njit-etd2003-081 - New Jersey Institute of Technology

njit-etd2003-081 - New Jersey Institute of Technology njit-etd2003-081 - New Jersey Institute of Technology

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101 The quantity C(ω) has a range of 0.0 to 1.0, where 1.0 indicates that all of the measured output power is due to the input excitation. This is the most desirable situation and will only be true at frequencies where the spectral energy of the noise ny (t) is negligible. The coherence can therefore be viewed as a measurement quality indicator. When a significant portion of the measured output is not related to the excitation, a low coherence results. This indicates that for a given amount of averaging, the variance of the transfer function at these frequencies will be higher than the variance where there is good coherence (closer to 1.0). It is important to recognize that since this estimator is unbiased, given sufficient averaging, the transfer function estimate will converge to the system's actual transfer function in spite of possibly low coherence. The above transfer function and coherence estimation calculations are calculated in Lab VIEW and/or MatLab System Identification Toolbox. 3.13.2 The ARX Models The timing of electrical and mechanical events within the heart is vital to its function. In "normal" healthy humans, a bundle of spontaneously depolarizing cells located on the right atrium of the heart, called the sino-atrial (SA) node, acts as the pacemaker for the heart. Through an upward drift in electrical potential, the cells spontaneously reach a threshold potential, at which point the cells rapidly depolarize, or "fire", as a group. This is followed by a reset which marks the start of a new cycle. The firing initiates the spread of electrical activity through the heart, and therefore initiates the contraction that is necessary for blood to be delivered to the rest of the body. Although temporal

102 variability exists in the propagation of the electrical activity across the tissue of the heart, the primary interest is in the temporal variability from "beat-to-beat", which can be captured through observations of a distinct electrical event contained within each cycle. The spontaneous depolarization of SA nodal cells has an intrinsic rate that is modulated by direct input from the two branches of the autonomic nervous system (ANS). The basal activity of each branch has an effect on the mean rate of depolarization, but also the vast majority of variability in the timing of the electrical events of the heart is produced via this autonomic innervation by varying how quickly the SA nodal cells reach the threshold and "fire". Activity of the respiratory rhythm generator has been shown to modulate the rate of depolarization of SA nodal cells at the respiratory frequency via the parasympathetic branch, and baroreflex feedback mechanisms have been shown to modulate the rate through both branches at sub respiratory frequencies. The goal of the modeling, therefore, will be to capture the dynamics of these mechanisms in a relatively simple ARX-modeling scheme, which has direct physiological interpretation. Here two models are used for this study. The first model is an open loop input driven ARX model which can capture the characteristics of the "heart rate" variability. One input is simply a filtered Gaussian white process, for which several nice results will be developed. Other inputs correspond directly to autonomic mediation specifically related to respiration and blood pressure related modulation. The other model includes a feedback that allows one to investigate the feedback mechanisms in the ARX model, which will lay the groundwork for capturing the effect of baroreflex activity on heart rate variability.

101<br />

The quantity C(ω) has a range <strong>of</strong> 0.0 to 1.0, where 1.0 indicates that all <strong>of</strong> the<br />

measured output power is due to the input excitation. This is the most desirable<br />

situation and will only be true at frequencies where the spectral energy <strong>of</strong> the noise<br />

ny (t) is negligible. The coherence can therefore be viewed as a measurement quality<br />

indicator. When a significant portion <strong>of</strong> the measured output is not related to the<br />

excitation, a low coherence results. This indicates that for a given amount <strong>of</strong> averaging,<br />

the variance <strong>of</strong> the transfer function at these frequencies will be higher than the variance<br />

where there is good coherence (closer to 1.0).<br />

It is important to recognize that since this estimator is unbiased, given sufficient<br />

averaging, the transfer function estimate will converge to the system's actual transfer<br />

function in spite <strong>of</strong> possibly low coherence.<br />

The above transfer function and coherence estimation calculations are calculated<br />

in Lab VIEW and/or MatLab System Identification Toolbox.<br />

3.13.2 The ARX Models<br />

The timing <strong>of</strong> electrical and mechanical events within the heart is vital to its function. In<br />

"normal" healthy humans, a bundle <strong>of</strong> spontaneously depolarizing cells located on the<br />

right atrium <strong>of</strong> the heart, called the sino-atrial (SA) node, acts as the pacemaker for the<br />

heart. Through an upward drift in electrical potential, the cells spontaneously reach a<br />

threshold potential, at which point the cells rapidly depolarize, or "fire", as a group. This<br />

is followed by a reset which marks the start <strong>of</strong> a new cycle. The firing initiates the<br />

spread <strong>of</strong> electrical activity through the heart, and therefore initiates the contraction that<br />

is necessary for blood to be delivered to the rest <strong>of</strong> the body. Although temporal

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