TRANSFORM HF’s Trainee Awards support University of Toronto graduate students and postdoctoral fellows who are conducting research that focuses on new approaches and models of care to address heart failure and inequities in care.
To learn more about our Trainee Awards, visit our Opportunities page.
2023 Trainee Awards
Wearable Textile-Based Remote System for Long-Term Lung Fluid Monitoring for a Pulmonary Congestion Population
Ivana Culjak, postdoctoral fellow at KITE Research Institute
Supervised by: Drs. Azadeh Yadollahi and Darshan Brahmbhatt
Ivana is developing a wearable technology to monitor flood buildup in the lungs, or pulmonary edema, which is a common symptom of worsening heart failure. She hopes that if patients and their clinicians are aware of edema at an early stage, there will be more time for changes in treatment to ultimately keep patients out of hospital and living well. Ivana’s system will be designed for continuous monitoring over an extended period of time, enabling healthcare providers to monitor the progression of pulmonary edema and make care decisions in real-time.
This monitoring system has the potential to reduce healthcare costs by enabling preventative treatment and thereby reducing hospitalizations. Additionally, the use of a wearable design makes the system comfortable and customizable for patients. Moreover, the proposed system is unobtrusive, unlike the current standard method for monitoring pulmonary congestion which requires an implantation procedure.
The end product of Ivana’s research will be a battery-powered, energy-efficient, compact, and lightweight device accompanied by software capable of accurately acquiring, processing, and wirelessly transmitting information to a third-party device for storage and further analysis.
Developing and Validating a Textile Based Wearable to Manage Sleep Apnea in People with Heart Failure
Delaram Sadatamin, PhD student, Institute of Biomedical Engineering
Supervised by: Drs. Azadeh Yadollahi and Quynh Pham
Did you know approximately 50% of people living with heart failure also experience sleep apnea? This may be due to a gravitational overnight shift of fluid from the legs to the neck and lungs. Despite this high prevalence, there is a lack of accessible and user-centered solutions for diagnosis and monitoring of sleep apnea. Rather, it’s commonly assessed with in-laboratory or at-home polysomnography, which is uncomfortable, requires technical expertise, and has long waitlists; additionally, it fails to measure overnight changes in body fluid.
Delaram aims to develop and validate a smart textile that can collect physiological data to ultimately monitor fluid levels and sleep apnea in people living with heart failure. This technology will not only require less effort to use than polysomnography, but will also monitor fluid accumulation. Delaram believes this information will help us better understand the connection between sleep apnea and heart failure.
The results of this study could help facilitate optimum treatment for managing sleep apnea in people living with heart failure, leading to better health outcomes and improved quality of life.
Medly Caretown: An equitable, culturally inclusive, and family-centered digital health intervention to support patient-caregiver dyads living with heart failure
Ting Xiong, PhD student, Institute of Health Policy, Management & Evaluation
Supervised by: Drs. Quynh Pham and Lindsay Jibb
Technology has the ability to support healthcare delivery and improve clinical outcomes for people living with heart failure. However, these benefits are not experienced equally by all. Specifically, there is an increasing need for access to equitable healthcare in ethnic and aging groups.
An emerging model of disease co-management by patients and family caregivers (care dyads) is shedding light on a more ethnically inclusive and family-centered approach to heart failure care. Ting’s research aims to build upon this model by further developing a culturally inclusive digital health intervention for heart failure care dyads under Medly Caretown. In collaboration with diverse community partners and people with lived experience, she will develop and test the intervention.
Ting hopes that Medly Caretown will serve as a conceptual model to design and adapt family-centered interventions for improved healthcare services for the growing Canadian population of patients with chronic diseases. Her findings specifically will generate actionable and replicable knowledge to foster more equitable, resilient, and sustainable heart failure care.
A Wearable Diaper Sensor for Urinary Biomarkers of Pediatric Heart Failure
Kevin Da, Master’s Student, Insitute of Biomedical Engineering
Supervised by: Drs. Xinyu Liu, Aamir Jeewa, and Craig Simmons
Heart and kidney health is a careful balancing act: Dysfunction of one organ often leads to the dysfunction of the other. In pediatric heart health, this balance is even more delicate.
Acute kidney injury occurs in 30-50% of pediatric individuals after cardiac surgery, necessitating ongoing monitoring. However, conventional monitoring of kidney function relies on blood biomarkers. Blood draws are challenging for pediatric outpatients and in remote communities, placing significant burden on families and caregivers. Urine-based biomarkers are a promising alternative to blood biomarkers, as samples can be easily collected. As such, diaper-based sensors could enable remote and proactive monitoring, improving health autonomy and patient family empowerment.
Existing diaper-based urine sensors have been poorly adopted because they fail to address user needs. In this project, Kevin will develop a wearable sensor for diapers to remotely monitor kidney function in pediatric patients recovering from heart surgery at home. The technology Kevin develops and the knowledge he generates through co-development with people with lived experience will support patient-centered digital health solutions to improve pediatric heart care.
2022 Trainee Awards
Development of SafeSleep, a smart, accessible, and convenient textile-based technology for remote monitoring of sleep apnea and heart failure at home
Ahmed Elwali, postdoctoral fellow at KITE Research Institute
Supervised by: Drs. Azadeh Yadollahi and Daniel Franklin
Sleep apnea is a disorder that causes breathing to repeatedly stop during sleep. The disorder affects 10% of adults, leading to reduced blood oxygen and a quadrupled risk of heart failure. When untreated, sleep apnea may double heart failure mortality rates.
Ahmed’s project responds to the need for further monitoring of sleep apnea in those living with heart failure. He aims to develop and validate a smart textile, SafeSleep, to diagnose sleep apnea, investigate its interrelationship with heart failure, and continuously monitor heart performance for long-term, at-home use. SafeSleep will integrate sensors into clothing to monitor various biometrics and body movements during both sleep and wakefulness. Ahmed and his supervisors will conduct a user experience study to identify metrics for measurement and inform the design of a suitable T-shirt.
By creating an accessible and scalable technology to simultaneously diagnose sleep apnea and monitor heart failure, Ahmed hopes to minimize hospitalizations, enable the delivery of preventative therapies, and allow people living with heart failure to effectively self-manage at home.
Deep learning framework for cardiopulmonary fitness prediction in heart failure patients using Apple Watch biometric data
William Gao, first-year PhD student in the Department of Medical Biophysics
Supervised by: Drs. Chris McIntosh and Yas Moayedi
Remote monitoring can help clinicians better understand heart failure patients’ health conditions outside of the hospital. However, it is rarely implemented in clinics due to the lack of accessibility of devices and patient discomfort with the devices. William’s research will focus on understanding how novel technologies like the Apple Watch can be used to provide more available, easy-to-use monitoring of cardiac fitness.
Past research in wearable devices has suggested that daily step count derived from wearable devices is a more objective metric of heart failure status than the NYHA classes. The immense amount of biometric data from the Apple Watch may provide even more accurate metrics for determining the cardiac fitness of heart failure patients than previous results. William’s research will utilize deep learning models to create meaningful understandings from this data. This includes predicting cardiorespiratory fitness in heart failure patients.
Through integrating novel technologies and machine learning, William’s project aims to revolutionize remote monitoring of heart failure.
Equitable wearable opto-electronics to monitor heart failure
Megh Rathod, graduate trainee in Biomedical Engineering
Supervised by: Drs. Daniel Franklin and Heather Ross
Light-based technology provides an exciting tool for non-invasive monitoring, with applications for heart failure diagnostics and monitoring. Unfortunately, existing technology fails to account for variations in skin melanin levels, resulting in inaccurate readings and inequities in care. Megh’s project aims to develop a non-invasive way to precisely measure cardiovascular metrics – regardless of skin colour.
By leveraging the rapid advancements in embedded electronics, Megh aims to develop a wearable device that utilizes multiwavelength spectroscopy to account for melanin when obtaining measurements. Megh and his supervisors will validate their devices across skin tones and illness levels by partnering with patients and clinicians.
The ultimate goal of Megh’s research is to advance the development of equity-focused medical devices for diverse populations in Canada, and beyond.
2021 Trainee Awards
Remote monitoring of patients with left ventricular assist devices: A safety and feasibility study
Dr. Darshan Brahmbhatt, Clinical Fellow, Heart Failure & Cardiac Transplantation
Supervised by: Drs Phyllis Billia and Emily Seto
HF is an important cause of morbidity and mortality, with many patients requiring hospitalization to stabilize them. Remote monitoring (RM) — a technique which can assess HF patients outside of hospital — collects and automatically transmits patients’ information to their clinical team. Through intervention at the earliest sign of deterioration, RM can reduce instances of hospitalization.
RM techniques have been well-studied in general HF patients; however, little research has been conducted on patients with left ventricular assist devices (LVAD). These patients, who are at high risk of deterioration, require frequent hospital visits to monitor condition stability. Darshan’s study will review the impact of RM in this understudied population.
Investigating the interrelationship of sleep and heart failure in people experiencing homelessness
Dr. Nasim Montazeri, Postdoctoral Fellow at KITE Research Institute
Supervised by: Drs Azadeh Yadollahi and Heather Ross
Though half of people with HF have sleep apnea, it is highly underdiagnosed in HF patients. There are no specific guidelines for sleep studies in HF, and referrals are based on symptoms which are not common in HF patients. The reference sleep test is costly and inconvenient, especially in underrepresented populations, such as shelter residents who are at higher risk of heart disease.
Through portable sleep screening among shelter residents, Nasim’s project will investigate the association between sleep apnea and heart disease and identify sleep-related indices for each sex that differ between people with and without heart problems.
Design and evaluation of a digital mental health stepped care model for a heart failure remote monitoring program
Amika Shah, PhD Candidate at the Institute for Health Policy, Management and Evaluation
Supervised by: Drs. Emily Seto and Rob Nolan
Approximately 22% of the population living with HF experiences depression; however, it remains unclear how to deliver mental health care within cardiology settings to address the needs of these patients. Stepped care models which combine routine screening with connections to appropriate mental health supports are promising, but an entirely digital model that is connected to HF care does not yet exist. Amika’s research involves working with patients, caregivers, and clinicians to co-design a digital mental health stepped care model for a HF remote monitoring program called Medly. To our knowledge, this is the first entirely digital stepped care model that integrates care for both physical and mental health.
A digital microfluidic platform for point-of-care testing of cardiac biomarkers
Anthony Yong, Graduate Student in the Department of Chemistry
Supervised by: Drs. Aaron Wheeler and Heather
Diagnosis of HF can require large volumes of blood tested at centralized laboratories. In many clinics and hospitals in remote areas, limited access to such laboratories can delay diagnosis. One potential solution is digital microfluidic (DMF) technology — credit card-sized devices that miniaturize laboratory procedures. Using just a pinprick of blood, DMF could perform onsite analysis and rapidly deliver diagnostic information to healthcare providers.
Anthony will be developing a DMF-based platform that will provide off-site clinicians with an overview of a patient’s cardiovascular health. The final phase of this research will include field-testing the device with patients in Northern Ontario.