Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
15 participants
INTERVENTIONAL
2020-03-31
2020-12-31
Brief Summary
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Detailed Description
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Currently, accurate seizure detection relies on EEG and video which are limited by time, size and mobility. Seizure detection can also use biomarkers such as movement patterns described by gyroscopes. These devices can monitor patterns of movement which correspond to the activity during seizures and kept in a log of seizures without patient input. The log can be used to notify patients or caregivers of seizures.
This study is to determine the accuracy of a system using a commercial, wearable device linked to a computer algorithm based in the cloud which stores the movement pattern and notifies the patient and others of a generalized major motor seizure. The accuracy will be determined by a comparison of the system detections to simultaneously recorded video electroencephalogram, considered the "gold standard" of seizure detection.
Conditions
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Study Design
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NA
SINGLE_GROUP
OTHER
NONE
Study Groups
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Single Arm
This is a single-arm study. All subjects enrolled in the study will wear the device during stay in the EMU.
Motor Seizure Detection Algorithm (mSDA)
A seizure detection algorithm installed on a propriety mobile application to be used on a commercially available watch with a gyroscope to detect movement.
Interventions
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Motor Seizure Detection Algorithm (mSDA)
A seizure detection algorithm installed on a propriety mobile application to be used on a commercially available watch with a gyroscope to detect movement.
Eligibility Criteria
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Inclusion Criteria
2. Stated willingness to comply with all study procedures and availability for the duration of the study.
3. Meets the standard of care criteria for admission to an epilepsy monitoring unit (EMU).
4. Male or female.
5. Aged 18 and above.
6. The patient has experienced at least one generalized major motor seizure prior to admission.
7. Agreement to wear a wristwatch throughout the duration of the study on the left wrist.
8. Ability to cancel false positive alarms via interaction with the application on the watch.
Exclusion Criteria
2. Known allergic reactions to components of the (watch materials).
3. Treatment with another investigational drug or other intervention within the study
4. Children under the age of 18.
5. Women who are pregnant or nursing.
6. Inability to give consent to the study.
7. Active skin infection or rash on the upper extremities
18 Years
ALL
No
Sponsors
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Bracane Company
INDUSTRY
Overwatch Digital Health
INDUSTRY
Responsible Party
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Principal Investigators
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Haytham Elgammal, MD
Role: PRINCIPAL_INVESTIGATOR
Overwatch Digital Health
Subha Sarcar, PhD
Role: STUDY_DIRECTOR
Bracane Company
Locations
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Covenant Hospital and Covenant Medical Group
Lubbock, Texas, United States
Countries
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Central Contacts
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References
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Fisher RS, Cross JH, French JA, Higurashi N, Hirsch E, Jansen FE, Lagae L, Moshe SL, Peltola J, Roulet Perez E, Scheffer IE, Zuberi SM. Operational classification of seizure types by the International League Against Epilepsy: Position Paper of the ILAE Commission for Classification and Terminology. Epilepsia. 2017 Apr;58(4):522-530. doi: 10.1111/epi.13670. Epub 2017 Mar 8.
Proposal for revised clinical and electroencephalographic classification of epileptic seizures. From the Commission on Classification and Terminology of the International League Against Epilepsy. Epilepsia. 1981 Aug;22(4):489-501. doi: 10.1111/j.1528-1157.1981.tb06159.x. No abstract available.
Kramer U, Kipervasser S, Shlitner A, Kuzniecky R. A novel portable seizure detection alarm system: preliminary results. J Clin Neurophysiol. 2011 Feb;28(1):36-8. doi: 10.1097/WNP.0b013e3182051320.
Janse SA, Dumanis SB, Huwig T, Hyman S, Fureman BE, Bridges JFP. Patient and caregiver preferences for the potential benefits and risks of a seizure forecasting device: A best-worst scaling. Epilepsy Behav. 2019 Jul;96:183-191. doi: 10.1016/j.yebeh.2019.04.018. Epub 2019 May 29.
Jalloul N. Wearable sensors for the monitoring of movement disorders. Biomed J. 2018 Aug;41(4):249-253. doi: 10.1016/j.bj.2018.06.003. Epub 2018 Sep 11.
Muennig PA, Glied SA. What changes in survival rates tell us about us health care. Health Aff (Millwood). 2010 Nov;29(11):2105-13. doi: 10.1377/hlthaff.2010.0073. Epub 2010 Oct 7.
Johansson D, Malmgren K, Alt Murphy M. Wearable sensors for clinical applications in epilepsy, Parkinson's disease, and stroke: a mixed-methods systematic review. J Neurol. 2018 Aug;265(8):1740-1752. doi: 10.1007/s00415-018-8786-y. Epub 2018 Feb 9.
Nijsen TM, Arends JB, Griep PA, Cluitmans PJ. The potential value of three-dimensional accelerometry for detection of motor seizures in severe epilepsy. Epilepsy Behav. 2005 Aug;7(1):74-84. doi: 10.1016/j.yebeh.2005.04.011.
Horne MK, McGregor S, Bergquist F. An objective fluctuation score for Parkinson's disease. PLoS One. 2015 Apr 30;10(4):e0124522. doi: 10.1371/journal.pone.0124522. eCollection 2015.
Beniczky S, Polster T, Kjaer TW, Hjalgrim H. Detection of generalized tonic-clonic seizures by a wireless wrist accelerometer: a prospective, multicenter study. Epilepsia. 2013 Apr;54(4):e58-61. doi: 10.1111/epi.12120. Epub 2013 Feb 8.
Other Identifiers
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OW012019
Identifier Type: -
Identifier Source: org_study_id
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