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ECG Signal Classification using Higher-Order Complexity of Hjorth Descriptor Sugondo Hadiyoso School of Applied Science, Telkom University
[email protected] Achmad Rizal School of Electrical Engineering, Telkom University
[email protected]
Introduction ECG electrical activity of heart Some method for ECG signal processing: PCA (Bollman, et.al 2005, Xiao, et.al 2011, Joy, et.al 2013), wavelet (Addison, 2005, etc).. Signal complexity for ECG biological signal behavior (Costa, 2002)
Introduction Hjorth descriptor (Hjorth, 1973): parameter to quantify EEG signal complexity behavior Some Hjorth descriptor application in biomedical signal:
EEG (Hjorth, 1973), EMG (Mouzé-Amady & Horwat 1996), ECG (Blanco-velasco et al. 2010), Lung sound (Rizal et al, 2015)
Material and Method Data Atrial fibrillation (AF), Congestive Heart Failure (CHF), Normal Sinus Rhythm (NSR) (Physionet.org) 50 data each Fs= 250 Hz, 2-3 s length
Preprocessing Mean removal
Amplitude normalization
Material and Method Hjorth Descriptor (Hjorth 1973) First order signal variation Second order signal variation Standard deviation :
Material and Method Higher-order complexity of Hjorth Descriptor
n=1, 2, …, 5
Material and Method Classifier K-NN K=1,3,5, 7 euclidean distance, Multilayer Perceptron (MLP) 5-15-3, 5-30-3,5-45-3 Variation on number of hidden layer
Validation N-fold cross validation, N = 5 and N =10 50% training data, 50% testing data
Parameter of performance
Result & Discussion Normal Signal and its N-derivative for N =1,2,…,5
Result & Discussion CHF Signal and its N-derivative for N =1,2,…,5
Result & discussion Effect of hidden layer number on accuracy
Accuracy for various MLP configuration
Accuracy for K-NN
Result & Discussion Confusion matrix for the highest accuracy
Data
Classified as
NSR
AF
CHF
Se
Sp
NSR
50
0
0
100% 100%
AF
0
48
2
96%
93%
CHF
0
7
43
86%
98%
Acc
94%
Result & Discussion Complexity order 1-5 < Hjorth descriptor (activity, mobility, complexity order 1) Complexity order 1-5 multiscale behavior of biological signal (Costa, 2015) Advantages of Hjorth descriptor - low cost computation - less number of features Drawback of Hjorth descriptor - need signal segmentation - sensitive to noise
Conclussion Complexity order 1 – 5 of Hjorth descriptor accuracy up to 94% Less accurate than Hjorth descriptor (activity, mobility, complexity) Hjorth descriptor simple computation, less number of features Next challenges Effect of noise to accuracy Rare or uncommon ECG signal
