Falls are a significant concern for older adults who use wheelchairs and scooters, as many require assistance to recover from a fall. In the event of a fall, automated fall detection devices could immediately notify care partners and expedite recovery. However, existing fall alert devices on the market are designed for ambulatory individuals, and there are currently none validated for wheeled device users. As a preliminary step in developing a fall detection and alert device for this population, TechSAge researchers explored user preferences on the ideal design of these devices. A new article in Disability & Health Journal highlights findings from interviews with older adults who use wheelchairs or scooters on their desired specifications for a fall detection and alert device and their perceptions about ease of use and usefulness. Read the full open access article by Rice, Fliflet, Frechette, Brokenshire, Abou, Presti, Mahajan, Sosnoff, and Rogers.

Maya Dye is an undergraduate research assistant for the Human Factors and Aging Laboratory at the University of Illinois Urbana-Champaign. With TechSAge, Maya supports the Aging Concerns, Challenges, and Everyday Solution Strategies (ACCESS) Study, which explores the everyday challenges of older adults with long-term disabilities. In this study, Maya is involved with screening, administering questionnaires, and interviewing participants whose hearing loss was acquired after the development of speech (late-deafened). Maya also supports the TechSAge Participant Registry by running queries in the database to identify individuals who may qualify for research studies. Maya is studying Speech and Hearing Science with the goal of becoming a speech-language pathologist. In Maya’s spare time, she enjoys exercising, spending time with friends and family, and getting outdoors when the Illinois weather permits.