| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | September 13, 2013 |
| Latest Amendment Date: | September 13, 2013 |
| Award Number: | 1344613 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Sylvia Spengler
sspengle@nsf.gov (703)292-7347 IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | January 1, 2014 |
| End Date: | December 31, 2018 (Estimated) |
| Total Intended Award Amount: | $1,384,217.00 |
| Total Awarded Amount to Date: | $1,384,217.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
4333 BROOKLYN AVE NE SEATTLE WA US 98195-1016 (206)543-4043 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
4333 Brooklyn Ave NE Seattle WA US 98195-2500 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Smart and Connected Health |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Sleep is one of the key aspects of good health, along with a healthy diet and regular exercise. 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 underdiagnosed, and many people are unaware of how their activities or environments affect sleep. Thoughtfully designed ubiquitous computing technologies have the opportunity to improve sleep health through self-monitoring, awareness, and identification of ways to promote healthy sleep behaviors.
This grant provided funding for a 5-year, interdisciplinary research agenda that involved the design, development, and evaluation of novel ubiquitous computing approaches for supporting good sleep health and behaviors. This research brought together expertise in human-centered design, computer science, sleep medicine, and nursing to accomplish three main goals:
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Design and validate approaches for unobtrusive sensing and predicting sleep duration and time by creating a personalized model of a sleep quality based on wireless sensing technologies and ecological momentary assessment data.
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Understand how consumer-level applications can help people identify the behavioral and environmental factors that can disrupt their sleep through the design, development, and evaluation of low-burden software tools.
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Help people understand the impact sleep has on their own lives through assessing and modeling the individual impact of sleep quantity and quality on daily factors such as reaction time, cognitive functioning, and mood.
Specifically, researchers supported by this grant developed new ways of unobtrusively monitoring sleep and sleep quality and low-burden ways of monitoring aspects related to sleep such as alertness and potential sleep disruptors. This included a doppler radar contactless approach for assessing breathing and heart rate for predicting sleep, a new algorithm for assessing alertness via smartphone interactions, and a new model for assessing overall sleep health combining qualitative and quantitative measures.
The researchers also developed and evaluated several new consumer-facing technology designs, including 1) Lullaby: a capture and access tool for understanding environmental sleep disruptors; 2) SleepTight: a mobile application for low burden monitoring of behavioral sleep disruptors; 3) DreamCatcher: a family-based sleep monitoring tool for improving family communication about sleep; 4) PVT-Touch: a validated touch-screen based tool for assessing sleepiness outside of a lab setting; 5) A low-burden lockscreen widget that enables sleep monitoring through the unlock motion on a mobile device.
This research also contributed more broadly to understanding sleep within a broader umbrella of smart and connected health technologies by supporting empirical research on how families think about health monitoring, how people decide to change their behaviors, how health technologies might be designed to have lower user burden, and how technology can be used to support people in conducting self-experimentation for improved health outcomes.
Intellectual Merit: This research established the domain of sleep as a focus area for human-centered computing research and helped bridge the gap between the computing and sleep health research communities. The design and evaluation of the novel applications for sleep contributed new knowledge of how technology can be designed for long-term health tracking and behavior change, and the designs and evaluations have helped move commercial products to be more in line with people?s needs. 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. The research also contributed to an empirical understanding of how people adopt, accept, and benefit from technologies that promote good sleep health.
Broader Impacts: An estimated 40.6 million people in the U.S. have a sleep disorder or chronic sleep deprivation, and thus there is growing interest in support healthy sleep. As a result, sleep technology market is estimated to be $80 billion in 2020. However, these technologies have a high rate of abandonment. By exploring novel approaches to sleep monitoring and individualized and obtrusive sleep measures, this research influences the success of these technologies, which will benefit a significant portion of the population. In addition, this grant has supported over 22 faculty and 32 students in developing their scientific careers, leveraged their expertise to promote computing education, and supported numerous outreach efforts for engaging underrepresented groups in computing research and education.
Last Modified: 03/31/2019
Modified by: Julie A Kientz
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