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

Fully-Customizable Wireless Wearable EEG Monitoring Platform with Motion Artifact Resilience and Input-Adaptive Active-Electrode Recording
完全可定制的无线可穿戴脑电图监测平台,具有运动伪影弹性和输入自适应有源电极记录
批准号:
571248-2022
负责人:
Kassiri, Hossein
金额:
$1.46万
依托单位:
依托单位国家:
加拿大
项目类别:
Idea to Innovation
财政年份:
2021
资助国家:
加拿大
项目状态:
已结题
起止时间:
2021-01-01 至 2022-12-31

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中文摘要
翻译
脑电(EEG)是一种非侵入性的测量方法,可以测量人的大脑活动,具有很高的空间和时间分辨率。它的应用范围从监测和诊断各种神经疾病(如癫痫、阿尔茨海默病)到脑机接口。由于等待时间长、医疗系统负担重(例如,设备、受过培训的实验技术人员、分析专家),在过去十年中开发了几种无线头戴式耳机,以实现动态(即门诊)脑电监测和分析。这款可穿戴解决方案必须轻便、不显眼、无线、易于设置,并且电池续航时间合理。最重要的是,它应该能够以临床级的质量记录脑电信号,同时消除运动伪影,这是无线脑电耳机最常见的问题。我们开发了一种集成电路(IC),它采用了一种新型的记录通道架构,能够实时去除运动伪影,同时对脑电信号进行放大、采样和数字化,与现有技术相比具有更高的质量(在功耗、信噪比等方面)。与在后端信号处理单元中执行伪影检测/去除的替代解决方案不同,我们的解决方案中采用的通道内方法显著降低了记录电路所需的动态范围(因此,其功率消耗,从而更好的电池寿命),使每个记录通道成为独立的单元,而不需要中央处理单元,并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。这显著降低了设备的外形尺寸和复杂性。记录通道(也称为有源电极)的独立独立操作以及最小的互连线使得本发明的技术在通道的数量(即,出色的可扩展性)及其放置方面是完全可定制的。
英文摘要
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.
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Next Generation Implantable Neural Interface Microsystems
  • 批准号:
    RGPIN-2017-05658
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.11万
  • 财政年份:
    2022
  • 负责人:
    Kassiri, Hossein
  • 依托单位:
Next Generation Implantable Neural Interface Microsystems
  • 批准号:
    RGPIN-2017-05658
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.11万
  • 财政年份:
    2021
  • 负责人:
    Kassiri, Hossein
  • 依托单位:
Next Generation Implantable Neural Interface Microsystems
  • 批准号:
    RGPIN-2017-05658
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.11万
  • 财政年份:
    2020
  • 负责人:
    Kassiri, Hossein
  • 依托单位:
Next Generation Implantable Neural Interface Microsystems
  • 批准号:
    RGPIN-2017-05658
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.11万
  • 财政年份:
    2019
  • 负责人:
    Kassiri, Hossein
  • 依托单位:
海外基金