Staffordshire University logo
STORE - Staffordshire Online Repository

Development of a computerized ECG analysis model using the cubic spline interpolation method

Kalovrektis, Konstantinos, Ganetsos, Theodore, SHAMMAS, Noel, Taylor, Ian and ANDONOPOULOS, John (2011) Development of a computerized ECG analysis model using the cubic spline interpolation method. In: CSS'11 Proceedings of the 5th WSEAS international conference on Circuits, systems and signals, 14-16 July 2011, Corfu Island, Greece.

[img]
Preview
Image
development 21.JPG

Download (92kB) | Preview

Abstract or description

An electrocardiogram (ECG) is a bioelectrical signal which records the heart's electrical activity versus time. It is an important diagnostic tool for assessing heart functions. The interpretation of ECG signal is an application of pattern recognition. The techniques used in this pattern recognition comprise: signal preprocessing, QRS detection, creation of variables and signal classification. In this method, signal processing and programs implementation are based in Matlab environment. Matlab was used to develop a program that could further examine, analyze and study the ECG samples. Since the heart waveform can be simulated by cubic spline interpolation, this feature was used by the implemented Matlab program. The ECG samples were normalized and processed to produce 4 specific coefficients. These 4 coefficients of cubic spline were used in the applied methodology in order to evaluate and separate the various heart disorders with mathematical terms and equations. Based on the results of the applied methodology, the categorization of heart disorders without actual clinical examination is possible.

Item Type: Conference or Workshop Item (Paper)
Faculty: Previous Faculty of Computing, Engineering and Sciences > Engineering
Event Title: CSS'11 Proceedings of the 5th WSEAS international conference on Circuits, systems and signals
Event Location: Corfu Island, Greece
Event Dates: 14-16 July 2011
Depositing User: Khaja MOHAMMED
Date Deposited: 28 Jan 2013 15:16
Last Modified: 24 Feb 2023 13:36
URI: https://eprints.staffs.ac.uk/id/eprint/423

Actions (login required)

View Item View Item

DisabledGo Staffordshire University is a recognised   Investor in People. Sustain Staffs
Legal | Freedom of Information | Site Map | Job Vacancies
Staffordshire University, College Road, Stoke-on-Trent, Staffordshire ST4 2DE t: +44 (0)1782 294000