Introducing Pace™, encompassing an innovative pacemaker design, integrated with a software component, to remove the risks associated with current pacemakers on the market. Our product implements a leadless dual chamber pacemaker in combination with a program to ease the surgical fixation process, thus reducing the associated risks.
Program: Our program is a software that can integrate into the surgeon’s computer desk, by helping them to navigate the surgery. This is meant to reduce any possible complications that may arise from implanting a leadless pacemaker. It is important to note that leadless pacemakers are generally harder to implant and can lead to the aforementioned issues. Pace™ comes with a software program that uses fragment Machine Learning (ML) using data collected from an echocardiograph generated from an ultrasound.
Prior to the surgery, patient specific echocardiography data is acquired to determine heart measurements and more. From this, the program is able to calculate the optimal insertion location of the leadless devices to reduce risk. Then, the physician is able to go into surgery knowing the optimal approach to the surgery. Additionally, Pace ™ collects live sensor data via the cathode that is used to insert these devices, thus throughout the surgery the program will be able to notify the physician of any potential dangers.
The current version of Pace™ is developed in Python, utilizing libraries like Matplotlib and NumPy. This marks just the beginning for Pace™! Future iterations will focus on enhanced verification, improved validity, advanced image analysis, and the integration of Machine Learning (ML).