Entropy measurement as features extraction in automatic lung sound classification

@article{Rizal2017EntropyMA,
  title={Entropy measurement as features extraction in automatic lung sound classification},
  author={Achmad Rizal and Risanuri Hidayat and Hanung Adi Nugroho},
  journal={2017 International Conference on Control, Electronics, Renewable Energy and Communications (ICCREC)},
  year={2017},
  pages={93-97}
}
Lung sound is one of the important information in the diagnosis of respiratory disease. Many researchers have developed various algorithms to diagnose lung disease through the lung sounds. One of the parameters used as the feature of lung sound is entropy, a measure of the signal complexity in which the normal biological signal and the pathological biological signal have different complexities. Entropy measurement has some different methods performed in a different signal domain as well. This… CONTINUE READING

References

Publications referenced by this paper.
SHOWING 1-10 OF 26 REFERENCES

Physiological time-series analysis using approximate entropy and sample entropy.

  • American journal of physiology. Heart and circulatory physiology
  • 2000
VIEW 7 EXCERPTS
HIGHLY INFLUENTIAL

A Mathematical Theory of Communication

C. E. Shannon
  • Bell Syst. Tech. J., vol. 27, no. 3, pp. 379–423, 1948.
  • 1948
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Fundamentals of lung auscultation.

  • The New England journal of medicine
  • 2014
VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

Determining lung sound characterization using Hjorth descriptor

  • 2015 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)
  • 2015
VIEW 2 EXCERPTS