A Wearable EEG Real-time Measure and Analysis Platform for Home Applications

Abstract

Scalp electroencephalography (EEG) is widely used to study human electrophysiological activity noninvasively. With the gradual improvement of the quality of the multi-channel bioelectric signal acquisition device, the volume and power consumption are gradually reduced, which makes it suitable for portable and wearable application. To ensure sufficient signal gain and acquisition accuracy, it is a huge challenge to effectively suppress external interference and obtain a better bioelectric signal. This paper presents a new kind of wireless EEG signal real-time analysis and acquisition system. The system can be wearable at home environment and wirelessly send the real-time EEG signal to the host. The results show that the system can collect EEG signal robustly. The noise of the test system is reduced by 60% through the design of the isolated circuit. The software algorithm also enables the ability to perform basic analysis of biological signals by using Python digital signal processing module. The system provides a new safety platform for human-machine interfacing, rehabilitation and mental disease monitoring at home.