date
March 2018
Overall Recruitment Status
Completed
Study Start Date
November 1, 2017 (Actual)
Primary Completion Date
February 25, 2018 (Actual)
Study Completion Date
January 30, 2019 (Actual)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Mohawk College
Collaborators
Hamilton Health Sciences Corporation, Toronto Metropolitan University
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
Yes
5. Study Description
Brief Summary
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.
Detailed Description
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.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Seizures, Tonic-Clonic
7. Study Design
Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
5 (Actual)
8. Arms, Groups, and Interventions
Arm Title
Measurement of Motor Movements
Arm Type
Experimental
Arm 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(s)
Wearable sensors
Intervention Description
Wearable sensors will be given to the participants to be worn and movement data will be collected
Primary Outcome Measure Information:
Title
Measurement of Acceleration
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
Time Frame
3 months
Secondary Outcome Measure Information:
Title
Digital Signal processing of the data
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
Time Frame
3 months
10. Eligibility
Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
Accepts Healthy Volunteers
Eligibility Criteria
Inclusion Criteria:
subject has seizures or symptoms of seizures
Exclusion Criteria:
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Mini Thomas, M.Eng.
Organizational Affiliation
Mohawk College
Official's Role
Principal Investigator
Facility Information:
Facility Name
Mini Thomas
City
Hamilton
State/Province
Ontario
ZIP/Postal Code
L9C 0E5
Country
Canada
12. IPD Sharing Statement
Plan to Share IPD
Undecided
Links:
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
Learn more about this trial
Detection of Motor Seizures Using WBAN
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