Title

Grouping Similar Seismocardiographic Signals Using Respiratory Information

Keywords

cardio-respiratory; intrathoracic pressure; lung volume; respiration effect; Seismocardiographic signal

Abstract

Seismocardiography (SCG) offers a potential noninvasive method for cardiac monitoring. Quantification of the effects of different physiological conditions on SCG can lead to enhanced understanding of SCG genesis, and may explain how some cardiac pathologies may affect SCG morphology. In this study, the effect of the respiration on the SCG signal morphology is investigated. SCG, ECG, and respiratory flow rate signals were measured simultaneously in 7 healthy subjects. Results showed that SCG events tended to have two slightly different morphologies. The respiratory flow rate and lung volume information were used to group the SCG events into inspiratory/expiratory groups or low/high lung-volume groups, respectively. Although respiratory flow information could separate similar SCG events into two different groups, the lung volume information provided better grouping of similar SCGs. This suggests that variations in SCG morphology may be due, at least in part, to changes in the intrathoracic pressure or heart location since those parameters correlates more with lung volume than respiratory flow. Categorizing SCG events into different groups containing similar events allows more accurate estimation of SCG features, and better signal characterization, and classification.

Publication Date

7-1-2017

Publication Title

2017 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2017 - Proceedings

Volume

2018-January

Number of Pages

1-6

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/SPMB.2017.8257053

Socpus ID

85050542876 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85050542876

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