After receiving a pacemaker, 20% of patients will develop heart failure as a direct result of the artificial stimulations pacemakers provide. However, there is currently no way for cardiologists to predict whether a patient will be one of these 20% until symptoms are already present. Pace Locator aims to solve this issue by providing cardiologists with a tool that identifies the underlying cause of pacing induced heart failure before it’s too late. Pace Locator is developing software that turns 12-lead ECG into a visual guide of how well the left and right sides of the heart beat in sync – a major predictor of whether the patient is at risk for pacing induced heart failure. Our goal is to enable more effective treatment for pacemaker patients and to reduce the long-term burden of the disease.

In the first phase of the InnoBooster project, we are optimizing the robustness of our signal processing algorithms to improve both the speed and the diagnostic accuracy of the software with the integration of machine-learning algorithms to help identify pathological ECG patterns. In the next stage, we will focus on developing a refined user interface to prepare for testing the software in the clinical environment, through both usability studies and clinical trials.