Identifying Heart Murmurs Through the Use of Artificial Neural Network Classifiers
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Identifying Heart Identifying Heart Murmurs Through the Murmurs Through the Use of Artificial Use of Artificial Neural Network Neural Network Classifiers Classifiers Aaron Aikin Aaron Aikin [email protected] [email protected] Supervisor: Roop Mahajan Supervisor: Roop Mahajan In collaboration with The Children’s In collaboration with The Children’s Hospital in Denver Hospital in Denver Introduction to Research, October 11 th , 2004
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Identifying Heart Murmurs Through the Use of Artificial Neural Network Classifiers. Aaron Aikin [email protected] Supervisor: Roop Mahajan In collaboration with The Children’s Hospital in Denver. Introduction to Research, October 11 th , 2004. Introduction. - PowerPoint PPT Presentation
Transcript of Identifying Heart Murmurs Through the Use of Artificial Neural Network Classifiers
Identifying Heart Murmurs Identifying Heart Murmurs Through the Use of Artificial Through the Use of Artificial Neural Network ClassifiersNeural Network Classifiers
Aaron AikinAaron [email protected]@colorado.eduSupervisor: Roop MahajanSupervisor: Roop Mahajan
In collaboration with The Children’s Hospital in DenverIn collaboration with The Children’s Hospital in Denver
Introduction to Research, October 11th, 2004
IntroductionIntroduction
Children currently screened for heart Children currently screened for heart murmurs by earmurmurs by earClinical auscultation is a dying artClinical auscultation is a dying artClinical screening not available in many parts of Clinical screening not available in many parts of
the worldthe worldEchocardiogram is very effective in heart defect Echocardiogram is very effective in heart defect
detectiondetectionExpensive (~$1000)Expensive (~$1000)
Want to create an inexpensive, effective Want to create an inexpensive, effective screening process for pediatric patients through screening process for pediatric patients through automated cardiac auscultationautomated cardiac auscultation
FacilitiesFacilities
Heart sound samples from Dr. Curt Heart sound samples from Dr. Curt DeGroff at Children’s HospitalDeGroff at Children’s HospitalCardionics stethoscopeCardionics stethoscope
Matlab and CUANN softwareMatlab and CUANN software
Methodology: Signal Processing Methodology: Signal Processing and ANN Classificationand ANN Classification
Current PerformanceCurrent Performance
~75% overall performance in determining ~75% overall performance in determining pathological from innocent heart soundspathological from innocent heart sounds~10% drop when noisy data is included~10% drop when noisy data is included
Goal is >85%Goal is >85%
Research Plans / TimelineResearch Plans / Timeline
Limited by CUANN softwareLimited by CUANN software Use Principle Component Analysis for data reduction Use Principle Component Analysis for data reduction
(late October)(late October) Implement code into Matlab (early November)Implement code into Matlab (early November)
Limitations in time-averaged FFTLimitations in time-averaged FFT Explore wavelet analysis (early December)Explore wavelet analysis (early December)
Potential limitations in ANN strategyPotential limitations in ANN strategy Explore other classification techniquesExplore other classification techniques
Nearest neighbor approachNearest neighbor approach ““Clustering” methodsClustering” methods
By February, Improve overall accuracyBy February, Improve overall accuracy
