Human-Computer Interaction Institute
School of Computer Science, Carnegie Mellon University
Task-based Embedded Assessment of
Matthew L. Lee
Many older adults desire to maintain their quality of life by living
and aging independently in their own homes. However, it is difficult for
older adults to notice and track the subtle changes in their own abilities
because these abilities can change gradually over a long period of time.
Technology in the form of ubiquitous sensors embedded in objects in the home
can play a role in keeping track of the functional abilities of individuals
unobtrusively, objectively, and continuously over a long period of time.
This work introduces a sensing technique called "task-based embedded
assessment" that monitors how well specific tasks important for independence
are carried out using everyday objects found in the home with which
individuals regularly interact.
Following formative studies on the information needs of older adults and their caregivers, a sensing system called "dwellSense" that can monitor, assess, and provide feedback about how well individuals complete tasks, such as taking medications, using the phone, and making coffee, was designed, built, and evaluated. Multiple longterm (over 10 months) field deployments of dwellSense were used to investigate how the data collected from the system could support greater self-awareness of abilities and intentions to improve in task performance. Presenting and reflecting on data from ubiquitous sensing systems such as dwellSense is challenging because it is both highly dimensional as well as large in volume, particularly if it is collected over a long period of time. Thus, this work also investigates the time dimension of reflection and has identified that real-time feedback is particularly useful for supporting behavior change, and longer-term trended feedback is useful for greater awareness of abilities.
Traditional forms of assessing the functional abilities of individuals tend to be either biased, lacking ecological validity, infrequent, or expensive to conduct. An automated sensor-based approach for assessment is compared to traditional performance testing by a trained clinician and found to match well with clinician-generated ratings that are objective, frequent, and ecologically valid. The contributions from this thesis not only advance the state of the art for maintaining quality of life and care for older adults, but also provide the foundations for designing personal sensing systems that aim to assess an individual’s abilities and support behaviors through the feedback of objective, timely sensed information.