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Updated: Oct 20, 2025
Design and Analysis for Fall Detection System Simplification
Published on: April 6, 2020
Insights on an automated fall detection device designed for older adult wheelchair and scooter users: A qualitative
Laura A Rice1, Alexander Fliflet2, Mikaela Frechette2
1Department of Kinesiology and Community Health, College of Applied Health Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Center for Health, Aging and Disability, College of Applied Health Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Background:
Falls are a concern for older adults who use wheelchairs and scooters. Many wheelchair and scooter users require assistance to recover from a fall and often lie on the ground waiting for assistance for 10 min or more. An automated fall detection device may facilitate communication with care partners and expedite recovery; however, there is limited research on the specifications and features of an automated fall detection device preferred by older adults who use wheelchair and scooter.
Objective:
To examine the desired specifications, perceived ease of use and perceived usefulness of an automated fall detection device desired by older adults who use a wheelchair or scooter through semi-structured interviews.
Methods:
Fifteen full-time wheelchair and scooter users (9 females; age: 68 ± 5 years) were interviewed from July to November 2020. Interviews were transcribed, coded, and analyzed.
Results:
Preferred features include wireless charging, a watch form, ability to change the individual who is contacted in the event of a fall, and the ability to disable a notification in the event of a false alarm. Participants felt that an automated fall detection device would be useful and easy to use.
Conclusions:
Older adults who use a wheelchair or scooter indicated the need for an automated fall detection device to facilitate recovery from a fall. Participants reported challenges with previous fall detection devices and the need for specific design requirements to facilitate ongoing use. Participants' insights inform the design of a fall detection device to maximize usability and prevent technology abandonment.
