Mobile Phone-Based Rheumatic Heart Disease Diagnosis

Mobile Phone-Based Rheumatic Heart Disease Diagnosis. Springer, D., B., Zühlke, L., J., Mayosi, B., M., Tarassenko, L., & Clifford, G., D. In Appropriate Healthcare Technologies for Low Resource Settings - AHT2014, pages 1, 9, 2014. IET Digital Library.

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It is estimated that between 15.6 and 19.6 million people are living with rheumatic heart disease (RHD) worldwide, accounting for about one million deaths annually and 60% of Africa's open heart surgeries. As RHD results in heart murmurs that are almost always audible during auscultation, a mobile phone-based automatic auscultation device has the potential to identify those individuals with a high risk of having RHD. Such a device would allow cost-effective treatment while not requiring expert training or expensive equipment. This paper addresses two of the major steps when processing heart sounds recordings using such a device: signal quality classification, which achieved over 90% accuracy, and heart sound segmentation, with 93.5% F1 score. Future steps required to develop a fully automatic device are then discussed.

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 abstract = {It is estimated that between 15.6 and 19.6 million people are living with rheumatic heart disease (RHD) worldwide, accounting for about one million deaths annually and 60% of Africa&apos;s open heart surgeries. As RHD results in heart murmurs that are almost always audible during auscultation, a mobile phone-based automatic auscultation device has the potential to identify those individuals with a high risk of having RHD. Such a device would allow cost-effective treatment while not requiring expert training or expensive equipment. This paper addresses two of the major steps when processing heart sounds recordings using such a device: signal quality classification, which achieved over 90% accuracy, and heart sound segmentation, with 93.5% F1 score. Future steps required to develop a fully automatic device are then discussed.},
 bibtype = {inProceedings},
 author = {Springer, D.B. B and Zühlke, L.J. J and Mayosi, B.M. M and Tarassenko, L. and Clifford, Gari D},
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