Abstract—Heart rate variability (HRV) analysis attempts to assess cardiac autonomic regulation through quantification of sinus rhythm variability. The sinus rhythm times series is derived from the QRS to QRS (RR) interval sequence of the electrocardiogram (ECG), by extracting only normal sinus to normal sinus (NN) interbeat intervals. Relatively high frequency variations in sinus rhythm reflect parasympathetic (vagal) modulation, and slower variations reflect a combination of both parasympathetic and sympathetic modulation and non-autonomic factors. The paper focuses on the Neuro-fuzzy system. It is used to recognize the HRV signals for diagnosis by extract the QRST zone of ECG signals using Discrete Cosine Transform (DCT). The result is exciting as much as we have used only one of ECG lead to records input data, while the current diagnosis approaches require the set of 12 lead ECG signals!

Index Terms—Heart rate variability, neuro-fuzzy, discrete cosine transform.

Hoang ChuDuc and Thuan NguyenDuc are with Department of Electronics Technology and Biomedical Engineering, School of Electronics and Telecommunications, Hanoi University of Scicence and Technology, Hanoi, Vietnam (e-mail: hoang.chuduc@hust.edu.vn, thuan.nguyenduc @hust.edu.vn).
Trung LaiHuuPhuong is with Center of Electronics and Biomedical, Hanoi University of Scicence and Technology, Hanoi, Vietnam (e-mail: trung.laihuuphuong@hust.edu.vn).

 

Cite:Hoang ChuDuc, Thuan NguyenDuc, and Trung LaiHuuPhuong, "Neuro-Fuzzy Approach to Heart Rate Variability Analysis," International Journal of Bioscience, Biochemistry and Bioinformatics vol. 3, no. 5, pp. 456-459, 2013.