Topological properties of flat electroencephalography's state space

T. Ken, T. Ahmad, Mohd Sham bin Mohd, S. K. Ngien, T. Suwa, Ong Sie Meng
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引用次数: 0

Abstract

Neuroinverse problem are often associated with complex neuronal activity. It involves locating problematic cell which is highly challenging. While epileptic foci localization is possible with the aid of EEG signals, it relies greatly on the ability to extract hidden information or pattern within EEG signals. Flat EEG being an enhancement of EEG is a way of viewing electroencephalograph on the real plane. In the perspective of dynamical systems, Flat EEG is equivalent to epileptic seizure hence, making it a great platform to study epileptic seizure. Throughout the years, various mathematical tools have been applied on Flat EEG to extract hidden information that is hardly noticeable by traditional visual inspection. While these tools have given worthy results, the journey towards understanding seizure process completely is yet to be succeeded. Since the underlying structure of Flat EEG is dynamic and is deemed to contain wealthy information regarding brainstorm, it would certainly be appealing to explore in depth its structures. To better understand the complex seizure process, this paper studies the event of epileptic seizure via Flat EEG in a more general framework by means of topology, particularly, on the state space where the event of Flat EEG lies.
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平面脑电图状态空间的拓扑性质
神经逆问题常与复杂的神经元活动有关。它涉及到定位有问题的细胞,这是非常具有挑战性的。虽然借助脑电图信号可以实现癫痫病灶定位,但这在很大程度上依赖于提取脑电图信号中隐藏信息或模式的能力。平面脑电图是对脑电图的一种增强,是一种在真实平面上观察脑电图的方法。从动力系统的角度来看,Flat EEG相当于癫痫发作,是研究癫痫发作的一个很好的平台。多年来,各种数学工具被应用到平面脑电图中,以提取传统视觉检测难以发现的隐藏信息。虽然这些工具已经给出了有价值的结果,但完全理解癫痫发作过程的旅程尚未取得成功。由于平面脑电图的底层结构是动态的,并且被认为包含了丰富的头脑风暴信息,因此对其结构进行深入的探索肯定是有吸引力的。为了更好地理解复杂的癫痫发作过程,本文采用拓扑学的方法,在更一般的框架下研究了平面脑电图的癫痫发作事件,特别是对平面脑电图事件所在的状态空间进行了研究。
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来源期刊
Mathematics in Engineering, Science and Aerospace
Mathematics in Engineering, Science and Aerospace Mathematics-Applied Mathematics
CiteScore
1.70
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0.00%
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0
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