| Using voice-recognition technology to eliminate cardiac cycle segmentation in automated heart sound diagnosis. | |
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MedLine Citation:
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PMID: 17432672 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Advanced digital signal processing has the potential to revolutionize the stethoscope through the use of mathematical algorithms to interpret heart sound acoustic information. In this study, a novel classification algorithm that does not require cardiac cycle segmentation was used for identifying differences between normal and diseased heart sounds. The heart sound signals were not separated into systole and diastole. A recordable electronic stethoscope was used to record the heart sounds of 163 echocardiogram patients. Mel-cepstrum and Principal Components Analysis were applied to the 60 recorded heart sounds and decision spaces were developed. The algorithm was tested using 100 novel patients. The specificity of the algorithm is 72.4% and the sensitivity is 63.4%. |
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Authors:
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Marie Guion Johnson; Ahmed Tewfik; K P Madhu; Arthur G Erdman |
Publication Detail:
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Type: Evaluation Studies; Journal Article |
Journal Detail:
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Title: Biomedical instrumentation & technology / Association for the Advancement of Medical Instrumentation Volume: 41 ISSN: 0899-8205 ISO Abbreviation: Biomed Instrum Technol Publication Date: 2007 Mar-Apr |
Date Detail:
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Created Date: 2007-04-16 Completed Date: 2007-05-16 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8905560 Medline TA: Biomed Instrum Technol Country: United States |
Other Details:
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Languages: eng Pagination: 157-66 Citation Subset: IM |
Affiliation:
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Department of Mechanical Engineering, University of Minnesota, Minneapolis 55455, USA. guio0001@umn.edu |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Adolescent Adult Aged Aged, 80 and over Algorithms* Artificial Intelligence* Biotechnology / methods Diagnosis, Computer-Assisted / methods* Female Heart Auscultation / instrumentation, methods* Heart Murmurs / diagnosis* Heart Valve Diseases / diagnosis* Humans Male Middle Aged Pattern Recognition, Automated / methods* Reproducibility of Results Sensitivity and Specificity Speech Recognition Software |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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