Improvement of ballistocardiogram processing by inclusion of respiration information.
In this paper a novel methodology for processing of a ballistocardiogram (BCG) is proposed in which the respiration signal is utilized to improve the averaging of the BCG signal and ultimately the annotation and interpretation of the signal. Previous research works filtered out the respiration signal while the novelty of the current research is that, rather than removing the respiration effect from the signal, we utilize the respiration information to improve the averaging and thus analysis and interpretation of the BCG signal in diagnosis of cardiac malfunctions. This methodology is based on our investigation that BCG cycles corresponding to the inspiration and expiration phases of the respiration cycle are different in morphology. BCG cycles corresponding to the expiration phase of respiration have been proved to be more closely related to each other when compared to cycles corresponding to inspiration, and therefore expiration cycles are better candidates to be selected for the calculation of the averaged BCG signal. The new BCG average calculated based on this methodology is then considered as the representative and a template of the BCG signal for further processing. This template can be considered as the output of a clinical BCG instrument with higher reliability and accuracy compared to the previous processing methods.
Computational and Integrative Bio-Engineering Research Laboratory (CIBER), School of Engineering Science, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6, Canada. kouhyart@sfu.ca
Kouhyar
K
Tavakolian
Ali
A
Vaseghi
Bozena
B
Kaminska
D001450:Ballistocardiography / Q000379:methods*; D004562:Electrocardiography; D006801:Humans; D012119:Respiration