Remotely Powered Flexible Wearable Sensors for Managing Chronic Diseases

用于管理慢性病的远程供电柔性可穿戴传感器

• 批准号: RGPIN-2020-06116
• 负责人: Lian, Peter
• 金额: $ 4.01万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=718242
• 关键词: Remotely; Powered; Flexible; Wearable; Sensors

Cardiovascular diseases (CVDs) are the number ONE cause of death globally according to World Health Organization. As pointed out in the 2019 Report from Heart & Stroke Foundation of Canada, one person dies in Canada every five minutes from heart conditions, stroke or vascular cognitive impairment. This death rate outpaces other diseases, i.e. 13% more people die of heart condition, stroke and vascular cognitive impairment than die from all cancers combined. 2.6 million CVD related hospitalizations in Canada between 2007 and 2017. CVDs alone cost totaling $21.2 billion a year in direct (medical) and indirect (lost earnings) costs. Stroke costs the Canadian economy $3.6 billion a year in physician services, hospital costs, lost wages and decreased productivity. Dementia (the most severe form of vascular cognitive impairment) costs $33 billion a year in direct and indirect costs and this number is expected climb to $293 billion a year by 2040. With the advancement of information technologies, it is possible to prevent and detect CVDs at early stage with the help of wearable wireless biomedical sensors. Many types of wearable sensors were developed in the last decade for this purpose. However, none of them provides the information that are comparable to data recorded by medical grade equipment at hospital. This is mainly due to signal distortions caused by motion artifacts when people carry out daily activities with wearable devices. The motion artifacts are caused by several factors: (1) the weight of sensor that pulls the electrodes attached to skin causing signal distortion, and (2) the change of skin-electrode contact resistance due to motion and muscle activities. This project aims to create an innovative solution that solves the motion artifact problems faced by existing wearable sensors. We propose to conduct research in following areas: (1) thin flexible electrodes that conform to body shape with improved contact impedance; (2) ultra-high input impedance analog front-end interface circuit that is suitable for dry electrodes used in flexible electrodes. This will help to maximize input signal strength while minimizes the ambient noises; (3) large dynamic range instrumentation amplifier that is tolerant to large motion artifacts, i.e. to avoid saturation of amplifier when a large motion artifact is presented at input; (4) removal of battery in the sensor to reduce the weight by powering the sensor remotely; (5) ultra-low power embedded machine learning algorithm at the sensor for compensating motion artifacts and for CVD early warning sign detection. The goal is to design a system-on-chip solution for a remotely powered flexible wearable sensors that is thin, skin-friendly, bendable, light weight, and low cost. The success of proposed project will create a solution for preventing, predicting, and managing chronic diseases. It will help to improve the quality of CVD patient's life while helping reduce the CVD related health care cost.

根据世界卫生组织，心血管疾病（CVD）是全球头号死亡原因。加拿大心脏与中风基金会（Heart & Stroke Foundation of Canada）2019年报告指出，加拿大每五分钟就有一人死于心脏病、中风或血管性认知障碍。这一死亡率超过了其他疾病，即死于心脏病、中风和血管性认知障碍的人数比死于所有癌症的人数总和多13%。2.6 2007年至2017年期间，加拿大有100万例CVD相关住院。仅心血管疾病一项，每年的直接（医疗）和间接（收入损失）成本就高达212亿美元。中风每年给加拿大经济造成36亿美元的医疗服务、医院费用、工资损失和生产力下降。痴呆症（最严重的血管性认知障碍）每年的直接和间接成本为330亿美元，预计到2040年，这一数字将攀升至每年2930亿美元。 随着信息技术的进步，可穿戴无线生物医学传感器可以帮助早期预防和检测心血管疾病。在过去的十年中，许多类型的可穿戴传感器被开发用于此目的。然而，它们都没有提供与医院医用级设备记录的数据可比的信息。这主要是由于当人们使用可穿戴设备进行日常活动时，运动伪影引起的信号失真。运动伪影是由几个因素引起的：（1）拉动附着在皮肤上的电极的传感器的重量，导致信号失真，以及（2）由于运动和肌肉活动引起的皮肤-电极接触电阻的变化。该项目旨在创建一个创新的解决方案，解决现有可穿戴传感器面临的运动伪影问题。我们计划在以下几个方面进行研究：（1）符合人体形状并改善接触阻抗的薄柔性电极;（2）适用于柔性电极中使用的干电极的超高输入阻抗模拟前端接口电路。这将有助于最大化输入信号强度，同时最小化环境噪声;（3）大动态范围仪表放大器，其耐受大的运动伪影，即当在输入处呈现大的运动伪影时避免放大器饱和;（4）去除传感器中的电池，以通过远程为传感器供电来减轻重量;（5）在传感器处的超低功耗嵌入式机器学习算法，用于补偿运动伪影和用于CVD早期预警信号检测。我们的目标是为远程供电的柔性可穿戴传感器设计一个系统级芯片解决方案，该解决方案薄，皮肤友好，可弯曲，重量轻，成本低。拟议项目的成功将为预防、预测和管理慢性病提供解决方案。这将有助于提高心血管病患者的生活质量，同时有助于降低心血管病相关的医疗保健成本。