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pyPCG: a Python toolbox specialized for phonocardiography analysis.
Physiol Meas
December 2024
Biomedical Engineering, Technion Israel Institute of Technology, Julius Silver Building, Haifa, 32000, ISRAEL.
Objective: Phonocardiography has recently gained popularity in low-cost and remote monitoring, including passive fetal heart monitoring. The development of methods which analyse phonocardiographic data tries to capitalize on this opportunity, and in recent years a multitude of such algorithms and models have been published. In these approaches there is little to no standardization and multiple parts of these models have to be reimplemented on a case-by-case basis.
View Article and Find Full Text PDFMachine Learning Algorithms for Processing and Classifying Unsegmented Phonocardiographic Signals: An Efficient Edge Computing Solution Suitable for Wearable Devices.
Sensors (Basel)
June 2024
Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy.
The phonocardiogram (PCG) can be used as an affordable way to monitor heart conditions. This study proposes the training and testing of several classifiers based on SVMs (support vector machines), k-NN (k-Nearest Neighbor), and NNs (neural networks) to perform binary ("Normal"/"Pathologic") and multiclass ("Normal", "CAD" (coronary artery disease), "MVP" (mitral valve prolapse), and "Benign" (benign murmurs)) classification of PCG signals, without heart sound segmentation algorithms. Two datasets of 482 and 826 PCG signals from the Physionet/CinC 2016 dataset are used to train the binary and multiclass classifiers, respectively.
View Article and Find Full Text PDFEvaluation of a digital stethoscope for electrocardiographic recording in donkeys: Preliminary results.
J Equine Vet Sci
April 2024
Department of Veterinary Medicine and Animal Science, Università degli Studi di Milano, via dell'Università 6, Lodi, Italy, 26900. Electronic address:
The digital stethoscope (DS) is a cost-effective single-lead digital stethoscope that allows simultaneous electrocardiographic (ECG) and phonocardiographic recordings on a smartphone. Despite its application in small animals and horses, there are currently no studies on its use in donkeys. The aim of this study was to evaluate the use of a new smartphone-based DS device in recording ECG tracings in donkeys.
View Article and Find Full Text PDFThe accurate detection of physiologically-related events in photopletismographic (PPG) and phonocardiographic (PCG) signals, recorded by wearable sensors, is mandatory to perform the estimation of relevant cardiovascular parameters like the heart rate and the blood pressure. However, the measurement performed in uncontrolled conditions without clinical supervision leaves the detection quality particularly susceptible to noise and motion artifacts. This work proposes a new fully-automatic computational framework, based on convolutional networks, to identify and localize fiducial points in time as the foot, maximum slope and peak in PPG signal and the S1 sound in the PCG signal, both acquired by a custom chest sensor, described recently in the literature by our group.
View Article and Find Full Text PDFCan Heart Sound Denoising be Beneficial in Phonocardiogram Classification Tasksƒ.
Annu Int Conf IEEE Eng Med Biol Soc
November 2021
The purpose of computer-aided diagnosis (CAD) systems is to improve the detection of diseases in a shorter time and with reduced subjectivity. A robust system frequently requires a noise-free input signal. For CADs which use heart sounds, this problem is critical as heart sounds are often low amplitude and affected by some unavoidable sources of noise such as movement artifacts and physiological sounds.
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