Quantitative Evaluation of ECG Changes Reflecting Heart Activity Control during Postural Changes A. Krisciukaitis1 , R. Simoliuniene1, V. Saferis1, F.P. Falcão2, R. Cardoso2, F. Macagnan 2, T. Lapa 2, and T. Russomano2 2
1 Kaunas University of Medicine, Kaunas, Lithuania Pontifícia Universidade Católica do Rio Grande do Sul / Microgravity Centre, Porto Alegre, Brasil
Abstract—The system for investigation of heart activity control in changing gravity conditions was elaborated in cooperation between scientists of Kaunas University of Medicine and Microgravity Centre, Pontifícia Universidade Católica do Rio Grande do Sul, Brazil. Structural analysis and quantitative evaluation of parameters of ECG was performed on recordings registered during passive orthostatic test. P-Q interval duration changes and specific P-wave morphology variation estimated by means of Principal Component Analysis were found as informative parameters reflecting adaptation abilities of the persons in extreme conditions. Keywords—P-wave, Gravity changes, Heart activity control, Principal Component Analysis.
I. INTRODUCTION Occupations like pilots, astronauts, and racing car drivers can face sudden changes of gravity, atmospheric pressure and weight. These abnormal conditions can have a substantial impact, especially on the cardiovascular system. Orthostatic intolerance of spacemen has been a problem since the beginning of manned space flight in the 1960’s and remains the focus of scientific research in space centers in the USA [1,2]. It displays as tachycardia, variable blood pressure, pre-syncope or Frank syndrome, impaired mobility and reduced physical activity. Dysfunction of autonomous heart control is a possible cause and evaluations of the functionality of this are reported in numerous publications, including our previous works [3]. Quantitative evaluation of the degree of such pathology would enable ongoing patient assessment and follow up during rehabilitation. It could be also used as a tool for candidate selection for specific occupations or athletes. It could help to control of their training. Autonomous heart control is the adaptation of rate and contraction of the heart muscle to meet the momentary needs of the organism. The heart rate is determined by the rate of spontaneous electrical activity of the cells usually located in the sinoatrial node. This rate is the result of permanent interplay between sympathetic and parasympathetic influences [4]. The P-wave shape reflects the spread of the electrical excitation front over the atria. The start point of
which could be influenced by the release of neuromediators from nerve terminals. As has been reported in [5], the topology of neural ganglionated subplexuses suggests that during a parasympathetic activity the neuromediators are released in the site of the true pacemaker suppressing its spontaneous activity. Thus it is possible that some latent pacemaker would take over the role of the true pacemaker. Such shifting of the pacemaker site should be reflected as changes in the ECG P-wave morphology [6]. An orthostatic test partly imitates changes of the gravity vector. It evokes a sudden misbalance in the interplay between the sympathetic and the parasympathetic heart control, and properties of the control by each nerve system can then be observed. The aim of this work was to elaborate the experimental system for signal registration and to create an algorithm and program for evaluation of parameters of electrocardiogram (ECG) signals, registered from subjects under conditions of posture change.
II. METHODS The passive orthostatic test was performed using Tilt Table (Fig.1). The experiments were held on imitating possible usage of the method in practices during, remote testing of investigative in the extreme conditions. Video control of the protocol and collection/transmission of minimal yet sufficient amount of data was used. The experiments were performed in Microgravity Centre, Pontifícia Universidade Católica do Rio Grande do Sul, Brazil during on-line SKYPE videoconference with Kaunas University of Medicine, Lithuania. ECG signals in DI lead were registered and sampled at 12 bit resolution, 250 Hz sampling rate. The specially elaborated Tilt Table enables fixation of various positions of the immobilized investigative starting from -40 degrees (head down) till +90 degrees (head up). The protocol of position of the subject’s body during experiments was as follows: horizontal, -35 degrees head down, 65 degrees head up, horizontal, 65 degrees head up -35 degrees head down, and horizontal position again. The subject was held in each position for 2 minutes. Ten young healthy volunteers (age between 21 and 30) participated in the study.
O. Dössel and W.C. Schlegel (Eds.): WC 2009, IFMBE Proceedings 25/IV, pp. 1850–1853, 2009. www.springerlink.com
Quantitative Evaluation of ECG Changes Reflecting Heart Activity Control during Postural Changes
Analysis of the ECG signals was performed in Kaunas University of Medicine using MatLabTM computation environment.
Fig. 1 Subject under investigation with electrodes for registration of ECG on Tilt Table. Data being collect at the Microgravity Centre (Brazil) and transmitted live via SKYPE videoconference to researchers in Kaunas University of Medicine, Lithuania The structural analysis of ECG was performed in aim to extract the part of the ECG signal reflecting excitation spread in atria during each cardiac-cycle. The minimum of signal derivative, which corresponds to the negative slope of the QRS, was chosen as preliminary fiducial point of cardiac-cycle. Bicubic spline interpolation using values of samples between the end of T-wave of preceding cardiaccycle and beginning of P-wave of current cardiac-cycle was used to calculate baseline wander component, which was subtracted from the original signal. We maximized crosscorrelation in time of the preliminary detected R-wave with the R-wave template to extract cardiac-cycles maximally aligned to R-wave. The R-wave template was constructed from first 10 cardiac-cycles of the recording and updated after every processed cardiac-cycle. Our preliminary tests, as well as [7] showed that not only morphology of P-wave, but also P-Q interval changes are expected during orthostatic test. The part of the extracted and aligned cardiac-cycle, starting from -330 ms till -50 ms back in time from the fiducial point of the cardiac-cycle was considered as array of samples including P-wave. The excerpt with aligned in time P-wave samples we took from this interval maximizing cross-correlation with the P-wave template constructed from first 10 cardiac-cycles of the recording and updated after every processed cardiac-cycle. The time shift of every ordinary P-wave till maximal correlation with the template was considered as P-Q interval
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change and stored into separate array. The final arrays of samples of P waves formed two-dimensional array reflecting the shapes of P-wave during the whole recording. It is redundant but comprehensive representation of P-wave shape variety:
x1,1 x2,1 X= ...
x1, 2 x2,1 ...
... ... xi , j
x1,n x2,n , ...
xm,1
xm , 2
...
x m ,n
(1)
where xi,j is the jth sample of ith P-wave. The number of columns represents the number of cardiac-cycles obtained during the experiment. Multivariate analysis methods, such as Principal Component Analysis (PCA) are used for reduction of dimensionality in representation of biomedical signals and could be successfully used for evaluation of morphology changes in quasi-periodic biomedical signals [8]. The PCA transforms the original data set into a new set of vectors (the principal components) which are uncorrelated and each of them involve information represented by several interrelated variables in the original set. The calculated principal components are ordered so that the very first of them retain most of the variation present in all the original variables. Thus it is possible to perform a truncated expansion of ST-T complexes representing vectors by using only the first several principal components. Every vector xi representing ordinary P-wave is then represented by linear combination of the principal components φk multiplied by coefficients wi,k : n
xi = ∑ wi ,k ϕ k .
(2)
k =1
We calculated the basis functions (principal components) as eigenvectors of covariation matrix Rx:
[
]
R x = E X ⋅ XT .
(3)
Calculation of the co variation matrix was performed by using MatLabTM function “COV” which gave mathematical expectation E after removing the mean from each column. For determination of the minimal, yet sufficient, number of principal components (basis functions) for truncated expansion of P-wave samples array, we used the cross-validation criterion based on the parameter called PRESS (PREdiction Sum of Squares) [9]:
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n
p
PRESS (m) = ∑∑ ( m xˆij − xij ) 2 , i =1 j =1
(4)
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where
A. Krisciukaitis et al.
m
xˆij is the estimate of the original data set based
not on all but the first m basis functions,
xij - the original
data set. The PCA was performed separately for the P wave array of each recording. The coefficients of the orthonormal basic functions represent P-wave shape during each cardiaccycle as a point in the n - dimensional orthogonal space, where n is the minimal yet sufficient number of basic functions. It was defined according to the methodology described in [10]. Previous our works have shown that different shapes of P waves during orthostatic tests create clusters of special forms. Those clusters were identified by testing statistical hypothesis of uniformity [11]. For each vector wi Euclidian distances were calculated to all other vectors (formula 5). More generally this method is described [3].
d ij =
tude in regard to the body position changes. We applied simple amplitude scaling of P-wave as compensation of amplitude changes minimizing difference between template and current P-wave for preliminary detail analysis of Pwave array. Typical P-wave shape examples during one recording are presented in fig.3(A,B). It revealed that changes in P-wave shape, particularly in the first half of it were present in some recordings in regard to the body position changes. A
(5)
k =1
C 0.4 0.3 0.2 w4 0.1 0 -0.1 0.6
m
∑ (wik − w jk ) 2
B
0.4
w3
0.2
0
-0.2 0.5
1
1.5
2
2.5
w2
Fig. 3 Typical variety of P-wave shapes during one recording. Original Pwaves (A) and amplitude-normalized (B). Representation of P-wave shape in the orthogonal space of coefficients of principle components (C)
III. RESULTS Figure 2 presents a typical ECG response to an orthostatic test. The duration of the RR interval and body position are shown at the end of each cardiac-cycle.
PCA of P-wave samples array gave quantitative estimates of the shape changes. Minimal yet sufficient number of principle components to be used for truncated P-wave representation in most recordings were 4. Amplitude scaling in fact was not necessary for quantitative evaluation of Pwave shape by means of PCA because normally first principal coefficient does it and we observed absolute correlation between coefficient of the first principal component and scaling coefficient in our preliminary tests. So for estimation of amplitude changes we used coefficient of the 1st principal component while detail estimation of P-wave shape changes was done using coefficients from 2nd till 4th principal components. Representation of P-wave shape in the orthogonal space of coefficients of principle components revealed that dots representing shape of every P-wave are not randomly distributed, but accumulated in some clusters (fig. 3 C). Number of clusters in our recordings usually varied from 2 till 3.
Fig. 2 Typical ECG response to an orthostatic test. The duration of the RR
IV. DISCUSSION
interval and body position are shown at the end of each cardiac-cycle
Certain visible changes in heart rate and the shape of whole ECG cardiac-cycle corresponding to the altering body position can be observed. In the head-up position a decrease in T-wave amplitude was observed. Our main focus was put on the changes of the part of cardiac-cycle representing excitation spread in the atria. First of all one can notice a P-wave shift in time and changes in it’s ampli-
This paper presents only a preliminary results of our study from physiological point of view. However it shows that elaborated experimental system and available means for data collecting, transmission and analysis allow remote testing of subjects in non-ordinary conditions. The physiological parameters evaluated during our experiments in general comply with the data of other authors. Changes in amplitude of parts of cardiac-cycle comply with the results
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Quantitative Evaluation of ECG Changes Reflecting Heart Activity Control during Postural Changes
reported in [12] about vectorcardiographic changes during gravity changes during parabolic flights. In our case such changes are reflected as amplitude changes in one lead ECG. Observed changes in P-R interval length comply with the data reported in [13] reflecting changes in parasympathetic influence on atrioventricular conductance. However contrarily [13] we did not observe respiration-related alterations in this parameter in head-up body position. Observed changes in P-wave shape could be valued as most interesting results. As mentioned in introduction, changes in excitation start point (earliest pacemaker site) even within the sinus node due to the parasympathetic activity results the changes in excitation spread in right atria. The sinus node is not a localized structure but a widespread tissue along the crista terminalis. More significant effect we notice when earliest pacemaker site exceeds sinus node. The effects on changes of so called P-wave axis are reported in [14,15]. However excitation spread in the right atrium is reflected only in the beginning of the P-wave, the rest of P-wave reflects excitation spread in both atria or even in the left one. So changes in shape caused by the shift of earliest pacemaker site due to the parasympathetic activity we can expect only in the first part of P-wave. Exactly such phenomena was observed in our experiments. Non-even or nonrandomly distributed, but accumulated in clusters quantitative estimates of P-wave shape show that the shift of earliest pacemaker site takes place between some discrete locations, what complies with the data reported in [16].
3.
4. 5. 6.
7. 8. 9. 10.
11. 12. 13.
V. CONCLUSIONS This study was a collaborative work conducted using modern information technologies. It demonstrates not only the possibility of virtual cooperation and contribution between distant institutions, but also demonstrates the ability to send, receive and process biomedical diagnostic information to remote or difficult to access places, such as ships and spacecraft.
ACKNOWLEDGMENT International Federation of Telemedicine and Electronic Health (IsfTeH) and Lithuanian Fund for Science and Studies has supported this work.
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Author: Institute: Street: City: Country: Email:
Wyckliffe H. G., R. L. Johnson, A. E. Nicogossian, S. A.Bergman,Jr., M. M.Jackson, Vectorcardiographic Results From Skylab Medical Experiment M092: Lower Body Negative Pressure, http://lsda.jsc.nasa.gov/books/skylab/Ch30.htm
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Algimantas Krisciukaitis Kaunas University of medicine Eiveniu str. 4 Kaunas Lithuania
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