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Automated Identification of Psychogenic Nonepileptic Seizures

NCT03013348 — Unknown, 104 participants, Brain Sentinel
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RegistryNCT03013348
StatusUnknown
Study typeObservational
Enrollment104 (Actual)
SponsorBrain Sentinel (Other)
ConditionsConvulsion, Non-Epileptic
InterventionsBrain Sentinel's sEMG Post-processing algorithm (Device)
Datesstart 2017-01-01, primary completion 2019-05-21, completion 2020-08-01 (estimated), first posted 2017-01-06, last updated 2019-12-19

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-Summary

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

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+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

+Arms and interventions

ArmTypeInterventionsDescription
Adults (22-99),Device: Brain Sentinel's sEMG Post-processing algorithmMale 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.
Adolescents (13-21)Device: Brain Sentinel's sEMG Post-processing algorithmMale 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.
Children (2-12)Device: Brain Sentinel's sEMG Post-processing algorithmMale 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.
  • Brain Sentinel's sEMG Post-processing algorithm (Device): 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.

+Outcome measures

Primary outcomes

  • > 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]

+Eligibility

Sex: All, ages: 2 Years to 99 Years

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.

+Investigators

My Notes