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Cardiac auscultation analysis system with neural network and SVM technique

  • Pipatthana Phatiwuttipat
  • , Waree Kongprawechon
  • , Kanokvate Tungpimolrut
  • , Sumeth Yuenyong
  • Thammasat University
  • National Science and Technology Development Agency (NSTDA)

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Citations (Scopus)

Abstract

The system of this study is aimed to support doctors with an analyzed Cardiac auscultation. Extract the information from the heart sound signal obtained from stethoscope mobbed on the robot arm control is used in the further signal processing. Due to time consuming and accuracy, Support Vector Machine is introduced to replace Neural Network for better performance.With the proposed technique, the high classification performances were achieved 96.4% accuaracy for classifying normal and abnormal heart sound while shortening the training time almost 300%. As the result, multi-classifier was introduced for advance development. This paper shows the comparison work between Neural Network and Support Vector Machine.

Original languageEnglish
Title of host publicationECTI-CON 2011 - 8th Electrical Engineering/ Electronics, Computer, Telecommunications and Information Technology (ECTI) Association of Thailand - Conference 2011
Pages1027-1030
Number of pages4
DOIs
Publication statusPublished - 2011
Event8th Electrical Engineering/ Electronics, Computer, Telecommunications and Information Technology (ECTI) Association of Thailand - Conference 2011, ECTI-CON 2011 - Khon Kaen, Thailand
Duration: 17 May 201119 May 2011

Publication series

NameECTI-CON 2011 - 8th Electrical Engineering/ Electronics, Computer, Telecommunications and Information Technology (ECTI) Association of Thailand - Conference 2011

Conference

Conference8th Electrical Engineering/ Electronics, Computer, Telecommunications and Information Technology (ECTI) Association of Thailand - Conference 2011, ECTI-CON 2011
Country/TerritoryThailand
CityKhon Kaen
Period17/05/1119/05/11

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