An EEG Signal Recognition Algorithm During Epileptic Seizure Based on Distributed Edge Computing

被引:3
|
作者
Qiu, Shi [1 ]
Cheng, Keyang [2 ]
Zhou, Tao [3 ]
Tahir, Rabia [2 ]
Ting, Liang [4 ]
机构
[1] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Key Lab Spectral Imaging Technol CAS, Xian 710119, Peoples R China
[2] Jiangsu Univ, Sch Comp Sci & Commun Engn, Zhenjiang 212000, Jiangsu, Peoples R China
[3] North Minzu Univ, Sch Comp Sci & Engn, Yinchuan 750021, Ningxia, Peoples R China
[4] Xi An Jiao Tong Univ, Affiliated Hosp 1, Dept Radiol, Xian 71006, Peoples R China
来源
INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE | 2022年 / 7卷 / 05期
基金
美国国家科学基金会;
关键词
Clinical Feature; Cloud Computing; Deep Learning; Edge Computing; EEG Signal; Epilepsy; Seizure; Takagi-Sugeno-Kang (TSK); NEURAL-NETWORK; TEMPORAL-LOBE; CLASSIFICATION; MEMORY;
D O I
10.9781/ijimai.2022.07.001
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Epilepsy is one kind of brain diseases, and its sudden unpredictability is the main cause of disability and even death. Thus, it is of great significance to identify electroencephalogram (EEG) during the seizure quickly and accurately. With the rise of cloud computing and edge computing, the interface between local detection and cloud recognition is established, which promotes the development of portable EEG detection and diagnosis. Thus, we construct a framework for identifying EEG signals in epileptic seizure based on cloud-edge computing. The EEG signals are obtained in real time locally, and the horizontal viewable model is established at the edge to enhance the internal correlation of the signals. The Takagi-Sugeno-Kang (FSK) fuzzy system is established to analyze the epileptic signals. In the cloud, the fusion of clinical features and signal features is established to establish a deep learning framework. Through local signal acquisition, edge signal processing and cloud signal recognition, the diagnosis of epilepsy is realized, which can provide a new idea for the real-time diagnosis and feedback of EEG during epileptic seizure.
引用
收藏
页码:6 / 13
页数:8
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