SCH: INT: Supporting Healthy Sleep Behaviors through Ubiquitous Computing

睡眠是健康的关键因素之一，此外还有健康的饮食和规律的锻炼。计算机研究人员最近致力于了解系统如何支持营养和锻炼，但尽管睡眠对健康有重大好处，但研究相对较少。适量的高质量睡眠可以改善身体和精神健康，并与较低的心脏病、糖尿病、抑郁症和肥胖症风险相关。然而，睡眠障碍往往没有得到诊断，许多人没有意识到他们的活动或环境是如何影响睡眠的。泛在计算有机会通过自我监控、感知和确定促进健康睡眠行为的策略来提供帮助。这一跨学科研究议程将涉及设计、开发和评估新的泛在计算方法以支持良好的睡眠健康和行为。这项研究将结合以人为中心的设计、计算机科学、睡眠医学和护理方面的专业知识。研究人员之前与目标用户和睡眠专家一起进行的形成性工作，为这一领域的技术提供了设计需求。这项工作将侧重于通过三项主要活动在这些成果的基础上再接再厉。首先，他们将应用机器学习来根据一个人的智能手机使用情况对睡眠模式进行建模，以不引人注目地感知和预测睡眠持续时间和时间。然后，他们将采用以人为中心的设计流程来开发和研究两种新型软件工具的可行性和初步效果，以帮助个人感知、记录和可视化可能扰乱他们睡眠的行为因素(例如咖啡因的使用、食物的摄入量)和环境因素(例如噪音环境、光照水平)。然后，他们将开发和评估一种新的技术和工具的可行性和初步效果，该技术和工具用于评估、建模和可视化睡眠剥夺对用户的反应时间、认知功能和情绪的影响，以帮助他们确定睡眠的优先顺序。这项研究将使睡眠领域成为以人为中心的计算研究的新领域。睡眠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，这些设计和评估超出了目前业界正在解决的问题。技术贡献是监测睡眠的新方法，以及关于技术如何适应不同用户的独特健康需求的知识的扩展。最后，这项研究试图联合睡眠研究和计算机研究领域，开发更好地理解和治疗睡眠障碍的解决方案。这项工作可能会显著影响美国约4060万睡眠障碍或睡眠剥夺患者的生活，这有助于解决一个重大的公共健康问题。此外，每年因睡眠不足造成的经济损失估计为638亿美元。这项研究将允许免费获得通过该项目开发的新行为改变技术，从而产生立竿见影的效果。此外，这项研究还将影响教育，将睡眠研究作为吸引女性和少数族裔参与计算机研究的手段，并通过学生项目和指导性研究小组让学生参与跨学科设计团队。

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.