EEG and behavioural correlates of fatigue indicated by real-time monitoring of saccadic eye movements

通过实时监测眼跳运动表明脑电图和疲劳行为的相关性

• 批准号: 485531-2015
• 负责人: Fogel, Stuart
• 金额: $ 1.77万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=585024
• 关键词: EEG; behavioural; correlates; fatigue; indicated

As a society, we are becoming increasingly sleep-deprived. Consequently, sleep restriction is having a greater impact on our day-to-day lives. One potentially life-threatening outcome is increased driver fatigue, often resulting in serious motor vehicle accidents. The main objective of the proposed research is the development of a non-invasive, ubiquitous and unobtrusive in-vehicle system to detect driver fatigue before a motor vehicle accident occurs. Our proposed system uses near infra-red (NIR) camera technology, in combination with our novel algorithm to detect somnolence, to be used to alert the driver while driving. While seemingly similar technology currently exists on the market, they rely on the duration of eyelid closures or other facial features to detect sleepiness. The major limitation of this technology is that it may detect sleepiness too late, which is crucial in order to successfully prevent motor vehicle accidents. Thus, we aim to study the relationship between saccadic eye movements and driver sleepiness, to refine our method to detect sleepiness and alert drivers before impairment and lapses in judgement occur. Here, we will study eye movements and their relationship to behavioural vigilance, brain arousal and sleep micro-states using EEG and investigate how this relates to sleep-pressure. The proposed research will help to scientifically validate this technology, foster training opportunities, mobilize knowledge to the community, and help to transfer knowledge about the dangers of drowsy driving. Ultimately, this development will result in the commercialization of an "early warning system" to prevent sleepiness-related accidents in the transport-trucking industry, public transit and in individual passenger vehicles. We expect that this research initiative will open up further avenues for research about the fitness to drive due to various causes, such as alcohol or drug use, distraction and even cognitive impairment due to dementia.

作为一个社会，我们越来越缺乏睡眠。因此，睡眠限制对 影响我们的日常生活。一个可能危及生命的结果是驾驶员疲劳加剧，通常 造成严重的机动车事故。拟议研究的主要目标是开发 一个非侵入性的，无处不在的和不显眼的车载系统，以检测驾驶员疲劳之前，机动车辆 事故发生。我们提出的系统使用近红外（NIR）相机技术，结合我们的 新的算法来检测嗜睡，用于提醒司机，而驾驶。虽然看起来很相似 技术目前存在于市场上，他们依靠眼睑闭合或其他面部特征的持续时间， 检测睡意。这项技术的主要局限性是，它可能会检测到嗜睡太晚，这是 这对于成功预防机动车事故至关重要。因此，我们旨在研究 扫视眼球运动和驾驶员困倦，以完善我们的方法来检测困倦和提醒司机之前， 出现减值和判断失误。在这里，我们将研究眼动及其与 行为警觉，大脑唤醒和睡眠微状态使用脑电图，并调查这是如何与 睡眠压力拟议中的研究将有助于科学地验证这项技术，促进培训， 机会，动员知识到社区，并帮助转移有关危险的知识， 疲劳驾驶最终，这一发展将导致“预警系统”的商业化。 为了防止运输卡车运输业、公共交通和个人交通中与睡眠有关的事故， 乘用车。我们希望这项研究举措将为研究 健康驾驶由于各种原因，如酒精或药物的使用，分心，甚至认知障碍 因为痴呆