Vital signs monitoring wearable technologies

生命体征监测可穿戴技术

• 批准号: 530659-2018
• 负责人: Golnaraghi, Farid
• 金额: $ 0.91万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Engage Plus Grants Program
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=652111
• 关键词: Vital; signs; monitoring; wearable; technologies

DyMo Technology Corp (DyMoTech) is a Vancouver engineering firm specialized in developing Health**Monitoring systems for heavy-duty machines to provide a maintenance schedule and prevent potential failures.**The company is active in mining Industry and through the close connection with the mining companies.**DyMoTech's team of specialists has acquired in-depth knowledge of this industry's requirement and points of**pain. The company is currently engaged in an R&D project to create a wearable intelligent drowsiness**prognosis System. Based on company's years of experiences there is a need in the mining industry for staff**fatigue and vital health signs monitoring systems. The lack of drowsiness monitoring and prognosis system in**mining industry can cause irrecoverable losses. Integrated intelligent prognosis system can be utilized in the**mining industry in order to save the operators life and expensive mining instruments. This Engage Plus**proposal is an extension of an earlier Engage Grant that was completed recently where we have conducted a**preliminary study to define the functionality of a wearable drowsiness prognosis hardware for this application.**A wearable cap with dry EEG sensors and related hardware which is used for collecting and transferring EEG**data to drowsiness detection algorithm is developed. A preliminary drowsiness detection idea with EEG signal**processing that included innovative a patentable concept was presented to the company. DyMoTech identified**significant added benefits to drowsiness prognosis system.**In the earlier Engage grant, the focus was on coming up with the functionally and features of a proper wearable**drowsiness prognosis hardware. So far, we have developed a proof of concept. The next task is to develop a**drowsiness detection algorithm to process this data and to arrive at a sensitive, accurate, with better response**time in comparison to the available drowsiness monitoring systems. Our ultimate aim of this study is, therefore,**to design a non-invasive and cost-effective wearable EEG system, which can measure brain activity and**provide drowsiness prognosis using the chaos theory methods.

DyMo Technology Corp（DyMoTech）是一家温哥华的工程公司，专门为重型机器开发健康 ** 监控系统，以提供维护计划并防止潜在故障。**该公司活跃于采矿业，并通过与采矿公司的密切联系。DyMoTech的专家团队已经深入了解了该行业的需求和痛点。公司目前正在进行一个研发项目，创建一个可穿戴智能嗜睡 ** 预测系统。根据公司多年的经验，采矿业需要员工疲劳和生命健康体征监测系统。煤矿行业缺乏嗜睡监测和预警系统，会造成不可挽回的损失。集成智能预测系统可用于采矿业，以节省操作人员的生命和昂贵的采矿仪器。该Engage Plus** 提案是最近完成的早期Engage Grant的扩展，我们已经进行了 ** 初步研究，以定义用于此应用的可穿戴嗜睡预测硬件的功能。设计了一种可穿戴式帽子，该帽子具有干EEG传感器和相关硬件，用于收集EEG** 数据并将其传输到困倦检测算法。一个初步的困倦检测想法与脑电图信号 ** 处理，其中包括创新的专利概念提交给该公司。DyMoTech确定了 ** 嗜睡预测系统的显著附加益处。**在早期的Engage资助中，重点是提出适当的可穿戴 ** 嗜睡预测硬件的功能和特性。到目前为止，我们已经开发了一个概念验证。下一个任务是开发一种睡意检测算法来处理这些数据，并与现有的睡意监测系统相比，达到灵敏、准确、响应时间更好的效果。因此，我们本研究的最终目的是设计一种非侵入性和成本效益的可穿戴EEG系统，该系统可以测量大脑活动并使用混沌理论方法提供嗜睡预测。