Aruzhan Nazarova

A Reproducible Evaluation of Hybrid Spectral–Temporal Features for Four-Class Respiratory Sound Event Classification

Respiratory-sound event classification is challenged by non-stationarity, class imbalance, heterogeneous acquisition, and participant-correlated recordings. This study evaluates whether direct fusion of short-time Fourier transform (STFT), mel-frequency cepstral coefficient (MFCC...

Artificial Intelligence-Based Respiratory Sound Analysis: A Scoping Review of Digital Auscultation Technologies, Public Datasets, Signal Processing, and Deep Learning Methods

Respiratory sound analysis is becoming increasingly popular as a non-invasive method for detecting adventitious sounds and aiding in the diagnosis of respiratory diseases such as chronic obstructive pulmonary disease (COPD), asthma, and pneumonia. However, studies in this field d...