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[1] C. C. Chan, W. C. Chou, C. W. Chen, Y. L. Ho, Y. H. Lin, and H. P. Ma, “Energy efficient diagnostic grade mobile ECG monitoring,” in IEEE International Conference on New Circuits and Systems (NEWCAS), Montreal, Canada, June 2012, pp. 153–156. [2] C. C. Chan, C. W. Chen, W. C. Chou, Y. L. Ho, Y. H. Lin, and H. P. Ma, “Live demonstration: A mobile ECG healthcare platform,” in IEEE International Conference on Biomedical Circuits and Systems (BioCAS), Hsinchu, Taiwan, November 2012, p. 87. [3] K. Maharatna, E. B. Mazomenos, J. Morgan, and S. Bonfiglio, “Towards the development of next-generation remote healthcare system: Some practical considerations,” in IEEE International Symposium on Circuits and Systems (ISCAS), Seoul, Korea, May 2012, pp. 1–4. [4] N. Verma, A. Shoeb, J. Bohorquez, J. Dawson, J. Guttag, and A. Chandrakasan, “A micro-power EEG acquisition SoC with integrated feature extraction processor for a chronic seizure detection system,” IEEE Journal of Solid-State Circuits, vol. 45, no. 4, pp. 804–816, 2010. [5] C. I. Ieong, P. I. Mak, C. P. Lam, C. Dong, M. I. Vai, P. U. Mak, S. H. Pun, F. Wan, and R. Martins, “A 0.83-µw QRS detection processor using quadratic spline wavelet trans- form for wireless ECG acquisition in 0.35-µm CMOS,” IEEE Transactions on Biomedical Circuits and Systems, vol. 6, no. 6, pp. 586–595, 2012. [6] S. Pal and M. Mitra, “QRS complex detection using empirical mode decomposition based windowing technique,” in IEEE International Conference on Signal Processing and Communications (SPCOM), Bangalore, Indian, July 2010, pp. 1–5.66 BIBLIOGRAPHY [7] E. Mazomenos, D. Biswas, A. Acharyya, T. Chen, K. Maharatna, J. Rosengarten, J. Morgan, and N. Curzen, “A low-complexity ECG feature extraction algorithm for mobile healthcare applications,” IEEE Journal of Biomedical and Health Informatics, vol. 17, no. 2, pp. 459–469, 2013. [8] Z. Zidelmal, A. Amirou, M. Adnane, and A. Belouchrani, “QRS detection based on wavelet coefficients,” Computer Methods and Programs in Biomedicine, vol. 107, no. 3, pp. 490 – 496, 2012. [9] Y. J. Min, H. K. Kim, Y. R. Kang, G. S. Kim, J. Park, and S. W. Kim, “Design of wavelet-based ECG detector for implantable cardiac pacemakers,” IEEE Transactions on Biomedical Circuits and Systems, vol. 7, no. 4, pp. 426–436, 2013. [10] M. W. Phyu, Y. Zheng, B. Zhao, L. Xin, and Y. S. Wang, “A real-time ECG QRS detection ASIC based on wavelet multiscale analysis,” in IEEE Interference Conference on Asian Solid-State Circuits Conference (A-SSCC), Tapei, Taiwan, November 2009, pp. 293–296. [11] C. V. Mieghem, M. Sabbe, and D. Knockaert, “The clinical value of the ECG in noncardiac conditions,” Chest Journal, vol. 125, no. 4, pp. 1561–1576, April 2004. [12] J. Loscalzo, Harrison’s Cardiovascular Medicine, 1st ed. New York, NY, USA: McGraw-Hill Prof Med/Tech, May 2010. [13] National Institute of Biomedical Imaging and Bioengineering. (2012, January) MIT-BIH arrhythmia database. [Online]. Available: http://www.physionet.org/physiobank/database/mitdb/ [14] E. Niedermeyer and F. da Silva, Electroencephalography: Basic Principles, Clinical Applications, and Related Fields, 5th ed. Philadelphia, PA, USA: Lippincott Williams & Wilkins, November 2004. [15] S. Mallat, A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way, 3rded. Burlington, MA, USA: Academic Press, 2008.BIBLIOGRAPHY 67 [16] L. G. Chen, C. T. Huang, C. Y. Chen, and C. C. Cheng, VLSI design of wavelet transform. Analysis, architecture and design examples. Hackensack, NJ, USA: World Scientific, 2007. [17] W. Sweldens, “The Lifting Scheme: A Custom-Design Construction of Biorthogonal Wavelets,” Applied and Computational Harmonic Analysis, vol. 3, pp. 186–200, 1996. [18] I. Daubechies and W. Sweldens, “Factoring wavelet transforms into lifting steps,” Journal of Fourier Analysis and Applications, vol. 4, no. 3, pp. 245–267, 1998. [19] S. H. Hung, C. F. Chao, S. K. Wang, B. S. Lin, and C. T. Lin, “VLSI implementation for epileptic seizure prediction system based on wavelet and chaos theory,” in IEEE International Conference on Trends and Developments in Converging Technology towards (TENCON), Fukuoka, Japan, November 2010, pp. 364–368. [20] S. Razmpour, A. M. Sodagar, M. Faizollah, M. Y. Darmani, and M. Nourian, “Reconfigurable biological signal co-processor for feature extraction dedicated to implantable biomedical microsystems,” in IEEE International Symposium on Circuits and Systems (ISCAS), Beijing, China, May 2013, pp. 861–864. [21] Y. Yang and A. Mason, “Implantable neural spike detection using lifting-based stationary wavelet transform,” in IEEE International Conference on Engineering in Medicine and Biology Society (EMBS), Boston, Massachusetts, U.S.A., August 2011, pp. 7294–7297. [22] H. Tan, A. C. Tan, P. Y. Khong, and V. H. Mok, “Best wavelet function identification system for ECG signal denoise applications,” in IEEE International Conference on Intelligent and Advanced Systems (ICIAS), Kuala Lumpur, Malaysia, November 2007, pp. 631–634. [23] A. Kasetwar and S. Gulhane, “A survey of FPGA based interference cancellation architectures for biomedical signals,” in IEEE International Conference on Computer Communication and Informatics (ICCCI), Tamil Nadu, India, January 2013, pp. 1–7.68 BIBLIOGRAPHY [24] H. Y. Lin and H. P. Ma, “A wavelet based method for noise reduction and R wave detection algorithm in ECG signal,” in VLSI Design/CAD Symposium, Kenting, Taiwan, August 7-10 2012. [25] M. Nakano, T. Konishi, S. Izumi, H. Kawaguchi, and M. Yoshimoto, “Instantaneous heart rate detection using short-time autocorrelation for wearable healthcare systems,” in IEEE International Conference on Engineering in Medicine and Biology Society (EMBS), San Diego, California, U.S.A., August 2012, pp. 6703–6706. [26] C. I. Ieong, M. I. Vai, and P. U. Mak, “ECG QRS complex detection with programmable hardware,” in IEEE International Conference on Engineering in Medicine and Biology Society (EMBS), Vancouver, British Columbia, Canada, August 2008, pp. 2920–2923. [27] J. Martinez, R. Almeida, S. Olmos, A. Rocha, and P. Laguna, “A wavelet-based ECG delineator: evaluation on standard databases,” IEEE Transactions on Biomedical Engineering, vol. 51, no. 4, pp. 570–581, 2004. [28] R. Soikkeli, J. Partanen, H. Soininen, A. Paakkonen, and P. Riekkinen, “Slowing of EEG in Parkinson’s disease.” Electroencephalogr Clin Neurophysiol, vol. 79, no. 3, pp. 159–65, 1991. [29] M. Signorino, E. Pucci, N. Belardinelli, G. Nolfe, and F. Angeleri, “EEG spectral analysis in vascular and Alzheimer dementia.” Electroencephalogr Clin Neurophysiol, vol. 94, no. 5, pp. 313–25, 1995. [30] J. Bosboom, D. Stoffers, C. Stam, B. van Dijk, J. Verbunt, H. Berendse, and E. Wolters,“Resting state oscillatory brain dynamics in Parkinson’s disease: An MEG study,” Clinical Neurophysiology, vol. 117, no. 11, pp. 2521 – 2531, 2006. [31] N. Salansky, A. fedotchev, and A. Bondar, “Responses of the nervous system to low frequency stimulation and EEG rhythms: Clinical implications,” Neuroscience and Biobehavioral Reviews, vol. 22, no. 3, pp. 395 – 409, 1998.BIBLIOGRAPHY 69 [32] J. Chilo and T. Lindblad, “Hardware implementation of 1D wavelet transform on an FPGA for infrasound signal classification,” IEEE Transactions on Nuclear Science,, vol. 55, no. 1, pp. 9–13, 2008. [33] R. Hourani, I. Dalal, W. Davis, C. Doss, and W. Alexander, “An efficient VLSI implementation for the 1D convolutional discrete wavelet transform,” in IEEE International Conference on Midwest Symposium on Circuits and Systems (MWSCAS), Knoxville, Tennessee, U.S.A., August 2008, pp. 870–873. [34] S. C. Huang, H. M. Wang, and W. Y. Chen, “A ±6ms-accuracy, 0.68mm 2 , and 2.21µW QRS detection ASIC,” VLSI Design, vol. 2012, no. Article ID 987209, 2012. [35] P. Y. Chang, S. Y. Hsu, and C. Y. Lee, “A 4.88 µW ECG delineator using wavelet transform for mobile healthcare application,” in IEEE International Conference on Biomedical Circuits and Systems Conference (BioCAS), Hsinchu, Taiwan, November 2012, pp. 376–379. [36] “Low-cost low-power 2.4 GHz RF transmitter,” Texas Instruments Inc., 2007. [Online]. Available: http://focus.ti.com/docs/prod/folders/print/cc2550.html
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