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IATSL develops assistive technology that is adaptive, flexible, and intelligent, enabling users to participate fully in their daily lives. Learn more about our research

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Projects

Automated pain assessment for older adults with dementia

Keywords: Automated, pain assessment, dementia.


Overview of Research

Although pain is very frequent in older populations, older adults are often undertreated for pain. This problem is especially serious for older persons with serious dementia (e.g., Alzheimerís Disease), who live in nursing homes and cannot report their pain because of cognitive impairments that accompany dementia.

Nursing staff acknowledge the challenges of effectively recognizing and monitoring pain in this population. Effective approaches to pain assessment for people with dementia, based on observation of specific pain behaviours (e.g., certain grimaces), are available but nursing homes often lack the human resources and, sometimes, expertise to use these assessment approaches on a regular basis.

We are developing a vision-based technology to unobtrusively monitor residents in dementia long-term care (LTC) and to automatically detect pain in individuals with severe dementia who cannot communicate their pain. Our technology will then automatically alert a nursing staff who could attend to the person. We will offer this technology in the form of hardware specifications (e.g. camera specs, specs for camera placements, computing specs), and software (artificially intelligent algorithms that process facial expressions in video and identify pain in real-time; as well as software to send alerts to a nursing staff). This will be an affordable technology that will facilitate regular pain assessment with minimal resources, based on list of valid pain-related behaviours.


Research Team

Babak Taati, Toronto Rehabilitation Institute

Ahmed Ashraf, University of Toronto

Azin Asgarian, University of Toronto

Greg Marchildon, University of Toronto

Kenneth Prkachin, University of Northern British Columbia

Michael Li, University of Toronto

Michelle Lukasik, Toronto Rehabilitation Institute

Paul Budnarain, Toronto Rehabilitation Institute

Shun Zhao, Toronto Rehabilitation Institute

Thomas Hadjistavropoulos, University of Regina


Funding Sources

AGE-WELL Canada's Technology and Aging Network