» Articles » PMID: 29142324

An Algorithm for the Beat-to-beat Assessment of Cardiac Mechanics During Sleep on Earth and in Microgravity from the Seismocardiogram

Overview
Journal Sci Rep
Specialty Science
Date 2017 Nov 17
PMID 29142324
Citations 8
Authors
Affiliations
Soon will be listed here.
Abstract

Seismocardiogram, SCG, is the measure of precordial vibrations produced by the beating heart, from which cardiac mechanics may be explored on a beat-to-beat basis. We recently collected a large amount of SCG data (>69 recording hours) from an astronaut to investigate cardiac mechanics during sleep aboard the International Space Station and on Earth. SCG sleep recordings are characterized by a prolonged duration and wide heart rate swings, thus a specific algorithm was developed for their analysis. In this article we describe the new algorithm and its performance. The algorithm is composed of three parts: 1) artifacts removal, 2) identification in each SCG waveform of four fiducial points associated with the opening and closure of the aortic and mitral valves, 3) beat-to-beat computation of indexes of cardiac mechanics from the SCG fiducial points. The algorithm was tested on two sleep recordings and yielded the identification of the fiducial points in more than 36,000 beats with a precision, quantified by the Positive Predictive Value, ≥99.2%. These positive findings provide the first evidence that cardiac mechanics may be explored by the automatic analysis of SCG long-lasting recordings, taken out of the laboratory setting, and in presence of significant heart rate modulations.

Citing Articles

SCG variability and spectral energy distribution during normal breathing and breath hold at different lung volumes and airway pressures.

Ahdy S, Hassan T, Rahman B, Sandler R, Mansy H Sci Rep. 2024; 14(1):17904.

PMID: 39095411 PMC: 11297340. DOI: 10.1038/s41598-024-68590-6.


Investigating Cardiorespiratory Interaction Using Ballistocardiography and Seismocardiography-A Narrative Review.

Balali P, Rabineau J, Hossein A, Tordeur C, Debeir O, van de Borne P Sensors (Basel). 2022; 22(23).

PMID: 36502267 PMC: 9737480. DOI: 10.3390/s22239565.


The evaluation of seismocardiogram signal pre-processing using hybridized variational mode decomposition method.

Naufal D, Pramudyo M, Erawati Rajab T, Setiawan A, Adiono T Biomed Eng Lett. 2022; 12(4):381-392.

PMID: 36238372 PMC: 9550903. DOI: 10.1007/s13534-022-00235-x.


Estimation of Changes in Intracardiac Hemodynamics Using Wearable Seismocardiography and Machine Learning in Patients With Heart Failure: A Feasibility Study.

Shandhi M, Fan J, Heller J, Etemadi M, Klein L, Inan O IEEE Trans Biomed Eng. 2022; 69(8):2443-2455.

PMID: 35100106 PMC: 9347221. DOI: 10.1109/TBME.2022.3147066.


Recent Advances in Seismocardiography.

Taebi A, Solar B, Bomar A, Sandler R, Mansy H Vibration. 2021; 2(1):64-86.

PMID: 34113791 PMC: 8189030. DOI: 10.3390/vibration2010005.


References
1.
Giorgis L, Frogerais P, Amblard A, Donal E, Mabo P, Senhadji L . Optimal algorithm switching for the estimation of systole period from cardiac microacceleration signals (SonR). IEEE Trans Biomed Eng. 2012; 59(11):3009-15. DOI: 10.1109/TBME.2012.2212019. View

2.
Di Rienzo M, Meriggi P, Vaini E, Castiglioni P, Rizzo F . 24h seismocardiogram monitoring in ambulant subjects. Annu Int Conf IEEE Eng Med Biol Soc. 2013; 2012:5050-3. DOI: 10.1109/EMBC.2012.6347128. View

3.
Jafari Tadi M, Lehtonen E, Saraste A, Tuominen J, Koskinen J, Teras M . Gyrocardiography: A New Non-invasive Monitoring Method for the Assessment of Cardiac Mechanics and the Estimation of Hemodynamic Variables. Sci Rep. 2017; 7(1):6823. PMC: 5533710. DOI: 10.1038/s41598-017-07248-y. View

4.
Javaid A, Ashouri H, Dorier A, Etemadi M, Heller J, Roy S . Quantifying and Reducing Motion Artifacts in Wearable Seismocardiogram Measurements During Walking to Assess Left Ventricular Health. IEEE Trans Biomed Eng. 2016; 64(6):1277-1286. PMC: 5444999. DOI: 10.1109/TBME.2016.2600945. View

5.
Laguna P, Thakor N, Caminal P, Jane R, Yoon H, Bayes de Luna A . New algorithm for QT interval analysis in 24-hour Holter ECG: performance and applications. Med Biol Eng Comput. 1990; 28(1):67-73. DOI: 10.1007/BF02441680. View