Lung sound classification using hjorth descriptor measurement on wavelet sub-bands
Penulis/Author
ACHMAD RIZAL (1); Prof. Dr. Ir. Risanuri Hidayat, M.Sc., IPM. (2); Prof. Ir. Hanung Adi Nugroho, S.T., M.Eng., Ph.D., IPM., SMIEEE. (3)
Tanggal/Date
2019
Kata Kunci/Keyword
Abstrak/Abstract
Signal complexity is one point of view to analyze the biological signal. It arises as a result of the physiological signal produced by biological systems. Signal complexity can be used as a method in extracting the feature for a biological signal to differentiate a pathological signal from a normal signal. In this research, Hjorth descriptors, one of the signal complexity measurement techniques, were measured on signal sub-band as the features for lung sounds classification. Lung sound signal was decomposed using two wavelet analyses: discrete wavelet transform (DWT) and wavelet packet decomposition (WPD). Meanwhile, multi-layer perceptron and N-fold cross-validation were used in the classification stage. Using DWT, the highest accuracy was obtained at 97.98%, while using WPD, the highest one was found at 98.99%. This result was found better than the multiscale Hjorth descriptor as in previous studies.
Rumpun Ilmu
Teknik Elektro
Bahasa Asli/Original Language
English
Level
Internasional
Status
Dokumen Karya
No
Judul
Tipe Dokumen
Aksi
1
Lung sound classification (1).pdf
[PAK] Full Dokumen
2
Similarity Lung sound classification using hjorth descriptor measurement on wavelet sub-bands.pdf
