Arrhythmia warning algorithm

Arrhythmias are cardiac conduction dysfunctions that cause abnormal heartbeats, which can be detected through electrocardiographic (ECG) signals. However, visually analyzing ECG signals can be challenging and time-consuming due to the low amplitudes involved. To address this issue, an automate...

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Main Author: Tan, Calvin Jun Hao
Other Authors: Vidya Sudarshan
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/166715
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1667152023-05-12T15:37:01Z Arrhythmia warning algorithm Tan, Calvin Jun Hao Vidya Sudarshan School of Computer Science and Engineering vidya.sudarshan@ntu.edu.sg Engineering::Computer science and engineering Arrhythmias are cardiac conduction dysfunctions that cause abnormal heartbeats, which can be detected through electrocardiographic (ECG) signals. However, visually analyzing ECG signals can be challenging and time-consuming due to the low amplitudes involved. To address this issue, an automated system can be utilized in the clinical context to improve the speed and accuracy of arrhythmia diagnosis. This report presents a proposed ensemble model comprising convolutional neural network (CNN) and Support Vector Machine (SVM) to automate the identification of arrhythmias in ECG data. The model's hyperparameters will be optimized to achieve the best performance, with solutions presented for any problems encountered in the methods chapter. The report also includes the demonstration and assessment of the model's performance on several datasets. Bachelor of Engineering (Computer Science) 2023-05-09T07:38:43Z 2023-05-09T07:38:43Z 2023 Final Year Project (FYP) Tan, C. J. H. (2023). Arrhythmia warning algorithm. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166715 https://hdl.handle.net/10356/166715 en SCSE22-0488 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
spellingShingle Engineering::Computer science and engineering
Tan, Calvin Jun Hao
Arrhythmia warning algorithm
description Arrhythmias are cardiac conduction dysfunctions that cause abnormal heartbeats, which can be detected through electrocardiographic (ECG) signals. However, visually analyzing ECG signals can be challenging and time-consuming due to the low amplitudes involved. To address this issue, an automated system can be utilized in the clinical context to improve the speed and accuracy of arrhythmia diagnosis. This report presents a proposed ensemble model comprising convolutional neural network (CNN) and Support Vector Machine (SVM) to automate the identification of arrhythmias in ECG data. The model's hyperparameters will be optimized to achieve the best performance, with solutions presented for any problems encountered in the methods chapter. The report also includes the demonstration and assessment of the model's performance on several datasets.
author2 Vidya Sudarshan
author_facet Vidya Sudarshan
Tan, Calvin Jun Hao
format Final Year Project
author Tan, Calvin Jun Hao
author_sort Tan, Calvin Jun Hao
title Arrhythmia warning algorithm
title_short Arrhythmia warning algorithm
title_full Arrhythmia warning algorithm
title_fullStr Arrhythmia warning algorithm
title_full_unstemmed Arrhythmia warning algorithm
title_sort arrhythmia warning algorithm
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/166715
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