| Author | Chakka, Asrith Krishna |
| Note | A thesis submitted in partial fulfillment of the requirements for the
degree of Master of Engineering in
Microelectronics and Embedded systems |
| Publisher | Asian Institute of Technology |
| Abstract | As per the data given by WHO many people die due to heart diseases and it is considered as the second greatest killer. So, any upgradations or improvements in treatments or diagnosis tools would be of great help to the society and are most encouraged in the medical field. Electrocardiogram (ECG) is considered as the most useful tool for diagnosing heart patients. This is operated by recording the electrical signals that heart emits and these emitted signals are recorded using electrodes that are placed on the chest and limbs. The main purpose of the project is to classify heart diseases by digital signal processing of ECG signals and diagnosing those diseases. Those diseases that can be classified by digital signal processing of ECG signals include arrhythmia, heat block, cardiomyopathy, bundle branch block etc. So, our main objective is to classify some of these diseases and diagnose them. Pan Tompkins algorithm is used for the purpose of detecting QRS complex and discrete wavelet transform for wave decomposition, for classifying these signals we used k- Nearest Neighbor algorithm. Using MATLAB these ECG signals are digital signal processed. ECG signals that are used in this paper are obtained from PTB Diagnostic database of physionet.org. |
| Year | 2017 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Industrial Systems Engineering (DISE) |
| Academic Program/FoS | Microelectronics (ME) |
| Chairperson(s) | Mongkol Ekpanyapong; |
| Examination Committee(s) | Bohez, Erik L. J.;Abeykoon; |
| Scholarship Donor(s) | Asian Institute of Technololgy Felloship; |
| Degree | Thesis (M.Eng.) -- Asian Institute of Technology, 2017 |