TY - GEN
T1 - ST Segment Detection in Myocardial Infarction Using STM32
AU - Setiawan, Rachmad
AU - Hikmah, Nada Fitrieyatul
AU - Sudrajat, Fadhil Zamzam
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Heart disease is a condition when the heart is disturbed. There are various forms of the disorder, including disorders of the heart's blood vessels, heart rhythm and heart valves. Data from the World Health organization (WHO) shows that 70% of deaths in the world are caused by non-communicable diseases (39.5 million of 56.4 deaths). Of all deaths due to non-communicable diseases (NCD), 45% were caused by heart and blood vessel disease, namely 17.7 million out of 39.5 million deaths. Therefore, this study was conducted to facilitate the process of prevention and treatment for patients with symptoms of heart disease, especially in conditions of myocardial infarction. In this study, the process of detecting heart signal waves in ST segmentation of cardiac data is processed using the biomedical signal classification method and heart signal wave classification using the hardware of the STM32F4 M4 microcontroller. This tool aims to record electrical signals in the heart and detect abnormalities in the rhythm and structure of the heart. The classification process is done by segmenting the signal from the ECG signal wave, segmenting the ST signal point and calculating the elevation point of the ST point segmentation of the heart signal. Furthermore, the process of inputting data into the STM32 microcontroller as hardware in this study that can be used and is available at public health centers.
AB - Heart disease is a condition when the heart is disturbed. There are various forms of the disorder, including disorders of the heart's blood vessels, heart rhythm and heart valves. Data from the World Health organization (WHO) shows that 70% of deaths in the world are caused by non-communicable diseases (39.5 million of 56.4 deaths). Of all deaths due to non-communicable diseases (NCD), 45% were caused by heart and blood vessel disease, namely 17.7 million out of 39.5 million deaths. Therefore, this study was conducted to facilitate the process of prevention and treatment for patients with symptoms of heart disease, especially in conditions of myocardial infarction. In this study, the process of detecting heart signal waves in ST segmentation of cardiac data is processed using the biomedical signal classification method and heart signal wave classification using the hardware of the STM32F4 M4 microcontroller. This tool aims to record electrical signals in the heart and detect abnormalities in the rhythm and structure of the heart. The classification process is done by segmenting the signal from the ECG signal wave, segmenting the ST signal point and calculating the elevation point of the ST point segmentation of the heart signal. Furthermore, the process of inputting data into the STM32 microcontroller as hardware in this study that can be used and is available at public health centers.
KW - discrete fourier transform
KW - electrocardiography
KW - feature extraction
KW - heart disease
KW - myocardial infarction
UR - http://www.scopus.com/inward/record.url?scp=85137872010&partnerID=8YFLogxK
U2 - 10.1109/ISITIA56226.2022.9855289
DO - 10.1109/ISITIA56226.2022.9855289
M3 - Conference contribution
AN - SCOPUS:85137872010
T3 - 2022 International Seminar on Intelligent Technology and Its Applications: Advanced Innovations of Electrical Systems for Humanity, ISITIA 2022 - Proceeding
SP - 18
EP - 23
BT - 2022 International Seminar on Intelligent Technology and Its Applications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd International Seminar on Intelligent Technology and Its Applications, ISITIA 2022
Y2 - 20 July 2022 through 21 July 2022
ER -