UC San Diego

In recent years, numerous technological advancements have revived a new interest in the study of Ballistocardiography (BCG). Ballistocardiography has many potential applications in the health field and has recently been integrated into various home health monitoring devices which allow users to consistently track information about their cardiovascular health. Despite these recent advancements, BCG signals are still very susceptible to noise due to the fact that the sensors must be sensitive enough to measure small mechanical movements of the body, unlike electrocardiography signals which are obtained from the body’s electrical activity. This paper focuses on examining two new techniques for processing BCG signals: Singular Spectrum Analysis and Savitzky-Golay filters. Multiple accelerometers are used to simultaneously collect data from varying locations of the body, and the strength of the BCG signal at these locations are independently analyzed. We determine the necessary parameters to enable each method to effectively and successfully remove noise and other artifacts from BCG data. Our results show that SSA is a powerful technique capable of separating the desired BCG signal from the numerous artifacts more effectively than standard techniques. Also, although BCG signals can be detected throughout the body, the sternum and parietal bone tends to contain the most distinguished signals.