While contactless vital sign monitoring technologies provide the great opportunity of fast and simple measurements, all these technologies have the unavoidable drawback that they suffer from strong motion artifacts. These motion artifacts may severely disrupt the signal of interest, which could lead to false peak detections and hence, result in false conclusions or diagnoses. Extensive and robust signal processing is needed for a reliable detection of these artifacts. In this work, a mathematical model of the motion artifacts is derived based on capacitive ECG measurements, as an example for contactless heart rate estimation. Thus, for the first time, it is possible to generate an arbitrary large database of heavily distorted capacitive ECG signals to test and verify algorithms for the robust detection of motion artifacts. (Author/publisher)
Abstract