Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:948-951. doi: 10.1109/EMBC.2016.7590858.
Short-lasting rhythmic activity in intracranial electroencephalogram (iEEG) in the frequency range of 80 to 500 Hz is regarded to be a promising biomarker of epileptogenicity. This activity is referred to as high-frequency oscillation (HFO), and its detection from iEEG is considered the first step to several applications. In this study, several multi-channel algorithms for HFO detection are proposed. With the proposed multi-channel statistics and threshold determination scheme, the algorithms allow HFO detection to be performed without breaking the iEEG channel structure and the detection threshold to be determined automatically. Experimental simulation results illustrate the advantage of the proposed algorithms over existing single-channel-based approaches.
颅内脑电图（iEEG）中频率范围在80至500赫兹的短时程节律性活动被视为癫痫致痫性的一种有前景的生物标志物。这种活动被称为高频振荡（HFO），从iEEG中检测到它被认为是多种应用的第一步。在本研究中，提出了几种用于HFO检测的多通道算法。通过所提出的多通道统计和阈值确定方案，这些算法能够在不破坏iEEG通道结构的情况下进行HFO检测，并能自动确定检测阈值。实验模拟结果说明了所提出算法相对于现有基于单通道的方法的优势。
