Systolic time intervals are highly correlated to fundamental cardiac functions. In this paper we investigate the feasibility of using heart sound (HS) to accurately measure the opening and closing moments of the aortic valve, since these are crucial moments to define the main systolic timings of the heart cycle, i.e. the pre-ejection period (PEP) and the left ventricular ejection time (LVET). We introduce a HS model, which is applied to define several features that provide clear markers to identify these moments in the HS. Using these features and a comparative analysis with registered echocardiographies from 17 subjects, the results achieved in this study suggest that HS can be used to accurately estimate LVET and PEP.
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http://dx.doi.org/10.1109/IEMBS.2009.5332565 | DOI Listing |
Advances in personalized medicine and Systems Biology have introduced probabilistic models and error discovery to cardiovascular care, aiding disease prevention and procedural planning. However, clinical application faces cultural, technical, and methodological hurdles. Patient autonomy remains essential, with shared decision-making (SDM) gaining importance in managing complex cardiovascular treatment options.
View Article and Find Full Text PDFFront Neurosci
January 2025
Department of Evidence-Based Medicine and Social Medicine, School of Public Health, Chengdu Medical College, Chengdu, Sichuan, China.
Introduction: Sleep deprivation (SD) significantly disrupts the homeostasis of the cardiac-brain axis, yet the neuromodulation effects of deep magnetic stimulation (DMS), a non-invasive and safe method, remain poorly understood.
Methods: Sixty healthy adult males were recruited for a 36-h SD study, they were assigned to the DMS group or the control group according to their individual willing. All individuals underwent heart sound measurements and functional magnetic resonance imaging scans at the experiment's onset and terminal points.
Comput Biol Med
January 2025
Univ. Grenoble Alpes, CNRS, CHU Grenoble Alpes, Grenoble INP, TIMC-IMAG, La Tronche, France.
Background And Objective: Heart auscultation enables early diagnosis of cardiovascular diseases. Automated segmentation of cardiograms into fundamental heart states can guide physicians to analyze the patient's condition more effectively. In this work, we propose an unsupervised method of segmentation into heart sounds and silences based on the detection of abrupt changes in the signal.
View Article and Find Full Text PDFAnimals (Basel)
January 2025
Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, 3584 CM Utrecht, The Netherlands.
Background: Purring in cats can interfere with cardiac auscultation. If the produced noise is loud enough, purring makes it impossible to perform a meaningful auscultation as it is much louder than heart sounds and murmurs. Our study introduced and tested a new, simple, fear-free, cat-friendly method to stop purring during auscultation.
View Article and Find Full Text PDFAntioxidants (Basel)
January 2025
Laboratory of Molecular Cardiology, Department of Cardiology 1, University Medical Center of the Johannes Gutenberg-University, 55131 Mainz, Germany.
Noise pollution is a known health risk factor and evidence for cardiovascular diseases associated with traffic noise is growing. At least 20% of the European Union's population lives in noise-polluted areas with exposure levels exceeding the recommended limits of the World Health Organization, which is considered unhealthy by the European Environment Agency. This results in the annual loss of 1.
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