Beating heart disease - non-invasive and non-contact diagnosis of cardiovascular disease

Cardiovascular disease (CVD), the leading cause of mortality globally, affects millions of individuals and poses a significant public health challenge. Early, non-invasive diagnostic tools capable of providing clinically relevant information have the potential to improve patient care and significantly reduce CVD-related morbidity and mortality.

This project aims to advance a novel, camera-based imaging system designed to estimate carotid artery and jugular venous pressure waveforms. The system works by analyzing skin deformations on the neck caused by vessel pulsations. The research will focus on developing new methods to extract additional physiological markers, such as blood pressure and quantifying regions of maximum pulsation. The methodologies will leverage data from dual-camera imaging systems and mobile phones. Artificial intelligence (AI) and machine learning algorithms will be employed to identify and analyze features of interest. These innovations will be validated against existing clinical methods and applied in patient cohort studies to assess their clinical utility.

The project is embedded within a multidisciplinary team comprising engineers and clinicians, offering a unique opportunity to contribute to translational research. It will involve diverse areas such as camera and optics development, imaging experiments, signal processing, data analysis, AI, and machine learning. While prior experience in medical imaging is not required, a strong interest in these domains is desired.

• Programming and some instrumentation
• Interest in the cardiac field and clinical translation
• Eager to learn and be challenged
  

This project is eligible for funding but is subject to eligibility criteria & funding availability.

Page expires: 13 December 2025