THE USAGE OF STATISTICAL FEATURES IN THE APPROXIMATION COMPONENTS OF WAVELET DECOMPOSITION FOR ECG CLASSIFICATION: A CASE STUDY FOR STANDING, WALKING AND SINGLE JUMP CONDITIONS

Makbule Hilal MÜTEVELLİ; Semih ERGİN

Makale detayları

THE USAGE OF STATISTICAL FEATURES IN THE APPROXIMATION COMPONENTS OF WAVELET DECOMPOSITION FOR ECG CLASSIFICATION: A CASE STUDY FOR STANDING, WALKING AND SINGLE JUMP CONDITIONS

Yazarlar:

Makbule Hilal MÜTEVELLİ | Semih ERGİN

Yayıncı:

Kirklareli University

Dergi:

Ejovoc (Electronic Journal of Vocational Colleges) 2018 Vol.8 Issue 2, pp.178-182

Belge Tipi:

Makale

Yayın Tarihi:

11/2018

Belge Dili:

İngilizce

Document ID (Org No.):

2000692995

eISSN:

2146-7684

pISSN:

2146-7684

Özet:

 



The purpose of this study is to classify
electrocardiogram (ECG) signals with a high accuracy rate. The ECG signals used
are obtained from the Physiobank archive. These signals are preprocessed to
remove noise. Features with distinctiveness in classification are obtained both
in the time domain and the frequency domain. The Discrete Wavelet Transform
method is used for feature extraction in frequency domain. ECG signals are
classified by the Naive Bayes method after the required features are extracted.




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The purpose of this study is to classify
electrocardiogram (ECG) signals with a high accuracy rate. The ECG signals used
are obtained from the Physiobank archive. These signals are preprocessed to
remove noise. Features with distinctiveness in classification are obtained both
in the time domain and the frequency domain. The Discrete Wavelet Transform
method is used for feature extraction in frequency domain. ECG signals are
classified by the Naive Bayes method after the required features are extracted.




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Makale detayları

THE USAGE OF STATISTICAL FEATURES IN THE APPROXIMATION COMPONENTS OF WAVELET DECOMPOSITION FOR ECG CLASSIFICATION: A CASE STUDY FOR STANDING, WALKING AND SINGLE JUMP CONDITIONS

Yazarlar: Makbule Hilal MÜTEVELLİ | Semih ERGİN

Yayıncı: Kirklareli University

Dergi: Ejovoc (Electronic Journal of Vocational Colleges) 2018 Vol.8 Issue 2, pp.178-182

Belge Tipi: Makale

Yayın Tarihi: 11/2018

Belge Dili: İngilizce

Document ID (Org No.): 2000692995

eISSN: 2146-7684

pISSN: 2146-7684

Sayı

Yazarlar:

Makbule Hilal MÜTEVELLİ | Semih ERGİN

Yayıncı:

Kirklareli University

Dergi:

Ejovoc (Electronic Journal of Vocational Colleges) 2018 Vol.8 Issue 2, pp.178-182

Belge Tipi:

Makale

Yayın Tarihi:

11/2018

Belge Dili:

İngilizce

Document ID (Org No.):

2000692995

eISSN:

2146-7684

pISSN:

2146-7684