Lin Chin-Teng, Liu Chi-Hsien, Wang Po-Sheng, King Jung-Tai, Liao Lun-De
Centre for AI, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney NSW 2007, Australia.
Brain Research Center, National Chiao Tung University, Hsinchu 300, Taiwan.
Micromachines (Basel). 2019 Oct 25;10(11):720. doi: 10.3390/mi10110720.
A brain-computer interface (BCI) is a type of interface/communication system that can help users interact with their environments. Electroencephalography (EEG) has become the most common application of BCIs and provides a way for disabled individuals to communicate. While wet sensors are the most commonly used sensors for traditional EEG measurements, they require considerable preparation time, including the time needed to prepare the skin and to use the conductive gel. Additionally, the conductive gel dries over time, leading to degraded performance. Furthermore, requiring patients to wear wet sensors to record EEG signals is considered highly inconvenient. Here, we report a wireless 8-channel digital active-circuit EEG signal acquisition system that uses dry sensors. Active-circuit systems for EEG measurement allow people to engage in daily life while using these systems, and the advantages of these systems can be further improved by utilizing dry sensors. Moreover, the use of dry sensors can help both disabled and healthy people enjoy the convenience of BCIs in daily life. To verify the reliability of the proposed system, we designed three experiments in which we evaluated eye blinking and teeth gritting, measured alpha waves, and recorded event-related potentials (ERPs) to compare our developed system with a standard Neuroscan EEG system.
脑机接口(BCI)是一种能帮助用户与周围环境交互的接口/通信系统。脑电图(EEG)已成为脑机接口最常见的应用方式,为残疾人士提供了一种交流途径。虽然湿传感器是传统脑电图测量中最常用的传感器,但它们需要相当长的准备时间,包括准备皮肤和使用导电凝胶所需的时间。此外,导电凝胶会随着时间变干,导致性能下降。此外,要求患者佩戴湿传感器来记录脑电信号被认为非常不便。在此,我们报告一种使用干传感器的无线8通道数字有源电路脑电信号采集系统。用于脑电图测量的有源电路系统使人们在使用这些系统时能够参与日常生活,并且通过使用干传感器可以进一步提升这些系统的优势。此外,干传感器的使用可以帮助残疾人和健康人在日常生活中享受脑机接口带来的便利。为了验证所提出系统的可靠性,我们设计了三个实验,分别评估眨眼和咬牙、测量阿尔法波以及记录事件相关电位(ERP),以便将我们开发的系统与标准的Neuroscan脑电图系统进行比较。