Open Access Journal
ISSN : 2394 - 6849 (Online)
International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)
Open Access Journal
International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)
ISSN : 2394-6849 (Online)
Reference :
[1]J.W.Schleifer and K.Srivathsan, “Ventricular arrhythmias: State of the art,” Cardiol. Clin., vol. 31, no. 4, pp. 595–605, 2013.
[2] D.P. Zipes and H. J. J. Wellens, “Sudden cardiac death,” Circulation,vol. 98, no. 21, pp. 2334–2351, 1998.
[3]C.J.Garratt,Mechanisms and Management of Cardiac Arrhythmias. London, U.K.: BMJ Books, 2001.
[4]P.de Chazal, M. O’Dwyer, and R. B. Reilly, “Automatic classification of heartbeats using ECG morphology and heartbeat interval features,”IEEE Trans. Biomed. Eng., vol. 51, no. 7, pp. 1196–1206, Jul. 2004.
[5]A.Amann, R. Tratnig, and K. Unterkofler, “Detecting ventricular fibrillation by time-delay methods,” IEEE Trans. Biomed. Eng., vol. 54,no. 1, pp. 174–177, Jan. 2007.
[6] O. Sayadi, M. B. Shamsollahi, and G. D. Clifford, “Robust detection of premature ventricular contractions using a wave-based Bayesian framework,” IEEE Trans. Biomed. Eng., vol. 57, no. 2, pp. 353–362, Feb. 2010.
[7]X.-S. Zhang, Y.-S. Zhu, N. V. Thakor, and Z.-Z. Wang, “Detecting ventricular tachycardia and fibrillation by complexity measure,” IEEETrans. Biomed. Eng., vol. 46, no. 5, pp. 548–555, May 1999.
[8]J. Pardey, “Detection of ventricular fibrillation by sequential hypothesis testing of binary sequences,” in Proc. IEEE Comput. Cardiol., Sep./Oct. 2007, pp. 573–576.
[9]Q.Li, C. Rajagopalan, and G. D. Clifford, “Ventricular fibrillation and tachycardia classification using a machine learning approach,” vol. 61, no. 3, pp. 1607–1613, Jun. 2013.
[10]B.-Y. Shiu, S.-W. Wang, Y.-S. Chu, and T.-H. Tsai, “Low-power low-noise ECG acquisition system with dsp for heart disease identification,” in Proc. IEEE Biomed. Circuits Syst. Conf. (BioCAS),Oct./Nov. 2013, pp. 21–24.
[11] H. Kim, R. F. Yazicioglu, T. Torfs, P. Merken, H.-J. Yoo, and C. Van Hoof, “A low power ECG signal processor for ambulatory arrhythmia monitoring system,” in Proc. IEEE Symp. VLSI Circuits (VLSIC), Jun. 2010, pp. 19–20.
[12] H. Kim, R. F. Yazicioglu, P. Merken, C. Van Hoof, and H.-J. Yoo, “ECG signal compression and classification algorithm with quad level vector for ECG holter system,” IEEE Trans. Inf. Technol. Biomed., vol. 14, no. 1, pp. 93–100, Jan. 2010.
[13] S.-Y. Lee, J.-H. Hong, C.-H. Hsieh, M.-C. Liang, S.-Y. C. Chien, and K.-H. Lin, Low-power wireless ECG acquisition and classification system for body sensor networks,” IEEE J. Biomed. Health Informat., vol. 19, no. 1, pp. 236–246, Jan. 2015.
[14] Y.-P. Chen et al., “An injectable 64 nW ECG mixed-signal SoC in 65 nm for arrhythmia monitoring,” IEEE J. Solid-State Circuits, vol. 50, no. 1, pp. 375–390, Jan. 2015.
[15] J. Pan and W. J. Tompkins, “A real-time QRS detection algorithm,”IEEE Trans. Biomed. Eng., vol. BME-32, no. 3, pp. 230–236,Mar. 1985