人脑电信号实时监测原型系统设计与实现

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英文篇名：EEG Signals Real-Time Monitoring Prototype Design and Implementation 作者：苗立志 ; 徐韬 ; 郭静 ; 焦东来 英文作者：MIAO Lizhi;XU Tao;GUO Jing;JIAO Donglai;College of Geographical and Biological Information, Nanjing University of Posts and Telecommunications;Jiangsu Engineering Laboratory for Smart Analysis of Healthy Big Data and Location Based Services, Nanjing University of Posts and Telecommunications;Engineering Research Center of Ubiquitous Network Health Service System of Ministry of Education, Nanjing University of Posts and Telecommunications;College of Telecommunications & Information Engineering, Nanjing University of Posts and Telecommunications; 关键词：脑电信号 ; 实时监测 ; 位置服务 ; 智慧健康 ; 移动医疗 英文关键词：Electroencephalograph(EEG);;real-time monitoring;;Location-Based Service(LBS);;smart healthcare;;mobile telemedicine 中文刊名：JSGG 英文刊名：Computer Engineering and Applications 机构：南京邮电大学地理与生物信息学院;南京邮电大学江苏省智慧健康大数据分析与位置服务工程实验室;南京邮电大学泛在网络健康服务系统教育部工程研究中心;南京邮电大学通信与信息工程学院; 出版日期：2018-05-19 17:34 出版单位：计算机工程与应用 年：2019 期：v.55;No.921 基金：国家自然科学基金(No.41471329);; 南京邮电大学自制实验仪器设备(No.2016XZZ03) 语种：中文; 页：JSGG201902037 页数：5 CN：02 分类号：242-245+258

摘要

针对脑部病患突发状况时不能够在最短的时间内预警并发现和监测效率不高的问题,设计了一种基于无线通信技术和LBS的脑电信号实时监测方法,实现对脑电监测仪携带者的位置和脑电信号的实时监测。将GIS技术、无线传输技术、智能移动终端与现有的信息管理平台相融合,提出了人脑脑电信号实时动态监测框架体系结构,并设计开发了原型系统。该系统可将采集到的脑电数据实时显示并传送到服务器端,实现在服务器端的实时监控与动态分析,并对发生异常的情况做出应急响应,为应急救援提供帮助。
        Towards the problems that sudden brain disease cannot be warned and detected without delay in the shortest time, and inefficient monitoring in the emergency situation, a real-time monitoring method is proposed to collect Electroencephalograph(EEG)brain signals based on wireless communication technology and Location-Based Service(LBS),which can monitor the users' position and EEG in real time. The system architecture for monitoring human brain EEG dynamically is generated through integrating GIS, wireless transmission technologies, smart mobile terminals and legacy information management platforms. Furthermore, a prototype system is developed and implemented based on the above architecture. This system can display the collected EEG data and send them to the server, which will analyze dynamically to identify whether the user is normal or not. In case abnormal situation occurs, the system will alert to suggest an optimal rescue solution.

引文

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