SCH: INT: Supporting Healthy Sleep Behaviors through Ubiquitous Computing

SCH：INT：通过普适计算支持健康的睡眠行为

• 批准号: 1344613
• 负责人: Julie Kientz
• 金额: $ 138.42万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1344613&HistoricalAwards=false
• 关键词: SCH; INT; Supporting; Healthy; Sleep

Sleep is one of the key aspects of good health, along with a healthy diet and regular exercise. Computing researchers have recently worked to understand how systems can support nutrition and exercise, but sleep has been relatively under-studied despite its significant health benefits. The right amount of quality sleep can improve both physical and mental health and is associated with a lower risk for heart disease, diabetes, depression, and obesity. However, sleep disorders are often undiagnosed, and many people are unaware of how their activities or environments affect sleep. Ubiquitous computing has the opportunity to help through self-monitoring, awareness, and identification of strategies to promote healthy sleep behaviors.This interdisciplinary research agenda will involve the design, development, and evaluation of novel ubiquitous computing approaches to support good sleep health and behaviors. This research will combine expertise in human-centered design, computer science, sleep medicine, and nursing. The researchers' previous formative work with target users and sleep experts has informed design requirements for technologies in this field. The work will focus on building on those results through three main activities. First, they will apply machine learning to model sleep patterns based on a person's smartphone usage to unobtrusively sense and predict sleep duration and timing. Then they will employ a human-centered design process to develop and study the feasibility and initial efficacy of two novel software tools to assist individuals in sensing, recording, and visualizing the behavioral (e.g., caffeine use, food intake) and environmental factors (e.g., noisy environment, light levels) that can disrupt their sleep. And then, they will develop and assess the feasibility and initial efficacy of a new technique and tool for assessing, modeling, and visualizing the impact of sleep deprivation on users' reaction time, cognitive functioning, and mood to help them prioritize sleep.This research will bring into focus the domain of sleep as a new area for human-centered computing research. The design and evaluation of new applications for sleep will further knowledge of how technology can be designed for long-term health tracking and behavior change, and the designs and evaluations move beyond what is currently being addressed in industry. The technical contributions are novel approaches to monitoring sleep and an expansion of knowledge about how technologies can adapt to meet the unique health needs of different users. Finally, the research seeks to unite the fields of sleep research and computing research to develop solutions for better understanding and treating sleep disorders.This work has the potential to significantly affect the lives of the estimated 40.6 million individuals in the U.S. with sleep disorders or sleep deprivation, which helps address a major public health issue. In addition, the economic cost of sleep deprivation has been estimated to be $63.8 billion per year. The research will have immediate impact by allowing free access to new behavior change technologies developed through this project. In addition, the research will also impact education by using sleep research as a means for attracting women and minorities to computing research and engaging students in interdisciplinary design teams through student projects and directed research groups.

睡眠是身体健康的关键方面之一，以及健康的饮食和定期运动。计算研究人员最近努力了解系统如何支持营养和运动，但是尽管健康益处很大，但睡眠却相对研究。适量的质量睡眠可以改善身心健康，并与患心脏病，糖尿病，抑郁症和肥胖的风险较低有关。但是，睡眠障碍通常无法诊断，许多人不知道他们的活动或环境如何影响睡眠。无处不在的计算有机会通过自我监控，认识和确定促进健康睡眠行为的策略。这项跨学科研究议程将涉及对新型无处不在的计算方法的设计，开发和评估，以支持良好的睡眠健康和行为。这项研究将结合以人为本的设计，计算机科学，睡眠医学和护理方面的专业知识。研究人员以前与目标用户和睡眠专家的形成性工作已经为该领域的技术设计了设计要求。这项工作将着重于通过三个主要活动来建立这些结果。 首先，他们将根据人的智能手机使用来对机器学习进行建模，以毫不显着地感知并预测睡眠持续时间和时机。 然后，他们将采用以人为本的设计过程来开发和研究两种新型软件工具的可行性和初始功效，以帮助个人感应，记录和可视化行为（例如咖啡因的使用，食物摄入量）和环境因素（例如嘈杂的环境，光线，光线）可能会破坏其睡眠的行为。 然后，他们将开发和评估一种新技术和工具的可行性和初始功效，以评估，建模和可视化睡眠剥夺对用户的反应时间，认知功能以及情绪的影响，以帮助他们优先级睡眠。这项研究将使人们成为以人为以人为以人为以人为以人为本的睡眠领域的焦点。对睡眠的新应用的设计和评估将进一步了解如何设计用于长期健康跟踪和行为改变的技术，以及设计和评估超出了行业目前所解决的问题。技术贡献是监测睡眠的新方法，以及有关技术如何适应以满足不同用户的独特健康需求的知识的扩展。最后，该研究旨在将睡眠研究和计算研究领域团结起来，以开发解决方案，以更好地理解和治疗睡眠障碍。这项工作有可能显着影响美国估计有4060万人患有睡眠障碍或睡眠剥夺的人的生活，这有助于解决一个重大的公共卫生问题。此外，据估计，睡眠不足的经济成本为每年638亿美元。这项研究将通过该项目开发的新行为变更技术，从而立即产生影响。此外，这项研究还将通过使用睡眠研究作为吸引妇女和少数民族通过学生项目和指导研究小组来计算研究和吸引学生参与跨学科设计团队的手段来影响教育。