Evaluating Human Interaction with MMM: A Creative AI System for Music Composition

Although research focusing on developing AI-based systems is well established, research which investigates the user-experience of persons who interact with these systems is still in its early stages. This developing field will continue to be an important area of research, as AI-based systems are increasingly being integrated into various workflows across all disciplines. Our research focuses on the integration of a generative music system into the Cubase Digital Audio Workstation, which will allow users to collaboratively compose music with the system.

Body pose estimation using Mocap data acquisition

Recent advances in wearable devices have allowed athletes to monitor some determinant factors of their sport performance. In addition, they can be used to develop real-time 3D avatars of people to compete with them during dynamic activities. Kinetyx recently developed insoles with multiple sensors that can be worn within a shoe while performing many activities. These sensors can monitor the loading and kinematics of individuals during outdoor activities as well as identify the type of activity.

Cognitive effects of individualized lifestyle interventions in typical ageing

With a predominantly ageing population around the globe, we have seen a shift in ageing–focused research from a disease-oriented to a health-oriented approach. Planned, large-scale longitudinal and cross-sectional studies of ageing have generated multimodal databases. These data have advanced multi-level and interdisciplinary research on the interactive effects of behaviour, biology, social environments on well-being as people age. As a result, researchers have the unique opportunity, as never before, to study these factors.

Empathic Conversational AI Agent for pain understanding and management

Currently in Canada, 8 out of 10 Canadians have ongoing musculoskeletal pain preventing from doing regular day to day activity, and looking for solutions for their pain. The proposed research is aimed to create a conversational chatbot that can engage in empathetic conversation to examine the effect of empathic conversation in engagement and pain management in users, by evoking self reflection and self-awareness in the user.

Investigating the effect of the Virtual Meditative Walk on brain in chronic pain conditions: A longitudinal fMRI study - Year two

The Virtual Meditative Walk (VMW) (1) is a well-developed therapeutic protocol that can be used alone or in combination with the Mindfulness-Based Stress Reduction techniques in an Immersive Virtual Reality (IVR) environment. It has been shown to be effective in reducing pain levels in patients with chronic pain (CP); however, little is known about how IVRs such as VMW may affect pain processing networks in the brain.

Scalable Chatbot Framework for Multi Layered Chatbots and Memory.

The general objective of this research project is to develop a new natural and empathic chatbot by integrating the transformer and intent-based systems. The goal is to implement a system for expressive 3D interactive characters that can move between the structure of an intent-based system with specific Question and Answer pairs and the more open-ended smart system of the Transformer. Most currently existing chatbot systems are limited in their abilities to engage in open-ended and natural dialogues with human users.

Benefits and Challenges of using a Digital Health Platform for Remote Delivery of Allied Health Provider Services

The proposed research is aimed at understanding and predicting the adoption rate for a proposed commercialized platform, based on the HQB Prototype, and for providing essential insights into the user experience by both user groups of the HQB Prototype that will be included in the design specifications for the commercialized product.

HealthQB has been researching indications of the parasympathetic nervous system and wellbeing of chronic pain patients in allied health since 2018.

Project ABCI: Authorization, Booking and Coordination Internships for widespread Testing and Vaccination for COVID-19

Ensuring efficient and effective disease testing during a pandemic requires the integration and automation of complex, versatile assessment, scheduling, and planning tools. Project ABC, funded by Canada’s Digital Technology Supercluster, will deploy technologies that enable the BC health system to deliver a high volume of COVID-19 tests to the patients who most urgently need them, and when available, vaccination/immunization. This MITACS proposal, Project ABCI, is the companion internship package led by SFU faculty Gromala and Shaw and three interns.

Visual Analytics Methods to Support Sensemaking under Ambiguity in Avalanche Forecasting

Analysis of complex systems involves much more than what is evident in data alone. Background knowledge and experience are used to inform interpretation. Often this results in ambiguity, a state where multiple potential interpretations must be considered and evaluated. When analysis is shared these challenges are compounded by the complexity of communication. Ambiguity is common in avalanche forecasting.

Investigating Machine-Learning-Based Mocap Data Augmentation for Live Performance

This project is a collaboration between researchers from the Simon Fraser University and industry partners, Lifelike & Believable Animation Design and Animatrik Film Design. Its goal is to research and develop machine learning techniques for capturing and analyzing movement data in real-time to support the world’s first immersive in-game 3D simulcast of a live, real-time motion-capture circus performance, featuring death-defying physical performances and stunning, cinematic quality visuals.