Journal
ANNALS OF NEUROLOGY
Volume 77, Issue 2, Pages 348-351Publisher
WILEY-BLACKWELL
DOI: 10.1002/ana.24338
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Funding
- Peter and Jytte Wolf Foundation for Epilepsy [07/002F]
- Danish National Advanced Technology Foundation
- Romanian National Authority for Scientific Research
- CNCS-UEFISCDI [PN-II-ID-PCE-2011-3-0847, PN-II-PT-PCCA-2011-3.2-1290]
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Our objective was the clinical validation of an automated algorithm based on surface electromyography (EMG) for differentiation between convulsive epileptic and psychogenic nonepileptic seizures (PNESs). Forty-four consecutive episodes with convulsive events were automatically analyzed with the algorithm: 25 generalized tonic-clonic seizures (GTCSs) from 11 patients, and 19 episodes of convulsive PNES from 13 patients. The gold standard was the interpretation of the video-electroencephalographic recordings by experts blinded to the EMG results. The algorithm correctly classified 24 GTCSs (96%) and 18 PNESs (95%). The overall diagnostic accuracy was 95%. This algorithm is useful for distinguishing between epileptic and psychogenic convulsive seizures. Ann Neurol 2015;77:348-351.
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