Paul Yash
School of Informatics, Eötvös Loránd University, Budapest, Hungary.
Brain Inform. 2018 Jul 10;5(2):6. doi: 10.1186/s40708-018-0084-z.
Epilepsy is a chronic chaos of the central nervous system that influences individual's daily life by putting it at risk due to repeated seizures. Epilepsy affects more than 2% people worldwide of which developing countries are affected worse. A seizure is a transient irregularity in the brain's electrical activity that produces disturbing physical symptoms such as a lapse in attention and memory, a sensory illusion, etc. Approximately one out of every three patients have frequent seizures, despite treatment with multiple anti-epileptic drugs. According to a survey, population aged 65 or above in European Union is predicted to rise from 16.4% (2004) to 29.9% (2050) and also this tremendous increase in aged population is also predicted for other countries by 2050. In this paper, seizure detection techniques are classified as time, frequency, wavelet (time-frequency), empirical mode decomposition and rational function techniques. The aim of this review paper is to present state-of-the-art methods and ideas that will lead to valid future research direction in the field of seizure detection.
癫痫是一种慢性中枢神经系统紊乱疾病，由于反复发作的癫痫发作使其处于危险之中，从而影响个人的日常生活。癫痫影响着全球超过2%的人口，其中发展中国家受影响更为严重。癫痫发作是大脑电活动的一种短暂异常，会产生令人不安的身体症状，如注意力和记忆力减退、感觉错觉等。尽管使用了多种抗癫痫药物进行治疗，但大约每三名患者中就有一人频繁发作。一项调查显示，预计欧盟65岁及以上的人口比例将从2004年的16.4%升至2050年的29.9%，到2050年其他国家的老年人口也预计会有大幅增长。在本文中，癫痫发作检测技术被分为时域、频域、小波（时频）、经验模态分解和有理函数技术。这篇综述文章的目的是介绍当前的先进方法和理念，这些方法和理念将为癫痫发作检测领域带来有效的未来研究方向。
