Automatic Artifact Detection in Impedance Cardiogram Using Pulse Similarity Index

Abstract

Impedance cardiography (ICG) is a noninvasive technique for evaluation of cardiac hemodynamic parameters such as cardiac output and pre-ejection period. However, the sensitivity of the technique to motion artifact, electrode displacement, and cardiovascular pathologies can severely impact the accuracy of hemodynamic parameter estimates. In this paper, we proposed a new algorithm for the automatic detection and exclusion of corrupted ICG cardiac cycles by defining a pulse similarity index that quantifies the level of pulse corruption and its diversion from a typical-shaped pulse. The index considers different features (activity, structure, shape, and pattern) of the ICG cardiac cycles. The algorithm is compared on sleep data collected from 20 participants against expert identified corrupted cycles. The artifact rejection algorithm achieved a high accuracy of 96% in detection of expert-identified corrupted ICG cycles, including those with normal amplitude as well as out-of-range values, and was robust to different types and levels of artifact. The algorithm shows promise toward applications requiring accurate and reliable automatic measurement of cardiac hemodynamic parameters from prolonged data sets.