Author(s): Mansik Kim, Hyunsoo Chung, Moon-seog Jun

Email(s): Email ID Not Available

DOI: 10.5958/0974-360X.2019.00377.9   

Address: Mansik Kim1, Hyunsoo Chung2, Moon-seog Jun3*
1,3Department of Computer Science and Engineering, Soongsil University, 369 Sangdo-Ro, Dongjak-gu, Seoul 156-743, Korea
2Department of IT Convergence Industry Technology Center, Soongsil University, 369 Sangdo-Ro, Dongjak-gu, Seoul 156-743, Korea
*Corresponding Author

Published In:   Volume - 12,      Issue - 5,     Year - 2019


ABSTRACT:
Background/Objectives: With the development of medical technology and the improvement of sanitary environment, human life expectancy has been increasing overcoming fatal diseases, but some diseases still remain as major causes of death. Among them, heart disease is one of the most common causes of death in the world, always in 1st or 2nd place for causes of death. Methods/Statistical analysis: In order to minimize the death from heart disease, prevention and early diagnosis should be done rather than treatment, and in general, ECG measurement can be used to diagnose heart disease. The ECG is a measurement of the electrical signal of the heart using an ECG measuring instrument, which is diagnosed by a specialist, which causes the problem that the patient has to visit the hospital every time. With the recent development of ICT technology, wearable ECG measurement devices are now available for measuring ECG in real life, and by using them it is possible to detect heart disease by measuring ECG without visiting a hospital. Findings: This paper proposes an ECG heart disease detection scheme and infrastructure to diagnose and prescribe heart disease remotely by extracting ECG biomarker from a patient through a wearable ECG measurement device. ECG biomarker can be extracted to provide real-time comparative analysis of heart disease ECG signatures to detect heart disease in an ECG analyzer without the help or expertise of a specialist. Improvements/Applications: Through the proposed ECG biomarker-based heart disease detection scheme and infrastructure, patients and average people can prevent heart disease early and cope with it early.


Cite this article:
Mansik Kim, Hyunsoo Chung, Moon-seog Jun. ECG Biomarker based Heart Disease Automation Detection Scheme. Research J. Pharm. and Tech. 2019; 12(5):2267-2270. doi: 10.5958/0974-360X.2019.00377.9


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RNI: CHHENG00387/33/1/2008-TC                     
DOI: 10.5958/0974-360X 


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