Journal of Engineering and Applied Sciences

Year: 2018
Volume: 13
Issue: 21
Page No. 9101 - 9105

Fusion of Induced Variations Using Quality Metrics to Estimate Respiratory Rate from Photoplethysmography Signal

Authors : Nazrul Anuar Nayan and Nur Azhani Mohamad Rosli

References

Addison, P.S., J.N. Watson, M.L. Mestek, J.P. Ochs and A.A. Uribe et al., 2015. Pulse oximetry-derived respiratory rate in general care floor patients. J. Clin. Monit. Comput., 29: 113-120.
PubMed  |  Direct Link  |  

Charlton, P.H., M. Villarroel and F. Salguiero, 2016. Waveform Analysis to Estimate Respiratory Rate. In: Secondary Analysis of Electronic Health Records, MIT Critical Data (Ed.). Springer, Cham, Switzerland,ISBN:978-3-319-43740-8, pp: 377-390.

Drummond, G.B., A.F. Nimmo and R.A. Elton, 1996. Thoracic impedance used for measuring chest wall movement in postoperative patients. Br. J. Anaesthesia, 77: 327-332.
PubMed  |  Direct Link  |  

Elgendi, M., 2016. Optimal signal quality index for photoplethysmogram signals. Bioeng., 3: 1-15.
CrossRef  |  Direct Link  |  

Garde, A., W. Karlen, J.M. Ansermino and G.A. Dumont, 2014. Estimating respiratory and heart rates from the correntropy spectral density of the photoplethysmogram. PloS one, 9: 1-11.
PubMed  |  Direct Link  |  

Goldhill, D.R., S.A. White and A. Sumner, 1999. Physiological values and procedures in the 24 h before ICU admission from the ward. Anaesthesia, 54: 529-534.
Direct Link  |  

Karlen, W., S. Raman, J.M. Ansermino and G.A. Dumont, 2013. Multiparameter respiratory rate estimation from the photoplethysmogram. IEEE. Trans. Biomed. Eng., 60: 1946-1953.
CrossRef  |  PubMed  |  Direct Link  |  

Madhav, K.V., M.R. Ram, E.H. Krishna, K.N. Reddy and K.A. Reddy, 2010. Estimation of respiratory rate from principal components of photoplethysmographic signals. Proceedings of the 2010 IEEE EMBS International Conference on Biomedical Engineering and Sciences (IECBES), November 30-December2, 2010, IEEE, Kuala Lumpur, Malaysia, ISBN:978-1-4244-7599-5, pp: 311-314.

Nilsson, L., A. Johansson and S. Kalman, 2000. Monitoring of respiratory rate in postoperative care using a new photoplethysmographic technique. J. Clin. Monit. Comput., 16: 309-315.
PubMed  |  Direct Link  |  

Orphanidou, C., T. Bonnici, P. Charlton, D. Clifton and D. Vallance et al., 2015. Signal-quality indices for the electrocardiogram and photoplethysmogram: Derivation and applications to wireless monitoring. IEEE. J. Biomed. Health Inf., 19: 832-838.
CrossRef  |  PubMed  |  Direct Link  |  

Prutchi, D. and M. Norris, 2005. Design and Development of Medical Electronic Instrumentation: A Practical Perspective of the Design, Construction and Test of Medical Devices. John Wiley & Sons, Hoboken, New Jersey, Pages: 460.

Saeed, M., M. Villarroel, A.T. Reisner, G. Clifford and L.W. Lehman et al., 2011. Multiparameter intelligent monitoring in intensive care II (MIMIC-II): A public-access intensive care unit database. Crit. Care Med., 39: 952-960.
CrossRef  |  PubMed  |  Direct Link  |  

Varady, P., T. Micsik, S. Benedek and Z. Benyo, 2002. A novel method for the detection of apnea and hypopnea events in respiration signals. IEEE. Trans. Biomed. Eng., 49: 936-942.
CrossRef  |  Direct Link  |  

Design and power by Medwell Web Development Team. © Medwell Publishing 2024 All Rights Reserved