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A retrospective validation study of a post-processing method intended to identify psychogenic nonepileptic seizures
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
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| 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. |
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| 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. |
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| 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. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| 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. |
| 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 |
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Inclusion Criteria:
A subject will be eligible for inclusion in this study if the following criteria apply.
Exclusion Criteria:
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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.
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| Name | Affiliation | Role |
|---|---|---|
| Jonathan Halford, MD | Medical University of South Carolina | Principal Investigator |
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| ID | Term |
|---|---|
| D012640 | Seizures |
| ID | Term |
|---|---|
| D009461 | Neurologic Manifestations |
| D009422 | Nervous System Diseases |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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