Automated differentiation between epileptic and nonepileptic convulsive seizures

Sándor Beniczky, Isa Conradsen, Mihai Moldovan, Poul Jennum, Martin Fabricius, Krisztina Benedek, Noémi Andersen, Helle Hjalgrim, Peter Wolf

34 Citationer (Scopus)


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.

TidsskriftAnnals of Neurology
Udgave nummer2
Sider (fra-til)348-51
Antal sider4
StatusUdgivet - feb. 2015


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