Intelligent Diagnosis of Heart Murmurs in Children with Congenital Heart Disease

Autor: Bangzhou Wang, Fei Qu, Jiaming Wang, Kang Yi, Tao You, Qilian Xie, Yaqin Gong, Zhaoming He
Rok vydání: 2020
Předmět:
Heart Defects
Congenital
Medicine (General)
congenital
hereditary
and neonatal diseases and abnormalities
medicine.medical_specialty
Normal heart sounds
Adolescent
Article Subject
Heart disease
0206 medical engineering
Wavelet Analysis
Biomedical Engineering
Health Informatics
Heart Auscultation
02 engineering and technology
R5-920
Internal medicine
Medical technology
0202 electrical engineering
electronic engineering
information engineering
medicine
Humans
cardiovascular diseases
R855-855.5
Child
Phonocardiogram
Heart Murmurs
business.industry
Infant
Signal Processing
Computer-Assisted
medicine.disease
020601 biomedical engineering
Child
Preschool
Heart sounds
cardiovascular system
Heart murmur
Cardiology
020201 artificial intelligence & image processing
Surgery
Neural Networks
Computer
medicine.symptom
business
Algorithms
Research Article
Biotechnology
Zdroj: Journal of Healthcare Engineering, Vol 2020 (2020)
Journal of Healthcare Engineering
ISSN: 2040-2309
2040-2295
DOI: 10.1155/2020/9640821
Popis: Heart auscultation is a convenient tool for early diagnosis of heart diseases and is being developed to be an intelligent tool used in online medicine. Currently, there are few studies on intelligent diagnosis of pediatric murmurs due to congenital heart disease (CHD). The purpose of the study was to develop a method of intelligent diagnosis of pediatric CHD murmurs. Phonocardiogram (PCG) signals of 86 children were recorded with 24 children having normal heart sounds and 62 children having CHD murmurs. A segmentation method based on the discrete wavelet transform combined with Hadamard product was implemented to locate the first and the second heart sounds from the PCG signal. Ten features specific to CHD murmurs were extracted as the input of classifier after segmentation. Eighty-six artificial neural network classifiers were composed into a classification system to identify CHD murmurs. The accuracy, sensitivity, and specificity of diagnosis for heart murmurs were 93%, 93.5%, and 91.7%, respectively. In conclusion, a method of intelligent diagnosis of pediatric CHD murmurs is developed successfully and can be used for online screening of CHD in children.
Databáze: OpenAIRE
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