Engaging the Patient into the Virtual Care Loop: An E-Health Framework using Data and Knowledge-Driven Methods for Ambient Sensor-Based Health Activity Monitoring to Remotely Determine Patient's Health and Functional Status

让患者参与虚拟护理循环：电子健康框架使用数据和知识驱动的方法进行基于环境传感器的健康活动监测，以远程确定患者的健康和功能状态

• 批准号: RGPIN-2021-03094
• 负责人: Abidi, SyedSibteRaza
• 金额: $ 2.55万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=742376
• 关键词: Engaging; Patient; into; Virtual; Care

In Canada, there is a recognition of the need to have a healthcare system which provides at--home care, especially to the elderly, chronic and mental health patients. The recent covid-19 pandemic further emphasized the need and utility of virtual care programs that offer remote therapeutic consultations to patients in the safety of their homes. Our intent is to provide unobtrusive and privacy-preserving remote monitoring of seniors, chronic and mental health patients' living at home, to assist them self-manage their health, maintain their autonomy, lifestyle and comfort whilst living a healthy life at their homes. This research proposes a novel e--Health based virtual care platform that employs ambient intelligence to provide assistive healthcare by remotely monitoring a patient's health in a home setting. Ambient intelligence refers to smart environments that use environmental sensors to collect location and movement data of individuals to help them perform daily-life activities by providing guidance and reminders. We are proposing a novel virtual care approach based on the concept of Activity Recognition (AR)-i.e. monitoring the targeted individual's daily life activities to determine health and function. It has been noted that when health is affected, the ability to carry out routine daily-life activities is also affected, so by identifying variations in daily-life activities over time we will be able to detect decline in health and deliver timely assistive healthcare interventions. This research will pursue scientific investigations in remote sensing, knowledge-- and data--driven decision support and e--Health systems to develop innovative unobtrusive AR methods for remote monitoring of a patient's daily activities. The AR methods will be used to generate digital biomarkers to assess the ability of an individual to perform daily-life activities. For remote sensing, we will use contactless sensors to collect the patients' activity data. We will develop a novel hybrid AR solution, where knowledge--driven methods will be used to represent the patient's home environment and daily-life activity models, and data--driven methods to recognize the patients' daily-life activities. Based on the recognized activities, we will generate digital biomarkers to determine the patient's health status. The AR and health assessment methods will be implemented as an e-Health virtual care platform for healthcare providers to remotely monitor their patient's health status. This project's significance is an e-Health platform for virtual care, enabling seniors and patients with dementia, mental health and chronic conditions to safely live in their homes. This research is timely and relevant given the increase in elderly Canadians and in light of the loss of life due to COVID-19 in long-term care facilities. The project will develop novel AR methods to identify the activities of a specific person in a multi-person home and personalize activity models over time.

在加拿大，人们认识到需要建立一个提供家庭护理的医疗保健系统，特别是向老年人、慢性病患者和精神疾病患者提供家庭护理。最近的 covid-19 大流行进一步强调了虚拟护理项目的必要性和实用性，这些项目可以在家中安全地为患者提供远程治疗咨询。我们的目的是为老年人、慢性病和精神疾病患者的居家生活提供不显眼且保护隐私的远程监控，帮助他们自我管理健康，保持自主性、生活方式和舒适度，同时在家中过上健康的生活。这项研究提出了一种基于电子健康的新型虚拟护理平台，该平台利用环境智能通过远程监控家庭环境中患者的健康状况来提供辅助医疗保健。环境智能是指利用环境传感器收集个人的位置和运动数据，通过提供引导和提醒来帮助他们进行日常生活活动的智能环境。我们提出了一种基于活动识别（AR）概念的新型虚拟护理方法，即监测目标个人的日常生活活动以确定健康和功能。人们注意到，当健康受到影响时，进行日常日常生活活动的能力也会受到影响，因此通过识别日常生活活动随时间的变化，我们将能够发现健康状况的下降并及时提供辅助医疗干预措施。 这项研究将在遥感、知识和数据驱动的决策支持以及电子医疗系统方面进行科学研究，以开发创新的、不引人注目的 AR 方法，用于远程监控患者的日常活动。 AR方法将用于生成数字生物标记，以评估个人进行日常生活活动的能力。对于遥感，我们将使用非接触式传感器来收集患者的活动数据。我们将开发一种新颖的混合AR解决方案，其中知识驱动的方法将用于表示患者的家庭环境和日常生活活动模型，并使用数据驱动的方法来识别患者的日常生活活动。根据公认的活动，我们将生成数字生物标记来确定患者的健康状况。 AR 和健康评估方法将作为电子健康虚拟护理平台实施，供医疗保健提供者远程监控患者的健康状况。该项目的意义在于建立一个用于虚拟护理的电子健康平台，使老年人和患有痴呆症、心理健康和慢性病的患者能够安全地在家中生活。鉴于加拿大老年人的增加以及长期护理机构中因 COVID-19 造成的生命损失，这项研究是及时且相关的。该项目将开发新颖的 AR 方法来识别多人家庭中特定人员的活动，并随着时间的推移个性化活动模型。