Heart function grading evaluation based on heart sounds and convolutional neural networks

• Published in: Australasian physical & engineering sciences in medicine Vol. 46; no. 1; pp. 279 - 288
• Main Authors: Chen, Xiao, Guo, Xingming, Zheng, Yineng, Lv, Chengcong
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.03.2023; Springer Nature B.V
• Subjects: Adaptive algorithms; Algorithms; Artificial neural networks; Biological and Medical Physics; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Biophysics; Cardiac function; Classification; Continuous wavelet transform; Feature extraction; Heart; Heart function; Heart Sounds; Humans; Markov chains; Medical and Radiation Physics; Neural networks; Neural Networks, Computer; Noise reduction; Regression models; Scientific Paper; Wavelet Analysis; Wavelet transforms; Heart sounds; NYHA classification; Cardiac function classification; Convolutional neural network

Accurate and rapid cardiac function assessment is critical for disease diagnosis and treatment strategy. However, the current cardiac function assessment methods have their adaptability and limitations. Heart sounds (HS) can reflect changes in heart function. Therefore, HS signals were proposed to a...