Abstract
Cardiovascular diseases (CVDs) have been ranked as the main cause of death worldwide by the World Health Organization (WHO). CVD has a high prevalence and is aggravated by lifestyle disorders. To reduce the impact of CVDs, exercise-based cardiac rehabilitation (CR) is often prescribed by clinicians, aiming to reduce the risk of cardiovascular disease and promote the adoption and adherence to healthy habits. CR is also prescribed to patients suffering from cardiac diseases like valvular heart disease, heart transplantation, heart failure with reduced ejection fraction (EF), postcoronary artery bypass grafting (CABG), etc. to improve the quality of life and reduce re-hospitalization. Along with exercise medicine, the response of heart under stress should be accounted for and evaluated in patient management plans, as most of the stress and exercise conditions create a high demand for blood circulation across the cardiac system, often revealing adverse conditions during exercise. Recent statistics from WHO report that around 80000 athletes died in sudden cardiac arrest in the last year. Hence, for CR or exercise prescriptions to be fruitful, modeling and monitoring exercise behavior on cardiac parameters are required because they might indicate early diagnosis of an individual.
To address the aforementioned issue, a digital twin of a cardiovascular simulation framework is required for predicting cardiopulmonary parameters and infusing predictability and intelligence in the exercise medicine prescription of an individual during exercise. Such a system could also be useful for recording cardiac irregularities and generating alarms, aiding in the early screening of several CVDs. Moreover, it can also assist doctors in analyzing data, simulating, and checking the functionality of the process for potential problems, and analyzing ‘what if’ scenarios.
Personal Information
Dibyendu Roy received his Ph.D in Control Systems and Robotics Engineering in 2023 from Jadavpur University, Kolkata, India. He is currently working as a scientist in the Agency for Science, Technology and Research (A*STAR), Singapore. He has around 10+ years of working experience in the domain of control systems and robotics. He has published several journal and conference articles, 10+ granted patents. His research interest includes control system modelling for robotics application and healthcare.