可穿戴脑电图设备关键技术及其应用综述

可穿戴脑电图（EEG）设备是一种用于日常实时监测的无线EGG系统，因其便携性、实时性、无创性及低成本等优势迅速发展并得到广泛应用。该系统主要由信号采集模块、信号处理模块、微控制模块、通信模块及电源模块等硬件部分以及移动终端模块和云存储模块等软件部分组成。就可穿戴EEG设备关键技术进行论述。首先，阐述了对EGG信号采集模块的改进，另外对可穿戴EEG设备信号预处理模块、信号的降噪、伪影处理及特征提取技术进行比较；然后，对机器学习、深度学习分类算法的优缺点进行分析，并对穿戴式EEG设备的应用领域进行总结；最后，提出可穿戴EEG设备的关键技术未来的发展趋势。

Review of key technology and application of wearable electroencephalogram device

Wearable ElectroEncephaloGram （EEG） device is a wireless EEG system to daily real-time monitoring. It is developed rapidly and widely applied because of its portability， real-time performance， non-invasiveness， and low-cost advantages. This system is mainly composed of hardware parts such as signal acquisition module， signal processing module， micro-control module， communication module and power supply module， and software parts such as mobile terminal module and cloud storage module. The key technologies of wearable EEG devices were discussed. First， the improvement of EEG signal acquisition module was explained. In addition， the comparisons of wearable EEG device signal preprocessing module， signal noise reduction， artifact processing and feature extraction technology were performed. Then， the advantages and disadvantages of machine learning and deep learning classification algorithms were analyzed， and the application fields of wearable EEG device were summarized. Finally， future development trends of the key technologies of wearable EEG device were proposed.