Fully-Customizable Wireless Wearable EEG Monitoring Platform with Motion Artifact Resilience and Input-Adaptive Active-Electrode Recording

脑电图（EEG）是一种非侵入性的方法，用于测量具有高空间和时间分辨率的人的大脑活动。其应用范围从监测和诊断各种神经系统疾病（例如，癫痫，阿尔茨海默病）到脑机接口。由于医疗保健系统的大量等待时间和负担（例如，设备、用于进行实验的训练有素的技术人员、用于分析的专家），在过去的十年中已经开发了几种无线头戴式耳机以使得能够移动（即，门诊患者）EEG监测和分析。这种可穿戴解决方案必须是轻等待，不显眼，无线，易于设置，并具有合理的电池寿命。最重要的是，它应该能够以临床级质量记录EEG，同时消除运动伪影，这是无线EEG耳机最常见的问题。我们开发了一种集成电路（IC），该集成电路采用了一种新型的记录通道架构，能够实时消除运动伪影，同时进行放大，采样，和EEG信号的数字化，与现有技术相比具有上级质量（在功耗、信噪比等方面）。与在后端信号处理单元中进行伪影检测/去除的替代解决方案不同，在我们的解决方案中采用的通道内方法显著减小了记录电路所需的动态范围（因此，它的功耗，因此，更好的电池寿命），使每个记录通道成为独立的独立单元，不需要中央处理单元，因此，最大限度地减少了创建多通道EEG记录设备所需的互连线的数量。这显著降低了器件的形状因数和复杂性。记录通道的独立独立操作（也称为，沿着的有源电极）以及最少的互连线导致所提出的技术在通道数量方面完全可定制（即，优秀的可伸缩性）和它们的位置。

The electroencephalogram (EEG) is a non-invasive method for measuring a person's brain activity with high spatial and temporal resolution. Its applications span from monitoring and diagnosis of various neurological disorders (e.g., epilepsy, Alzheimer's disease) to brain-computer interfaces. Driven by the significant wait time and burden on the healthcare system (e.g., equipment, trained technicians for conducting the experiments, specialists for analysis), several wireless headsets have been developed over the past decade to enable ambulatory (i.e., outpatient) EEG monitoring and analysis. This wearable solution must be light-wait, unobtrusive, wireless, easy to set up, and with reasonable battery life. Most importantly, it should be capable of EEG recording with clinical-grade quality while removing motion artifacts, the most common problem with wireless EEG headsets.We have developed an integrated circuit (IC) that employs a novel recording channel architecture capable of real-time motion artifact removal while conducting amplification, sampling, and digitization of EEG signals with the superior quality compared to the state of the art (in terms of power consumption, signal-to-noise ratio, etc.). Unlike the alternative solutions where the artifact detection/removal is conducted in a backend signal processing unit, the in-channel approach employed in our solution significantly reduces the required dynamic range for the recording circuit (thus, its power consumption, hence, better battery life), making each recording channel a stand-alone independent unit, needless of a central processing unit, and consequently, minimizes the number of interconnecting wires required for creating a many-channel EEG recording device. This significantly reduces the device form factor and complexity. The stand-alone independent operation of recording channels (a.k.a., active electrodes) along with the minimal interconnecting wires results in the presented technology being fully customizable in terms of the number of channels (i.e., excellent scalability) and their placement.