Testing the efficacy of different methods for mitigating aviation-related hypovigilance after detecting it on-line using physiological parameters

使用生理参数在线检测后，测试不同方法缓解与航空相关的警惕性不足的效果

• 批准号: 544424-2019
• 负责人: Klein, Raymond
• 金额: $ 0.91万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Engage Plus Grants Program
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=675277
• 关键词: Testing; efficacy; different; methods; mitigating

Fatigue-related decreases in vigilance (hypovigilance) and their negative effects on performance are widelyrecognized as posing a serious risk to aviation safety. In a prior Engage project, scientists at Thales Research &Technology (TRT) Canada (Quebec) collaborated with the Klein laboratory to design and conduct a researchproject in which participants performed tasks over an 8 hour period during which a variety of physiological,oculomotor and performance parameters, and self-reports of fatigue, were collected either continuously orregularly. Thales scientists then developed a mathematical model that from the physiological data could predictfatigue-related hypovigilance; a model that was successful when generalized to "new" data and that wasrecently tested in a more ecologically valid scenario (an intercontinental flight). In a followup project theDalhousie-Thales team plans to test the efficacy of mitigation measures of hypovigilance based on this model'son-line analysis of wearable data collecting during performance on a driving-like task. Thales is a world-classprovider of cockpit solutions. Their success, with the Klein laboratory, in using the data collected fromwearable devices to detect fatigue, lays the foundation for the current project in which the Klein lab willgenerate data that will allow Thales to include fatigue-mitigation strategies in their cockpit solutions.

与疲劳相关的警惕性下降（警惕性低下）及其对工作表现的负面影响被广泛认为对航空安全构成严重威胁。在之前的一个Engage项目中，泰雷兹研究与技术公司（TRT）加拿大（魁北克）的科学家与克莱因实验室合作设计并实施了一个研究项目，在该项目中，参与者在8小时的时间内执行任务，在此期间，各种生理、眼动和性能参数以及疲劳的自我报告被连续或定期收集。泰利斯公司的科学家随后开发了一个数学模型，根据生理数据可以预测疲劳相关的警惕性低下；这个模型在推广到“新”数据时是成功的，最近在一个更生态有效的场景（洲际飞行）中进行了测试。在后续项目中，戴尔豪斯-泰雷兹团队计划基于该模型在线分析可穿戴设备在执行类似驾驶任务时收集的数据，测试缓解警惕性低下措施的有效性。泰雷兹是世界一流的驾驶舱解决方案供应商。他们与克莱因实验室合作，利用可穿戴设备收集的数据来检测疲劳，为当前项目奠定了基础，克莱因实验室将生成数据，使泰雷兹能够将疲劳缓解策略纳入其驾驶舱解决方案。