Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/524493
Title: | Certain investigations on ecg signal denoising arrhythmia detection and classification using hybrid classifiers |
Researcher: | Thirrunavukkarasu R R |
Guide(s): | Meera Devi T |
Keywords: | Computer Science Computer Science Information Systems Engineering and Technology |
University: | Anna University |
Completed Date: | 2023 |
Abstract: | newline Arrhythmia is one of the most persistent chronic heart diseases in the newlineelderly and is associated with high morbidity and mortality such as stroke, newlinecardiac failure, and coronary artery diseases. It is significant for patients with newlinearrhythmias to automatically detect and classify arrhythmia heartbeats using newlineElectrocardiogram (ECG) signals. Denoising, feature extraction, and newlineclassification has become a major difficult task in ECG signals. In order to newlinesolve these problems, three major contributions have been made in this newlineresearch work are described as follows. newline |
Pagination: | x,144p |
URI: | http://hdl.handle.net/10603/524493 |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 10.42 kB | Adobe PDF | View/Open |
02_prelim.pdf | 1.71 MB | Adobe PDF | View/Open | |
03_content.pdf | 279.89 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 9.83 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 500.12 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 214.13 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 991.77 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 1.17 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 670.07 kB | Adobe PDF | View/Open | |
10_annexures.pdf | 107.62 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 78.44 kB | Adobe PDF | View/Open |
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