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用于困倦检测的现有低成本脑电图耳机的系统评价。

A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection.

作者信息

LaRocco John, Le Minh Dong, Paeng Dong-Guk

机构信息

Ocean Systems Engineering, Jeju National University, Jeju City, South Korea.

出版信息

Front Neuroinform. 2020 Oct 15;14:553352. doi: 10.3389/fninf.2020.553352. eCollection 2020.

Abstract

Drowsiness is a leading cause of traffic and industrial accidents, costing lives and productivity. Electroencephalography (EEG) signals can reflect awareness and attentiveness, and low-cost consumer EEG headsets are available on the market. The use of these devices as drowsiness detectors could increase the accessibility of safety and productivity-enhancing devices for small businesses and developing countries. We conducted a systemic review of currently available, low-cost, consumer EEG-based drowsiness detection systems. We sought to determine whether consumer EEG headsets could be reliably utilized as rudimentary drowsiness detection systems. We included documented cases describing successful drowsiness detection using consumer EEG-based devices, including the Neurosky MindWave, InteraXon Muse, Emotiv Epoc, Emotiv Insight, and OpenBCI. Of 46 relevant studies, ~27 reported an accuracy score. The lowest of these was the Neurosky Mindwave, with a minimum of 31%. The second lowest accuracy reported was 79.4% with an OpenBCI study. In many cases, algorithmic optimization remains necessary. Different methods for accuracy calculation, system calibration, and different definitions of drowsiness made direct comparisons problematic. However, even basic features, such as the power spectra of EEG bands, were able to consistently detect drowsiness. Each specific device has its own capabilities, tradeoffs, and limitations. Widely used spectral features can achieve successful drowsiness detection, even with low-cost consumer devices; however, reliability issues must still be addressed in an occupational context.

摘要

嗜睡是导致交通事故和工业事故的主要原因,会造成人员伤亡和生产力损失。脑电图(EEG)信号能够反映意识和注意力,市场上也有低成本的消费级EEG头戴设备。将这些设备用作嗜睡探测器,可以提高小企业和发展中国家获取安全及提高生产力设备的机会。我们对目前可用的基于消费级EEG的低成本嗜睡检测系统进行了系统综述。我们试图确定消费级EEG头戴设备是否可以可靠地用作基本的嗜睡检测系统。我们纳入了描述使用基于消费级EEG的设备(包括Neurosky MindWave、InteraXon Muse、Emotiv Epoc、Emotiv Insight和OpenBCI)成功进行嗜睡检测的文献案例。在46项相关研究中,约27项报告了准确率得分。其中最低的是Neurosky Mindwave,最低为31%。OpenBCI的一项研究报告的第二低准确率为79.4%。在许多情况下,算法优化仍然是必要的。准确率计算、系统校准的不同方法以及嗜睡的不同定义使得直接比较存在问题。然而,即使是EEG频段的功率谱等基本特征,也能够持续检测出嗜睡。每种特定设备都有其自身的能力、权衡和局限性。即使使用低成本的消费级设备,广泛使用的频谱特征也能成功检测出嗜睡;然而,在职业环境中,可靠性问题仍需解决。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/90d1/7593569/823cf38da9ea/fninf-14-553352-g0001.jpg

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