Page 447 -

438 CHAPTER 14 Online and ubiquitous HCI research

Sensors and monitoring tools have been developed to use computing to address
challenges associated with everyday lives. Noting the difficulties that many families
face in dealing with aging relatives who may want to remain in their own homes
despite increased frailty and need for support, Elizabeth Mynatt and colleagues de-
veloped the digital family portrait, which would use sensors distributed throughout
the house of an older person to collect data associated with successful completion
of activities of daily life. These readings would be collected electronically and dis-
tributed via the Internet to a computerized picture frame in the home of the younger
family member. A border on the screen would display icons that might vary in size
and intensity to indicate recent activity levels and trends, assuring the younger care-
taker that their older relative was safely up and about, while maintaining privacy
for the older person (Figure 14.3) (Mynatt et al., 2001; Rowan and Mynatt, 2005).
Similar concerns about the well-being of older people have led to designs combin-
ing motion sensing data from smartphones with Microsoft Kinect motion sensing
(see Chapter 13) and social media feeds to identify activities in the home and related
variations in mood (Ghose et al., 2013). Other studies have been more purely forma-
tive, such as a contextual interview study that asked older adults about objects of

FIGURE 14.3
A digital family portrait, with a picture of an older relative surrounded by butterfly icons
scaled to indicate relative levels of activity. Levels for the current day are represented with
new icons added hourly, while the previous 27 days are summarized with one icon per day.
From Rowan, J., Mynatt, E.D., 2005. Digital family portrait field trial: support for aging in place. In: Proceedings
of the SIGCHI Conference on Human Factors in Computing Systems. ACM, Portland, OR, pp. 521–530.