njit-etd2003-081 - New Jersey Institute of Technology
njit-etd2003-081 - New Jersey Institute of Technology njit-etd2003-081 - New Jersey Institute of Technology
5 breathing room air (RA) or with oxygen supplement (02) during rest and exercise, that alter baroreflex activity, in order to assess COPD related changes in baroreflex response. When HRV is analyzed in the frequency domain, the power spectrum of HRV does not show its temporal changes. There are many physiological situations of interest where heart rate changes rapidly over time and the monitoring of these temporal changes may be very important. Time frequency representations are perfect candidates to monitor these temporal-spectral changes. Time frequency analysis is performed on the HRV data to show vagal tone and the sympatho-vagal balance as a function of time. In this part of the study, several time frequency representations such as the short time Fourier transform, the smoothed pseudo Wigner-Ville, the Choi-William, the Born- Jordan-Cohen are used in comparison with wavelet distributions (Morlet, Meyer, Daubechies, Mexican Hat and Haar) for analyzing HRV and physiological signals. Coherence spectral plots are graphical representations of the coherence between two signals. Coherence can be viewed as correlation coefficients in the frequency domain [5]. It is a measure of the linear dependence between two signals, normalized to values between zero and one. The applications of coherence in past studies have been directed toward the analysis of the electroencephalogram or EEG signals. In this study, however, coherence is used not for EEG signals but for the combinations between heart rate, blood pressure and respiration signals. The coherence spectral plots in the whole HRV frequency range (0.04 to 0.7 Hz) are presented and the average weighted sum, the weighted coherence values, in the low frequency band (LF: 0.04 to 0.15 Hz) and in the high frequency band (HF: 0.15 to 0.4 Hz) are obtained for further statistical analyses (i.e. principal component analysis, PCA and cluster analysis, CA). These values are
6 examined for determining the inter-relationship between heart rate, blood pressure and respiration of the cardiovascular system. Once the study of the relationships between heart rate, blood pressure and respiration are established, the influence of one component was removed while the coherence between the two residual (signal) components were examined. It is here the technique of partial coherence is introduced as another novel technique in investigating HRV. Again the weighted partial coherence values in the LF and HF bands are obtained for further analysis. Beside the traditional data analysis in the time domain and frequency domain the last part of this study also used other control system techniques of system identification to examine stationary and non-stationary conditions of heart rate variability. To further investigate the role of the autonomic nervous system and to understand the complex links between respiratory activity and arterial pressure, the transfer functions between respiration, heart rate (HR), and arterial systolic blood pressure in COPD and healthy subjects were determined during 5-min periods in which the respiratory rate was controlled in a predetermined but pseudo-random fashion. Linear analyses of fluctuations in heart rate and other hemodynamic variables have been used to elucidate cardiovascular regulatory mechanisms. Since the role of nonlinear contributions to fluctuations in hemodynamic variables has not been fully explored, this study also presents a nonlinear system analysis of the effect of fluctuations in respiration and arterial blood pressure (ABP) on heart rate (HR) fluctuations. A time domain technique is presented to estimate transfer characteristics from fluctuations of respiration to heart rate (HR). Pure moving average (MA) and
- Page 1 and 2: Copyright Warning & Restrictions Th
- Page 3 and 4: ABSTRACT TIME-FREQUENCY INVESTIGATI
- Page 5 and 6: TIME-FREQUENCY INVESTIGATION OF HEA
- Page 7 and 8: APPROVAL PAGE TIME-FREQUENCY INVEST
- Page 9 and 10: BIOGRAPHICAL SKETCH (Continued) D.A
- Page 11 and 12: ACKNOWLEDGMENT The author wishes to
- Page 13 and 14: TABLE OF CONTENTS Chapter Page 1 IN
- Page 15 and 16: TABLE OF CONTENTS (Continued) Chapt
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- Page 19 and 20: TABLE OF CONTENTS (Continued) Chapt
- Page 21 and 22: LIST OF FIGURES Figure Page 2.1 The
- Page 23 and 24: LIST OF FIGURES (Continued) Figure
- Page 25 and 26: LIST OF FIGURES (Continued) Figure
- Page 27 and 28: ABBREVIATIONS A ABP Arterial Blood
- Page 29 and 30: ABBREVIATIONS (Continued) P PID Pro
- Page 31 and 32: 2 mortality and sudden death. [2] B
- Page 33: 4 1) Patients with severe pulmonary
- Page 37 and 38: 8 identified using principal compon
- Page 39 and 40: 1 0 1. Present the application of t
- Page 41 and 42: 12 1.3 Outline of the Dissertation
- Page 43 and 44: CHAPTER 2 PHYSIOLOGY BACKGROUND Bio
- Page 45 and 46: 16 Figure 2.2 The systemic and pulm
- Page 47 and 48: 18 illustrated in Figure 2.3. The i
- Page 49 and 50: 20 2.2 Blood Pressure The force tha
- Page 51 and 52: 22 2.4 The Nervous System Human beh
- Page 53 and 54: 24 The sympathetic nerve fibers lea
- Page 55 and 56: 26 Without these sympathetic and pa
- Page 57 and 58: 28 center in the medulla, which con
- Page 59 and 60: 30 Figure 2.6 Autonomic innervation
- Page 61 and 62: 32 average heart rate was measured
- Page 63 and 64: 34 However, they do note that there
- Page 65 and 66: Figure 2.9 The placement of the pos
- Page 67 and 68: 38 female. While more men suffer fr
- Page 69 and 70: 40 Stage II: Moderate COPD - Worsen
- Page 71 and 72: CHAPTER 3 ENGINEERING BACKGROUND Th
- Page 73 and 74: 44 Two common types of time-frequen
- Page 75 and 76: 46 STFT: Short-Time Fourier Transfo
- Page 77 and 78: 48 3.3 The Analytic Signal and Inst
- Page 79 and 80: 50 The advantage of using equation
- Page 81 and 82: 52 3.5 Covariance and Invariance Th
- Page 83 and 84: where H(f), S(f) are Fourier transf
6<br />
examined for determining the inter-relationship between heart rate, blood pressure and<br />
respiration <strong>of</strong> the cardiovascular system.<br />
Once the study <strong>of</strong> the relationships between heart rate, blood pressure and<br />
respiration are established, the influence <strong>of</strong> one component was removed while the<br />
coherence between the two residual (signal) components were examined. It is here the<br />
technique <strong>of</strong> partial coherence is introduced as another novel technique in investigating<br />
HRV. Again the weighted partial coherence values in the LF and HF bands are obtained<br />
for further analysis.<br />
Beside the traditional data analysis in the time domain and frequency domain the<br />
last part <strong>of</strong> this study also used other control system techniques <strong>of</strong> system identification<br />
to examine stationary and non-stationary conditions <strong>of</strong> heart rate variability. To further<br />
investigate the role <strong>of</strong> the autonomic nervous system and to understand the complex<br />
links between respiratory activity and arterial pressure, the transfer functions between<br />
respiration, heart rate (HR), and arterial systolic blood pressure in COPD and healthy<br />
subjects were determined during 5-min periods in which the respiratory rate was<br />
controlled in a predetermined but pseudo-random fashion.<br />
Linear analyses <strong>of</strong> fluctuations in heart rate and other hemodynamic variables<br />
have been used to elucidate cardiovascular regulatory mechanisms. Since the role <strong>of</strong><br />
nonlinear contributions to fluctuations in hemodynamic variables has not been fully<br />
explored, this study also presents a nonlinear system analysis <strong>of</strong> the effect <strong>of</strong> fluctuations<br />
in respiration and arterial blood pressure (ABP) on heart rate (HR) fluctuations.<br />
A time domain technique is presented to estimate transfer characteristics from<br />
fluctuations <strong>of</strong> respiration to heart rate (HR). Pure moving average (MA) and
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