STUDY FOCUSES ON ENABLING THE ELDERLY TO REMAIN INDEPENDENT
NORTHAMPTON, Mass.—Virtual medical appointments and online dinner dates with far-away friends are among a range of technological possibilities being tested on the elderly by an interdisciplinary team led by Smith College and focused on helping the aged remain independent.
The ambitious three-year project, recently funded by a $780,000 grant from the National Science Foundation (NSF), brings together social scientists with specialization in geriatric care and computer scientists with expertise in human-computer interactions.
“In the near future, the growing number of elderly in need of support to live independently will severely test the social services infrastructure,” said Phebe Sessions, Smith College School for Social Work professor and one of the project’s lead investigators.
“We owe it to the elder segment of our population to meet their changing needs in a way that enriches their lives and enhances their continuing contribution to society.”
The team brings together researchers from the Smith College School for Social Work, the University of Massachusetts and the Mitsubishi Electronics Research Lab (MERL) to develop and test the use of a multi-camera video tracking system and speech and sound recognition systems in the lives of the elderly. Study participants volunteer through the local Highland Valley Elder Services.
Factors such as the geographic dispersal of families and the diminished mobility of the elderly create a need for technology that will connect them to family, friends and caregivers, according to Sessions. Researchers will focus on technology-aided communication in two main areas:
Most seniors have regular doctor’s appointments and medication requirements. Yet the elderly often have serious difficulty getting to and from a doctor’s office. Moreover, health care professionals and facilities will become increasingly burdened as this population increases in size. Researchers are testing ways to avoid some in-person visits while maintaining health care supervision.
Seniors living at home often report a lack of interest or ability in preparing meals and performing exercise. Researchers are testing new tools for social service professionals to assess and respond to a client’s needs. A major component of cyber-social service will consider the appropriateness of technology in independent-living situations when an individual’s cognitive and physical abilities vary over time.
It is well known that seniors are often isolated at home for large portions of the day. Researchers are testing ways to place the elderly in contact with family and friends as if they were virtually in the same room. The media already exists, but the challenge is how to deliver these services in a way that the elderly find natural and empowering.
“An important element of empowerment is the freedom to maintain control over as many aspects of one’s life as possible,” said Sessions. “Interventions to enhance control can have a significant impact on individual well-being and physical status.”
In addition to Sessions, Edward Riseman, UMass professor of computer science, is leading the project. The research team also includes: Julie Abramson, Highland Valley Elder Services; Mary Olson, School for Social Work; Allen Hanson, UMass; Erik Learned-Miller, UMass; Roderic Grupen, UMass; Candace Sidner, MERL.
The Smith College School for Social Work is nationally recognized for its specialization in clinical social work. The program requires students to master clinical theory and practice, and understand of the socio-cultural, social service and policy contexts of practice.
The University of Massachusetts, Amherst, Computer Science Department is a nationally recognized program in computer vision and robotics with a leading graduate research program.
Mitsubishi Electronics Research Lab (MERL), Cambridge, Mass., is the North American arm of the research and development organization of the Mitsubishi Electric Company in Japan. Investigators research computer and communication technologies such as audio-visual event detection, face recognition and human-robot interaction.
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