Detection and Identification of Common Murmurs in Human Heart

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dc.contributor.authorRajaguru, R. W. M. N. D.
dc.contributor.authorSabani, M. J. A.
dc.date.accessioned2022-02-24T08:39:52Z
dc.date.available2022-02-24T08:39:52Z
dc.date.issued2013
dc.description.abstractAccording to the World Health Organization, heart diseases continue to remain one of the four major non communicable diseases in the world. Therefore early recognition of heart disease is an important goal in pediatrics. Heart murmurs are the results of underlying pathological changes in heart valves (Gupta et al. 2005). At present stethoscopes are used by medical professionals to detect and identify those (Leung et al. 2000). The main objective of this research is to implement a system where by a person can use a stethoscope themselves to check the condition of their hearts. This will save time and money. Professionals can use these systems to confirm their decision and also as an alternative to the traditional method. Recently, many research efforts have been carried out to apply artificial intelligence (AI) to auscultation based methods for rigorous detection/classification of heart murmurs but with low accuracy ( Ana et al., 2010). Most of the proposed systems have been using ECG or an Electronic Stethoscope for the implementation. In this project the input is obtained through an Acoustic Stethoscope and the system is implemented with a different procedure. For such circumstances, an ‘intelligent stethoscope’ with decision support abilities would be of great value. Here the aim is to develop an inexpensive screening device that can assist in the diagnosis of heart disorders where systolic murmurs and pulmonary stenosis murmurs are mainly focused. Methodology MATLAB was used as the main technology. MATLAB (matrix laboratory) is a numerical computing environment and fourth-generation programming language. Developed by Math Works, MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, artificial neural networks and also interfacing with programs written in the same language. The heart sound was given as the input to the computer using a microphone. As it is very low it has to be amplified using an amplifier. Then the amplified heart sound is sent to a computer audio port. Data is acquired from pre-recorded sources like a CD drive and the internet. Then the system was tested using 15 patients and results were documented. The stethoscope and an amplifier were used to develop the hardware part. Sound was recorded using a sound recorder and sent to the software.en_US
dc.identifier.urihttp://www.erepo.lib.uwu.ac.lk/bitstream/handle/123456789/8439/21-CST-Detection%20and%20Identification%20of%20Common%20Murmurs%20in%20Human%20Heart%20.pdf?sequence=1&isAllowed=y
dc.language.isoenen_US
dc.publisherUva Wellassa University of Sri Lankaen_US
dc.subjectComputer Scienceen_US
dc.subjectScience and Technologyen_US
dc.subjectTechnologyen_US
dc.subjectSystemen_US
dc.subjectHealth Scienceen_US
dc.subjectSoftware Developingen_US
dc.titleDetection and Identification of Common Murmurs in Human Hearten_US
dc.title.alternativeResearch Symposium 2013en_US
dc.typeOtheren_US
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