[3I4-OS-5b] 生体信号を活用した医療・ヘルスケアAI(2/2)

[3I4-OS-5b-03] Phasing of epileptic seizure spreading and extending using hidden Markov model

〇Shuji Komeiji¹, Toshiki Orihara¹, Takumi Mitsuhashi², Hidenori Sugano², Toshihisa Tanaka¹ (1. Tokyo University of Agriculture and Technology, 2. Juntendo University)

Keywords:epileptic seizure, Hidden Markov Model

This paper argues the phasing of epileptic seizure spreading and extending using the hidden Markov model (HMM).
The intracranial electroencephalography during an epileptic seizure is thought to have several phases with time transitions.
In this paper, we identified clinically interpretable phases in all 30 cases of epileptic seizures by unsupervised learning of HMM.
Data-driven discovery of phases may contribute to understanding the mechanisms of epileptic seizure onset to settle and lead to new treatments.