Below are current and past research projects conducted by members of the CHiLL Lab. Please see the respective project web pages on the dub website linked for each project to find associated researchers, publications, and downloads.

Baby Steps

Baby Steps

We are interested in designing technology to help detect, record, and track important developmental milestones that occur in children during their first 5 years of life. By tracking these milestones, we can help parents and healthcare providers detect developmental delays such as autism or deafness earlier, which can improve the effects of interventions. We have developed design guidelines for developing technology to support new parents in record-keeping and implementing novel technologies to support better record-keeping and decision-making about developmental progress. We have also designed and evaluated two systems called Baby Steps and KidCam, which were aimed to meet the record-keeping needs of new parents. We are currently in the process of developing a web portal with subsequent text messaging, Twitter, and Facebook links to help make tracking more interesting and motivating. Baby Steps is funded by the National Science Foundation.

Empathy in Health Technologies

Empathy in Health Technologies

Many projects in HCI focus on health care and data collection, including those that help might diagnose or identify different disorders or communicate health information. One danger of this is the potential for these technologies to cause unnecessary fear and anxiety in its users over their health or the health of their loved ones. We are exploring ways that technology can be designed to be more empathic and sensitive to the prospect of delivering potentially negative health care information, and in particular, technology that may potentially identify bad news of a diagnosis.


Heuristic Evaluation of Persuasive Health Technologies

Persuasive technologies for promoting physical fitness, good nutrition, and other healthy behaviors have been growing in popularity. Despite their appeal, the evaluation of these technologies remains a challenge and typically requires a fully functional prototype and long-term deployment. In this project, we attempt to help bridge this gap by presenting a method for using heuristic evaluation to evaluate persuasive technologies. We developed a set of 10 heuristics intended to find problems in persuasive technologies that would affect persuasive elements, adoption, or long-term effectiveness of the technologies. We compared the performance of Nielsen's heuristics to our heuristics on two persuasive technologies using 10 different evaluators. Using our heuristics, evaluators found more severe problems more frequently. In addition, the issues that found only by our heuristics were more severe and more relevant to persuasive, cultural, and informational issues of the interfaces evaluated. Our method can be helpful in finding problems in persuasive technologies for promoting healthy behaviors earlier in the design process.


Interfaces that Make us Think

We have been researching and designing ways that computing interfaces can actually make us think more rather than less. The research includes determining opportune times to make tasks cognitively harder, methods that make users think more without being frustrating or annoying, and activities that can be seamlessly integrated into people’s everyday tasks. Example ideas include a Firefox extension that requires you to solve 10 simple arithmetic problems before you load Facebook, switching the order of items on a person’s iGoogle home page every visit, and a digital picture frame that quizzes you on facts about your family. Our work has included formative work, design ideation, prototyping, and the definition of a design space framework for technologies in this space. We are also working toward developing a design framework for categorizing and generating new ideas.



Lullaby is a system designed to help users improve the quality of their sleep by monitoring environmental factors that disrupt sleep (currently light, sound, temperature, and motion) along with sleep quality itself (using commercial sleep trackers like the Fitbit) and providing feedback. To be practical for deployment into bedrooms, it is designed to be unobtrusive and inexpensive. It aims to respect users’ privacy in this sensitive context by providing them with the ability to selectively disable data collection and to review and delete collected data. Lullaby helps users identify relationships between sleep disruptions and environmental factors; in the future, we plan for Lullaby to give concrete recommendations for addressing identified sleep disruptors. Lullaby consists of four components: the sensor suite, the data collection computer, a sleep tracking device, and a tablet interface for control and feedback. We are currently conducting evaluations of this study. Lullaby was funded by the UW Royalty Research Fund, Intel Labs Seattle, and an NSERC PhD fellowship.


Personality & Persuasive Technology

Though a variety of persuasive health applications have been designed with a preventive standpoint toward diseases in mind, many have been designed largely for a general audience. Designers of these technologies may achieve more success if applications consider an individual’s personality type. Our goal for this research was to explore the relationship between personality and persuasive technologies in the context of health-promoting mobile applications. We conducted an online survey with 240 participants using storyboards depicting eight different persuasive strategies, the Big Five Inventory for personality domains, and questions on perceptions of the persuasive technologies. Our results and analysis revealed a number of significant relationships between personality and the persuasive technologies we evaluated. The findings from this study can guide the development of persuasive technologies that can cater to individual personalities to improve the likelihood of their success.

Sensing & Inference in the Home

We have conducted several studies to understand the acceptability of sensing and inference systems in the home. The first study used an anonymous postcard and surveys to understand and characterize the private moments that occur in the home that participants would not want recorded. The second study used sensor proxies to probe people's responses in situ to sensing and inference systems.



ShutEye is a research application that was developed by the University of Washington and Intel Labs Seattle for Android-based mobile phones. The intent of ShutEye is to help improve people's awareness about healthy sleep hygiene—that is, the practices that are believed to promote improved quality of sleep. A glanceable display on the wallpaper of a person's mobile phone provides recommendations about common activities that are known to impact sleep relative to sleep and wake times: consuming caffeine, napping, exercising, eating heavy meals, consuming alcohol, ingesting nicotine, and relaxing. For example, a person can quickly glance at his or her phone to see if having a cup of coffee or doing vigorous exercise right now is likely to impact tonight's sleep. ShutEye was evaluated in a 4-week field study with 12 participants who were recruited from the general population.

Sleep Technology Design Space

Sleep Technologies Design Space

We are investigating the design space for the use of technologies to support health sleep behavior. As part of this research, we conducted a large survey, interviews with 16 participants, and a contextual inquiry with a sleep disorders center. We determined a number of design opportunities and challenges for working in this space. To help map out the space of existing and future computing technologies for supporting healthy sleep, we developed a framework that can be used to organize existing technologies and look for opportunities to design new ones.