Remote Monitoring using Smart Watches to Monitor and Manage Cardio Vascular Disease (CVD)

使用智能手表进行远程监控来监测和管理心血管疾病 (CVD)

• 批准号: 2283771
• 金额: --
• 依托单位: University of Strathclyde
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2283771
• 关键词: Remote; Monitoring; using; Smart; Watches

The well documented phenomenon of an increasing ageing population brings with it both challenges and opportunities. People are living longer and as a result are often managing multiple morbidities and increasingly expected to, or wanting to manage their health and wellbeing out of hospitals and care homes. The promise of emerging digital health technologies such as mobile phone apps, wearables and smart watches offers us novel ways to proactively monitor and manage our health and wellness (for example via applications such as Strava or Fitbit). Wearables such as smart watches for example offer opportunity for us to track and monitor not just our movements (via accelerometers for example) but also to monitor vital signs such as blood pressure, heart rate etc. As interaction via watches becomes more common, we can also explore how to capture self-reported outcomes (how the person is reporting they feel) and experiences of the patient/user in real time and on the go. This wealth of generated data (both self-reported and sensed) could be used to identify patterns, and events, that can be used to decide when to intervene with tailored health information at the right time, and the right place in ways that can help to better monitor and/or prevent a range of symptoms from exacerbating.The aim of this project will be to use large scale rapid prototyping and studies 'in the wild' to empirically investigate the use of smart watch technology to support the remote monitoring of the population (targeting both healthy populations and sub sets of people with long term conditions such as respiratory disease or diabetes for example). This will include exploring (i) what new vital signs and symptoms can be reliably detected using sensors available in the watch; (ii) what patterns of activity (e.g. sedentary behaviour or physical activity) can be meaningfully detected via modern smart watches, (iii) the best ways (experience sampling, diary entries, speech) to remotely monitor patient reported outcomes via such wearable devices in real time and (iv) how to best deliver (modality, timing, context) tailored notifications to the users based on patterns of data collected from (i-iv).The student will:1 - Review the literature to examine how smart watch and sensor technology has been used effectively in both the health and HCI (human computer interaction) literature - Y12 - Review of existing sensor based technology to examine the current accuracy and utility of using sensors to detect and recognise vital signs and symptoms - Y13 - Qualitatively explore the perceptions and attitudes of either (or both of) patients, consumers, clinicians with regards to the acceptance and usability of such symptom monitoring via watches (e.g. trust, privacy, usability) - Y1-Y24 - Design and develop demonstrator 'apps' in order to systematically investigate different methods of monitoring symptoms - Y25 - Conduct a large scale user trial of remote symptom monitoring via smart watches which will allow: - Y3 - (a) systematic evaluation of both the performance of, and preference for a variety of different methods for remote symptom monitoring via smart watches - (b) evaluation of feedback modalities and methods (ways of delivering health based notifications/messages) to the user/patient via the smart watch.6 - Produce recommendations and guidelines for both health and wellness practitioners and also smartwatch developers. - Y4This PhD is in the domain of data science and health, key areas of investment for both UK and Scottish governments (e.g. via the SFC funded Digital Health and Care Institute and DataLab.This PhD is relevant to a wide range of health and care specialists (inc. NHS) and decision makers and to both big players such as Apple (watch) as well as an increasing number of smaller sensor and wearable companies

人口日益老龄化这一有据可查的现象既带来了挑战，也带来了机遇。人们的寿命越来越长，因此经常管理多种疾病，并且越来越期望或希望在医院和护理院之外管理他们的健康和福祉。新兴数字健康技术的前景，如移动的手机应用程序，可穿戴设备和智能手表，为我们提供了主动监测和管理我们的健康和健康的新方法（例如通过Strava或Fitbit等应用程序）。例如，智能手表等可穿戴设备为我们提供了机会，不仅可以跟踪和监测我们的运动（例如通过加速度计），还可以监测血压，心率等生命体征。随着通过手表进行交互变得越来越普遍，我们还可以探索如何在真实的时间和旅途中捕获自我报告的结果（人们如何报告他们的感受）和患者/用户的体验。这些丰富的生成数据（自我报告的和感测的）可以用于识别模式和事件，其可以用于决定何时在正确的时间用定制的健康信息进行干预，和正确的地方，可以帮助更好地监测和/或防止一系列症状恶化。该项目的目的是使用大规模快速原型和“野外”研究，经验研究智能手表技术的使用，以支持对人群的远程监测（针对健康人群和患有长期疾病（例如呼吸系统疾病或糖尿病）的人群）。这将包括探索（i）使用手表中可用的传感器可以可靠地检测到哪些新的生命体征和症状;（二）活动的模式（例如久坐行为或身体活动）可以通过现代智能手表进行有意义的检测，（iii）（经验抽样，日记条目，语音）以通过此类可穿戴设备真实的实时远程监控患者报告的结果以及（iv）如何最好地提供根据从（i-iv）中收集的数据模式，为用户定制通知（模态、定时、上下文）。学生将：1 -回顾文献，研究智能手表和传感器技术如何有效地用于健康和HCI（人机交互）文学- Y12 -审查现有的基于传感器的技术，以检查使用传感器检测和识别生命体征和症状的当前准确性和实用性- Y13 -Qualitative探讨了患者、消费者、临床医生（或两者）关于经由手表的这种症状监测的接受度和可用性的意见（例如信任、隐私、可用性）- Y1-Y24 -设计和开发演示“应用程序”，以便系统地研究监测症状的不同方法- Y25 -通过智能手表进行远程症状监测的大规模用户试验，这将允许：- Y3 -（a）系统地评估用于经由智能手表进行远程症状监测的各种不同方法的性能和偏好-（B）评估经由智能手表向用户/患者的反馈模态和方法（递送基于健康的通知/消息的方式）。6-为健康和保健从业者以及智能手表开发者产生建议和指南。- Y 4这个博士学位是在数据科学和健康领域，为英国和苏格兰政府的投资的关键领域（例如通过证监会资助的数字健康和护理研究所和DataLab。NHS）和决策者，以及苹果（Apple）（手表）等大公司以及越来越多的小型传感器和可穿戴设备公司