Projets novateurs réalisés

Intra-operative imagery processing for for computer-assisted interventions

Using wild potato species for blight resistance breeding research

Research and Development of Ultra-portable Modulus Structures

This Mitacs internship program is targeted to recruit a top mechanical engineering student to research and design a state-of-the-art braking system for the Greenheart’s high-speed ziplines. The intern will conduct literature review of different braking systems used in the zipline industry and develop robust numerical models to examine the performance of existing designs. Using the finding from the finite element study, the high stress area of the existing braking system will be identified. These findings will be used to design alternate braking system for Greenheart’s high-speed ziplines. The intern will work with Greenheart personnel to build a working prototype and verify the safety and efficiency of the braking system through experimental testing. Successful development of the braking system will significantly benefit Greenheart’s position as the leader in the eco-tourism company by allowing Greenheart to providing more versatile and safe transportation for its client to access the remote areas in Canada and worldwide.

L2M QC Spring 2025 | Personalized Daily Rhythm Optimizer (Technohealth): Using wearable sensor data to detect an individual’s biological clock and optimize daily schedules for peak mental performance, relaxation, and recovery.

Canada’s healthcare system is facing growing challenges, including rising costs, overworked providers, and limited access to preventive care. At the same time, mental health disorders and chronic diseases are increasing, often linked to disrupted sleep and daily activity patterns. Despite their impact, these disruptions are difficult to track because they rely on self-reports, occasional doctor visits, and expensive medical tests that are impractical for daily use. As a result, early warning signs are missed, leading to worsening health conditions and higher healthcare demands.
TechnoHealth aims to solve this problem by using wearable device data to improve health monitoring. While smartwatches and fitness trackers already collect valuable information, most systems struggle to turn this data into useful insights. TechnoHealth bridges this gap by integrating data from multiple devices, such as Fitbit and Empatica, and applying artificial intelligence (AI) to detect health disruptions before they become serious.
Our innovation has two key steps. First, TechnoHealth organizes and standardizes wearable data, ensuring consistent and reliable tracking over time. Second, it uses AI to provide personalized recommendations, helping individuals improve their sleep, activity, and overall well-being. Unlike traditional tracking apps that only display raw data, TechnoHealth translates this information into meaningful insights that support both users and healthcare professionals.
We have already tested our system with real data, demonstrating its ability to predict changes in sleep and activity patterns. A prototype mobile app has been developed, providing a foundation for further growth. Through Lab2Market, we aim to refine our solution, ensure compliance with privacy regulations, and explore business opportunities. TechnoHealth has the potential to make healthcare more proactive, reduce strain on the system, and help people lead healthier lives.

L2M QC Spring 2025 | Social Worker Safety and Reporting Application – SafeSocial

SafeSocial is a mobile and web application designed to improve the safety and efficiency of social workers during home visits. By providing real-time monitoring, emergency response, and AI-powered incident reporting, the app helps social workers feel more secure and supported in the field. Key features include a panic button, live location tracking, risk assessments, and voice/video recording. This project will benefit social work organizations by enhancing worker safety, reducing administrative burdens, and improving response times in critical situations.

Advanced Methods in Neuroimaging and Applications to Reward Processing

L2M – Automated Weight Monitoring for Free-Range Beef Cattle

The beef cattle industry faces significant challenges in cattle weight monitoring, particularly in free-range systems where traditional methods are labor-intensive, inaccurate, or infrequent. This results in delayed growth, increased feeding costs, and a larger environmental footprint, requiring the development of innovative and sustainable technologies, as well as collaborative efforts. To address this, we propose an automated, non-invasive weight monitoring system that combines vision-based sensors and machine learning to track cattle growth in real time without disrupting farm operations. By providing data analysis and insights, this solution will enable farmers to make data-driven decisions and optimize herd management to sustainably and efficiently improve livestock quality of life and health, optimize resource use, and boost productivity. Through the L2M Launch program, the proposed solution will be refined from a market perspective by tackling specific commercialization challenges and developing a comprehensive business model that reflects the economic and operational realities of the beef cattle industry to ensure product-market fit, while also promoting entrepreneurial skills and enabling research discoveries to move out of the laboratory and be commercialized, thereby accelerating and growing the translation of research excellence to impact the Canadian economy.

Behavioral Analysis Internship: Assessing Gerbil Personalities through Behavior and Vocalizations

Nutrition and Microbiota

Testing of Fibre Properties for their Biomedical Applicability

Natural fibres have been used in many industry sectors such as automobiles, aerospace,
construction, etc., but their use in the biomedical industry is relatively new. The major obstacle to their use is the lack of information on relevant fibre properties. This project focuses on testing three critical properties: antimicrobial properties, antioxidant properties, and water sorption in flax, hemp, canola, and sweet clover fibres. Testing these properties will be a stepping stone for proving the applicability of natural fibres in biomedical applications. This research will provide the industrial partners with data and information regarding the biomedical properties of natural fibres, and can help them open a new door for future research on other natural fibres in biomedical applications.

Auxetic-geometry sleeve of a continuum soft robot for stiffness variation

The project aims to the improvement of a soft robot dexterity by adjusting its stiffness while performing a task, through an auxetic shell. This project will address current limitations in design and control of these types of robots. By combining the expertise of McGill University and CINVESTAV, researchers will explore auxetic geometries, design and manufacturing of pneumatic soft robots, with experimental validation of the resulting stiffness variation. The result of this project will lead to new knowledge, improved soft robot design methodologies, and a stronger foundation for future collaborative research in soft robotics, benefiting both institutions through technological advancement and a fruitful partnership.

Optimization of Carbonyl Produced Powder Metal Based Filaments for Low-Cost 3D Printing – Verification of Printability, Debinding Conditions and Application Potential.

The objective of this project is to create and improve metal-infused filaments for low-cost 3D printers by including recyclable elements. We combine recyclable and bio-based polymers with eco-friendly metal particles, including carbonyl nickel, to provide a durable and sustainable 3D printing material. During the first phase, we produce and test these metal/polymer filaments to ensure they print easily and have equal particle dispersion. Next, we improve the debinding and sintering processes required to convert printed green pieces into solid metal products. By investigating the strength and structure of these completely sintered components, we hope to contribute to a circular manufacturing process that supports recycling and low-cost 3D printing.