CASE STUDY OF USING THE ECG SIGNAL AS A REFERENCE SIGNAL IN OPTICAL PULSE TRANSIT TIME MEASUREMENT OF BLOOD FLOW - THE EFFECT OF DIFFERENT ELECTRODE PLACEMENTS ON PULSE TRANSIT TIME Teemu Myllylä, Erkki Vihriälä, Hannu Sorvoja, University of Oulu, Optoelectronics and Measurement Techniques Laboratory, Finland Vesa Korhonen, Oulu University Hospital, Radiology Clinic, Finland Introduction Electrocardiography (ECG) is commonly used in pulse transit time (PTT) measurements to provide a reference signal. This method is based on computing the temporal difference between the R wave of the QRS complex of the ECG and the beginning of the following pulse wave measured by photoplethysmography (PPG) [1,2,3]. However, PTT also relates to non-invasive blood pressure measurements, since a correlation exists between PTT and blood pressure fluctuations [4,5]. Correlation analysis has proven useful, for example, when compared to BP measurements by cuff-based methods [6]. Nevertheless, to our knowledge, there are not many studies assessing the accuracy of the ECG signal itself, especially in relation to ECG electrode placement, and whether it has an effect on the accuracy of PTT measurements. This is probably because the time position of the R wave of the ECG signal with regard to PTT measurements is assumed to be the same regardless of electrode placement. Introduction The following slides present experimental measurements of ECG signals at various electrode placements. Measurements at a high sampling rate indicate that the placement of ECG electrodes can have a certain impact on the position of the R wave in the time domain. This effect takes the form of small time delays of the R wave pulse between different ECG measurements, when electrodes are replaced between the measurements and the placements are not exactly identical. This can be relevant, particularly when accurate time domain determination of the R wave is required as a reference in determining the pulse transit time of blood flow. Additionally, we studied what sensor placements are most suitable for use in pulse transit time and velocity measurements. Measurement method In our experiments, ECG signals were measured simultaneously and independently by two ECG devices. Both ECG electrodes and their amplifiers were identical. All in all, the effect of six different electrode placements were measured on three test persons. Concurrently with the ECG measurement, heart pulse waves were measured at various sensor placements by PPG sensors. As a reference measurement, also a Finapres device was simultaneously measuring PPG and blood pressure from the finger tip. PPG was measured to estimate the effect of possible R wave delays on PTT. Measurement method To verify the accuracy of our ECG measurements, a verification measurement was initially conducted on every person. Figure 1 shows the sensor placement used in this measurement (on the left). This placement provided a reference, when the sensors of the other ECG device were moved to a different location for each measurement. Pulse responses of both ECGs were measured independently and simultaneously. Moreover, the amplifiers of the electrodes were swapped between measurements 1 and 2. Figure 1. Verification measurement. Sensors were placed in the positions shown on the left. As assumed, the recorded pulses are identical. Measurement method In subsequent measurements, all sensor placements were measured twice by swapping the amplifiers of the electrodes (marked between the measurements n.1 and n.2). This was done to ensure that the amplifiers did not have an effect on signal response. The sampling frequency used in the measurements was 40kHz, and each measurement continued for about one minute. Possible time delays between the R waves of ECG signals obtained from different sensor placements, were recorded. Naturally, both ECG signals were measured simultanously by the two ECG devices. Measurement method Figure 2 shows the sensor placements used in our measurements. To ensure an easy repeatability, only the + electrode of the other ECG was moved to a different place. Throughout the entire measurement, the other ECG device continued measuring in the same way using the same sensor placement. Figure 2. Sensor placements used in the measurements. In each measurement, only one of the electrodes (+ electrode) was moved to a different position. The placement of the three electrodes of the other ECG device was always the same, as shown in the figure on the left. Likewise, for the other ECG, the remaining two electrodes ( + and ref) were always in the same position. In the placement shown on the right, the + electrode is placed on the person’s back. Results Comparison of two ECG signal responses measured simultaneously using different sensor placements Figure 3. Measurements 1.1 and 1.2. The replaced + electrode was located on the left shoulder and the distance between the + and – electrodes was 7 cm. This caused a delay of approx. 1.5 ms on the R wave, highlighted on the right showing one R wave. Results Comparison of two ECG signal responses measured simultaneously using different sensor placements Figure 4. Measurements 2.1 and 2.2. The replaced + electrode was located on the left shoulder (almost on the neck) and the distance between the + and – electrodes was 12 cm. This caused a delay of approx. 0.3 ms on the R wave, highlighted on the right showing one R wave. Results Comparison of two ECG signal responses measured simultaneously using different sensor placements Figure 5. Measurements 3.1 and 3.2. The replaced + electrode was located on the right shoulder and the distance between the + and – electrodes was 29 cm. This caused a delay of approx. 2 ms on the R wave, highlighted on the right showing one R wave. Results Comparison of two ECG signal responses measured simultaneously using different sensor placements Figure 6. Measurements 4.1 and 4.2. The replaced + electrode was located on the right side of the stomach, and the distance between the + and – electrodes was 31 cm. This caused a delay of approx. 4 ms on the R wave, highlighted on the right showing one R wave. Results Comparison of two ECG signal responses measured simultaneously using different sensor placements Figure 7. Measurements 5.1 and 5.2. The replaced + electrode was located on the right side and the distance between the + and – electrodes was 50 cm. This caused a delay of approx. 6 ms on the R wave, highlighted on the right showing one R wave. Results Comparison of two ECG signal responses measured simultaneously using different sensor placements Figure 8. Measurements 6.1 and 6.2. The replaced + electrode was located on the back and the distance between the + and – electrodes was 50 cm. This caused a delay of approx. 10 ms on the R wave, highlighted on the right showing one R wave. Results Calculation of the delays between R waves Two methods were used in signal delay calculations: 1. Searching for maximum values in the time interval -> Information about delay is the difference between peaks 2. Checking the correlation between signals in the time interval -> Delay is calculated using the correlation function The first method finds the maximum value of each signal for each time interval. Figure 8 illustrates an ECG signal response containing interference. This response presents 30 time intervals. Additional ‘maximum’ values were cut using thresholds. In this figure, recorded maximums are marked as dots. Delays between ECG signals were calculated as a time difference between each peak pair. In the second method, signals were divided into 24 parts, and the cross-correlation between signals was checked for each part. The correlation function yielded information about the delay for each part. Table 1 shows the results of both methods. Results Figure 8. Example of an ECG signal response including some interference, using electrode placement shown in figure 4. Found maximums are numbered and marked as dots. Time delays of the numbered peaks are presented in Table 1. Results Table 1. Time delays calculated by two methods. The interval numbers refer to Figure 8. Typical time delays between R waves acquired at different electrode placements ranged approximately from 1 to 15 ms. Wrong results are colored with red ECG signal 1 Number of interval 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 ECG signal 2 Maximum Correlation Time of maximum [s] Time of maximum [s] Delay [s] Delay [s] 0,688825 0,69895 0,010125 1,90705 1,9168 0,00975 3,039675 3,049225 0,00955 4,182925 4,193175 0,01025 5,39135 5,4012 0,00985 6,661675 6,671675 0,01 7,969625 7,97935 0,009725 9,208725 9,21865 0,009925 10,459375 10,4696 0,010225 11,6822 11,692325 0,010125 12,893975 12,9033 0,009325 14,1439 14,153475 0,009575 15,306625 14,9143 0,392325 16,846125 16,582175 0,26395 17,797 17,8073 0,0103 19,086725 19,0972 0,010475 20,408875 20,41875 0,009875 21,663925 21,674275 0,01035 22,8977 22,907875 0,010175 24,10155 24,1108 0,00925 25,31665 25,326175 0,009525 26,5444 26,55295 0,00855 27,876075 27,8868 0,010725 29,192325 29,2031 0,010775 0,0132 0,0076 0,011875 0,0169 0,3409 0,01615 0,01095 0,011975 0,016725 0,28345 0,0118 0,016825 0,299725 0,147325 0,016325 0,015825 0,0149 0,011225 0,2453 0,0116 1,093425 0,274575 0,017125 0,01295 Standard deviation 0,09181349 0,236610598 Average 0,03644583 0,121610417 Results The results for both methods shown in Table 1 are comparable, but the maximum method seems more accurate. The correlation method cannot properly manage signals that are very different from each other, especially when a measurement error occurs (as in interval no. 5). In Table 1, wrong delay times are coloured with red. The maximum method seems to always find the narrowest peak and to ignore measurement errors, if they are wide. Narrow errors, however, the method is not able to deal with (magenta marker no. 13). It would probably also have problems, if the searched peak were attenuated by some error. The Mean Square Error between both methods was calculated by Results As the presented ECG signals show, three electrodes, as used in the measurements here, allowed us to acquire a clear and sharp R wave for PTT measurements. The R peak was sufficiently good at every electrode placement, but the first three placements on the left in Figure 2 gave a slightly better signal-to-noise ratio than the others. Besides the EEG cap, some EEG devices also include one electrode that can be placed on back of a patient, as shown in Figure 8. In addition to EEG, this also allows to measure ECG. However, in our measurements, this placement gave the lowest quality ECG signal, although it sufficed for PTT measurements. Additionally, this electrode placement produced more delay in the R peak than the other placements. Results The effect of R wave delays of the ECG on PTT measurements was studied by simultaneous measurements using three PPG sensors in different places, as shown in Figure 9. One PPG, with a source detector distance of 3 cm, was attached on the forehead to obtain pulsations from deeper within tissue. PPG 2 and PPG 3 measured skin blood pulsations. Figure 9. PPG sensors placed on the forehead, neck and right finger tip. Results Figure 10 presents signal pulses in the time domain when sensors are placed as shown in Figure 9. It can be seen that the effect of the ECG time delay between two ECGs is rather small in comparison to pulse transit time. This can be noticed especially when PTT is measured from the finger tip (PPG 3), Table 2. Figure 10. Comparison of measured signals in the time domain. Results Table 2. Comparison of PTT values between ECG1 - PPG3 and ECG2 – PPG 3, placement in Figure 4. ECG 1 ECG 2 PPG 3 Time of maximum [s] Time of maximum [s] Time of maximum [s] Delay ECG 1-ECG2 [s] Delay ECG1-PPG3 [s] Delay ECG2-PPG3 [s] Approximation error [%] 1 0,298375 0,29825 0,573025 0,000125 0,27465 0,274775 0,045512 2 1,08315 1,083725 1,3603 0,000575 0,27715 0,276575 0,207469 3 1,911325 1,91135 2,1605 2,5E-05 0,249175 0,24915 0,010033 4 2,775825 2,7756 3,0419 0,000225 0,266075 0,2663 0,084563 5 3,69085 3,690725 3,956525 0,000125 0,265675 0,2658 0,04705 6 4,610475 4,609925 4,889825 0,00055 0,27935 0,2799 0,196886 7 5,52075 5,5211 5,795375 0,00035 0,274625 0,274275 0,127447 8 6,4299 6,430475 6,696575 0,000575 0,266675 0,2661 0,215618 9 7,323925 7,32415 7,6047 0,000225 0,280775 0,28055 0,080135 10 8,192775 8,1926 8,46565 0,000175 0,272875 0,27305 0,064132 11 9,069925 9,069725 9,34165 0,0002 0,271725 0,271925 0,073604 12 9,94965 9,949325 10,21583 0,000325 0,266175 0,2665 0,1221 13 10,82463 10,82463 11,10093 0 0,2763 0,2763 0 14 11,658 11,65765 11,93648 0,00035 0,278475 0,278825 0,125685 15 12,47158 12,4712 12,74898 0,000375 0,2774 0,277775 0,135184 16 13,28725 13,28745 13,5566 0,0002 0,26935 0,26915 0,074253 17 14,10833 14,10833 14,37673 0 0,2684 0,2684 0 18 14,9247 14,9245 15,19205 0,0002 0,26735 0,26755 0,074808 19 15,7485 15,7486 16,0206 1E-04 0,2721 0,272 0,036751 20 16,6089 16,60898 16,8672 7,5E-05 0,2583 0,258225 0,029036 21 17,50643 17,50655 17,77088 0,000125 0,26445 0,264325 0,047268 22 18,4129 18,4127 18,68403 0,0002 0,271125 0,271325 0,073767 23 19,2927 19,29208 19,5716 0,000625 0,2789 0,279525 0,224095 24 20,1621 20,1623 20,4292 0,0002 0,2671 0,2669 0,074878 25 21,04273 21,04305 21,30803 0,000325 0,2653 0,264975 0,122503 26 21,90338 21,90308 22,1775 0,0003 0,274125 0,274425 0,109439 27 22,72163 22,72145 23,01365 0,000175 0,292025 0,2922 0,059926 28 23,52815 23,52835 23,80445 0,0002 0,2763 0,2761 0,072385 29 24,35685 24,35718 24,61708 0,000325 0,260225 0,2599 0,124892 30 25,20358 25,204 25,45558 0,000425 0,252 0,251575 0,168651 31 26,08335 26,08348 26,33258 0,000125 0,249225 0,2491 0,050155 32 26,9658 26,96558 27,21618 0,000225 0,250375 0,2506 0,089865 33 27,88778 27,88798 28,1382 0,0002 0,250425 0,250225 0,079864 34 28,82398 28,82433 29,08825 0,00035 0,264275 0,263925 0,132438 35 29,74188 29,7422 30,01268 0,000325 0,2708 0,270475 0,120015 st dev 0,000159015 0,009974738 0,010068773 average 0,000258333 0,26855 0,268534286 Results Figures 11 and 12 present ECG cycles measured both with Einthoven and Goldberg connections by the ECG devices used in our measurements. In figure 11 signals are obtained with Einthoven connection 1 signals being related to the elektromagnetic field between left and right arm and in figure 12 using Goldberger connection aVF, signals relating to the field between left leg and both arms. Figure 11. ECG cycles measured with an Einthoven connection 1 (N=30). Figure 12. ECG cycles measured with a Goldberger connection aVF (N=30). Results Figures 13 and 14 presents vector cardiograms determined with all separate cycles (Figure13) and with calculated average values (Figure 14). Determining of the vector cardiogramm was performed by calculating the vector summs of the of the signals in Fig.11 (y-axis) and 12 (x-axis). These ECG cycles show the position of the R wave in the time domain with calculated vector sums (the loops pointed by arrows). Some of in the results presented differences in the ECG signal caused by different ECG placements can be explained by change of direction of R wave vector. Figure 13. Determined vector ECG cycles (N=30) calculated using signals shown in Figs. 11 and 12. Figure 14. Vector ECG cycle using calculated average signals in Figs.11 and 12. Conclusion The results show that the position of the R peak in the time axis depends on the placement of the electrodes used in ECG measurements. Although variations in the time axis are small, they may be in some situations relevant when the R wave of the ECG is used as a reference in pulse transit time measurements of blood flow. Placing the electrode on the back has a larger impact on the time position of the R wave. Furthermore, it is reasonable to claim that the resolution of the ECG signal in proportion to the time domain can be partially dependent on electrode placement. Acknowledgements The authors would like to extend their warmest thanks to the following students for their assistance Aleksandra Zienkiewicz and Łukasz Surażyński, Gdansk University of Technology References [1] Suyoung Bang, Changik Lee, Jinwoo Park, Min-Chang Cho, Young-Gyu Yoon and SeongHwan Cho, "A pulse transit time measurement method based on electrocardiography and bioimpedance," in Biomedical Circuits and Systems Conference, 2009. BioCAS 2009. IEEE, 2009, pp. 153-156. [2] Qiao Zhang, Yang Shi, D. Teng, Anh Dinh, Seok-Bum Ko, Li Chen, J. Basran, V. Dal Bello-Haas and Younhee Choi, "Pulse transit time-based blood pressure estimation using hilbert-huang transform," in Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE, 2009, pp. 1785-1788 [3] J. Lass, K. Meigas, R. Kattai, D. Karai, J. Kaik, M. 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