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    •   BracU IR
    • School of Engineering (SoE)
    • Department of Electrical and Electronic Engineering (EEE)
    • Thesis & Report, BSc (Electrical and Electronic Engineering)
    • View Item
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    Automatic classified myocardial infarction detection using machine learning and forewarning system with location of the patient using GSM module

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    17221001, 18121107, 17221008, 18121064_EEE.pdf (5.617Mb)
    Date
    2021-09
    Publisher
    Brac University
    Author
    Shrestha, Soptorsi Paul
    Amin, Md. Hasnatul
    Faisal, MD. Amir
    Alam, Syed Md. Jawadul
    Metadata
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    URI
    http://hdl.handle.net/10361/15613
    Abstract
    Myocardial Infarction (MI) is a crucially leading reasons of huge mortality and modality all over the world. The prior reasons for most of the demise are delayed diagnosis and disrupted medical attention. Our endeavor objectifies developing a portable system to detect MI instantly and incorporating a forewarning system using GSM and GPS module. The paper is focusing on the warning system delivering text messages containing classified MI information. Initially, the dataset has been preprocessed using Standard Scalar method and the preprocessed data has been trained and tested using K-Nearest Neighbor (KNN), Random Forest (RF), Support Vector Machine (SVM) and Naive Bayes (NB) to distinguish the MI affected ECG from normal ECG signal. The aim of this project is to avail immediate attention to a MI affected patient to ensure medical deliberation rapidly. Proper activation of the system will minimize the deadly effect of MI and hence reduce the mortality rate due to MI.
    Keywords
    Myocardial infarction; GSM; GPS; Text message; Standard scalar method; K-Nearest Neighbor; Random forest; Support Vector Machine; Naive bayes; ECG; Mortality rate
     
    LC Subject Headings
    Myocardial infarction; Medicine--Research; Global system for mobile communications
     
    Description
    This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2021.
     
    Cataloged from PDF version of thesis.
     
    Includes bibliographical references (pages 81-88).
    Department
    Department of Electrical and Electronic Engineering, Brac University
    Collections
    • Thesis & Report, BSc (Electrical and Electronic Engineering)

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