標題: A hierarchical approach for online temporal lobe seizure detection in long-term intracranial EEG recordings
作者: Liang, Sheng-Fu
Chen, Yi-Chun
Wang, Yu-Lin
Chen, Pin-Tzu
Yang, Chia-Hsiang
Chiueh, Herming
電子工程學系及電子研究所
生醫電子轉譯研究中心
Department of Electronics Engineering and Institute of Electronics
Biomedical Electronics Translational Research Center
公開日期: 1-Aug-2013
摘要: Objective. Around 1% of the world's population is affected by epilepsy, and nearly 25% of patients cannot be treated effectively by available therapies. The presence of closed-loop seizure-triggered stimulation provides a promising solution for these patients. Realization of fast, accurate, and energy-efficient seizure detection is the key to such implants. In this study, we propose a two-stage on-line seizure detection algorithm with low-energy consumption for temporal lobe epilepsy (TLE). Approach. Multi-channel signals are processed through independent component analysis and the most representative independent component (IC) is automatically selected to eliminate artifacts. Seizure-like intracranial electroencephalogram (iEEG) segments are fast detected in the first stage of the proposed method and these seizures are confirmed in the second stage. The conditional activation of the second-stage signal processing reduces the computational effort, and hence energy, since most of the non-seizure events are filtered out in the first stage. Main results. Long-term iEEG recordings of 11 patients who suffered from TLE were analyzed via leave-one-out cross validation. The proposed method has a detection accuracy of 95.24%, a false alarm rate of 0.09/h, and an average detection delay time of 9.2 s. For the six patients with mesial TLE, a detection accuracy of 100.0%, a false alarm rate of 0.06/h, and an average detection delay time of 4.8 s can be achieved. The hierarchical approach provides a 90% energy reduction, yielding effective and energy-efficient implementation for real-time epileptic seizure detection. Significance. An on-line seizure detection method that can be applied to monitor continuous iEEG signals of patients who suffered from TLE was developed. An IC selection strategy to automatically determine the most seizure-related IC for seizure detection was also proposed. The system has advantages of (1) high detection accuracy, (2) low false alarm, (3) short detection latency, and (4) energy-efficient design for hardware implementation.
URI: http://dx.doi.org/10.1088/1741-2560/10/4/045004
http://hdl.handle.net/11536/22582
ISSN: 1741-2560
DOI: 10.1088/1741-2560/10/4/045004
期刊: JOURNAL OF NEURAL ENGINEERING
Volume: 10
Issue: 4
結束頁: 
Appears in Collections:Articles


Files in This Item:

  1. 000322221600006.pdf