Liang Zhenhu, Wu Shufeng, Yang Chunlin, Jiang Zhenzhou, Yu Tao, Lu Chengbiao, Li Xiaoli
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2016 Feb;33(1):31-7.
The clinical electroencephalogram (EEG) monitoring systems based on personal computer system can not meet the requirements of portability and home usage. The epilepsy patients have to be monitored in hospital for an extended period of time, which imposes a heavy burden on hospitals. In the present study, we designed a portable 16-lead networked monitoring system based on the Android smart phone. The system uses some technologies including the active electrode, the WiFi wireless transmission, the multi-scale permutation entropy (MPE) algorithm, the back-propagation (BP) neural network algorithm, etc. Moreover, the software of Android mobile application can realize the processing and analysis of EEG data, the display of EEG waveform and the alarm of epileptic seizure. The system has been tested on the mobile phones with Android 2. 3 operating system or higher version and the results showed that this software ran accurately and steadily in the detection of epileptic seizure. In conclusion, this paper provides a portable and reliable solution for epileptic seizure monitoring in clinical and home applications.
基于个人计算机系统的临床脑电图（EEG）监测系统无法满足便携性和家庭使用的要求。癫痫患者必须在医院接受长时间监测，这给医院带来了沉重负担。在本研究中，我们设计了一种基于安卓智能手机的便携式16导联联网监测系统。该系统采用了有源电极、WiFi无线传输、多尺度排列熵（MPE）算法、反向传播（BP）神经网络算法等技术。此外，安卓移动应用程序软件可以实现脑电数据的处理与分析、脑电波形显示以及癫痫发作报警。该系统已在安卓2.3操作系统或更高版本的手机上进行测试，结果表明该软件在癫痫发作检测中运行准确、稳定。总之，本文为临床和家庭应用中的癫痫发作监测提供了一种便携式且可靠的解决方案。
