Heart condition determination based on MET value to NYHA classification and abnormal ST segment identification
Cardiovascular diseases have always been among the top causes of death. Thus, there were variety of research focuses on cardiac stress test and on self-stress test as well. However, the portable device existed for heart monitoring were still insufficient where most device are for fitness monitoring...
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Main Authors: | , , |
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Format: | Conference or Workshop Item |
Language: | English |
Published: |
2023
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Subjects: | |
Online Access: | http://eprints.utm.my/107889/1/MohdAfzanOthman2023_HeartConditionDeterminationbasedonMET.pdf http://eprints.utm.my/107889/ http://dx.doi.org/10.1088/1742-6596/2622/1/012007 |
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Institution: | Universiti Teknologi Malaysia |
Language: | English |
Summary: | Cardiovascular diseases have always been among the top causes of death. Thus, there were variety of research focuses on cardiac stress test and on self-stress test as well. However, the portable device existed for heart monitoring were still insufficient where most device are for fitness monitoring rather than functional capacity. Thus, this paper determines heart condition based on New York Heart Classification (NYHA) for The Rockport Walking Fitness Test (TRWFT). TRWFT gave out parameters to calculate maximum oxygen consumption (VO2max) to find metabolic equivalent (MET) value. The MET values were compared with NYHA functional capacity classes. Hence, the comparison simplified the heart condition to the urgency to visit hospitals. Plus, ST segments of MIT-BIH ECG database were extracted and assessed for abnormality. Accordingly, a mobile application was developed. The prototype is built using Genuino 101 microcontroller, an AD8232 ECG module with leads to sense heart pulse, and a SD card module. Meanwhile, simulation test on the prototype shows that the prototype succeeds in produce the same values with manual calculation and managed to assess ST segments as programmed. In conclusion, a prototype to demonstrate the implementation of TRFWT and prediction of cardiac condition based on MET value is successful. |
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