Classification of respiratory signals by linear analysis

  title={Classification of respiratory signals by linear analysis},
  author={Sergul Aydore and I. Sen and Y. Kahya and M. K. Mihçak},
  journal={2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
  • Sergul Aydore, I. Sen, +1 author M. K. Mihçak
  • Published 2009
  • Mathematics, Medicine
  • 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
The aim of this study is the classification of wheeze and non-wheeze epochs within respiratory sound signals acquired from patients with asthma and COPD. Since a wheeze signal, having a sinusoidal waveform, has a different behavior in time and frequency domains from that of a non-wheeze signal, the features selected for classification are kurtosis, Renyi entropy, f50/ f90 ratio and mean-crossing irregularity. Upon calculation of these features for each wheeze and non-wheeze portion, the whole… Expand
Joint Application of Audio Spectral Envelope and Tonality Index in an E-Asthma Monitoring System
Classification of lung sounds based on linear prediction cepstral coefficients and support vector machine
  • M. Azmy
  • Engineering, Medicine
  • 2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT)
  • 2015
Respiratory Wheeze Sound Analysis Using Digital Signal Processing Techniques
Pulmonary crackle feature extraction using tsallis entropy for automatic lung sound classification
Automatic Differentiation of Normal and Continuous Adventitious Respiratory Sounds Using Ensemble Empirical Mode Decomposition and Instantaneous Frequency


Respiratory sound classification by using an incremental supervised neural network
  • Z. Dokur
  • Computer Science
  • Pattern Analysis and Applications
  • 2008
On Applying Continuous Wavelet Transform in Wheeze Analysis
Wheeze detection based on time-frequency analysis of breath sounds
Time-frequency detection and analysis of wheezes during forced exhalation
Combining Neural Network and Genetic Algorithm for Prediction of Lung Sounds
WED: An efficient wheezing-episode detector based on breath sounds spectrogram analysis
A comparison of neural network models for wheeze detection