Artificial Intelligence Enhanced Electrocardiography in Emergency Departments

Pulse AI
Ulster University

Computer electrocardiogram (ECG) interpretation algorithms have been widely used in healthcare since the late 1950s, but current iterations are limited in their diagnostic accuracy, which can result in inappropriate treatment for patients.

Peter’s project seeks to use Artificial Intelligence (AI) to address the shortcomings of existing systems. It will investigate whether current state of the art ECG models can be improved with a more data-centric approach to training deep learning models, whether current model predictions are optimised correctly for use in clinical practice, and whether it is possible to use AI to detect Occlusion Myocardial Infarction, where currently there is unreliability.

Taking advantage of PulseAI’s proprietary database and a recent rapid progress in literature, Peter’s project would lead to the introduction of a new AI enhanced electrocardiography software. This in turn will help to address significant shortcomings within a vitally important area of the healthcare sector.


Peter’s journey into connected health technologies began after graduating from Bangor university with a Master’s in Engineering, when he was recruited by Dr Alan Kenedy to work on ECG biometrics for a new start-up, who he now works with at PulseAI. Peter is also a Chartered Engineer with the Institute of Engineering and Technology. He found that the knowledge he gained whilst working in on automotive sensors and systems at Jaguar Land Rover was transferable to the healthcare domain, and of use for his current PhD at Ulster University.