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Volumn 9, Issue 1, 2014, Pages

Estimating respiratory and heart rates from the correntropy spectral density of the photoplethysmogram

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ALGORITHM; ARTICLE; BREATHING RATE; CALIBRATION; CORRENTROPY SPECTRAL DENSITY; HEART RATE; PHOTOELECTRIC PLETHYSMOGRAPHY; PULSE OXIMETER; PULSE OXIMETRY; QUALITY CONTROL; SIMULATION; SPECTROMETRY;

EID: 84899636858     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0086427     Document Type: Article
Times cited : (88)

References (31)
  • 1
    • 0033856887 scopus 로고    scopus 로고
    • Photoplethysmography for simultaneous recording of heart and respiratory rates in newborn infants
    • (Oslo, Norway: 1992)
    • Olsson E, Ugnell H, Oberg Pa, Sedin G (2000) Photoplethysmography for simultaneous recording of heart and respiratory rates in newborn infants. Acta Paediatrica (Oslo, Norway: 1992) 89: 853-861.
    • (2000) Acta Paediatrica , vol.89 , pp. 853-861
    • Olsson, E.1    Ugnell, H.2    Oberg, P.3    Sedin, G.4
  • 3
    • 11144238311 scopus 로고    scopus 로고
    • The vexatious vital: Neither clinical measurements by nurses nor an electronic monitor provides accurate measurements of respiratory rate in triage
    • DOI 10.1016/j.annemergmed.2004.06.016, PII S0196064404006493
    • Lovett PB, Buchwald JM, Stürmann K, Bijur P (2005) The vexatious vital: neither clinical mea- surements by nurses nor an electronic monitor provides accurate measurements of respiratory rate in triage. Annals of Emergency Medicine 45: 68-76. (Pubitemid 40051170)
    • (2005) Annals of Emergency Medicine , vol.45 , Issue.1 , pp. 68-76
    • Lovett, P.B.1    Buchwald, J.M.2    Sturmann, K.3    Bijur, P.4
  • 5
    • 0034448449 scopus 로고    scopus 로고
    • Monitoring of respiratory rate in postoperative care using a new photoplethysmographic technique
    • DOI 10.1023/A:1011424732717
    • Nilsson L, Johansson A, Kalman S (2000) Monitoring of respiratory rate in postoperative care using a new photoplethysmographic technique. Journal of Clinical Monitoring and Computing 16: 309-315. (Pubitemid 32435532)
    • (2000) Journal of Clinical Monitoring and Computing , vol.16 , Issue.4 , pp. 309-315
    • Nilsson, L.1    Johansson, A.2    Kalman, S.3
  • 8
    • 34247467602 scopus 로고    scopus 로고
    • Photoplethysmography and its application in clinical physiological measurement
    • Allen J (2007) Photoplethysmography and its application in clinical physiological measurement. Physiological Measurement 28: R1-39.
    • (2007) Physiological Measurement , vol.28
    • Allen, J.1
  • 9
    • 39949085790 scopus 로고    scopus 로고
    • Can photoplethysmography variability serve as an alternative approach to obtain heart rate variability information?
    • Lu S, Zhao H, Ju K, Shin K, Lee M, et al. (2008) Can photoplethysmography variability serve as an alternative approach to obtain heart rate variability information? Journal of Clinical Monitoring and Computing 22: 23-29.
    • (2008) Journal of Clinical Monitoring and Computing , vol.22 , pp. 23-29
    • Lu, S.1    Zhao, H.2    Ju, K.3    Shin, K.4    Lee, M.5
  • 10
    • 70349576555 scopus 로고    scopus 로고
    • Estimation of respiratory rate from photoplethysmogram data using time-frequency spectral estimation
    • Chon KH, Dash S, Ju K (2009) Estimation of respiratory rate from photoplethysmogram data using time-frequency spectral estimation. IEEE Transactions on Biomedical Engineering 56: 2054-2063.
    • (2009) IEEE Transactions on Biomedical Engineering , vol.56 , pp. 2054-2063
    • Chon, K.H.1    Dash, S.2    Ju, K.3
  • 11
    • 84859957036 scopus 로고    scopus 로고
    • Deriving Respiration from the Pulse Photoplethysmographic Signal
    • Gil E, Bail R, Laguna P (2011) Deriving Respiration from the Pulse Photoplethysmographic Signal. In: Computing in Cardiology. 713-716.
    • (2011) Computing in Cardiology , pp. 713-716
    • Gil, E.1    Bail, R.2    Laguna, P.3
  • 14
    • 84860015594 scopus 로고    scopus 로고
    • Estimation of Spontaneous Respiratory Rate from Photoplethysmography by Cross Time-Frequency Analysis
    • Orini M, Bail R, Gil E (2011) Estimation of Spontaneous Respiratory Rate from Photoplethysmography by Cross Time-Frequency Analysis. In: Computing in Cardiology. 661-664.
    • (2011) Computing in Cardiology , pp. 661-664
    • Orini, M.1    Bail, R.2    Gil, E.3
  • 15
    • 33745121601 scopus 로고    scopus 로고
    • The use of joint time frequency analysis to quantify the effect of ventilation on the pulse oximeter waveform
    • DOI 10.1007/s10877-006-9010-7
    • Shelley KH, Awad AA, Stout RG, Silverman DG (2006) The use of joint time frequency analysis to quantify the effect of ventilation on the pulse oximeter waveform. Journal of Clinical Monitoring and Computing 20: 81-87. (Pubitemid 43899087)
    • (2006) Journal of Clinical Monitoring and Computing , vol.20 , Issue.2 , pp. 81-87
    • Shelley, K.H.1    Awad, A.A.2    Stout, R.G.3    Silverman, D.G.4
  • 16
    • 84894130551 scopus 로고    scopus 로고
    • Empirical mode decomposition for respiratory and heart rate estimation from the photoplethysmogram
    • Sep, 2013. p. In press
    • Garde A, Karlen W, Dehkordi P, Ansermino JM, Dumont GA (2013) Empirical mode decomposition for respiratory and heart rate estimation from the photoplethysmogram. In: Computing in Cardiology, Sep, 2013. p. In press.
    • (2013) Computing in Cardiology
    • Garde, A.1    Karlen, W.2    Dehkordi, P.3    Ansermino, J.M.4    Dumont, G.A.5
  • 17
    • 0030199595 scopus 로고    scopus 로고
    • Monitoring of heart and respiratory rates by photoplethysmography using a digital filtering technique
    • DOI 10.1016/1350-4533(95)00066-6
    • Nakajima K, Tamura T, Miike H (1996) Monitoring of heart and respiratory rates by photoplethysmography using a digital filtering technique. Medical Engineering & Physics 18: 365-372. (Pubitemid 26201933)
    • (1996) Medical Engineering and Physics , vol.18 , Issue.5 , pp. 365-372
    • Nakajima, K.1    Tamura, T.2    Miike, H.3
  • 18
    • 77954637792 scopus 로고    scopus 로고
    • Correntropy-based spectral characterization of respiratory patterns in patients with chronic heart failure
    • Garde A, Sörnmo L, Jan R, Giraldo B (2010) Correntropy-based spectral characterization of respiratory patterns in patients with chronic heart failure. IEEE Transactions on Biomedical Engineering 57: 1964-1972.
    • (2010) IEEE Transactions on Biomedical Engineering , vol.57 , pp. 1964-1972
    • Garde, A.1    Sörnmo, L.2    Jan, R.3    Giraldo, B.4
  • 19
    • 33744538091 scopus 로고    scopus 로고
    • Generalized correlation function: Definition, properties, and application to blind equalization
    • DOI 10.1109/TSP.2006.872524
    • Santamaria I, Pokharel PP, Principe JC (2006) Generalized correlation function: definition, properties, and application to blind equalization. IEEE Transactions on Signal Processing 54: 2187-2197. (Pubitemid 43811412)
    • (2006) IEEE Transactions on Signal Processing , vol.54 , Issue.6 I , pp. 2187-2197
    • Santamaria, I.1    Pokharel, P.P.2    Principe, J.C.3
  • 20
    • 36249029853 scopus 로고    scopus 로고
    • Correntropy: Properties and applications in non-Gaussian signal processing
    • DOI 10.1109/TSP.2007.896065
    • Liu W, Pokharel PP, Principe JC (2007) Correntropy: properties and applications in non-Gaussian signal processing. IEEE Transactions on Signal Processing 55: 5286-5298. (Pubitemid 350130741)
    • (2007) IEEE Transactions on Signal Processing , vol.55 , Issue.11 , pp. 5286-5298
    • Liu, W.1    Pokharel, P.P.2    Principe, J.C.3
  • 23
    • 0038259114 scopus 로고    scopus 로고
    • Classes of kernels for machine learning: A statistics perspective
    • Genton M (2002) Classes of kernels for machine learning: a statistics perspective. The Journal of Machine Learning Research 2: 299-312.
    • (2002) The Journal of Machine Learning Research , vol.2 , pp. 299-312
    • Genton, M.1
  • 25
    • 0018015137 scopus 로고
    • Modeling by shortest data description
    • Rissanen J (1978) Modeling by shortest data description. Automatica 14: 465-471.
    • (1978) Automatica , vol.14 , pp. 465-471
    • Rissanen, J.1
  • 26
    • 79952750627 scopus 로고    scopus 로고
    • Normal ranges of heart rate and respiratory rate in children from birth to 18 years of age: A systematic review of observational studies
    • Fleming S, Thompson M, Stevens R, Heneghan C, Plüddemann A, et al. (2011) Normal ranges of heart rate and respiratory rate in children from birth to 18 years of age: a systematic review of observational studies. Lancet 377: 1011-1019.
    • (2011) Lancet , vol.377 , pp. 1011-1019
    • Fleming, S.1    Thompson, M.2    Stevens, R.3    Heneghan, C.4    Plüddemann, A.5
  • 28
    • 0037842965 scopus 로고    scopus 로고
    • Neural network for photoplethysmographic respiratory rate monitoring
    • Johansson A (2003) Neural network for photoplethysmographic respiratory rate monitoring. Medical & Biological Engineering & Computing 41: 242-250.
    • (2003) Medical & Biological Engineering & Computing , vol.41 , pp. 242-250
    • Johansson, A.1
  • 30
    • 84886031819 scopus 로고    scopus 로고
    • Systolic peak detection in acceleration photoplethysmograms measured from emergency responders in tropical conditions
    • Elgendi M, Norton I, Brearley M, Abbott D, Schuurmans D (2013) Systolic peak detection in acceleration photoplethysmograms measured from emergency responders in tropical conditions. PLoS ONE 8: e76585.
    • (2013) PLoS ONE , vol.8
    • Elgendi, M.1    Norton, I.2    Brearley, M.3    Abbott, D.4    Schuurmans, D.5
  • 31
    • 67349186919 scopus 로고    scopus 로고
    • Sensor fusion using a hybrid median filter for artifact removal in intraoperative heart rate monitoring
    • Yang P, Dumont GA, Ansermino JM (2009) Sensor fusion using a hybrid median filter for artifact removal in intraoperative heart rate monitoring. Journal of Clinical Monitoring and Computing 23: 75-83.
    • (2009) Journal of Clinical Monitoring and Computing , vol.23 , pp. 75-83
    • Yang, P.1    Dumont, G.A.2    Ansermino, J.M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.