Silicone-mounted fiber-Bragg grating sensor for cardiac pulse-waveform monitoring

Cardiovascular disease (CVD) is a major cause of morbidity and mortality internationally. Current CVD diagnostics are limited to basic tools that provide a generalized number without quantitative indication of overall health, such as blood pressure, or lifestyle risk scores. More invasive diagnostic imaging can be done, but at great cost to the healthcare system. We have developed a basic optical device capable of non-invasively studying the cardiac pulse-waveform, thus potentially allowing for direct measures of cardiovascular risk and health.

Novel Adhesive For Use In Sternal Fixation and Application

Median sternotomy is the standard approach in heart surgery. Over 1.5M operations are performed worldwide annually; 45K in Canada. Wires are used post-operatively to close the sterna, leading to instability, micro-motion and pain. Alternative techniques lack effectiveness or are cost prohibitive. Glass polyalkenoate cements (GPCs) are used in restorative dentistry, orthodontics and ear, nose and throat surgeries.

Investigation into methods and materials to simulate neuroanatomical structures for MR Imaging applications

During their tenure at Preoperative Performance Inc. the interns will focus on the research, design, fabrication and testing of a number of novel MRI phantom assemblies to be used as calibration equipment and research tools for diffusion weighted imaging systems. The conclusions drawn from this research will contribute to interventional planning to provide better healthcare to patients suffering from several conditions including brain tumours, TBI, and neurodegenerative disorders.

Real-time food analysis using deep learning for Diabetes Self -Monitoring

Our proposed research is to create an algorithm capable of pre-evaluating diabetes patients’ meals before they consume them with the snap of a picture. We are attempting to accomplish this goal by employing AI, machine learning as well as computer vision for real-time analysis. Our goal is to analyse a users meal to return an accurate carb count and offer portion size adjustments to reduce their blood sugar fluctuations.

Detargeting Protein-Protein Interactions For Cellular Design Applications, Using 3D Structure-Based Deep Learning Models

Rational protein design has had a tremendous impact on pharmaceutical, agriculture, and chemical industries over the past 30 years, by focusing exclusively on individual proteins and their intrinsic activities. The next generation of protein design tasks will seek to modify function inside living cells, competing and interacting directly with pre-existing cellular machinery. Modifying systems in living cells will open a new wave of biotechnology applications, such as living drug implants and diagnostic tools.

PATH: Program to Accelerate Technologies for Homecare

Most people would like to continue living in their own homes as they age. A new ecosystem is needed to enable home health technologies to be developed, tested and successfully commercialized. This will require a program that provides a low-cost way for developers to test their products before introduction to the market. Therefore, in our Program to Accelerate Technologies for Homecare (PATH), the intern will develop a novel versatile connection protocol that will connect different devices and sensors to a single hub.

A novel multi-echo MRI technique for prostate cancer detection and grading

We propose to develop a novel, clinically relevant MRI based technique for prostate cancer detection. We also propose to develop a novel reporting system that would be more accurate and easier to use by the radiologists. The new technique will be first developed on a research MRI scanner at UBC, and subsequently implemented on the clinical MRI scanner at VGH. The main benefit to the hospital will be a new, improved MRI technique for prostate cancer detection and grading.

Developing an Efficient Ensemble Machine Learning Model for Evaluating Construction Project Bidding Quality and Optimal Winning Strategies

PledgX is interested in building a solution that aims to optimize the bidding process to maximize key performance indicators for contactors and vendors. For bidding optimization, several strategies and methods have been proposed; however, with the massive amount of available bidding datasets, the quality and performance of such methods are questionable. Machine learning introduces intelligent solutions to optimize the bidding decision, however these solutions are applicable to a range of prediction or classification tasks.

Development of a Deep Learning algorithm to improve the image quality of the pictures taken by Quartet® real-time

1 in 5 people suffer from a mental illness, such as depression, Alzheimer’s & Parkinon’s during their lifetime. Currently, there are no treatments for these diseases, because the underlying causes of these diseases is not known. Neurescence has developed a technology that is essential for understanding how local and long-range neuronal circuits form to create healthy brain function, hence understand how these neuronal circuits are disrupted in each disease.

Feasibility of physiological assessment for objective confirmation of non-invasive electrical recruitment of the saphenous nerve

Overactive bladder, urinary urgency, affects 14-18% of the Canadian population and costs our health care system over $350,000,000 annually. Most current treatments require ongoing in-person support or have low adherence rates, enhancing greater strain on our healthcare system and economy. Non-invasive saphenous nerve stimulation (nSNS) overcomes these issues however there is currently no objective method of confirming whether patients can activate the saphenous nerve during each treatment session.