Simulating Electrocardiogram Using Finite Element Model During Ischemia Development

Electrocardiogram (ECG) is the most commonly used tool to detect anomaly in heart function due to its non-invasive nature and relatively inexpensive. However, it captures a summary of heart activity viewed from the perspective of different electrodes, as such pin-pointing a certain characteristic of the ECG waveforms to a certain event in the heart are not straight forwards, often requiring extensive signal processing via large number of datasets. The finite element model of the human torso has been utilized to link spatial changes in local heart cellular characteristics to a global ECG waveform. In the present study, we explore the possibility of simulating beat-to-beat changes in ECG waveforms during the course of ischemic development. We utilized an established idealized torso model with phenomenological Rogers-McCulloch action potential model representing the transmembrane potential. An ischemic region was gradually developed over the course of 5 seconds by inhibiting the action potential and tissue electrical conductivity at the apical region, and the ECG shape changes were compared against healthy ECG. A gradual change in the shape can be noted by the drop in Q-wave magnitude and loss of ST segment. As such, using this finite element model can be used to relate local changes in action potential with certain ECG characteristics. In future, such an approach can be used to recognize beat-to-beat changes and be applied in validating signal processing approach.