Parametric Models for the Analysis of Interactions in Biomedical Signals

Advanced Methods of Biomedical Signal Processing

Volumn , Issue , 2011, Pages 99-125

  Baselli, Giuseppe ^a   Porta, Alberto ^b   Bolzern, Paolo ^a  

^a POLITECNICO DI MILANO   (Italy)

^b UNIVERSITY OF MILAN   (Italy)

Author keywords

Biomedical signals; Signal to noise ratio (SNR); SISO

Indexed keywords

EID: 84887192485     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9781118007747.ch5     Document Type: Chapter

References (44)

1. Akaike, H., Some Problems in the Application of the Cross-Spectral Method, in B. Harris (Ed.), Spectral Analysis of Time Series, pp. 81-107, Wiley, 1967
2. Baccala, L. A., and Sameshima, K., Partial Directed Coherence: A New Concept in Neural Structure Determination, Biol. Cybern., Vol. 84, 463-474, 2001
3. Baselli, G., Caiani, E., Porta, A., Montano, N., Signorini, M. G., and Cerutti, S., Biomedical Signal Processing And Modeling In Cardiovascular Systems, Criti-cal Reviews in Biomed. Eng., Vol. 30, 57-87, 2002
4. Baselli, G., Cerutti, S., Badilini, F., Biancardi, L., Porta, A., Pagani, M., Lombardi, F., Rimoldi, O., Furlan, R., and Malliani, A., Model for the Assessment of Heart Period and Arterial Pressure Variability Interactions and Respiratory In-fluences, Med. Biol. Eng. Comput., Vol. 32, 143-152, 1994
5. Baselli, G., Cerutti, S., Civardi, S., Malliani, A., and Pagani, M., Cardiovascular Variability Signals: Towards the Identification of a Closed-Loop Model of the Neural Control Mechanisms, IEEE Trans. Biomed. Eng., Vol. 35, 1033-1046, 1988
6. Baselli, G., Porta, A., Rimoldi, O., Pagani, M., and Cerutti, S., Spectral Decom-position in Multi-Channel Recordings Based on Multi-Variate Parametric Identification, IEEE Trans, on Biomed. Engin., Vol. 44, No. 11, 1092-1101, 1997
7. De Boer, R. W., Karemaker, J. M., and Strackee, J., Relationships between Short-Term Blood Pressure Fluctuations and Heart Rate Variability in Resting Sub-jects I: A Spectral Analysis Approach, Med. Biol. Eng. Comput., Vol. 23, 352-358, 1985
8. Faes, L., Cucino, R., and Nollo, G., Mixed Predictability and Cross-Validation to Assess Non-Linear Granger Causality in Short Cardiovascular Variability Se-ries, Biomedizinische Technik, Vol. 51, 255-259, 2006
9. Faes, L., Pinna, G. D., Porta, A., Maestri, R., and Nollo, G., Surrogate Data Analy-sis for Assessing the Significance of the Coherence Function, IEEE Trans. Bio-med. Eng., Vol. 51,1156-1166, 2004a
10. Faes, L., Porta, A., Cucino, R., Cerutti, S., Antolini, R., and Nollo, G., Causal Transfer Function to Describe Closed Loop Interactions between Cardiovascu-lar and Cardiorespiratory Variability Signals, Biol. Cybern., Vol. 90, 390-399, 2004b
11. Feldmann, U., and Bhattacharya, J., Predicatability Improvement as an Asymmet-rical Measure of Interdependence in Bivariate Time Series, Int. J. Bifurc. Chaos, Vol. 14, 505-514, 2004
12. Granger, C. W. J., Economic Processes Involving Feedback, Information and Con-trol, Vol. 6, 28-48, 1963
13. Hoyer, D., Bauer, R., Walter, B., and Zwiener, U., Estimation of Nonlinear Cou-plings on the Basis of Complexity and Predictability: A New Method Applied to Cardiorespiratory Coordination, IEEE Trans. Biomed. Eng., Vol. 45, 545-552,1998
14. Kaminski, M. J., and Blinowska, K. J., A New Method of the Description of the Information Flow in the Brain Structures, Biol. Cybern., Vol. 65, 203-210, 1991
15. Kay, S. M., Modern Spectral Analysis: Theory and Application, Prentice-Hall, 1989
16. Khoo, C. K., Physiological Control Systems: Analysis, Simulation, and Estimation, IEEE Press, 2000
17. Koepchen, H. P. History of Studies and Concepts of Blood Pressure Waves, in: Miyakawa, K., Polosa, C, and Koepchen, H. P. (Eds.), Mechanisms of Blood Pressure Waves, pp 3-23, Springer-Verlag, 1984
18. Laude, D., Elghozi, J., Girard, A., Bellard, E., Bouhaddi, M., Castiglioni, P., Cerut-ti, C, Cividjian, A., Rienzo, M. D., Fortrat, J., Janssen, B., Karemaker, J. M., Leftheriotis, G., Parati, G., Persson, P. B., Porta, A., Quintin, L., Regnard, J., Rudigger, H., and Stauss, H. M., Comparison of Various Techniques Used to Estimate Spontaneous Baroreflex Sensitivity (the EuroBaVar Study), Am. J. Physiol. Regul. Integr. Comp. Physiol., Vol. 286, R226-R231, 2004
19. Le Van Quyen, M., Adam, C, Baulac, M., Martinerie, J., and Varela, F. J., Non Linear Interdependencies of EEG Signals in Human Intracranially Recorded Temporal Lobe Seizures, Brain Res., Vol. 792, 24-0, 1998
20. Ljung, L., System Identification: Theory for the User, Prentice-Hall, 1999
21. Lucini, D., Porta, A., Milani, O., Baselli, G., and Pagani, M., Assessment of Arter-ial Cardiopulmonary Baroreflex Gains from Simultaneous Recordings of Spon-taneous Cardiovascular and Respiratory Variability,/ Hypertension, Vol. 18, 281-286,2000
22. Mukkamala, R., Kim, J., Li, Y., Sala-Mercado, J., Hammond, R. L., Scislo, T J., and OLeary, D. S., Estimation of Arterial and Cardiopulmonary Total Peripheral Resistance Baroreflex Gain Values: Validation by Chronic Arterial Baroreceptor Denervation, Am. J. Physiol. Heart Circ. Physiol, Vol. 290, H1830-H1836, 2006
23. Nollo, G., Faes, L., Porta, A., Antolini, R., and Ravelli, F., Exploring Directionali-ty in Spontaneous Heart Period and Systolic Arterial Pressure Variability Inter-actions in Humans: Implications in the Evaluation of Baroreflex Gain, Am. J. Physiol., Vol. 288, H1777-H1785, 2005
24. Nollo, G., Faes, L., Porta, A., Pellegrini, B., Ravelli, F., Del Greco, M., Disertori, M., and Antolini, R., Evidence of Unbalanced Regulatory Mechanism of Heart Rate and Systolic Pressure after Acute Myocardial Infarction, Am. J. Physioi, Vol. 283, H1200-H1207, 2002
25. Palus, M., Detecting Phase Synchronisation in Noisy Systems, Phys. Lett. A, Vol. 235,341-351, 1997
26. Palus, M., Komarek, V., Hrncir, Z., and Sterbova, K., Synchronization as Adjust-ment of Information Rates: Detection from Bivariate Time Series, Physical Re-viewE, Vol. 63,046211,2001
27. Porta, A., Baselli, G., and Cerutti, S., Implicit and Explicit Model-Based Signal Processing for the Analysis of Short Term Cardiovascular Interactions, Proc. IEEE, Vol. 94, 805-818, 2006
28. Porta, A., Baselli, G., Guzzetti, S., Pagani, M., Malliani, A., and Cerutti, S., Predic-tion of Short Cardiovascular Variability Signals Based on Conditional Distribu-tion, IEEE Trans. BME, Vol. 47, 1555-1564, 2000a
29. Porta, A., Baselli, G., Liberati, D., Montano, N., Cogliati, C, Gnecchi-Ruscone, T., Malliani, A., and Cerutti, S., Measuring the Degree of Regularity by Means of a Corrected Conditional Entropy in Sympathetic Outflow, Biol. Cybern., Vol. 78, 71-78, 1998
30. Porta, A., Baselli, G., Lombardi, F., Montano, N., Malliani, A., and Cerutti, S., Conditional Entropy Approach for the Evaluation of the Coupling Strength, Biol. Cyber., Vol. 81, 119-129, 1999
31. Porta, A., Baselli, G., Rimoldi, O., Malliani, A., and Pagani, M., Assessing Barore-flex Gain from Spontaneous Variability in Conscious Dogs: Role of Causality and Respiration, Am. J. Physioi, Vol. 279, 2558-H2567, 2000b
32. Porta, A., Furlan, R., Rimoldi, O., Pagani, M., Malliani, A., and van de Borne, P., Quantifying Linear Causal Coupling in Closed Loop Interacting Cardiovascular Variability Series, Biol. Cybern., Vol. 86, 241-251, 2002
33. Porta, A., Gnecchi-Ruscone, T., Tobaldini, E., Guzzetti, S., Furlan, R., and Mon-tano, N., Progressive Decrease of Heart Period Variability Entropy-Based. Complexity during Graded Head-up Tilt, of Appl. Physio., Vol. 103, 1143-1149, 2007a
34. Porta, A., Guzzetti, S., Furlan, R., Gnecchi-Ruscone, T., Montano, N., and Malliani, A., Complexity and Nonlinearity in Short-Term Heart Period Vari-ability: Comparison of Methods Based on Local Nonlinear Prediction, IEEE Trans. Biomed. Eng., Vol. 54, 94-106, 2007b
35. Porta, A., Guzzetti, S., Montano, N., Pagani, M., Somers, V. K., Malliani, A., Baselli, G., and Cerutti, S., Information Domain Analysis of Cardiovascular Variability Signals: Evaluation of Regularity, Synchronisation and Co-ordina-tion, Med. Biol. Eng. Comput., Vol. 38, 180-188, 2000c
36. Porta, A., Montano, N., Furlan, R., Cogliati, C, Guzzetti, S., Gnecchi Ruscone, T., Malliani, A., Chang, H.S., Staras, K., and Gilbey, M. P., Automatic Classifica-tion of Interference Patterns in Driven Event Series: Application to Single Sym-pathetic Neuron Discharge Forced by Mechanical Ventilation, Biol. Cybern., Vol. 91,258-273,2004
37. Porta, A., Montano, N., Pagani, M., Malliani, A., Baselli, G., Somers, V. K., and van de Borne, P., Non-Invasive Model-Based Estimation of the Sinus Node Dy-namic Properties from Spontaneous Cardiovascular Variability Series, Med. Biol. Eng. Comput, Vol. 41, 52-61, 2003
38. Richman, J. S., and Moorman, J. R., Physiological Time-Series Analysis Using Approximate Entropy and Sample Entropy, Am. J. Physiol, Vol. 278, H2039-H2049, 2000
39. Robbe, H. W. J., Mulder, L. J. M., Ruddel, H., Langewitz, W. A., Eldman, J. B. P., and Ider, G., Assessment of Baroreceptor Reflex Sensitivity by Means of Spec-tral Analysis, Hypertension, Vol. 10, 538-543, 1987
40. Saito, Y., and Harashima, H., Tracking of Information Within Multichannel EEG Record-Causal Analysis in EEG, in Yamaguchi, N. and Fujisawa, K. (Eds.), Recent Advances in EEG and EMG Data Processing, pp 133-146, Elsevier, 1981
41. Saul, J. P., Berger, R. D., Albrecht, P., Stein, S. P., Chen, M. H., and Cohen, R. J., Transfer Function Analysis of the Circulation: Unique Insights into Cardiovas-cular Regulation, Am. J. Physiol., Vol. 261, H1231-H1245, 1991
42. Schiff, S. J., So, P., Chang, T., Burke, R., and Sauer, T., Detecting Dynamical Ia-terdependence and Generalized Synchrony through Mutual Prediction in a Neural Ensemble, Phys. Rev. E, Vol. 54, 6708-6724, 1996
43. Schreiber, T., and Schmitz, A., Improved Surrogate Data for Nonlinearity Tests, Phys. Rev. Lett, Vol. 77, 635-638, 1996
44. Xiao, X., Mullen, T. J., and Mukkamala, R., System Identification: A Multi-Signal Approach for Probing Neural Cardiovascular Regulation, Physiol. Meas., Vol. 26, R41-R71,2005