Signal Processing | TMU Multimedia Research Laboratory

Stress Classification From ECG Signals Using Vision Transformer

Mon, 02 Feb 2026 00:00:00 +0000

Intelligent Analysis of Intestinal Ultrasound

Sun, 05 Oct 2025 00:00:00 +0000

Overview

Collaborating with Dova Health Intelligence, the team will develop AI algorithms for segmentation and analysis of intestinal ultrasound to improve speed and accuracy of Inflamatory Bowel Disease (IBD) assessment.

Funding

NSERC Alliance + Mitacs Accelerate - $120K

Multimodal Affective Computing

Mon, 05 Apr 2021 00:00:00 +0000

Overview

Collaborating with Shaftesbury (now Wellwave Inc.), we will develop a machine learning model for mutlimodal assessment of stress. The multimodal sensors can be physiological (e.g. EEG, heart-rate) and behavioural (e.g. facial expressions). The target is to use the assessed stress for Shaftesbury’s Positive Distraction Entertainment System which adapts game content dynamically to reduce stress in children before a complex medical procedure, which can reduce complexity and recovery time.

Funding

NSERC Collaborative Research and Development Grant (CRD) - $450K
NSERC Alliance + Mitacs Accelerate Grant - $488K
New Frontiers in Research Fund - Exploration - $250K

De-escalation training for emergency responders

Thu, 01 Apr 2021 00:00:00 +0000

Overview

In partnership with the Ontario Provincial Police, the project will create adaptive scenario-based VR training experiences using multimodal sensing to dynamically respond to trainee behaviour in real time. The interdisciplinary team includes:

Dr. Natalie Alvarez (School of Performing Arts) — narrative design and embodied learning
Dr. Jennifer Lavoie (Criminology, Wilfrid Laurier University) — crisis intervention expertise

Funding

New Frontiers in Research Fund - Exploration - $250K
NSERC Alliance COVID-19 - $50K

Intelligent Analysis and Visualization of IoT Signals for Medical Emergency

Tue, 01 Jan 2019 00:00:00 +0000

Overview

In collaboration with Dapasoft Inc., this project develops new information processing tools and techniques to enhance emergency medical services. The system utilizes various IoT sensors to record patient symptoms, analyzes the data with machine learning, and presents results through immersive context-aware visualization methods — helping healthcare professionals perform timely decision-making in emergency situations.

Collaborators

Dapasoft Inc.

Funding

NSERC Collaborative Research and Development Grant (CRD) — $669K