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.
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.
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.
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.
The proposed research is a collaboration between Virtro and SFU’s iVizLab to collaboratively work on ways to understand the processes involved in analyzing and visualizing 3D spatial data. iVizLab’s research focuses on AI based computational models, in this case a data visualization tool that help users analyze 3D spatial data. In creating this user interface, the iVizLab will help teachers find insights and make sense of the errors their students do in a VR training simulator to provide personalized feedback to each student.
Design data is broadened beyond specifying built-environments to support evidence-based decision-making in the early phases of design. For using data, designers usually rely on specialized data visualizations. There is a need for interfaces specifically tailored for reporting designs with their form and performance data to and for seeking feedback from the other stakeholders who are not directly involved in design. Given their diversity and complexity of the design data, such interfaces are hard to develop.
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.
The research project aims to discover the experience of two user groups interacting with a prototype developed by HealthQb. The user groups are patients suffering from anxiety, chronic pain and/or infertility, and their allied health practitioners, such as chiropractors, kinesiologists, naturopaths, osteopaths and physiotherapists.
Generative design involves creating a large number of design alternatives. It is emerging as a frequently used computational design paradigm in exploring alternative designs. The practical use of generative design demands evaluating the alternatives generated using their form and performance data. We propose to further develop DesignSense, a design (data) analytics tool from the Computational Design Lab and experiment with its use during generative design workflows at Perkins and Will.
This research is focused on the design and development of a new digital platform for capturing energy and environmental performance data from building systems. Through interviews with key UBC staff and researchers this research will heavily focus on identifying matches between the key pains, reasons and capabilities needs of building owners and municipalities and new information technology features and functions.