Time-Frequency-Domain Deep Learning Framework for the Automated Detection of Heart Valve Disorders Using PCG Signals

• Published in: IEEE transactions on instrumentation and measurement Vol. 71; pp. 1 - 11
• Main Authors: Karhade, Jay, Dash, Shaswati, Ghosh, Samit Kumar, Dash, Dinesh Kumar, Tripathy, Rajesh Kumar
• Format: Journal Article
• Language: English
• Published: New York IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Artificial neural networks; Automation; Convolutional neural networks; deep convolutional neural network (CNN); Deep learning; Diseases; Disorders; Evaluation; Feature extraction; Frequency domain analysis; Geometric accuracy; Heart; heart valve diseases; Heart valves; Machine learning; phonocardiogram (PCG) signal; Phonocardiography; Polynomials; Sound; Time-frequency analysis; time–frequency (TF) analysis; transfer learning; Transforms

The damage to the heart valves causes heart valve disorders (HVDs). The detection of HVDs is crucial in a clinical study as these diseases may cause congestive heart failure, hypertrophy, and stroke. The phonocardiogram (PCG) signal reveals information regarding the mechanical activity of the heart....