Automated Identification of Psychogenic Nonepileptic Seizures

A retrospective validation study of a post-processing method intended to identify psychogenic nonepileptic seizures

Study Overview

• Status: Unknown
• Conditions: Convulsion, Non-Epileptic
• Intervention / Treatment: Device: Brain Sentinel's sEMG Post-processing algorithm

Detailed Description

This is a validation study of a post-processing method intended to identify psychogenic nonepileptic seizures by analysis of surface electromyographic (sEMG) artifact previously recorded during routine video-electroencephalographic (vEEG) monitoring

• Study Type: Observational
• Enrollment (Actual): 104

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 2 years to 99 years (Child, Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

Subjects previously admitted to the Medical University of South Carolina for inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit with at least one PNES recorded during that admission.

Description

Inclusion Criteria:

A subject will be eligible for inclusion in this study if the following criteria apply.

• Subject was previously admitted to the Medical University of South Carolina for inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit and at least one PNES was recorded during that admission.
• Male or female between the ages of 2-99
• Can understand and sign written informed consent, or will have a parent or a legally authorized representative (LAR) who can do so, prior to the performance of any study assessments

Exclusion Criteria:

• No exclusion criteria have been established for this study.

Study Plan

How is the study designed?

Number of groups / cohorts

3

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Adults (22-99),; Male or female subject between the ages of 22-99, previously admitted to the Medical University of South Carolina for inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit with at least one PNES was recorded during that admission. Validation of Brain Sentinel's sEMG Post-processing algorithm will involve prospective evaluation of at least 30 PNES events in this group.	Device: Brain Sentinel's sEMG Post-processing algorithm; Brain Sentinel has developed a post processing method that identifies sEMG signals (recorded from the biceps brachii or as muscle artifact in electroencephalography [EEG] recordings) that are pathognomonic for PNES activity.
Adolescents (13-21); Male or female subject between the ages of 13-21, previously admitted to the Medical University of South Carolina for inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit with at least one PNES was recorded during that admission. Validation of Brain Sentinel's sEMG Post-processing algorithm will involve prospective evaluation of at least 30 PNES events in this group.	Device: Brain Sentinel's sEMG Post-processing algorithm; Brain Sentinel has developed a post processing method that identifies sEMG signals (recorded from the biceps brachii or as muscle artifact in electroencephalography [EEG] recordings) that are pathognomonic for PNES activity.
Children (2-12); Male or female subject between the ages of 2-12, previously admitted to the Medical University of South Carolina for inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit with at least one PNES was recorded during that admission. Validation of Brain Sentinel's sEMG Post-processing algorithm will involve prospective evaluation of at least 30 PNES events in this group.	Device: Brain Sentinel's sEMG Post-processing algorithm; Brain Sentinel has developed a post processing method that identifies sEMG signals (recorded from the biceps brachii or as muscle artifact in electroencephalography [EEG] recordings) that are pathognomonic for PNES activity.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Time Frame
> 70% sensitivity of a post processing method for classification of psychogenic nonepileptic seizures in sEMG artifact captured during vEEG recordings as compared to vEEG interpretation by a panel of three independent Neurologists.	6 months

Collaborators and Investigators

• Sponsor: Brain Sentinel
• Investigators: Principal Investigator: Jonathan Halford, MD, Medical University of South Carolina

Study record dates

Study Major Dates

• Study Start (Actual): January 1, 2017
• Primary Completion (Actual): May 21, 2019
• Study Completion (Anticipated): August 1, 2020

Study Registration Dates

• First Submitted: January 4, 2017
• First Submitted That Met QC Criteria: January 5, 2017
• First Posted (Estimate): January 6, 2017

Study Record Updates

• Last Update Posted (Actual): December 19, 2019
• Last Update Submitted That Met QC Criteria: December 18, 2019
• Last Verified: December 1, 2019

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Nervous System Diseases; Neurologic Manifestations; Seizures
• Other Study ID Numbers: NES-1.5-09.2016

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO