Variation Analysis of Sphygmogram to Assess Cardiovascular System Under Meditation

Chuan-Yi Liu; Ching-Chuan Wei; Pei-Chen Lo

Disclosures

Evid Based Complement Alternat Med. 2009;6(1):107-112. 

In This Article

Experiment and Results

Processing the Signal

The blood pressure waveforms of radial artery non-invasively detected at wrist by piezoelectric transducer were recorded for 10 s and digitized at a sampling rate of 100 Hz. To reduce high frequency noise, a low-pass filter is designed with a 3dB cutoff frequency of 50 Hz. Since null baseline was required in the analysis, we removed the mean value of each BPW period in pre-processing. Accordingly, negative waveforms might appear.Note that non-constant, linear baseline drift sometimes interfered in the BPW (Fig. 5)[15]. The sources of interference include the body movement, heavy respiration, etc. The resulting artifacts might be false amplitude or position shift of peaks/valleys.Although removal of the baseline drift may help, we found it necessary to further correct the interference patterns. In that case, baseline removal involved a linear-regression method for baseline-drift detection.

Figure 5.

The linear baseline drift in the BPW (upper) and the result after removing it (lower).

The BPW recording instrument can only continuously trace for up to 10 s. BPW is a quasi-periodic signal with 10-16 complete cycles in a 10 s term. Here we averaged out the 10-16 cycles to get the final BPW for further quantification of embedded features. We thus can obtain triple to quadruple SNR (signal-to-noise ratio) that is linearly dependent of the square root of the number of measurements. The SNR level could fulfill our research requirements.

Subjects

The participants were divided into two groups—20 meditationpractitioners and 20 normal, healthy people without any experiencein meditation. In the experimental group, 13 females and 7 maleswith a mean age of 26.6 ± 2.2 years participated. Their experiences in Zen-Buddhist practice span 6.9 ± 3.3 years.The control group comprised 9 females and 11 males with a mean age of 25.2 ± 1.8 years. All the meditation practitioners learned Zen-Buddhist meditation in the Taiwan Zen-Buddhist Association.Only experienced practitioners with more than 3 years of meditation experience were invited. The controls were graduate students of National Chiao-Tung University. No subjects had any cardiovascular disease in their medical histories.

Recording

Participants sat in an isolated space during the experiments.Blood pressure waves were recorded before and after the 40 minmain session (meditation or relaxation). In the main session,experimental group practiced Zen meditation, while controls sat in normal relaxed position with eyes closed.

BPW Before and After Meditation

Figure 6 illustrates an example of the BPW of a meditation practitioner.The solid curve shows the before-meditation BPW and the dashed one shows that after meditation. In Fig. 6, after-meditation P wave rises more steeply than the before-meditation one. For this particular subject, poor arterial elasticity makes the before-meditation T wave occur earlier and merge with P wave,resulting in a broadened P wave. In after-meditation BPW, the T wave becomes evident and distinguishable from the P wave,inferring that enhanced arterial elasticity is a consequence of meditation practice. Moreover, the V 3 valley descends (i.e.h 4 decreases) after meditation, indicating a decrease in peripheral resistance. The D wave magnitude is also strengthened after meditation. A typical example of 10 s BPW is shown in Fig. 7. Note that the pulse rate is slower after meditation, resulting in a phase difference between the two waves. In summary, the after-meditation BPW reflects a more robust cardiovascular system that could have been tuned up by the Zen meditation.

Figure 6.

The before-meditation (solid curve) and after-meditation (dashed curve) BPW for an experimental subject.

Figure 7.

The 10s typical BPW of one meditation practitioner.

Comparison Between Groups

Table 1 shows the results of the four parameters measured in both groups. The variation percentage of each parameter in each group is calculated by the formula[6]. The P-values in Table 1 are evaluated using t-test, which is used to check whether the variation percentages show statistical differences between the groups. In this preliminary investigation, we concentrated on intra-subject differences between various experimental sessions because the inter-subject variations in BPW were too complicated to manipulate.

In comparison with the control group, Zen-meditation practitioner shave higher ranges of variation percentages in all four parameters.The performance details of each parameter are as follows: When considering the rising slope of P wave, h 1/t 1, that reflects the ejection ability of left ventricle or aorta elasticity,the experimental group had a mean increase from 390.8 to 435.1,a variation percentage of 11.7%, that was 5% higher than the variation percentage of control group. The second parameterh 3/h 1, measuring the effect of T wave, demonstrated distinct enhancement of arterial elasticity in the experimental group(three times the increasing rate of the control group). We discovered that even though some experimental subjects had vague T wave before meditation, it was often boosted after meditation. On the other hand, T wave variation was not as obvious in the control group. We observed that some control subjects did not even have a T wave before and after relaxation. If T waves merged with P waves, the parameter h 3/h 1 was considered to be zero. Next,the high decreasing rate of h 4/h 1 revealed reduced peripheral resistance after meditation. Finally, the increasing h 5/h 1 infers that Zen meditation significantly improves the quality of semi-lunar valves and arterial elasticity. The t-test results showed that all P-values were <0.05, further corroborating the significance of the improvement in the meditation group. In comparison with normal relaxation, Zen meditation may effectively improve the characteristics of cardiovascular system according to parameters extracted from blood pressure waves.

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