Babak Taati, PhD PEng, is a Scientist at KITE | Toronto Rehab – UHN and an Assistant Professor at the University of Toronto. His research applies computer vision technologies to continuous health monitoring and the management of chronic conditions. A major focus of his work is to move away from the laboratory and contrived situations, and to develop devices that work reliably in the home or in long-term care. Examples include affordable pain assessment technology to continually monitor people with advanced dementia who cannot verbally express their pain and automated fall risk assessment based on changes in gait.
- The feasibility of a vision-based sensor for longitudinal monitoring of mobility in older adults with dementia. E Dolatabadi, YX Zhi, AJ Flint, A Mansfield, A Iaboni, B. Taati - Archives of gerontology and geriatrics, 2019.
- Algorithmic Bias in Clinical Populations–Evaluating and Improving Facial Analysis Technology in Older Adults with Dementia. B Taati, S Zhao, AB Ashraf, A Asgarian, ME Browne, KM Prkachin, A Mihailidis, T Hadjistavropoulos. - IEEE Access, 2019.
- Vision-based assessment of parkinsonism and levodopa-induced dyskinesia with pose estimation. MH Li, TA Mestre, SH Fox, B Taati - Journal of neuroengineering and rehabilitation, 2018.
- Automated assessment of levodopa-induced dyskinesia: Evaluating the responsiveness of video-based features. MH Li, TA Mestre, SH Fox, B Taati - Parkinsonism & related disorders, 2018.
- Automatic detection of compensation during robotic stroke rehabilitation therapy. YX Zhi, M Lukasik, MH Li, E Dolatabadi, RH Wang, B Taati - IEEE journal of translational engineering in health and medicine, 2017.
Honours and AwardsName:
- Top ranked grant and distinction as the 2018 Dr. Tony Hakim Stroke Research Award, Canadian Partnership for Stroke Recovery 2018
- TRI-UHN Best Paper Award 2017
- Best Poster Presentation Award, IEEE Conference on Automatic Face and Gesture Recognition (FG19), May 2019.