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Diferansiyel Gelişim Algoritması Kullanılarak Adaptif Süzgeçleme ile Fetal Elektrokardiyogram İşaretinin Çıkarılması ve İncelenmesi

Yıl 2018, Cilt: 39 Sayı: 1, 294 - 302, 22.03.2018
https://doi.org/10.17776/csj.407424

Öz

Son yıllarda yapılan çalışmalar fetal elektrokardiyogram (ECG)
işaretinin elde edilmesinin ve incelenmesinin sağladığı avantajları
göstermektedir. Bu çalışmada, diferansiyel gelişim algoritması ve adaptif
süzgeçleme kullanılarak fetal EKG işaretinin çıkarımı için yeni bir yaklaşım
önerilmiştir. Önerilen yaklaşım ile elde edilen sonuçlar literatürde en küçük
ortalama kareler metoduna dayanan adaptif metodun sonucu ile
karşılaştırılmıştır. Elde edilen sonuçlara göre önerilen yaklaşım fetal EKG
işaretini elde etme açısından daha iyi sonuç vermektedir.

Kaynakça

  • [1]. Barold S.S. Willem Einthoven and the Birth of Clinical Electrocardiography a Hundred Years Ago. Cardiac Electrophysiology Review, 7 (2003) 99-104.
  • [2]. Jia W., Yang C., Zhong G., Zhou M., Wu S. Fetal ECG extraction based on adaptive linear neural network. In:3rd International Conference on Biomedical Engineering and Informatics, Yantai, China,16–18 October 2010, pp.889-902.
  • [3]. Wu S., Shen Y., Zhou Z., Lin L., Zeng Y., Gao X. Research of fetal ECG extraction using wavelet analysis and adaptive filtering. Computers in Biology and Medicine, 43 (2013) 1622-7.
  • [4]. Congenital Heart Defects in Children Fact Sheet, American Heart Association 2008. [Online]. Available: http://www.americanheart.org/children.
  • [5]. Lathauwer L.D., Moor B.D., Vandewalle J. Fetal electrocardiogram extraction by blind source subspace separation. IEEE Trans. Biomed. Eng., 47 (2000) 567-572.
  • [6]. Ahmadieh H., Asl B.M. Fetal ECG extraction via Type-2 adaptive neuro-fuzzy inference systems. Computer Methods and Programs in Biomedicine, 142 (2017) 101-8.
  • [7]. Poungponsri S., Yu X-H. An adaptive filtering approach for electrocardiogram (ECG) signal noise reduction using neural networks. Neurocomputing, 117 (2013) 206-13.
  • [8]. Wei Z., Xueyun W., Jian ZJ., Hongxing L. Noninvasive fetal ECG estimation using adaptive comb filter. Computer Methods and Programs in Biomedicine, 112 (2013) 125-34. [9]. Martinek R., Kahankova R., Nazeran H., Konency J., Jezewski J., Janku P., Bilik P., Zidek J., Nedoma J., Fajkus M. Non-Invasive Fetal Monitoring: A Maternal Surface ECG Electrode Placement-Based Novel Approach for Optimization of Adaptive Filter Control Parameters Using the LMS and RLS Algorithms. Sensors, 17 (2017) 1-31.
  • [10]. Jagannath D.J., Selvakumar A.I., Issues and research on foetal electrocardiogram signal elicitation. Biomedical Signal Processing and Control, 10 (2014) 224-44.
  • [11]. Puthusserypady S., Extraction of fetal electrocardiogram using H(infinity) adaptive algorithms. Med. Biol. Eng. Comput., 45 (2007) 927-937.
  • [12]. Al-Zaben A., Al-Smadi A. Extraction of foetal ECG by combination of singular value decomposition and neuro-fuzzy inference system. Phys. Med. Biol., 51 (2006) 137-143.
  • [13]. Camps-Valls G., Martı́nez-Sober M., Soria-Olivas E., Magdalena-Benedito R., Calpe-Maravilla J., Guerrero-Martı́nez J. Foetal ECG recovery using dynamic neural networks. Artif. Intell. Med., 31 (2004) 197-209.
  • [14]. Khamene A., Negahdaripour Sh. A new method for the extraction of fetal ECG from the composite abdominal signal. IEEE Trans. Biomed. Eng., 47 (2000) 507-516.
  • [15]. Niknazar M., Rivet B., Jutten C. Fetal ECG extraction by extended state Kalman filtering based on single-channel recordings IEEE Trans. Biomed. Eng., 60 (2013) 1345-1352.
  • [16]. Assaleh K., Extraction of fetal electrocardiogram using adaptive neuro-fuzzy inference systems. IEEE Trans. Biomed. Eng., 54 (2007) 59-68.
  • [17]. Senim Y., Atasoy A., Performance evaluation of nonparametric ICA algorithm for fetal ECG extraction. Turk. J. Electr. Eng. Comput. Sci., 19 (2011) 657-666.
  • [18]. Najafabadi F.S., Zahedi E., Mohd Ali M.A., Fetal heart rate monitoring based on independent component analysis. Comput. Biol. Med., 36 (2006) 241-252.
  • [19]. Storn R., Price K., Differential Evolution – A simple and efficient heuristic for global optimization over continuous spaces. J. Global Optim., 11 (1997) 341-359.
  • [20]. Lathauwer L., Daisy: Database for the Identification of Systems: Biomedical Systems. http://homes.esat.kuleuven.be/~smc/daisy, 2000-10-10/2011-3-8.

Analysis and Extraction of Fetal Electrocardiogram Signal with Adaptive Filtering Using Differential Evolution Algorithm

Yıl 2018, Cilt: 39 Sayı: 1, 294 - 302, 22.03.2018
https://doi.org/10.17776/csj.407424

Öz

Recent studies have demonstrated the advantages
of fetal electrocardiogram (ECG) extraction and analysis. In this study, a new
approach is proposed for fetal ECG signal extraction using differential evolution
algorithm and adaptive filtering. The results obtained by the proposed approach
are compared with the result of the adaptive method based on the least mean
square method in the literature. According to the obtained results, the
proposed approach gives better results in terms of fetal ECG signal extraction.

Kaynakça

  • [1]. Barold S.S. Willem Einthoven and the Birth of Clinical Electrocardiography a Hundred Years Ago. Cardiac Electrophysiology Review, 7 (2003) 99-104.
  • [2]. Jia W., Yang C., Zhong G., Zhou M., Wu S. Fetal ECG extraction based on adaptive linear neural network. In:3rd International Conference on Biomedical Engineering and Informatics, Yantai, China,16–18 October 2010, pp.889-902.
  • [3]. Wu S., Shen Y., Zhou Z., Lin L., Zeng Y., Gao X. Research of fetal ECG extraction using wavelet analysis and adaptive filtering. Computers in Biology and Medicine, 43 (2013) 1622-7.
  • [4]. Congenital Heart Defects in Children Fact Sheet, American Heart Association 2008. [Online]. Available: http://www.americanheart.org/children.
  • [5]. Lathauwer L.D., Moor B.D., Vandewalle J. Fetal electrocardiogram extraction by blind source subspace separation. IEEE Trans. Biomed. Eng., 47 (2000) 567-572.
  • [6]. Ahmadieh H., Asl B.M. Fetal ECG extraction via Type-2 adaptive neuro-fuzzy inference systems. Computer Methods and Programs in Biomedicine, 142 (2017) 101-8.
  • [7]. Poungponsri S., Yu X-H. An adaptive filtering approach for electrocardiogram (ECG) signal noise reduction using neural networks. Neurocomputing, 117 (2013) 206-13.
  • [8]. Wei Z., Xueyun W., Jian ZJ., Hongxing L. Noninvasive fetal ECG estimation using adaptive comb filter. Computer Methods and Programs in Biomedicine, 112 (2013) 125-34. [9]. Martinek R., Kahankova R., Nazeran H., Konency J., Jezewski J., Janku P., Bilik P., Zidek J., Nedoma J., Fajkus M. Non-Invasive Fetal Monitoring: A Maternal Surface ECG Electrode Placement-Based Novel Approach for Optimization of Adaptive Filter Control Parameters Using the LMS and RLS Algorithms. Sensors, 17 (2017) 1-31.
  • [10]. Jagannath D.J., Selvakumar A.I., Issues and research on foetal electrocardiogram signal elicitation. Biomedical Signal Processing and Control, 10 (2014) 224-44.
  • [11]. Puthusserypady S., Extraction of fetal electrocardiogram using H(infinity) adaptive algorithms. Med. Biol. Eng. Comput., 45 (2007) 927-937.
  • [12]. Al-Zaben A., Al-Smadi A. Extraction of foetal ECG by combination of singular value decomposition and neuro-fuzzy inference system. Phys. Med. Biol., 51 (2006) 137-143.
  • [13]. Camps-Valls G., Martı́nez-Sober M., Soria-Olivas E., Magdalena-Benedito R., Calpe-Maravilla J., Guerrero-Martı́nez J. Foetal ECG recovery using dynamic neural networks. Artif. Intell. Med., 31 (2004) 197-209.
  • [14]. Khamene A., Negahdaripour Sh. A new method for the extraction of fetal ECG from the composite abdominal signal. IEEE Trans. Biomed. Eng., 47 (2000) 507-516.
  • [15]. Niknazar M., Rivet B., Jutten C. Fetal ECG extraction by extended state Kalman filtering based on single-channel recordings IEEE Trans. Biomed. Eng., 60 (2013) 1345-1352.
  • [16]. Assaleh K., Extraction of fetal electrocardiogram using adaptive neuro-fuzzy inference systems. IEEE Trans. Biomed. Eng., 54 (2007) 59-68.
  • [17]. Senim Y., Atasoy A., Performance evaluation of nonparametric ICA algorithm for fetal ECG extraction. Turk. J. Electr. Eng. Comput. Sci., 19 (2011) 657-666.
  • [18]. Najafabadi F.S., Zahedi E., Mohd Ali M.A., Fetal heart rate monitoring based on independent component analysis. Comput. Biol. Med., 36 (2006) 241-252.
  • [19]. Storn R., Price K., Differential Evolution – A simple and efficient heuristic for global optimization over continuous spaces. J. Global Optim., 11 (1997) 341-359.
  • [20]. Lathauwer L., Daisy: Database for the Identification of Systems: Biomedical Systems. http://homes.esat.kuleuven.be/~smc/daisy, 2000-10-10/2011-3-8.
Toplam 19 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Engineering Sciences
Yazarlar

Serdar Kockanat

Serkan Kockanat

Yayımlanma Tarihi 22 Mart 2018
Gönderilme Tarihi 17 Temmuz 2017
Kabul Tarihi 26 Aralık 2017
Yayımlandığı Sayı Yıl 2018Cilt: 39 Sayı: 1

Kaynak Göster

APA Kockanat, S., & Kockanat, S. (2018). Analysis and Extraction of Fetal Electrocardiogram Signal with Adaptive Filtering Using Differential Evolution Algorithm. Cumhuriyet Science Journal, 39(1), 294-302. https://doi.org/10.17776/csj.407424