Open Access
ITM Web Conf.
Volume 7, 2016
3rd Annual International Conference on Information Technology and Applications (ITA 2016)
Article Number 09014
Number of page(s) 4
Section Session 9: Computer Science and its Applications
Published online 21 November 2016
  1. M.G. William, W.B. Kannel, A. Belanger, R.B. D’Agostino,“Influence of heart rate on mortality among persons with hypertension: The Framingham Study”, Am Heart J, 125, 4 (1993) [Google Scholar]
  2. P. Palatini, “Heart rate: a strong predictor of mortality in subjects with coronary artery disease”, Eur Heart J, 26, 10 (2005) [Google Scholar]
  3. G.Z. Liu, L. Wang, Q. Wang, G.M. Zhou, Y. Wang, Q. Jiang, “A New Approach to Detect Congestive Heart Failure Using Short-Term Heart Rate Variability Measures”, PLOS ONE, 9, 4 (2014) [Google Scholar]
  4. C.G. Yu, Z.Q. Liu, T. McKenna, A.T. Reisner, J. Reifman, “A Method for Automatic Identification of Reliable Heart Rates Calculated from ECG and PPG Waveforms”, Jamia, 13,3 (2006) [Google Scholar]
  5. M.E. Valentinuzzi, “Bioelectrical impedance techniques in medicine: Bioimpedance measurement”, Crit. Rev. Biomed. Eng, 24, 4(1996) [Google Scholar]
  6. M.R. King, T.A. Anderson,, “Age related incidence of desaturation events and the cardiac on stroke index, cardiac index, and heart rate measured by continuous bioimpedancenoninvasivecardiac output monitoring in infants and children undergoing general anaesthesia”, j.jclinane, 32, 10 (2016) [Google Scholar]
  7. N.K. Kristiansen, J. Fleischer, M.S. Jensen, K.S. Andersen, H. Nygaard,“Design and evaluation of a handheld impedance plethysmograph formeasuring heart rate variability”, Medical&Biological Engineering & Computing, 43, 4(2005) [Google Scholar]
  8. R. Gonzalez-Landaeta, O. Casas, R. Pallas-Areny, “Heart Rate Detection from Plantar Bioimpedance Measurements”, TBME, 55, 3 (2008) [Google Scholar]
  9. M.C. Cho, J.Y. Kim, S. Cho, “A Bio-Impedance Measurement System for Portable Monitoring of Heart Rate and Pulse Wave Velocity Using Small Body Area”, ISCAS, IEEE (2009) [Google Scholar]
  10. P. Kligfield, S.G. Leonard, “Recommendations for the Standardization and Interpretation of the Electrocardiogram”, J Am CollCardiol, 49, 10 (2007) [Google Scholar]
  11. J.P. Pan, W.J. Tompkins, “A Real-Time QRS Detection Algorithm”, TBME, 32, 3 (1985) [Google Scholar]
  12. J.M. Bland,D.G. Altman, “Statistical methods for assessing agreement between two methods of clinical measurement”, Lancet, 327, 8476 (1986) [CrossRef] [Google Scholar]
  13. G.Z. Liu, G.M. Zhou, W.H. Chen, Q. Jiang, “A Principal Component Analysis Based Data Fusion Method for Estimation of Respiratory Volume”, JSEN, 15, 8 (2015) [Google Scholar]
  14. G.Z. Liu, B.Y. Huang, L. Wang, “A Wearable Respiratory Biofeedback System Based on Generalized Body Sensor Network”, tmj, 17, 5 (2011) [Google Scholar]

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