Electrophysiological studies of medical cannabinoids on 3D human cerebral organoids and neuroglial cultures

Epilepsy, characterized by recurrent seizures, affects 1% of the population. More than 30% of patients are drug-resistant, a significant burden to their lives. New innovative ways to treat the disorder are needed. Cannabidiol (CBD), a nonpsychoactive compound derived from the cannabis plant, has been shown to be a promising new treatment for epilepsy. In collaboration with Avicanna, we will test the antiepileptic effects of CBD and other cannabinoids alone and in combination with common anticonvulsant drugs on both mouse and human brain tissue.

Translation of recent evidence on the effect of sugars on cardiometabolic health - Year two

The proposed project includes 2 objectives: (1) provision of high quality evidence on the effect of specific food sources of sugars on cardiometabolic risk factors by conducting multiple systematic reviews and meta-analyses (SRMAs), to address the effect of replacing sugar-sweetened beverages with either diet pop or water in a randomized controlled clinical trial, and to analyze and report national data from StatsCan on current sugars consumption, and (2) efforts to translate the evidence from these studies both directly to the public and indirectly through communications to clinicians and pub

Evaluation of microbolometer-based imager for wildfire radiometric imaging

Monitoring of wildland fires through infra-red remote sensing has become increasing of interest to the wildland fire management community, and quality scientific analysis of the capabilities of such sensors is critical if they are to be used in any operational way. In 2019 a joint burning experiment was carried out over several days. In 2019 a collaboration between the Canadian Forest Service, Institut national d'optique (INO), and the University of Toronto saw the ignition and monitoring of a series of experimental fires in the field at a CFS field research station.

User research, design, and creation of an inclusive digital physical and mental wellness game

The physical and mental health of Canadian youth is one of the greatest issues facing the country today. This project partners Mitacs with X Movement to create a digital game that promotes emotional, physical, and social wellness for kids. A special emphasis is being placed on inclusion across many marginalized groups such as disabled people, racialized people, and those in low income communities. The project will follow a three stage format. First, we will consult with users to make sure the digital game can be as inclusive as possible. Second, we will design prototypes of the digital game.

Multi-sensor long-range object detection & classification under challenging perceptual conditions

Autonomous vehicles must be constantly aware of all aspects of the driving environment, and so are typically designed with both omni-directional and long-range forward sensor footprints. The ability to accurately detect, track and predict the motion of distant vehicles and pedestrians along the driving route remains a significant challenge, for today’s state of the art perception methods, however, despite ever-more complex network designs and ever-better sensor configurations.

Innovating Technologies for Reducing Falls Risk in COVID-19 Healthcare Settings

One of the side effects of the COVI D-19 pandemic is that older people in institutional care tend to be more socially isolated and get less physical exercise. This is likely to increase falls risk both directly through reduced strength and balance because of insufficient exercise, and indirectly due to effects of depression leading to reduced awareness of obstacles and trip hazards in the environment. In this project we will test an innovative exercise technology (2RaceWithMe, developed by AGEWELL NCE researchers) to see if it can reduce falls risk in institutional care environments.

Brainstem Arousal System and Chemosensitivity: Novel measures, Modulations, and Relationships to SUDEP

Sudden Unexpected Death in Epilepsy (SUDEP), the commonest cause of death in epilepsy, is the most feared complication. SUDEP usually occurs following a seizure, most often in patients who are non-responsive to antiepileptic drugs. These patients are typically found dead in bed following respiratory apnea and cardiac arrest. Our group has shown that seizures in the brainstem are associated with cardiorespiratory failure and death. It is not known whether the fatal brainstem seizures impair the brainstem arousal system or if seizure directly impairs brainstem cardio-respiratory centres.

Development of Artificial Intelligence Powered Technologies in Computational Pathology to Enable Automated Slide Screening in Whole Slide Imaging - Year two

Advances in Whole Slide Imaging (WSI) and Machine Learning (ML) open new opportunities to create innovative solutions in healthcare and in particular digital pathology to increase efficiencies, reduce cost and most importantly improve patient care. This project envisions the creation of new automated ML tools including the design of a custom Convolution Neural Network (CNN) architecture for whole slide imaging in digital pathology. The custom CNN will be trained to learn different representations of histology tissues so that it can separate healthy from diseased tissues.

Simultaneous Functional Calcium Imaging with Quartet® for studying odor memory circuits and developing second generation Quartet®

Episodic memory refers to an ensemble of memory processes and is the capacity to recollect where and when past events occurred, which involves subjective consciousness and a sense of time in retrieving past experiences. The hippocampus is essential for representing spatiotemporal context and establishing its association with the sensory details of daily life to form episodic memories and the olfactory cortex shares exclusive anatomical connections with the hippocampus as a result of their common evolutionary history. This makes olfaction a privileged sense for accessing memories.

Autonomous Motion Planning for a Safe and Efficient Last Mile Delivery Robot

In recent years, the North American population has become increasingly dependent on food and consumer product delivery. As a result of the current COVID-19 pandemic there have been surges in delivery demand. There are several active driving-based delivery methods, such as Uber Eats, however drivers are required to navigate through traffic, park, turn off their vehicle, exit and walk to the customer doorstep to drop products off. This cumbersome and inefficient final step of the service is known as the last-mile delivery problem.