Time-frequency mapping of the rhythmic limb movements distinguishes convulsive epileptic from psychogenic nonepileptic seizures
| Autor: | Jade Bayly, Anita Vinton, Bernard Yan, Jayavardhana Gubbi, Dilini A. Fernando, Terence J. O'Brien, Michelle Smit, Marimuthu Palaniswami, Slavé Petrovski, John Carino |
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| Rok vydání: | 2013 |
| Předmět: |
Adult
Male medicine.medical_specialty Periodicity Time Factors Movement Electroencephalography Audiology Brain mapping Epilepsy Young Adult Rhythm medicine Psychogenic disease Humans Cutoff score Conversion disorder Aged Retrospective Studies Aged 80 and over Brain Mapping medicine.diagnostic_test Extremities Middle Aged medicine.disease Psychophysiologic Disorders Neurology Conversion Disorder Anesthesia Kinetocardiography Female Neurology (clinical) Epileptic seizure medicine.symptom Psychology |
| Zdroj: | Epilepsia. 54(8) |
| ISSN: | 1528-1167 |
| Popis: | Purpose: A definite diagnosis of psychogenic nonepilepticseizures(PNES)usuallyrequiresin-patientvideo–electro-encephalography (EEG) monitoring. Previous researchhas shown that convulsive psychogenic nonepileptic sei-zures (PNES) demonstrate a characteristic pattern ofrhythmic movement artifact on the EEG. Herein wesought to examine the potential for time-frequency map-ping of data from a movement-recording device (acceler-ometer) worn on the wrist as a diagnostic tool todifferentiate between convulsive epileptic seizures andPNES.Methods: Time-frequency mapping was performed onaccelerometer traces obtained during 56 convulsiveseizure-like events from 35 patients recorded duringin-patient video-EEG monitoring. Twenty-six patientshad PNES, eight had epileptic seizures, and one had bothseizure types. The time-frequency maps were derivedfromfastFouriertransformationstodeterminethedomi-nant frequency for sequential 2.56-s blocks for the courseofeachevent.Key Findings: The coefficient of variation (CoV) of limbmovement frequency for the PNES events was less thanfor the epileptic seizure events (median, 17.18% vs.52.23%; p < 0.001). A blinded review of the time-fre-quencymapsbyanepileptologistwasaccurateindifferen-tiating between the event types, that is, 38 (92.7%) of 41and 6 (75%) of 8 nonepileptic and epileptic seizures,respectively, were diagnosed correctly, with seven eventsclassified as “nondiagnostic.” Using a CoV cutoff score of32% resulted in similar classification accuracy, with 42(93%) of 45 PNES and 10 (91%) of 11 epileptic seizureeventscorrectlydiagnosed.Significance: Time-frequency analysis of data from awristband movement monitor could be utilized as a diag-nostic tool to differentiate between epileptic and nonepi-lepticconvulsiveseizure-likeevents.KEY WORDS: Psychogenic nonepileptic seizures, Epilep-ticseizures,Time-frequencymapping,Limbmovements. |
| Databáze: | OpenAIRE |
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