A review on respiratory sound analysis using machine learning Makine Ögrenmesini Kullanarak Solunum Sesinin Analizinin Degerlendirilmesi

Altan G., Kutlu Y.

20th National Biomedical Engineering Meeting, BIYOMUT 2016, İzmir, Turkey, 3 - 05 December 2016, (Full Text) identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/biyomut.2016.7849379
  • City: İzmir
  • Country: Turkey
  • Keywords: crackles, machine learning, oscultation, Respiratory sounds, wheeze
  • Hatay Mustafa Kemal University Affiliated: Yes

Abstract

Auscultation of the respiratory sounds is an inexpensive and effective method for diagnosing cardio-pulmonary disorders using lung sounds from chest and back. Nowadays, high system performances in the management of robust processes that require great attention were increased using the computer-aided analysis methods and the developments of the diagnosis system. Analysis of the respiratory sounds with computer-aided systems allows objective and useful assessments. In this study, a brief description of the abnormal respiratory sounds was presented. The main aims of the study are performing a systematic review about methods and the machine learning algorithms that are used to classify the abnormal respiratory sounds for diagnosis of cardio-pulmonary disorders and evaluating the development of possible methods on respiratory sounds in the future.