The mission of the Graham Seed Fund is to strengthen the University’s health system partnerships by providing resources for collaborating directly with a full range of health providers and clinicians.
Round one recipients
Congratulations to ten award recipients who span across five Waterloo faculties. Their partnerships range from local hospitals and provincial health-care providers to industry partners and international universities and organizations.
Alex Wong, Systems Design Engineering
Partner(s): Grand River Hospital
AI for identifying and addressing inequities in the health systems to improve patient outcomes
Artificial Intelligence (AI)-powered data-driven models hold the promise of delivering timely quality care to patients in large healthcare systems. While the pandemic is exacerbating the acute shortage of Canadian healthcare workers, machine learning (ML) models have emerged as a necessary component of healthcare strategies. However, AI algorithms critically rely on historical patient data and records for training. As a result, they can lead to significant model performance disparities for protected attributes (e.g. age, gender, etc.) by: a) reinforcing any historical systemic biases in the data, and/or b) generating unreliable outcomes for under-represented populations. Since Canadian healthcare systems cater to an increasingly diverse populations, identifying such systemic biases, and data reliability risks is key for developing trustworthy healthcare solutions that can complement healthcare workers. Our collaboration with Grand River Hospital aims to carry-out this foundational work, establishing the groundwork for trustworthy AI-driven healthcare for the KW region and Canada.
Anita Layton, Applied Mathematics, Computer Science, Pharmacy and Biology
Partner(s): University of Toronto, University of Colorado, NorthShore University Health System
Clinical risk assessment tool for diabetic kidney disease in youth with type 2 diabetes
Puberty amplifies the risk of kidney injury in youth with obesity and diabetes, yet the mechanisms remain unknown. Puberty is a complex process of physiological changes including neurohormonal activation and drastic organ growth that predispose organs to injury, and the kidneys may be especially susceptible, given their high metabolic demand. During puberty, the kidneys almost double in size and this growth likely increases the kidneys’ already high energy expenditure. However, there is a paucity of kidney physiology studies interrogating the effects of puberty on kidney function in youth with and without pre-existing renal risk factors. To fully interrogate the complex and heterogenous morphometric, metabolic, and hemodynamic changes the kidneys undergo in response to puberty, we seek to integrate multi-dimensional data to identify mechanistic pathways using machine learning, with the goal of developing a clinical risk assessment tool for diabetic kidney disease in youth with diabetes.
Ben Thompson, Optometry and Vision Science
Partner(s): University of Waterloo Optometry Clinic
Enhancing adherence to amblyopia treatment using social robotics
Amblyopia, sometimes referred to as “lazy eye”, is a vision disorder affecting one eye that can lead to permanent vision loss if not successfully treated in childhood. The gold standard treatment for amblyopia involves covering the better seeing eye with a patch for 2-6 hours each day to encourage use of the amblyopic eye. Patching treatment is effective, but it only works if it is applied consistently. Unfortunately, many children and families find it difficult to follow the patching regime. This project will combine expertise in amblyopia treatment, social robotics and engagement with patients and their families to develop a social robot that can enhance understanding of amblyopia and its treatment. The resulting technology will increase adherence with amblyopia therapy and reduce the risk of life-long vision loss.
Charity Oga-Omenka, School of Public Health Sciences
Partner(s): TB Public-Private Mix Learning Network, Institute of Human Virology, Nigeria
Development of a website for TB care linkages between the public and private sector providers in Nigeria
Tuberculosis is a leading cause of illness and death globally with over 10 million infections in 2021. According to the World Health Organization, almost half of those infected were not diagnosed. Nigeria is among 5 countries accounting for most of this gap in diagnosis. Progress towards ending tuberculosis in settings like Nigeria has been hampered by weak linkages between the public sector where most tuberculosis healthcare services are available, and the private sector where most people go to first when they fall ill. Online technologies have the potential to improve TB control in settings like Nigeria, including improved prevention, diagnosis and treatment, laboratory, and national information management systems, contact tracing, and adherence monitoring and support for those infected. Our study will conduct an assessment towards developing a web-based portal to improve tuberculosis surveillance, diagnosis, and treatment in Nigeria.
Dillon Browne, Psychology
Partner(s): Sanctuary Refugee Health Centre, Family Psychology Centre Toronto, Children and Youth Planning Table Region of Waterloo
Virtual Psychotherapy for University Students Enhanced by Natural Language Processing: A Randomized Pilot Study of Artificial Intelligence using the Get A-Head® Software
The goal of this industry partnership is to assess feasibility of a larger trial examining the efficacy of psychotherapy enhanced with natural language processing (NLP) for reducing mental health problems in university students. NLP is an artificial intelligence (AI) approach to analyzing linguistic data. The algorithms are already incorporated into our partner’s cutting-edge platform: Get A-Head®. This innovative health technology was recently backed by the Ministry of Colleges and Universities and will be used to deliver virtual psychotherapy to University of Waterloo students. They will be randomly assigned to virtual therapy enhanced with NLP feedback on emotions for therapists and clients, or the same therapy without NLP (active control). The proposed innovation will promote accessible care for underserved young people, including 2SLGTBQ+, international, and racialized students.
Lili Liu, School of Public Health Sciences
Partner(s): Alzheimer Society of Ontario, CareLective, Mohawk Council of Kahnawà:ke
Acceptance and usability of the GuardIO, a mobile application to support care partners of persons living with dementia
The goal of this project is to examine the acceptance and usability of GuardIO - Family Care, mobile application. It supports persons with cognitive impairment and their care-partners to develop risk mitigation strategies through understanding the patterns of their mobility by leveraging a cloud-based telematics platform licensed by Health Canada. This enables the care-partners to receive timely care and support. This app is developed by WeTraq and available on app stores and SunLife Lumino Health marketplace. It combines GPS and WiFi to provide real-time location monitoring and safety alerts. It does not require additional device other than one’s personal smartphone. Participants are 20 dyads of persons living with dementia and their care-partners (total 40), 30% from an Indigenous community. Increasing prevalence of dementia in Canada calls for strategies like GuardIO to address risks of getting lost and going missing while supporting the health and wellbeing of persons aging in place.
Mahla Poudineh, Electrical and Computer Engineering
Partner(s): Grand River Hospital, McMaster University, Google
A new transdermal patch to continuously and without pain track and treat diabetes
We will develop a new artificial pancreas device (APD) system that is small (~ diameter = 3”) and is capable of simultaneously measuring insulin and glucose levels and delivering the correct dosages of insulin. Our system can be easily applied by diabetic patients, without pain. Our device reaches interstitial fluid (the fluid under the skin) to measure insulin and glucose and deliver insulin to the dermal layer of skin. Our APD system will change diabetes management and prevent diabetic complications.
Mihaela Vlasea, Mechanical and Mechatronics Engineering
Partner(s): St. Mary’s General Hospital, Grand River Hospital
Design of novel glaucoma stent
This work intends to combine the expertise and imagination of the Waterloo engineering team and the guidance of the clinical teams to design a new eye implant to treat glaucoma. Glaucoma is an eye disease that can result in blindness and affects many Canadians; this research intends to improve on existing implant solutions. The Waterloo team is deploying “additive manufacturing” (or 3D-printing) to design a proof-of-concept device to improve the treatment of the disease, leveraging the complex designs possible through the printing technology. This proof-of-concept device will be a crucial step towards future refined iterations that will be clinically tested. The work is an exciting collaboration among engineering, ophthalmology, and optometry that can impact various universities and organizations in Ontario and beyond.
Monica R. Maly, Kinesiology and Health Sciences
Partner(s): Arthritis Society Canada
Electronic-free, closed-loop soft robotic regenerative system for assisting people living with knee osteoarthritis
Over 10 million Canadians will develop osteoarthritis (OA), the most common form of arthritis. OA causes chronic joint pain, restricts mobility and occurs most often at the knee. There is no cure. We will test an innovative robotic system to be integrated within a conventional knee brace as a treatment that improves mobility in people living with knee OA. Our novel robotic system harnesses the energy produced by the leg during walking to deliver forces that counteract abnormal mechanical forces that act on the knee due to OA. Support from the Graham Seed Fund will enable the translation of this proof-of-concept, engineering-focused innovation in the next step toward practically improving healthcare for people with OA.
Veronika Magdanz, Systems Design Engineering
Partner(s): University Hospital Barcelona, University of Balearic Islands, Devicare
Microrobotic chemolytic kidney stone removal
About 10% of Canadians suffer from kidney stones at some point of their lives, with a high recurrence rate of up to 80%. Kidney stones can cause blockage of the urinary tract and severe pain. Conventional treatment of kidney stones involves oral treatment, or laparoscopic surgery, in case of ureter blockage and very large stones. We propose an innovative treatment of kidney stones with the help of small, flexible, wireless robots. These magnetic, millimeter-sized robots enter through a catheter into the ureter, are navigated to the kidney stone by weak external magnetic fields and locally dissolve the stones by chemical reactions. This research will offer a novel, less invasive and more targeted strategy for kidney stone treatment and can be extended to treating other kidney diseases in the future.
Round two recipients
Sirisha Rambhatla, Department of Management Science and Engineering
Partner(s): Grand River Hospital
Good data housekeeping: Building data strategies to make Canadian hospitals AI-ready with Grand River Hospital
This project aims to revolutionize healthcare by making Grand River Hospital "AI Ready." By addressing critical data challenges, the team will lay the foundation for innovative AI-driven solutions in healthcare. Through strategic "Data Housekeeping," we will analyze clinical data collection across departments, identifying both challenges and untapped opportunities. This groundwork is essential for future advancements in healthcare, enabling more responsive and efficient systems. By bridging the gap between current practices and AI-powered healthcare, this project has the potential to transform patient care, improve outcomes, and spark a new era of innovation in healthcare.
Edith Law, David R. Cheriton School of Computer Science
Partner(s): KW4OHT
Newcomer app for health and social service navigation: A field study with KW4OHT
Research shows that immigrants tend to be healthier than non-immigrants upon arrival in Canada, but their health advantage is lost the longer they live in Canada (Newbold, 2006) due to a number of social determinants of health factors. In collaboration with KW4 Ontario Health Team, we have created the Newcomer App – a multi-lingual and hyper-local resource navigation mobile app for immigrants and refugees. With the support of Graham Seed Fund, we will conduct a field study, deploying the Newcomer App to 80-100 newcomers to study the usability and utility of this technology. Our goal, ultimately, is to partner with government and community organizations to deploy the technology to tens of thousands of newcomers, making our proposed technological approach a new standard for addressing newcomers' social determinants of health in Ontario, as well as eventually in the rest of Canada.
Soo Jeon, Department of Mechanical and Mechatronics Engineering
Partner(s): Cambridge Memorial Hospital
Multisensory perception and control for robotic biohazardous material handling at the Cambridge Memorial Hospital
Many clinical lab tasks are time-consuming and could be made easier with robot assistants, reducing the workload for lab technicians. This project explores using robots for two key tasks at Cambridge Memorial Hospital’s diagnostic imaging lab. First, we examine how mobile robots with manipulators can autonomously collect and transport samples, navigating complex environments and handling objects. Second, we aim to automate the safe disposal of biohazardous waste. Both tasks rely on advanced sensors, such as cameras and tactile tools, to help the robots interact with objects and people effectively. Unlike traditional automation systems, these robots are designed to integrate seamlessly into existing workflows, working alongside healthcare staff without disrupting operations. Beyond healthcare, these solutions could also transform tasks in other industries, offering versatile and practical automation options.
Saeed Ghadimi, Department of Management science and engineering
Partner(s): St. Mary’s General Hospital
Pre-surgical appointment scheduling at St. Mary’s General Hospital
This project aims to propose a novel optimization approach for presurgical appointment scheduling that balances virtual and in-person appointments to reduce cancellations. Due to the uncertainty associated with the number of patients and possibly the length of service, our proposed model will be formulated as a stochastic optimization problem for which we provide optimal stochastic approximation algorithms. A successful implementation of our model is expected to facilitate pre-surgical appointment scheduling in St. Mary’s General Hospital. In particular, we will provide an efficient pre-surgical appointment scheduling for the hospital to reduce their current appointment cancellation rate, which has significantly increased over the past two years. While this is a stand-alone project, it can be envisioned as the first phase of a comprehensive initiative involving surgery and follow-up visits scheduling. It also has the potential to be converted into a commercial software that can be modified and used for other hospitals in the region.
Adil Al-Mayah, Department of Civil and Environmental Engineering
Partner(s): Grand River Hospital
Quantifying skin thickness across populations to improve delineation of the skin during radiation treatment planning of breast and head & neck cancers at Grand River Hospital
Radiotherapy (RT) is one of the most widely used cancer treatments. Its accuracy is dependent on the delivery of a calculated dose to the tumor while sparing the healthy tissues. Several organs at risk, including the skin, must be spared by keeping the dose within the dose tolerance limit through optimized planning. However, the skin thickness is often assumed to be between 5 mm to 1 cm, irrespective of the anatomical site treated, sex, and age. This clinical assumption may result in several limitations including under-treating the tumour, which ultimately affects the patient’s health and quality of life. Therefore, the goal of this project is to examine the influence of age and sex on skin thickness at two anatomical sites in a diverse group of participants. Ultrasound imaging will be used to investigate the skin thickness of two different anatomical sites (breast and neck) in a diverse sample of healthy participants, considering the influence of sex and age on skin thickness. Advanced image analysis software will be used for accurate segmentation of the images. This project will inform clinical decision-making on whether age, sex, and anatomical site are important factors to consider at the planning stage to better treat the affected site and it will pave the way for larger studies aimed at implementing automatic delineation of tissues.
Fatma Gzara, Department of Management Sciences and Engineering
Partner(s): Grand River Hospital
Improving door-to-needle time in acute stroke at Grand River Hospital
It is shown that the rapid administration of treatment in ischemic stroke improves clinical outcomes. In particular, the time it takes to administer treatment once the patient has arrived at the Emergency Department with stroke symptoms is called Door-to-needle Time (DTN). DTN time at Grand River Hospital (GRH) has a median of 54 minutes which exceeds the 30-minute target set by the 2022 Canadian Stroke Best Practice Guidelines. The goal of the project is to reduce DTN time so that stroke patients receive treatment within the target. Both behavioral and quantitative research methods using prospective and retrospective data will be applied. The anticipated outcomes are to identify critical factors affecting DTN time and to make recommendations for process improvement. The anticipated impacts are to achieve a significant decrease in DTN time and to meet the Canadian Stroke Best Practice target.
Houra Mahmoudzadeh, Department of Management Science and Engineering
Partner(s): Cambridge Memorial Hospital
Optimal operating room scheduling at the Cambridge Memorial Hospital
A significant challenge faced by CMH is the optimization of the Operating Room schedule with surgical bookings. Current scheduling and booking software lack the ability to forecast surgical caseload, volumes, and demand for inpatient beds and can lead to underutilized resources during certain periods and strain during peak times. This challenge leads to bottlenecks in patient flow and on occasion can lead to overcapacity issues with hospital surgical beds and flow through the Post Anesthesia Care Unit (PACU). This project leverages data analytics, simulation, and optimization tools to maximize operating room utilization. By implementing a data-driven approach, we provide a software solution to proactively identify and address bottlenecks and optimize available OR time. As a result, this project identifies potential issues that lead to surgical backlogs and provides prescriptive actions to increase efficiency, ultimately leading to enhanced patient care.
Yue Hu, Department of Mechanical and Mechatronics Engineering
Partner(s): KW4OHT
Enhancing senior care with social robots: A remote health monitoring initiative with KW4OHT
This project explores the use of social robots to enhance health monitoring for older adults, addressing challenges in traditional caregiving. Leveraging a user-centered design approach, the project focuses on integrating robots that assist with daily occurrences such as medication management and vital monitoring. We will collaborate directly with older adults, caregivers, and healthcare providers to ensure the technology aligns with real-world needs, via interviews and participatory design. The project focuses on enhancing accessibility and fostering engagement to improve health outcomes, ease caregiver burdens, and promote independence among older adults. By introducing interactive and personalized healthcare solutions, it aims to transform senior care and better support aging populations.