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Bringing Smart Home Data to Caregivers
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Achievement/Results
Health care visualization is a quickly evolving field. Wtih a significant increase in the data available, care providers are continually being bombarded with increasingly complex information about their patients.
Smart home technologies used to monitor older adults are no exception to this proliferation of information. To date little work has been done to discern what pieces of data are most important to care providers and how it is best delivered from a smart home system. The Center for Advanced Studies in Adaptive Systems (CASAS) at Washington State University has launched a series of evaluations to derive what interfaces and data are most useful to nurses in a continuing care retirement center environment.
Eventually this work will be used to guide how future smart environments are designed and presented to users. Later research will also address how these same systems should be shown to residents and various kinds of care givers. The outstanding questions surrounding acceptance, usability and privacy are all open issues to be addressed.
Smart environments have a place in the future of elder care. The renewed focus on aging in place as a means to blunt the impact of our rapidly aging population has left the health care community seeking new approaches to monitoring their wards at home. Smart environments provide a tool to monitor older adults in an unobtrusive, but comprehensive manner. These technologies have already been established in both the research and commercial worlds.
A key issue when bringing any technology into the health care community is determining its efficacy. The CASAS engineering and psychology researchers have begun the process of exploring how health care professionals perceive and can make use of smart environments to better help their wards.
The research for this work is based on the latest CASAS testbeds at a Continuing Care Retirement Center (CCRC) called Horizon House. These 16 smart environments have been installed as part of a longitudinal elder care project. The primary goal is to build and evaluate tools for supporting aging in place approaches to elder care. Other goals include testing new sensor technologies, algorithms development for activity detection, transfer learning and visualization.
At Horizon House the residents mostly live in individual apartments with their own facilities for daily living. Sixteen residents between the ages of 70 and 90 have had the CASAS smart home sensors installed in their homes and over 9 months of data have been gathered.
The smart home testbeds used at Horizon House are based off of previous CASAS projects. They utilize ceiling and wall mounted motion detectors, door sensors, light meters, and room temperature sensors to monitor the space. The resulting data sets from the residents can then be used to drive automatic classification of activities or other behaviors. Visualizing these large and complex data sets for the nursing staff is a keystone of making these tools successful.
Key questions about health monitoring are: What factors should be monitored and how should it be visualized? Several other researchers have focused on these questions as they relate to the patient. The work at CASAS has begun investigating methods of providing information to the caregiver.
There are a handful of key factors that the CASAS research has decided to focus on, which include sleep patterns, activity density, activity occurrences, socialization, and ambient environment conditions. These have been selected to give a caregiver a clear view of how their ward is doing, both in the long term and in the short term. The long term chart is based on earlier work about occupancy density, and extended to show individual ADL’s over time. As the researchers worked with care providers, it was determined that more immediate information about the wards was desired, as well as trend analysis. These newer toolsare geared to be more interesting to care providers on a day to day basis, and will be the basis for surveys that our IGERT Trainees are currently conducting with 12 participant nurses in the field.
Research into how to best visualize smart home data is a relatively untapped field. While some researchers have done studies on what the elder clients think about the system as a whole, visualizing the data is a new venture. In our IGERT program, Trainee Leah Zulas from Experimental Psychology is working together with Kyle Feuz from Computer Science to design visualization tools that are useful for nursing staff.
Our currently visualization tools are shown in the images. We are finishing our surveys with 12 participant nurses and will analyze the responses over the coming months.
Address Goals
In the future, questions about how best to communicate with those residents living in the home, how best to detect and relay emergencies, and how to help the caregiver by assisting older individuals in their everyday activities will need to be explored. Creating useful and usable assistive smart homes will provide means to support aging in place approaches to elder care. Delving into how to best present and visualize the data from the technology is a key aspect of achieving these goals. This project is exploring technologies for providing this capability in cooperation with nursing participants who ensure that the tools meet needs for their profession.
The project is jointly conducted between students and faculty in Psychology, Computer Science, and Nursing. Our IGERT program supported this multidisciplinary approach that would otherwise not have been pursued here or likely elsewhere in the near future.
