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njit-etd2003-081 - New Jersey Institute of Technology

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166<br />

HRV more information about HRV activities in both time and frequency domains can<br />

now be revealed and be waiting for researcher's new and appropriate interpretations.<br />

Figure 5.8 HR IIBI and power spectrum plots <strong>of</strong> a normal subject at 3 min rest paced<br />

breathing at 8 bpm.<br />

Figure 5.8 illustrates the case <strong>of</strong> a file from a normal subject paced breathing at 8<br />

bpm during a 3 minutes rest period. The HRV analysis was performed using the four<br />

different distributions with the same specifications (length <strong>of</strong> analysis window equal to<br />

256, the length <strong>of</strong> the FFT analysis is 1024 and time resolution <strong>of</strong> 0.195 seconds). Even<br />

though this was a poor choice <strong>of</strong> resolution, other resolutions showed even worse results.<br />

It is evident from looking at the results in the figures that all the distributions show the<br />

effect <strong>of</strong> respiration on HRV at about the respiration frequency <strong>of</strong> 0.133 Hz (due to<br />

paced-breathing at 8 breaths per minute). Figures 5.9 (a) — (d) all show a band at 0.133<br />

Hz and they all smear to other frequencies in various amounts. The 0.133 Hz bands <strong>of</strong><br />

the SPWV and CW distributions in figures 5.9 (b) and (c) show less smearing than the<br />

STFT or the BJC distribution. When comparing the contour plots <strong>of</strong> the SPWV and CW<br />

distributions, it is clear that CW shows the 0.133 Hz band with more intensity and much<br />

sharper than the SPWV distribution. From these observations, the CW is the best<br />

distribution <strong>of</strong> the four time-frequency distributions.

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