Electrocardiograph Signals Diagnosis Using Adaptive Neuro-Fuzzy Inference System
DOI:
https://doi.org/10.54388/jkues.v2i4.217Keywords:
ANFIS, ECG, ICA, Power spectrum, RR interval, GUI, MIT-BIHAbstract
Electrocardiograph (ECG) is a bioelectrical signal that is obtained by non-invasive method to register the electrical activities of the heart. This paper provides an attempt to develop computerized system for ECG signal filtering and classification. The proposed system encompass: pre-processing of the signal, extraction of pattern features through Independent Component Analysis (ICA), power spectrum, and RR interval calculation. These processes provide an input feature vector to the Adaptive Neuro Fuzzy Inference System (ANFIS) that acts as a signal classifier. All of the classification process steps are implemented in MATLAB
environment. This paper also provides a Graphical User Interface (GUI) that makes classification process easier. Three cases of ECG waveforms that are selected from MIT-BIH database are considered for the system test; they are Normal (N), Ventricle Fibrillation (VF), and Ventricular tachycardia (VTachy). An accuracy of 96.66% has been achieved by the proposed system
References
C.-C. Chiu, T.-H. Lin, and B.-Y. Liau, “Using correlation coefficientin ecg waveform for arrhythmia detection,” Biomedical Engineering: Applications, Basis and Communications, vol. 17, no. 03, pp. 147–152, 2005.
K. M. Bukkur, K. Ahmed, and M. Shukri, “Dynamic scheduling of assembly line using neural networks for saria industrial complex-sudan,” Journal of Karary University for Engineering and Science, 2022.
I. MathWorks, “Mathworks, inc. matlab: the language of technical computing. desktop tools and development environment, version 9.0. 0.341360,” Natwick: Math Works Inc., 1996.
E. K. E. I. Ahmed, “Effects of ferromagnetic cores in wireless power transfer system for charging electric vehicles,” Journal of Karary University for Engineering and Science, 2022.
S. W. Yoon, H. S. Shin, S. D. Min, and M. Lee, “Adaptive motion artifacts reduction algorithm for ecg signal in textile wearable sensor,” IEICE Electronics Express, vol. 4, no. 10, pp. 312–318, 2007.
M. A. Mustaffa, E. M. Hussein, and A. M. Ishag, “Ann based location of fault for 500kv transmission line in sudan from merowe to atbara,” Journal of Karary University for Engineering and Science, 2022.
J.-S. Jang, “Anfis: adaptive-network-based fuzzy inference system,” IEEE transactions on systems, man, and cybernetics, vol. 23, no. 3, pp. 665–685, 1993.
