Innovative Projects Realized

Model for assessment of risks of going missing in persons living with dementia during and post COVID-19 pandemic

According to the Institute for Health Metrics and Evaluation, the number of global deaths and disabilities related to mental health conditions, such as Alzheimer’s disease and related dementias, has risen in recent years. This applies to Canada in the same way, causing premature deaths and disabilities. The general objective of this project is to define, validate and apply a quantitative model that can capture data and generate numerical indicators of risks of going missing, injury and death for people living with dementia, based on the multiple factors identified in the conceptual model proposed by Neubauer and Liu (2020). In this project we will use a transdisciplinary approach of applied research, we will apply exploratory research with an observational design, that includes a critical literature review and a correlational and predictive study with Factor Analysis and Multilevel and Multivariate Linear Regression models. This will help us to understand and determinate the relation between factors and outcomes, and ultimately that will help to assess the risk of a person for going missing.

The Scleroderma Patient-centered Intervention Network (SPIN) COVID-19 Cohort and COVID-19 Home-isolation Activities Together (SPIN-CHAT) Trial

People with the autoimmune disease scleroderma are vulnerable in COVID-19 due to frailty, lung involvement, and immunosuppression; they are representative of vulnerable groups in terms of COVID-19 mental health ramifications. No previous randomized controlled trials have tested mental health interventions during infectious disease outbreaks. We leveraged our existing ongoing cohort of over 2,000 people with scleroderma and existing partnerships to launch a new cohort, the Scleroderma Patient-centered Intervention Network (SPIN)-COVID- 19 Cohort. We enrolled over 800 people in the cohort to assess mental health during COVID-19. The SPIN-CHAT trial is embedded in the cohort and will test a 4-week (3x/week) videoconference intervention that provides social support and positive mental health education. The primary outcome is anxiety symptoms. SPIN-CHAT is being tested among people with scleroderma, but could be used with any population of vulnerable individuals who are isolated and experiencing high levels of anxiety in COVID-19, such as people with pre-existing medical conditions or older persons.

Remote Activity Monitoring and Fall Detection System

Gold Sentintel has built a non-visual fall detection and respiration monitoring product for Long Term Care called ElephasCare LTC. ElephasCare LTC utilizes passive radar sensors to detect residents’ position within their rooms, monitoring motion and respiration, and automatically notifying caregivers in the event of a fall, or lack of respiration. This project looks to enhance the feature set to add temperature and other vital sign sensing – all remotely and autonomously monitored, reducing personal contact with caregivers, promoting physical distancing, and providing early detection for potentially infectious diseases where temperature, respiration or other vital sign metrics are indicative of possible infection.

Assessment and Information Dashboard of COVID 19 Readiness for Canadian Businesses

The project aims to research and develop the most effective way for making COVID 19 guidelines into measurable actions for organizations. This research will enhance Diversio’s Audit tool in two parallel tracks: 1) Methodology for developing sector- and region-specific compliance surveys, translating those survey responses into a scoring methodology, and 2) Technology for automating the process of converting survey responses into a real-time dynamic information dashboard. The research outcomes will provide real-time indicators of preparedness for COVID 19 responses and a tool for employers and employees to conduct just-in-time self-administered compliance checks to identify gaps and improve their responses to COVID 19.

Numerical Performance Assessment of Modular Two-Way Precast Slab Systems

The overarching goal of this partnership is to develop a modular accelerated building construction system that is suitable for implementation into the Canadian marketplace. The use of the post-tensioned, and friction-based, connections for modular system connections is atypical of North American design procedures and the reliance on these connections for resisting sustained gravity loads is generally not supported in existing Canadian building design standards. This research will critically examine the structural performance of such friction-based post-tensioned modular connections and will develop alternative post-tensioned RC connection details that incorporate desired redundancies. These findings will be used to develop system level models to assess the performances of buildings constructed using modular construction technologies. Research outcomes in the form of demonstrable and response-adequate structural performance characteristics for alternative modular building system connection details will enable Envision Integrated Building Technologies to introduce new cost-effective building construction technologies in Canada.

Validation Techniques for an Application Program Interface for Artificial Intelligence Agents Operating on an Internet of Things

This research project will aid in the creation of safe networks of wireless devices, such as security cameras. Computer software using artificial intelligence will watch the networks for problems with the devices or misuses of the networks. In particular, this project will discover ways to ensure that the networks are compatible with the right kind of artificial intelligence software. Smart Talk Beacon, the partner organization, will be creating the protocols for the networks and the artificial intelligence software in order to make sure that both the software and the networks are compatible with each other. They will benefit from this project because it will help them make networks safer, and more secure with the assistance of artificial intelligence software.

Monitoring and Analysis of COVID-19 Acute Respiratory Distress Syndrome on Ventilators

Front-line clinicians have reported that different respiratory stiffness results in different COVID-19 patient conditions on ventilators. In this project, we test and improve NovaResp’s monitoring hardware and analyze the collected data for development of algorithms with focus on respiratory stiffness of patients with COVID-19. The resulting algorithms and monitoring device could lead to determine whether patients need to be intubated, and when under ventilation, what ventilatory settings need to be applied for better patient outcome.

Uplift pipe-soil interaction under inclined ground surface

It is crucial to understand soil-pipeline interaction to be able to design buried pipes against Geohazards. Soil-pipe interaction in the level ground is well established, and the current design practice is based on the assumption that a pipe is installed on a flat ground surface. In reality, however, pipelines often cross natural slopes and sometimes riverbanks. The design of pipes embedded in slopes is different in the way that the inclination of the ground surface has found to affect the soil load significantly. This research aims to characterize the vertical soil load on pipe in a landslide in a dimensionless format convenient for design.

Improving Data Usability and Identification of Inconsistencies in a Unified Healthcare System

The proposed research project will enable a patient’s family doctor or specialist or emergency room doctor to quickly view the patients’ healthcare data most important to view to help the patient at that time. For example, before a doctor prescribes a drug, they can quickly make sure it will not cause problems for the patient when taken with the patient’s other prescriptions. An emergency room doctor can determine if an unconscious patient has any conditions, they should be aware of before treating the patient. For example, allergies to certain drugs or a recent procedure or operation.

The benefit to the partner organization is that they can commercialize the product to create an income stream through multiple healthcare service locations. As well, their staff will gain valuable experience through the implementation of the product to produce other healthcare information services.

Small and Medium Enterprises in a Covid19 context: Ecosystem business intelligence for increased resilience

Covid 19 has deeply disrupted supply chains. Companies face profoundly changing consumer demand, the elimination of entire subsectors of industries due to forced closures, or individual suppliers due to bankruptcy or temporary plant closures due to COVID19 outbreaks. In this environment, continued operations and continued profitability depends on company’s ability to obtain real time information on markets, competitors and their own supply chain.
While many large companies have much of this information, Small and Medium sized Enterprises (SMEs) often do not, substantially limiting their ability to respond to disruptions, and also to adapt to the longer-term structural changes that are anticipated during the recovery / re-imagination phase of the economy.
This project will develop and validate a BI system that will support SMEs during and following the COVID19 disruptions and integrate it into the Bivizio platform currently deployed to agri-food and transportation sectors to increase the resilience of these key sectors to the Canadian economy.

Farm Field Coverage Path Planning for Autonomous DOT Vehicles using Reeb Graphs and Reinforced Learning

The objective of this project is to develop full-coverage path plans for an autonomous vehicle, designed and developed by DOT Technology Corp., operating in a farm field. Conventional methods used in the realm of computational geometry, such as: (a) converting a digital representation of the physical space, i.e., the farm field of interest, to a Configuration space (C-space), where the robot can be seen as a automaton, i.e., a point robot, (b) breaking the C-space representation of the field to cells, via conventional cell decomposition methods, (c) generating the adjacency maps on decomposed cells, and (d) finding the optimal path for each cell that yields the best coverage, lowest number of turns, and minimal overlaps between runs will be investigated.

Digitizing the End-of-Life Final Document Service

During COVID-19, unexpected death has become more commonplace, and many are finding themselves in the unfortunate position of dealing with their loved ones’ estates while continuing to worry about their own health and well-being. In a time where we are asked to stay indoors to protect ourselves and help ‘flatten the curve’, grieving family members are expected to deal with dozens – or even hundreds – of administrative tasks related to the estate of their deceased loved one. Many of these administrative duties are labour intensive, manual processes, whereby executors must print and mail forms, wait in government offices and meet with advisors to sign paperwork.
The goal of this research is to develop a user-friendly software that simplifies the end-of-life final document service and reduces manual work and in-person contact during the bereavement period. The project will involve an environmental scan of the political, technical, business and regulatory landscape surrounding the digitization of service delivery in Canada. Drawing on user-centered design (UCD) theory, user needs assessments, service design sessions and usability testing will be conducted to inform the development of the solution.