A better online method of heart diagnosis
Conference Publication ResearchOnline@JCUAbstract
Heart related health conditions, such as heart attacks, are the primary reasons for millions of deaths worldwide. Most of the existing heart-disease diagnosis techniques are invasive and need trained medical professionals. The current paper reports the development of a rapid, non-invasive heart sound diagnosis method and describes its functionality in Health Social Networks (HSNs). HSNs are platforms for health professionals, organizations and patients to use IT applications to share information, including medical information, e.g., HSNs allow users to conveniently and inexpensively upload their heart sounds for professional analysis using mobile phones. This method offers great promise, as heart-related health conditions cause millions of deaths worldwide. This paper contributes to the development of a new feature extraction method based on Gaussian Hamming Distance (GHD). The approach that applying GHD to MFCC features (GMTS) is shown robust to noise and also solves the difficulties of recording heart sound activities. The proposed GMTS feature was tested with 0.05 seconds shifting stress and obtained accuracy, sensitivity and specificity of at least 84.2%, 77.8%, and 84.5%, respectively.
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Publication Name
ACM International Conference Proceeding Series
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ISBN/ISSN
978-1-4503-7224-4
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Pages Count
6
Location
Seoul, Korea
Publisher
ACM Digital Library
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Publisher Location
New York, NY, USA
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DOI
10.1145/3278229.3278237