Automated Identification of Psychogenic Nonepileptic Seizures

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

Detailed Description
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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

Official Title
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Automated Identification of Psychogenic Nonepileptic Seizures

Conditions
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Convulsion, Non-Epileptic

Intervention / Treatment
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* Device: Brain Sentinel's sEMG Post-processing algorithm


Participation Criteria
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Eligibility Criteria
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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.

Ages Eligible for Study
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Minimum Age: 2 Years
Maximum Age: 99 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Adults (22-99),<br>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<br>* 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.<br>|
| Adolescents (13-21)<br>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<br>* 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.<br>|
| Children (2-12)<br>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<br>* 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.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | 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 |