D2. Monitoring and Managing Falls

Principal Investigator

Laura Rice, Ph.D.


Jacob Sosnoff, Ph.D., Peter Presti, MSCS, Harshal Mahajan, Ph.D., & David Peeler, B.S.


Lauren Komrska, Sydney Steinkellner, & Malaak Yehya, B.S.


Permobil, AB; Post-Polio Health International; Illinois Community Health and Aging Collaborative


Falls are common among wheelchair users and can result in injury, added challenges with daily activities, and admissions to hospitals and long-term care facilities. We are developing a system that will accurately detect falls from wheelchairs to automatically alert caregivers or emergency professionals who can quickly respond to help. This will be accomplished through measuring acceleration patterns to detect a fall from a wheelchair and developing, refining, and evaluating a prototype for a customizable fall detection system. We will develop and test the prototype with the long-term goal of improving fall outcomes and recovery for wheelchair users.

woman getting off electric scooter to use crutches

electric scooter control pad

female using wheelchair in kitchen

Project Status

Our team recently shared the first iteration of the fall detection device with community-dwelling adults for usability and feasibility testing. Quantitative data collected during its use and qualitative data following its use are informing necessary changes to the device’s design and algorithm. The development of a compatible smartphone application is underway to allow for user interface with the device. Community testing of the second iteration will begin shortly!

In the video below, a student does a controlled, backwards fall from a wheelchair in the laboratory setting as part of an effort to measure acceleration patterns of different types of falls among wheelchair users.

Check out our project poster presented at the 2022 TechSAge State of the Science. This poster depicts the series of events that occur when a fall experienced by an individual using a wheelchair or a scooter is detected using the newly developed fall detection system.

Screenshot of poster "Monitoring and Managing Falls"

Select Publications

Abou, L., Fliflet, A., Presti, P., Sosnoff, J., Mahajan, H., Frechette, M., & Rice, L. (2023). Fall detection from a manual wheelchair: preliminary findings based on accelerometers using machine learning techniques, AssistiveTechnologyhttps://doi.org/10.1080/10400435.2023.2177775.

Rice, L.A., Fliflet, A., Frechette, M., Brokenshire, R., Abou, L., Presti, P., Mahajan, H., Sosnoff, J. Rogers, W. A. (2022) Insights on an Automated Fall Detection Device Designed for Older Adult Wheelchair and Scooter Users: A Qualitative Study. Disability and Health Journal, 15(1), Supplement. https://doi.org/10.1016/j.dhjo.2021.101207 

Abou, L., Fliflet, A., Hawari, L., Presti, P., Sosnoff, J.J., Mahajan, H.P., Frechette, M.L., & Rice, L.A. (2021) Sensitivity of Apple Watch fall detection feature among wheelchair users, Assistive Technology, https://doi.org/10.1080/10400435.2021.1923087 

Rice, L.A., Yarnot, R., Peterson, E.W., Backus, D., Sosnoff, J.M. (2021) Fall Prevention for People with Multiple Sclerosis Who Use Wheelchairs. Arch Phys Med Rehabil. 2021 April; 102 (4): 810-804. doi: 10.1016/j.apmr.2020.10.107

Sung J, Shen S, Peterson EW, Sosnoff JJ, Backus D, Rice LA. Fear of Falling, Community Participation, and Quality of Life Among Community-Dwelling People Who Use Wheelchairs Full Time. Arch Phys Med Rehabil. 2020 Dec 22: S0003-9993(20)31321-6. doi: 10.1016/j.apmr.2020.11.013.

Rice, LA., Sung, JH., Keane, K., Peterson, EW, Sosnoff, JJ. (2020) A Brief Fall Prevention Intervention for Manual Wheelchair Users with Spinal Cord Injury: A Pilot Study. J Spinal Cord Med. 2020, Sept; 43 (5): 607-615. doi: 10.1080/10790268.2019.1643070

Rice, L. A., Sung, J. H., Peters, J., Bartlo, W., Sosnoff, J. (2019). Perceptions of fall circumstances, recovery methods and community participation In manual wheelchair users. American Journal of Physical Medicine and Rehabilitation10.1097/PHM.0000000000001161

Sung, J., Trace, Y., Peterson, E., Sosnoff, J., Rice, LA. (2019) Falls among fulltime wheeled mobility device users with spinal cord injury and multiple sclerosis: A comparison of characteristics of fallers and circumstances of falls.  DisabilRehab 2019 Feb; 41(4): 389-395 doi: 10.1080/09638288.2017.1393111.

Rice, L.A., Peterson, E.W., Backus, D., Sung, J.H., Yarnot, R., Abou, L., VanDenend, T., Shen, S., Sosnoff, J.J. (2019) Validation of an Individualized Reduction of Falls (iROLL) Intervention Program Among Wheelchair and Scooter Users with Multiple Sclerosis.  Medicine. 2019 May; 98(19): e15418 doi: 10.1097/MD.0000000000015418.

Rice, LA., About, L., vanDenend, T., Peterson, E., Sosnoff, J.J. (2018). Falls among wheelchair and scooter users with multiple sclerosis. US Neurology, 14(2): 82-7. 10.17925/USN.2018.14.2.82
Rice, L.A., Sung, J.H, Peters, J., Bartlo, W., Sosnoff, J. (2018). Perceptions of fall circumstances, injuries and recovery techniques among power wheelchair users. Clinical Rehabilitation 32(7) 985-993. 

Project Alumni

Libak Abou, Ph.D., Alex Fliflet, B.A., & Mikaela Frechette, Ph.D.

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