Combining Phonocardiography (PCG) and Electrocardiography (ECG) data has been recognized within the state-of-the-art as of added value for enhanced cardiovascular assessment. However, multiple aspects of ECG data acquisition in a stethoscope form factor remain unstudied, and existing devices typically enforce a substantial change into routine clinical auscultation procedures, with predictably low technology acceptance. As such, in this paper, we present a novel approach to ECG data acquisition throughout the five main cardiac auscultation points, and that intends to be incorporated in a commonly used electronic stethoscope. Therefore, it enables analysis and acquisition of both PCG and ECG signals in a single pass. We describe the development, experimental evaluation, and comparison of the ECG signals obtained using our proposed approach and a gold standard medical device, through metrics that allow the evaluation of morphological similarities. Results point to a high correlation between the two evaluated setups, thus supporting the idea of meaningfully collecting ECG data along medical auscultation points with the proposed form factor. Moreover, this work has led us to conclude that for the studied population, signals acquired on focuses F1, F2, and F3 are usually highly correlated with leads V1 and V2 of the standard ECG medical recording procedure.
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http://dx.doi.org/10.1109/TBME.2019.2913913 | DOI Listing |
Heliyon
January 2025
Department of Information Engineering, Università Politecnica delle Marche, via Brecce Bianche, Ancona, 60131, Italy.
Background: Deep-learning applications in cardiology typically perform trivial binary classification and are able to discriminate between subjects affected or not affected by a specific cardiac disease. However, this working scenario is very different from the real one, where clinicians are required to recognize the occurrence of one cardiac disease among the several possible ones, performing a multiclass classification. The present work aims to create a new interpretable deep-learning tool able to perform a multiclass classification and, thus, discriminate among several different cardiac diseases.
View Article and Find Full Text PDFIran J Pharm Res
June 2024
Department of Pharmacoeconomics and Pharmaceutical Administration, School of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran.
Context: Breast cancer poses significant challenges due to its high incidence and prevalence, necessitating heightened attention. Understanding how patients prioritize different treatment options based on various attributes can assist healthcare decision-makers in maximizing patient utility. The discrete choice experiment, a conjoint method, facilitates preference elicitation by presenting different attributes and choices.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Cardiovascular Medicine and Hypertension, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, Japan.
The association between serum uric acid (UA) levels and left ventricular hypertrophy (LVH) remains unclear. We aimed to investigate this association using electrocardiographic findings. Health examination data from Kagoshima Kouseiren Hospital included 79,200 participants without cardiovascular diseases.
View Article and Find Full Text PDFJ Vet Emerg Crit Care (San Antonio)
January 2025
Center for Interdisciplinary Statistical Education and Research, Washington State University, Pullman, Washington, USA.
Objective: To evaluate the effect of rescuer team size on objective skill measures of basic life support (BLS) and advanced life support (ALS) using high-fidelity canine CPR simulation.
Design: Prospective, experimental study.
Setting: Veterinary clinical simulation center.
Seizure
January 2025
Faculty of Medicine, Dentistry & Health Sciences, The University of Melbourne, 29 Regent Street, Fitzroy VIC 3065, Australia; Seer Medical, Melbourne, Victoria, Australia; Department of Neurology, St Vincent's Hospital Melbourne, 41 Victoria Parade Fitzroy VIC 3065, Australia.
Background Anti-seizure medications (ASMs) are commonly prescribed in epilepsy. However some have been associated with adverse cardiac outcomes including cardiac arrhythmias. Methods We conducted an observational study evaluating patients aged ≥16 years undergoing ambulatory video - electroencephalographic (EEG) - electrocardiographic (ECG) monitoring (AVEEM) between 2020 and 2023 in Australia.
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