Two older Asian women using a smart speaker and electronic tablet while seated at a table at home.

Technologies to Support Aging-in-Place

Technologies to Support Aging-in-Place

The Rehabilitation Engineering Research Center on Technologies to Support Aging-in-Place for People with Long-Term Disabilities (RERC TechSAge) is a collaborative grant center based at Georgia Institute of Technology, University of Illinois Urbana-Champaign, and Georgia State University. Founded in 2013, TechSAge features multidisciplinary research, development, and training projects that are dedicated to understanding the needs of, and developing supportive technologies for, people aging with long-term vision, hearing, and mobility disabilities.

oon-Jae Lee and Yewon Na pose with the Stretch Robot, handing them their first-place certificate. Kangkyu Kwon not pictured.

Competition Winners Recognized for Innovative Solutions

Student winners of the 2022 Stretch Robot Pitch Competition were recently awarded for their creative concepts for using Stretch, an open-source mobile manipulator robot, to support adults aging with disabilities at home. This year’s competition, sponsored by TechSAge in collaboration with Hello Robot and AI-CARING, was hosted at Georgia Tech, where undergraduate and graduate students from a range of disciplines submitted a brief proposal and pitch video detailing their idea. The winning team (Kangkyu Kwon, Yoon-Jae Phillip Lee, and Yewon Na) proposed integrating virtual reality technology with Stretch to support users with housekeeping tasks that may require assistance, such as grabbing an item or opening a drawer. Congratulations to these impressive students! 

student in labratory setting performing a manual wheelchair fall as part of testing of fall detection device

Featured Article

Developing a Fall Detection Algorithm

Existing automated fall detection devices are lacking in their ability to detect falls among wheelchair users. A new TechSAge article in Assistive Technology highlights the development of a fall detection algorithm, developed in a laboratory setting using machine learning techniques, that can accurately differentiate between wheelchair-related falls and wheelchair mobility activities. Researchers conducted a pilot study wherein 30 young, healthy, and ambulatory adults simulated 258 wheelchair falls and 220 wheelchair mobility activities in a lab with fall data retrieved from accelerometers worn on participants’ wrist, chest, and head. Findings indicate that the algorithm should be integrated into wrist-worn devices and further tested among wheelchair users to evaluate its ability to minimize consequences from falls. Request the full article by Libak Abou, Alexander Fliflet, Peter Presti, Jacob Sosnoff, Harshal Mahajan, Mikaela Frechette, and Laura Rice.

Latest Publications

Digital Assistants

Potential of Digital Home Assistant Devices for Older Adults

Fall Prevention

Mobile Technology for Falls Prevention in Older Adults

Home Environment Design

Understanding Home Activities Challenges of Older Adults Aging with Mobility Disabilities
Ivy Rubio-Ramirez

Staff Spotlight: Ivy Rubio-Ramirez

Ivy Rubio-Ramirez is a senior Architecture student at Georgia Tech and a work-study research assistant at the Center for Inclusive Design and Innovation. Ivy supports the TechSAge team with a variety of clerical tasks, including conducting literature reviews, researching population statistics, automating references in EndNote, and supporting student design competitions. Additionally, Ivy interns at AKA Studio P.C., a local architecture firm. In her free time, Ivy enjoys caring for her plants and binge-watching movies through her movie theater membership.

Woman in a wheelchair filling out a form with a woman standing next to her

Become a Research Participant!

We maintain a registry of names of people who are interested in being contacted about research studies. Opportunities include: surveys, focus groups, interviews, and technology evaluations. Depending on the study, you may be able to participate on the phone, online, on campus, at your home, or in other locations.

Interested in joining? We need to ask a you a few questions about yourself to see which studies you might be eligible for and match your interests with our researchers. Complete the brief survey (5-10 minutes) online here:

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TechSAge research is funded by the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR grant number #90REGE0006-01-00 ). 

NIDILRR is a Center within the Administration for Community Living (ACL), Department of Health and Human Services (HHS).