Phase: |
Workpackage |
Theme: | Technology for Maintaining Good Mental and Cognitive Health (WP6 TECH-MCH) |
Type: | Research |
Status: | Active |
Start Date: | 2017-06-30 |
End Date: | 2017-06-30 |
Project Leader |
Rudzicz, Frank |
Project Overview
Clinical measures of cognition typically rely on time-consuming, subjective and expensive assessments. However, our recent advances in computational linguistics, signal processing, and machine learning now allow for objective, automatic, and rapid analysis of cognition, through speech. Our prior work has focused on binary classification problems between people with or without a particular disorder, such as Alzheimer’s disease. In this grant, we will use these modern tools to objectively assess cognition, differentially in people with post-stroke aphasia and memory impairment, by measures of speech and language at 5 time points. This will be applied to a new technological medium – the telephone, which will allow for broader data collection and unique insights in human-computer interaction.
Dr. Frank Rudzicz leads this project, with two industrial partners: WinterLight Labs, and CBI Health Group. WinterLight Labs will supply speech-based assessment to support data collection and data analysis. Patients will be recruited at CBI Health Group clinics, and clinical assessment will be provided by Drs. Regina Jokel and Andrea Iaboni. Research will be conducted at the Toronto Rehabilitation Institute, the Rotman Research Institute at Baycrest, and the University of Toronto.
Our primary objective is to validate the computational speech-based assessment techniques relative to current gold standard assessments. This will involve modern machine learning that is more incisive than the current state-of-the-art. This will be accomplished within two elicitation platforms: a traditional web-based interface, and a phone-based interface. Optimizing the latter is crucial in order to establish the feasibility of using this platform across as wide a population as possible.
In the short term, this project will 1) validate current automatic cognitive assessments, 2) create a new industrial collaboration between a large healthcare network and a local technology startup in Canada, and 3) further our understanding of cognitive function in different patient populations among older Canadians.
Outputs
Title |
Category |
Date |
Authors |
Multi-view representation learning via GCCA for multimodal analysis of Parkinson's disease | Scientific Excellence - Advancing Knowledge | 2017-01-01 | J.C. Vasquez-Correa |
On the impact of non-modal phonation on phonological features | Scientific Excellence - Advancing Knowledge | 2017-01-01 | M. Cernak |
Speech interaction with personal assistive robots in the home for people with Alzheimer's disease Toronto Rehab Institute, University Health Network | Scientific Excellence - Advancing Knowledge | 2016-10-01 | Frank Rudzicz |
12th annual Andreae Alzheimer Lecture (the Alzheimer Society)Invited talk on behalf of the Alzheimer Society Toronto Rehab Institute, University Health Network | Scientific Excellence - Leadership | 2017-06-19 | Frank Rudzicz |
Identifying and avoiding confusion in dialogue with people with Alzheimer's disease | Scientific Excellence - Advancing Knowledge | 2017-01-01 | Hamidreza Chinaei |
WP6 Face to face meeting (in Winnipeg, Manitoba) University of Alberta, University of Toronto, University of Regina, Toronto Rehab Institute, The KITE Research Institute at University Health Network, Toronto Rehab Institute, University Health Network, Bruyère Research Institute, Simon Fraser University, Toronto Rehab Institute/University of Toronto, Bruyere Research Institute, University of Waterloo | Networking and Partnerships | 2017-10-18 | Lili Liu, Eleni Stroulia, Mark Chignell, Thomas Hadjistavropoulos, Babak Taati, Frank Rudzicz, Frank Knoefel, Zahra Moussavi, Sylvain Moreno, Andrea Wilkinson, Tiffany Tong, Peyman Azad-Khaneghah, Victor Fernandez, Dillam Romero, Azin Asgarian, Ahmed Ashraf, Natasha Gallant, Erin Browne, Caroline Ethier, Christine Daum |