Premium
Screening of Chronic Obstructive Pulmonary Disease by Using Self‐Organizing Map
Author(s) -
AOKI HIROOKI,
MASHIMO SHUKO,
NAKAMURA HIDETOSHI
Publication year - 2016
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.11904
Subject(s) - waveform , pulmonary disease , copd , self organizing map , medicine , respiratory system , respiratory disease , respiration , pattern recognition (psychology) , artificial intelligence , computer science , cardiology , lung , cluster analysis , telecommunications , radar , anatomy
SUMMARY We have examined the noncontact respiration measurement by applying the active stereo for realizing easy screening of chronic obstructive pulmonary disease (COPD). In this study, we apply the self‐organizing map (SOM) for classification of unforced respiratory waveform. The automatic classification of the respiratory waveform is based on the difference in the undulating pattern of respiratory waveform between the COPD patients and the healthy subjects. As the result of the experiment, it became clear that the classification by SOM is almost equivalent to the classification by respiratory specialists.