Multi-level feature encoding algorithm based on FBPSI for heart sound classification

Analysis of heart sound signals plays an essential role in preventing and diagnosing cardiac diseases. This study proposes a multi-level feature encoding algorithm based on frequency-balanced power spectral intensity for heart sound signal classification. Firstly, a wavelet threshold function is emp...

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Veröffentlicht in:	Scientific reports Jg. 14; H. 1; S. 29132 - 12
Hauptverfasser:	Fang, Yu, Leng, Hongxia, Wang, Weibo, Liu, Dongbo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 25.11.2024 Nature Publishing Group Nature Portfolio
Schlagworte:	631/1647 639/166 692/700 Accuracy Algorithms Balanced power spectrum intensity Cardiomyopathy Cardiomyopathy, Hypertrophic - diagnosis Cardiomyopathy, Hypertrophic - physiopathology Cardiovascular disease Cardiovascular diseases Classification Coronary artery disease Datasets Electroencephalography Heart Heart diseases Heart sound classification Heart Sounds - physiology Humanities and Social Sciences Humans Hypertrophic cardiomyopathy Image coding Multi-level feature encoding multidisciplinary Neural networks Science Science (multidisciplinary) Signal Processing, Computer-Assisted Sound Heart sound classification Hypertrophic cardiomyopathy Balanced power spectrum intensity Multi-level feature encoding
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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