Medicine is an exciting environment for signal processing, as biological signals exhibit high variability, and the amount of data to be processed is increasing rapidly. Effective algorithms simplify diagnostics and are economically interesting as they save computing power or even the need for costly sensors, as we will show in an electrocardiography example.
The Institute for Human Centered Engineering at BFH is developing a new method for ECG recording from the esophagus. Due to the proximity of the esophagus to the heart, high-quality signals can be recorded, especially in the atrial region (p-waves). Thin and flexible esophageal catheters that record multichannel ECGs are used in this situation. Such catheters are in constant motion within the esophagus, driven by respiratory movements, peristalsis and physical activity of the patient. However, knowledge of the exact catheter position is important for precise ECG analysis. In this presentation, we demonstrate how the current catheter position within the esophagus can be efficiently determined solely from the ECG data recorded under real conditions, eliminating the need for an additional position sensor.
The presented solution is based on a signal processing method that examines and approximates multi-channel signals in their local environment, which has been developed over the past years in cooperation with the ETH Zurich. This method is specially designed for the processing of large, multi-channel data sets and allows optimization, pattern recognition and clustering problems to be solved efficiently. Such techniques are of particular interest and benefit in the field of medical devices, where computing power is limited.
Reto Wildhaber has been doing research in the field of esophageal electrocardiography at the Institute for Human Centered Engineering at BFH for the past 6 years. After studying electrical engineering from 1999 to 2002, he was employed in R&D in a mid-size company. Later, he started his studies in human medicine and received his M.D. (Dr. med.) degree from University of Zurich in 2014. In 2019 he completed his doctorate in signal processing at the Department of Information Technology and Electrical Engineering at ETH Zurich.
Frédéric Waldmann successfully completed his master’s thesis at the Institute for Human Centered Engineering in summer 2019. He is currently employed at ETH and BFH and works in the development of signal processing methods and their implementation in the ECG project.