뇌전증 경련 억제를 위한 실시간 폐루프 신경 자극 시스템 설계 (Development of Real-time Closed-loop Neurostimulation System for Epileptic Seizure Suppression)

서지정보

· 발행기관 : 대한의용생체공학회
· 수록지 정보 : 의공학회지 / 36권 / 4호 / 95 ~ 102페이지
· 저자명 : 김소원, 김선희, 이예나, 황서영, 강태경, 전상범, 이향운, 이승준

초록

Epilepsy is a chronic neurological disease which produces repeated seizures. Over 30% of epileptic patients cannot be treated with anti-epileptic drugs, and surgical resection may cause loss of brain functions. Seizure suppression by electrical stimulation is currently being investigated as a new treatment method as clinical evidence has shown that electrical stimulation to brain could suppress seizure activity. In this paper, design of a real-time closed-loop neurostimulation system for epileptic seizure suppression is presented. The system records neural signals, detects seizures and delivers electrical stimulation. The system consists of a 6-channel electrode, front-end amplifiers, a data acquisition board by National Instruments, and a neurostimulator and Generic Osorio-Frei algorithm was applied for seizure detection. The algorithm was verified through simulation using electroencephalogram data, and the operation of whole system was verified through simulation and in- vivo test.

영어초록

Epilepsy is a chronic neurological disease which produces repeated seizures. Over 30% of epileptic patients cannot be treated with anti-epileptic drugs, and surgical resection may cause loss of brain functions. Seizure suppression by electrical stimulation is currently being investigated as a new treatment method as clinical evidence has shown that electrical stimulation to brain could suppress seizure activity. In this paper, design of a real-time closed-loop neurostimulation system for epileptic seizure suppression is presented. The system records neural signals, detects seizures and delivers electrical stimulation. The system consists of a 6-channel electrode, front-end amplifiers, a data acquisition board by National Instruments, and a neurostimulator and Generic Osorio-Frei algorithm was applied for seizure detection. The algorithm was verified through simulation using electroencephalogram data, and the operation of whole system was verified through simulation and in- vivo test.

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