Approximate minimum bias multichannel spectral estimation for heart rate variability

Annals of Biomedical Engineering

Volumn 25, Issue 3, 1997, Pages 509-520

  Lovett, Eric G ^a   Myklebust, Joel B ^b,c  

^a HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^b MARQUETTE UNIVERSITY   (United States)

^c Marquette University   (United States)

Author keywords

Discrete Fourier transform; Magnitude squared coherence; Multitaper spectral analysis; Power spectrum; Respiratory sinus arrhythmia; Sinusoidal tapers

Indexed keywords

COMPUTATIONAL COMPLEXITY; ESTIMATION; FOURIER TRANSFORMS; NEUROLOGY; NONINVASIVE MEDICAL PROCEDURES; PATIENT MONITORING; REGRESSION ANALYSIS; SIGNAL PROCESSING; SPECTRUM ANALYSIS;

AUTONOMIC NERVOUS ACTIVITY; AUTOREGRESSIVE METHOD; DISCRETE FOURIER TRANSFORM (DFT); HEART RATE VARIABILITY (HRV); MULTICHANNEL SPECTRAL ESTIMATION; WELCH PERIODOGRAMS;

CARDIOLOGY;

ADULT; ARTICLE; CONTROLLED STUDY; FOURIER TRANSFORMATION; HEART RATE VARIABILITY; HUMAN; HUMAN EXPERIMENT; MALE; MULTICHANNEL RECORDER; NORMAL HUMAN; SPECTROSCOPY;

ADULT; ALGORITHMS; ELECTROCARDIOGRAPHY; FOURIER ANALYSIS; HEART RATE; HUMANS; MALE; MODELS, CARDIOVASCULAR; SIGNAL PROCESSING, COMPUTER-ASSISTED; STATISTICS, NONPARAMETRIC;

EID: 0031148794     PISSN: 00906964     EISSN: None     Source Type: Journal    
DOI: 10.1007/BF02684191     Document Type: Article

References (22)

1. Baselli, G., S. Cerutti, S. Civardi, D. Liberati, F. Lombardi, A. Malliani, and M. Pagani. Spectral and cross-spectral analysis of heart rate and arterial blood pressure variability signals. Comput. Biomed. Res. 19:520-534, 1986.
2. Belmont, M. R. Nonuniform sampling specifically for finite-length data. IEEE Proc. F 140:55-62, 1993.
3. Berger, R. D., S. Akselrod, D. Gordon, and R. J. Cohen. An efficient algorithm for spectral analysis of heart rate variability. IEEE Trans. Biomed. Eng. 33:900-904, 1986.
4. Berntson, G. G., J. T. Cacioppo, and K. S. Quigley. Respiratory sinus arrhythmia: autonomic origins, physiological mechanisms, and psychophysiological implications. Psychophysiology 30:183-196, 1993.
5. Bronez, T. P. Spectral estimation of irregularly sampled multidimensional processes by generalized prolate spheroidal sequences. IEEE Trans. Acoust. Speech Sign. Proc. 36: 1862-1873, 1988.
6. Bronez, T. P. On the performance advantage of multitaper spectral analysis. IEEE Trans. Sign. Proc. 40:2941-2946, 1992.
7. Cooley, J. W., and J. W. Tukey. An algorithm for the machine computation of complex Fourier series. Math. Comput. 19:297-301, 1965.
8. DeBoer, R. W., J. M. Karemaker, and J. Strackee. Comparing spectra of a series of point events particularly for heart rate variability data. IEEE Trans. Biomed. Eng. 31:384-387, 1984.
9. DeBoer, R. W., J. M. Karemaker, and J. Strackee. Description of heart-rate variability data in accordance with a physiological model for the genesis of heartbeats. Psychophysiology 22:147-155, 1985.
10. Friesen, G. M., T. C. Jannett, M. A. Jadallah, S. L. Yates, S. R. Quint, and H. T. Nagle. A comparison of the noise sensitivity of nine QRS detection algorithms. IEEE Trans. Biomed. Eng. 37:85-98, 1990.
11. Kamath, M. V., and E. L. Fallen. Power spectral analysis of heart rate variability: a noninvasive signature of cardiac autonomic function. Crit. Rev. Biomed. Eng. 21:245-311, 1993.
12. Marple, S. L. Digital Spectral Analysis with Applications. Englewood Cliffs, NJ: Prentice-Hall, 1987, 492 pp.
13. Oppenheim, A. V., and R. W. Schafer. Discrete-Time Signal Processing. Englewood Cliffs. NJ: Prentice-Hall, 1989, 879 pp.
14. Riedel, K. S., and A. Sidorenko. Minimum bias multiple taper spectral estimation. IEEE Trans. Sign. Proc. 43:188-195, 1995.
15. Ropella, K. M., and E. G. Lovett. Parametric approaches to coherence estimation for intracardiac electrograms. Proc. Conf. IEEE EMBS 2:707-708, 1993.
16. Sayers, B. M. Analysis of heart rate variability. Ergonomics 16:17-32, 1973.
17. TenVoorde, B. J., J. C. Faes, and O. Ropmelman. Spectra of data sampled at frequency-modulated rates in application to cardiovascular signals. Part 1. Analytical derivation of the spectra. Med. Biol. Eng. Comput. 32:63-70, 1994.
18. TenVoorde, B. J., J. C. Faes, and O. Ropmelman. Spectra of data sampled at frequency-modulated rates in application to cardiovascular signals. Part 2. Evaluation of Fourier transform algorithms. Med. Biol. Eng. Comput. 32:71-76, 1994.
19. Thomson, D. J. Spectrum estimation and harmonic analysis. Proc. IEEE 70: 1055-1096, 1982.
20. Walden, P. T., E. J. McCoy, and D. B. Percival. The effective bandwidth of a multitaper spectral estimator. Biometrika 82:201-214, 1995.
21. Welch, P. D. The use of the fast Fourier transform for estimation of spectra: a method based on time averaging over short, modified periodograms. IEEE Trans. Audio Electroacoust. 15:70-73, 1967.
22. Yamamoto, Y., and R. L. Hughson. Coarse-graining spectral analysis: new method for studying heart rate variability. J. Appl. Physiol. 71:1143-1150, 1991.