Stability analysis of cardiovascular oscillations together with nonlinear nalysis gives important and complements information about their autonomic regulations. New nonlinear tools like M-indexes gives

possibility to analyze stability of the most pure dynamic process that is observed with the help of RR and QT intervals variability

Aubert, A.E.

Beckers, F.

Martynenko, A.V.

Verheyden, B.

Yabluchansky, A.N.

Yabluchansky, N.I.

Електронного архіву Харківського національного університету імені В.Н.Каразіна (Electronic Archive V.N. Karazin Kharkiv National University)

1Stability analysis of RR and QT variability for cosmonauts dataN.Yabluchansky*, A.V.Martynenko*, A.Yabluchansky*, B.Verheyden**, F.Beckers** and A.E.Aubert*** School of Medicine, National University, Kharkov, Ukraine** Dept. of Cardiology, University Hospital Gasthuisberg, K.U. Leuven, Leuven, BelgiumAbstract – Stability analysis of cardiovascular oscilla-tions together with nonlinear analysis gives importantand complements information about their autonomicregulations.  New nonlinear tools like M-indexes givespossibility to analyze stability of the most pure dynamicprocess that is observed with the help of RR and QT in-tervals variability.Keywords — RR variability, QT variability, stabilityanalysis, M-indexesI. INTRODUCTIONSpace flight has an important impact on almost all of thehuman body’s systems, particularly the cardiovascular sys-tem [1]. Variability of cardiovascular oscillations has be-come a universal tool to study the neural control of the heartand include a variety of linear, non-linear, periodical andnon-periodical oscillation patterns that are present in heartrate fluctuations [2]. The nonlinear methods represent prom-ising tools for variability assessment and should be com-pleted by stability analysis.There are different approaches to stability analysis forcardiovascular behaviour. They can be understood in quali-tative sense as: cardiovascular reactivity in psychophysiol-ogy, e.g. blood pressure and heart rate reactions [3]; sponta-neous oscillations in systemic arterial pressure as the resultof instability inducted by baroreflex [4]; as electrical stabil-ity, e.g. absence of its opposite in clinical interpretation [5].Very few papers can suggest time series stability analysisquantitatively because of problem complexity. Mostly theyare based on linear methods of investigations [6] or interpretstability in structural sense [7].The current study presents new stability analysis toolbased on M-index measure of nonlinearity and nonstationar-ity. Applied stability investigation was made for RR and QTvariability of cosmonauts before and after space flight.II.MATERIALS AND METHODSSubjects: 4 cosmonauts; 20 days before space flight (4records) and on the 1st (3 records), 4th (3 records) and 5th (1record), 7th (1 record) and 9th (3 records) days after spaceflight.Signal acquisition: 2 minutes of 2 channels high resolu-tion (1 kHz) digital ECG recording was made by Prof.A.Aubert group. Automatic RR and QT detection and veri-fication was made by Prof. A.Martynenko group. Stability analysis of RR and QT variability: We use theterm stability in Lyapunov sense as applied to short intervalof time series observation. Naturally we can only make aconclusion that during time of observation data are stable,unstable or neutral. It is impossible in classical sense tomake a decision about infinite or asymptotical behaviour oftime series.Fig. 1 Stable pattern behaviour and example of stable QT intervals (D2 data)Fig. 2 Neutral pattern behaviour and example of neutral QT intervals (D4 data)Fig. 3 Unstable pattern behaviour and example of unstable QT intervals(B3 data)2We define: Stable behaviour if on the regular basis dur-ing the time series observation their phase space is shrink-ing; Neutral behaviour if on the regular basis during thetime series observation their phase space doesn’t change inthe mean; Unstable behaviour if on the regular basis duringthe time series observation their phase space is expanding.The patterns and examples of QT intervals behaviour areshown in Figure 1-3.All calculations we make are based on M-index that is acomplex measure of nonlinearity and nonstationarity oftime series in time symmetric (M0) and time asymmetric(M1) phase space [8].III. RESULTSThe result of stability calculations for RR and QT inter-vals variability of cosmonauts data are shown in Figure 4-7(“-” or green area – stable; “+” or red – unstable).-3-2-101231 2 3 4QTRRFig. 4 Stability RR and QT intervals for cosmonaut A data-3-2-101231 2 3QTRRFig. 6 Stability RR and QT intervals for cosmonaut C dataThere is good correlation between results for RR and QTstability analysis:  Pearson correlation coefficient r = 0.75and Spearman rank correlation R = 0.7. This is like the re-sults of M-index calculations for RR and QT where r =0.79. Weak correlation shown by comparison of results ofthe M-index nonlinear analysis and stability analysis: Pear-son correlation coefficient for RR data is r = 0.09 and forQT data is r = 0.28 Thereby we show that stability analysisis quantitatively different from M-index nonlinear analysisand both analyses are supplementing each other.First of all, we should ascertain that in all cases QT in-tervals behaviour is more stable (mean value -0.06) than RRintervals behaviour (mean value 0.6). Secondly – spaceflight disturbances often put cardiovascular system in transi-tion state.The last but not the least we note on the qualitative levelthat stability analysis show like in M-index nonlinear analy-sis two groups of stability behaviour:-3-2-101231 2 3 4QTRRFig. 5 Stability RR and QT intervals for cosmonaut B data-3-2-101231 2 3 4QTRRFig. 7 Stability RR and QT intervals for cosmonaut D data3return to stability zone after space flight disturbances (compen-sate motion) – cosmonauts A and D; unstable behaviour up tothe end of observation period (decompensate motion) – cos-monauts B and C. We make special emphasis on the fact ofcoincidence of cosmonauts groups in both analyses – nonlinearand stability.IV.DISCUSSIONThe short cardiovascular variability records especiallyheart rate variability are unstable in additional to non-stationary. This strengthens our previous result from nonlin-ear analysis that heart rate variability for short records arepoor for analysis by standard spectral methods and the bet-ter results can be obtained by analysis of QT intervals vari-ability. The stability and nonlinear analysis give differentresult in a quantitative sense but comparable on the qualita-tive level. Both analyses – nonlinear and stability completeeach other.V. CONCLUSIONSThe present study introduces M-index stability analysisfor cardiovascular oscillations. We have showed that QTintervals behaviour is more stable than RR; space flightdisturbances put cardiovascular system in transition state;stability of cardiovascular oscillations has strong individualbehaviour that can be consolidated in common behaviourgroups. These groups coinside for nonlinear and stabilityanalysis. We can note in additional that in group with un-compensated motion case B show movement into stable di-rection unlike C.  Thus stability analysis shows direction intime series behaviour but nonlinear indicate only if currentstate is stationary or not.REFERENCES1. Aubert A., Beckers F., Verheyden B. Cardiovascular function andbasics of physiology in microgravity. Acta Cardiol, 2005; 60: 129-151.2. Beckers F., Ramaekers D., Aubert A. Approximate Entropy of HeartRate Variability: Validation of Methods and Application in HeartFailure. Cardiovasc. Eng., 2001; 1(4): 177-182.3. Hazlett R., Falkin S., Lawhorn W., Friedman E., Haynes S.  Cardio-vascular Reactivity to a Naturally Occurring Stressor: Developmentand Psychometric Evaluation of a Psycho-physiological AssessmentProcedure. J. Behavioral Medicine, 1997; 20/6: 551-570.4. Magosso E., Biavati V., Ursino M.  Role of the Baroreflex in Cardio-vascular Instability: A Modeling Study. Cardiovascular Eng., 2001;1/2: 101-115.5. Fetsch Th., Reinhardt L., Wichter Th., Borggrefe M., Breithardt G.Heart rate variability and electrical stability. Basic Res Cardiol.,1998; 93/1: 117-124.6. Marple L. Digital Spectral Analysis with Applications. EnglewoodCliffs, 1987.7. Sammon M. Variational Approaches Toward Nonlinear Time-SeriesAnalysis. Annals Biomedical Eng., 1999; 27: 274-285.8. Yabluchansky N., Martynenko A., Isaeva A., Zinkovich I., Hri-pachenko I. Investigation of cardiovascular regulatory processes. Do-netsk Press, 2005.Corresponding author:Nicola YabluchanskyNational University4 Svoboda Sq.KharkovUkrainemydoctorlife@gmail.com

Stability analysis of RR and QT variability for cosmonauts data

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Stability analysis of RR and QT variability for cosmonauts data

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Електронного архіву Харківського національного університету імені В.Н.Каразіна (Electronic Archive V.N. Karazin Kharkiv National University)

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