A Real-Time, Automatic MCG Signal Quality Evaluation Method Using the Magnetocardiography and Electrocardiography

The quality of the obtained Magnetocardiogram (MCG) signal has significant influence on the reliability of deriving some important parameters, such as the interval between two R waves (RR interval), the interval between Q wave and the adjacent T wave (QT interval) and the interval between S wave and the adjacent T wave (ST interval), etc. The poor MCG signal might falsely trigger alarms frequently. The induced overloading of alarms can lead to alarm fatigue, and eventually reduce the care staffs’ attention level. Therefore, a real-time MCG signal quality evaluation algorithm is of great importance. It can allow inexperienced care staffs to collect MCG signals with sufficiently good diagnostic quality. In this work, we proposed an automatic MCG signal quality evaluation algorithm based on the multiparameters derived from MCG data and electrocardiogram (ECG) data. These MCG and ECG data are collected simultaneously. Unlike the available methods for evaluating the signal quality, seven parameters were extracted from the MCG and ECG data. For evaluation purpose, each parameter goes into two categories (good or poor) according to the set threshold. The quality of the MCG signal is evaluated according to the majority rule. The performances of the proposed algorithm were tested in a nine-channel MCG system. The achieved accuracy was 91%. Having demonstrated lower complexity and high accuracy, the proposed algorithm is promising for the real-time MCG signal quality evaluation.