Study to Validate Novel Seizure-Detection Algorithm

Epilepsy Clinical Trial

Official title:

Validation of an Algorithm for Identification and Notification of Generalized Major Motor Seizures

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT04291716
• Other study ID #: OW012019
• Status: Not yet recruiting
• Phase: N/A
• Start date: March 2020
• Est. completion date: December 2020

Study information

• Verified date: February 2020
• Source: Overwatch Digital Health
• Contact: Chis Czura, PhD
• Phone: 214-662-7322
• Email: chris.czura[@]overwatchdh.com
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

The specificity and sensitivity of a novel seizure-detection mobile software application with a generalized tonic/clonic seizure detection algorithm (Motor Seizure Detection Algorithm [mSDA]) installed on a wearable device to be worn by the subject. The software will be tested using subjects from a patient population in an epilepsy monitoring unit (EMU) undergoing video and electroencephalograph (VEEG) observation. The number of generalized major motor seizures detected by the mSDA will be compared with those detected by VEEG.

Description:

Seizures are paroxysmal, abnormal behaviors which usually are associated with altered awareness and amnesia. The frequency of seizures is not easily documented. The individual who suffers from seizures may be unaware that a seizure is occurring. Many seizures, including generalized major motor seizures, have stereotyped, vigorous motor activity associated with the events.

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.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 15
• Est. completion date: December 2020
• Est. primary completion date: October 2020
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

1. Provision of signed and dated informed consent form.

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:

1. Concurrent physiological diseases with movement disorders (Parkinson's, tremor, ataxia, Huntington's, paralysis of the upper body, pseudo-seizures).

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

Related Conditions & MeSH terms

• Epilepsy
• Epileptic
• Epileptic Seizures
• Seizure Disorder
• Seizures
• Seizures, Motor

Intervention

Device:
• 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.

Locations

Country	Name	City	State
United States	Covenant Hospital and Covenant Medical Group	Lubbock	Texas

Sponsors (2)

Lead Sponsor	Collaborator
Overwatch Digital Health	Bracane Company

Country where clinical trial is conducted

United States, 

References & Publications (10)

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. — View Citation

Fisher RS, Cross JH, French JA, Higurashi N, Hirsch E, Jansen FE, Lagae L, Moshé 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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. Review. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Sensitivity	Number of major motor seizure detections by algorithm with detection by video encephalogram data.	1 to 5 days
Secondary	False positive rate	Total number of false positives and number of false positives per day.	1 to 5 days
Secondary	Mean detection latency	Time between algorithm detection and application notification	1 to 5 days
Secondary	Notifications	Total number of seizure notifications received on subject's assigned email	1 to 5 days
Secondary	Cancellations	Total number of cancellations of false positive alerts made by the subject.	1 to 5 days

External Links

•   Sponsor website