Customized Spectro-Temporal CNN Feature Extraction and ELM-Based Classifier for Accurate Respiratory Obstruction Detection

The accurate prediction based on lung auscultation of respiratory obstruction conditions (ROC), such as chronic obstructive pulmonary disease (COPD) and asthma, is a challenging task due to the availability of small datasets, ambient noise, variability between patients, high computational power, ove...

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Veröffentlicht in:	IEEE access Jg. 13; S. 114145 - 114158
Hauptverfasser:	Muthulakshmi, M., Venkatesan, K., Bahiyah Rahayu, Syarifah, Nayana Sree, K. L.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Artificial neural networks Asthma Audio data Audio signals Auscultation Chronic obstructive pulmonary disease CNN enhanced time-frequency features Deep learning ELM Feature extraction feature fusion Health services Low cost Lungs Machine learning Mel frequency cepstral coefficient Noise Pneumonia Real time Representations Respiratory diseases respiratory obstruction condition Spectrogram Time-frequency analysis
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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