Eun Kyoung Choe (iSchool) and Matthew Kay (CSE)
Wed. Aug 15, 2012
Eun Kyoung's talk: Investigating Receptiveness to Sensing and Inference in the Home Using Sensor Proxies
In-home sensing and inference systems impose privacy risks and social tensions, which can be substantial barriers for the wide adoption of these systems. To understand what might affect people’s perceptions and acceptance of in-home sensing and inference systems, we conducted an empirical study with 22 participants from 11 households. The study included in-lab activities, four weeks using sensor proxies in situ, and exit interviews. In this talk, we report on two things: (1) participants’ perceived benefits and concerns of in-home sensing applications, and (2) tensions amongst stakeholders around the adoption and use of such systems. We conclude with a discussion on how the ubicomp design space might be sensitized to people’s perceived concerns and tensions regarding sensing and inference in the home.
I am a Ph.D. candidate at the Information School at the University of Washington advised by Prof. Julie Kientz and Wanda Pratt. My research area is at the intersection of Human-Computer Interaction, Design, and Self-monitoring for Health. In particular, I am interested in designing and evaluating persuasive technologies to support health behavior change for better sleep. I've been also exploring privacy implications of such systems which might collect sensitive data from home (e.g., sleep data collected from someone's bedroom). Currently, I am working on applying behavior change theories and nudging / persuasive techniques to influence mobile phone users' decision making process to achieve privacy.
Matt's talk: Lullaby: A Capture & Access System for Understanding the Sleep Environment
The bedroom environment can have a significant impact on the quality of a person’s sleep. Experts recommend sleeping in a room that is cool, dark, quiet, and free from disruptors to ensure the best quality sleep. However, it is sometimes difficult for a person to assess which factors in the environment may be causing disrupted sleep. In this paper, we present the design, implementation, and initial evaluation of a capture and access system, called Lullaby. Lullaby combines temperature, light, and motion sensors, audio and photos, and an off-the-shelf sleep sensor to provide a comprehensive recording of a person’s sleep. Lullaby allows users to review graphs and access recordings of factors relating to their sleep quality and environmental conditions to look for trends and potential causes of sleep disruptions. In this paper, we report results of a feasibility study where participants (N=4) used Lullaby in their homes for two weeks. Based on our experiences, we discuss design insights for sleep technologies, capture and access applications, and personal informatics tools.
Matt Kay is a PhD student in CSE at the University of Washington who does work in sleep sensing technology and, if there is such a thing, personal informatics. He works with Julie Kientz and Shwetak Patel. He used to (during a Master's in CS at the University of Waterloo) try to find ways to get people to read software license agreements. Ha! This summer he's at MSR working with Dan Morris and m.c. schraefel on something vaguely health feedback related maybe sorta.