597 lines
18 KiB
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597 lines
18 KiB
HTML
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LaTeX2HTML 2002 (1.62),
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original version by: Nikos Drakos, CBLU, University of Leeds
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* revised and updated by: Marcus Hennecke, Ross Moore, Herb Swan
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* with significant contributions from:
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Jens Lippmann, Marek Rouchal, Martin Wilck and others -->
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<TITLE>The dynamical model</TITLE>
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<B> Up:</B> <A NAME="tex2html64"
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HREF="index.shtml">A dynamical model for</A>
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<B> Previous:</B> <A NAME="tex2html58"
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HREF="node3.html">Heart rate variability</A>
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<H1><A NAME="SECTION00040000000000000000"></A>
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<A NAME="s:model"></A>
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<BR>
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The dynamical model
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</H1>
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The model generates a trajectory in a three-dimensional state space
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with co-ordinates <IMG
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WIDTH="56" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
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SRC="img1.png"
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ALT="$(x,y,z)$">. Quasi-periodicity of the ECG is reflected
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by the movement of the trajectory around an attracting limit cycle of
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unit radius in the <IMG
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WIDTH="41" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
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SRC="img11.png"
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ALT="$(x,y)$">-plane.
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Each revolution on this circle corresponds to one RR-interval or heart beat.
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Inter-beat variation in the ECG is reproduced using the
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motion of the trajectory in the <IMG
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WIDTH="12" HEIGHT="14" ALIGN="BOTTOM" BORDER="0"
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SRC="img12.png"
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ALT="$z$">-direction.
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Distinct points on the ECG, such as the P,Q,R,S and T are described by
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<I>events</I> corresponding to negative and positive attractors/repellors
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in the <IMG
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WIDTH="12" HEIGHT="14" ALIGN="BOTTOM" BORDER="0"
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SRC="img12.png"
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ALT="$z$">-direction. These events are placed at fixed angles along the
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unit circle given by <IMG
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WIDTH="22" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img13.png"
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ALT="$\theta_P$">, <IMG
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WIDTH="22" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img14.png"
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ALT="$\theta_Q$">,<IMG
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WIDTH="22" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img15.png"
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ALT="$\theta_R$">,<IMG
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WIDTH="21" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img16.png"
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ALT="$\theta_S$"> and
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<IMG
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WIDTH="22" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img17.png"
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ALT="$\theta_T$"> (see Fig. <A HREF="node4.html#f:pqrst3d">2</A>). When the trajectory
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approaches one of these events, it is pushed upwards or downwards
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away from the limit cycle, and then as it moves away it is pulled back
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towards the limit cycle.
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The dynamical equations of motion are given by a set of three ordinary
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differential equations
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<BR>
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<DIV ALIGN="CENTER"><A NAME="e:pqrst"></A>
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<!-- MATH
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\begin{eqnarray}
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{\dot x} &=& \alpha x - \omega y, \nonumber \\
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{\dot y} &=& \alpha y + \omega x, \nonumber \\
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{\dot z} &=& - \!\!\!\!\!\! \sum_{i \in \{P,Q,R,S,T\}} \!\!\!\!\!\!
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a_i \Delta \theta_i
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\exp(-\Delta \theta_i^2 / 2 b_i^2) - (z - z_0),
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\end{eqnarray}
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-->
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<TABLE ALIGN="CENTER" CELLPADDING="0" WIDTH="100%">
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<TR VALIGN="MIDDLE"><TD NOWRAP ALIGN="RIGHT"><IMG
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WIDTH="13" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img18.png"
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ALT="$\displaystyle {\dot x}$"></TD>
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<TD ALIGN="CENTER" NOWRAP><IMG
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WIDTH="16" HEIGHT="28" ALIGN="MIDDLE" BORDER="0"
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SRC="img19.png"
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ALT="$\textstyle =$"></TD>
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<TD ALIGN="LEFT" NOWRAP><IMG
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WIDTH="66" HEIGHT="28" ALIGN="MIDDLE" BORDER="0"
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SRC="img20.png"
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ALT="$\displaystyle \alpha x - \omega y,$"></TD>
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<TD WIDTH=10 ALIGN="RIGHT">
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</TD></TR>
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<TR VALIGN="MIDDLE"><TD NOWRAP ALIGN="RIGHT"><IMG
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WIDTH="12" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img21.png"
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ALT="$\displaystyle {\dot y}$"></TD>
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<TD ALIGN="CENTER" NOWRAP><IMG
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WIDTH="16" HEIGHT="28" ALIGN="MIDDLE" BORDER="0"
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SRC="img19.png"
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ALT="$\textstyle =$"></TD>
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<TD ALIGN="LEFT" NOWRAP><IMG
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WIDTH="66" HEIGHT="28" ALIGN="MIDDLE" BORDER="0"
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SRC="img22.png"
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ALT="$\displaystyle \alpha y + \omega x,$"></TD>
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<TD WIDTH=10 ALIGN="RIGHT">
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</TD></TR>
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<TR VALIGN="MIDDLE"><TD NOWRAP ALIGN="RIGHT"><IMG
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WIDTH="12" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img23.png"
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ALT="$\displaystyle {\dot z}$"></TD>
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<TD ALIGN="CENTER" NOWRAP><IMG
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WIDTH="16" HEIGHT="28" ALIGN="MIDDLE" BORDER="0"
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SRC="img19.png"
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ALT="$\textstyle =$"></TD>
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<TD ALIGN="LEFT" NOWRAP><IMG
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WIDTH="304" HEIGHT="56" ALIGN="MIDDLE" BORDER="0"
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SRC="img24.png"
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ALT="$\displaystyle - \!\!\!\!\!\! \sum_{i \in \{P,Q,R,S,T\}} \!\!\!\!\!\!
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a_i \Delta \theta_i
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\exp(-\Delta \theta_i^2 / 2 b_i^2) - (z - z_0),$"></TD>
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<TD WIDTH=10 ALIGN="RIGHT">
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(1)</TD></TR>
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</TABLE></DIV>
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<BR CLEAR="ALL"><P></P>
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where <!-- MATH
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$\alpha = 1 - \sqrt{x^2 + y^2}$
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-->
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<IMG
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WIDTH="130" HEIGHT="38" ALIGN="MIDDLE" BORDER="0"
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SRC="img25.png"
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ALT="$\alpha = 1 - \sqrt{x^2 + y^2}$">,
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<!-- MATH
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$\Delta \theta_i = (\theta - \theta_i) \ {\rm mod} \ 2 \pi$
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-->
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<IMG
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WIDTH="163" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
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SRC="img26.png"
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ALT="$\Delta \theta_i = (\theta - \theta_i) \ {\rm mod} \ 2 \pi$">,
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<!-- MATH
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$\theta = {\rm atan2}(y,x)$
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-->
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<IMG
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WIDTH="109" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
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SRC="img27.png"
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ALT="$\theta = {\rm atan2}(y,x)$"> and <IMG
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WIDTH="15" HEIGHT="14" ALIGN="BOTTOM" BORDER="0"
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SRC="img28.png"
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ALT="$\omega$"> is the angular velocity
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of the trajectory as it moves around the limit cycle.
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Baseline wander was introduced by coupling the baseline value <IMG
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WIDTH="19" HEIGHT="28" ALIGN="MIDDLE" BORDER="0"
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SRC="img29.png"
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ALT="$z_0$">
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in (<A HREF="node4.html#e:pqrst">1</A>) to the respiratory frequency <IMG
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WIDTH="19" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img30.png"
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ALT="$f_2$"> using
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<BR>
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<DIV ALIGN="RIGHT">
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<!-- MATH
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\begin{equation}
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z_0(t) = A \sin(2 \pi f_2 t),
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\end{equation}
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-->
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<TABLE WIDTH="100%" ALIGN="CENTER">
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<TR VALIGN="MIDDLE"><TD ALIGN="CENTER" NOWRAP><A NAME="e:baseline"></A><IMG
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WIDTH="142" HEIGHT="28" BORDER="0"
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SRC="img31.png"
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ALT="\begin{displaymath}
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z_0(t) = A \sin(2 \pi f_2 t),
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\end{displaymath}"></TD>
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<TD WIDTH=10 ALIGN="RIGHT">
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(2)</TD></TR>
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</TABLE>
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<BR CLEAR="ALL"></DIV><P></P>
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where <IMG
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WIDTH="66" HEIGHT="15" ALIGN="BOTTOM" BORDER="0"
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SRC="img32.png"
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ALT="$A = 0.15$"> mV.
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These equations of motion given by (<A HREF="node4.html#e:pqrst">1</A>) were integrated
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numerically using a fourth order
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Runge-Kutta method [<A
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HREF="node8.html#press92">15</A>] with a fixed time step <!-- MATH
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$\Delta t = 1/f_s$
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-->
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<IMG
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WIDTH="75" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
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SRC="img33.png"
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ALT="$\Delta t = 1/f_s$">
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where <IMG
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WIDTH="19" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img34.png"
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ALT="$f_s$"> is the sampling frequency.
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Visual analysis of a section of typical ECG from a normal subject
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was used to suggest suitable times (and therefore angles <IMG
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WIDTH="17" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img35.png"
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ALT="$\theta_i$">)
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and values of <IMG
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WIDTH="18" HEIGHT="28" ALIGN="MIDDLE" BORDER="0"
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SRC="img36.png"
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ALT="$a_i$"> and <IMG
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WIDTH="16" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img37.png"
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ALT="$b_i$"> for the PQRST points.
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The times and angles are specified relative to
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the position of the R-peak as shown in Table <A HREF="node4.html#t:pqrst">I</A>.
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A trajectory generated by equation (<A HREF="node4.html#e:pqrst">1</A>) in three-dimensions
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corresponding to <IMG
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WIDTH="56" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
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SRC="img1.png"
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ALT="$(x,y,z)$"> is illustrated in Fig. <A HREF="node4.html#f:pqrst3d">2</A>.
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This demonstrates how the
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positions of the events <IMG
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WIDTH="89" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img38.png"
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ALT="$P,Q,R,S,T$"> act on the trajectory in the
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<IMG
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WIDTH="12" HEIGHT="14" ALIGN="BOTTOM" BORDER="0"
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SRC="img12.png"
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ALT="$z$">-direction as it precesses around the unit circle in the <IMG
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WIDTH="41" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
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SRC="img11.png"
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ALT="$(x,y)$">-plane.
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The <IMG
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WIDTH="12" HEIGHT="14" ALIGN="BOTTOM" BORDER="0"
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SRC="img12.png"
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ALT="$z$"> variable from the three-dimensional system (<A HREF="node4.html#e:pqrst">1</A>)
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yields a synthetic ECG with realistic PQRST morphology
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(Fig. <A HREF="node4.html#f:pqrstcomplex">3</A>). The similarity between the synthetic
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ECG and the real ECG may be seen by comparing Fig. <A HREF="node4.html#f:pqrstcomplex">3</A>
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with Fig. <A HREF="node1.html#f:garipqrst">1</A>. Note that noise has not been added
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to the model at this point.
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<BR><P></P>
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<DIV ALIGN="CENTER">
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<DIV ALIGN="CENTER">
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<A NAME="286"></A>
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<TABLE CELLPADDING=3 BORDER="1">
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<CAPTION><STRONG>Table I:</STRONG>
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Parameters of the ECG model given by (<A HREF="node4.html#e:pqrst">1</A>)</CAPTION>
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<TR><TD ALIGN="LEFT">Index (i)</TD>
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<TD ALIGN="LEFT">P</TD>
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<TD ALIGN="LEFT">Q</TD>
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<TD ALIGN="LEFT">R</TD>
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<TD ALIGN="LEFT">S</TD>
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<TD ALIGN="LEFT">T</TD>
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</TR>
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<TR><TD ALIGN="LEFT">Time (secs)</TD>
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<TD ALIGN="LEFT">-0.2</TD>
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<TD ALIGN="LEFT">-0.05</TD>
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<TD ALIGN="LEFT">0</TD>
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<TD ALIGN="LEFT">0.05</TD>
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<TD ALIGN="LEFT">0.3</TD>
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</TR>
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<TR><TD ALIGN="LEFT"><IMG
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WIDTH="17" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img35.png"
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ALT="$\theta_i$"> (radians)</TD>
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<TD ALIGN="LEFT"><!-- MATH
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$-\frac{1}{3}\pi$
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-->
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<IMG
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WIDTH="36" HEIGHT="34" ALIGN="MIDDLE" BORDER="0"
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SRC="img39.png"
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ALT="$-\frac{1}{3}\pi$"></TD>
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<TD ALIGN="LEFT"><!-- MATH
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$-\frac{1}{12}\pi$
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-->
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<IMG
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WIDTH="43" HEIGHT="34" ALIGN="MIDDLE" BORDER="0"
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SRC="img40.png"
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ALT="$-\frac{1}{12}\pi$"></TD>
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<TD ALIGN="LEFT">0</TD>
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<TD ALIGN="LEFT"><!-- MATH
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$\frac{1}{12}\pi$
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-->
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<IMG
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WIDTH="30" HEIGHT="34" ALIGN="MIDDLE" BORDER="0"
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SRC="img41.png"
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ALT="$\frac{1}{12}\pi$"></TD>
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<TD ALIGN="LEFT"><!-- MATH
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$\frac{1}{2}\pi$
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-->
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<IMG
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WIDTH="24" HEIGHT="34" ALIGN="MIDDLE" BORDER="0"
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SRC="img42.png"
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ALT="$\frac{1}{2}\pi$"></TD>
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</TR>
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<TR><TD ALIGN="LEFT"><IMG
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WIDTH="18" HEIGHT="28" ALIGN="MIDDLE" BORDER="0"
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SRC="img36.png"
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ALT="$a_i$"></TD>
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<TD ALIGN="LEFT">1.2</TD>
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<TD ALIGN="LEFT">-5.0</TD>
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<TD ALIGN="LEFT">30.0</TD>
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<TD ALIGN="LEFT">-7.5</TD>
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<TD ALIGN="LEFT">0.75</TD>
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</TR>
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<TR><TD ALIGN="LEFT"><IMG
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WIDTH="16" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
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SRC="img37.png"
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ALT="$b_i$"></TD>
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<TD ALIGN="LEFT">0.25</TD>
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<TD ALIGN="LEFT">0.1</TD>
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<TD ALIGN="LEFT">0.1</TD>
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<TD ALIGN="LEFT">0.1</TD>
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<TD ALIGN="LEFT">0.4</TD>
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</TR>
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</TABLE>
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<A NAME="t:pqrst"></A>
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</DIV>
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</DIV>
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<BR>
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<DIV ALIGN="CENTER"><A NAME="f:pqrst3d"></A><A NAME="288"></A>
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<TABLE>
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<CAPTION ALIGN="BOTTOM"><STRONG>Figure 2:</STRONG>
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A typical trajectory generated by the dynamical model
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(<A HREF="node4.html#e:pqrst">1</A>) in the three-dimensional space given by <IMG
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WIDTH="56" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
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SRC="img1.png"
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ALT="$(x,y,z)$">. The dashed
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line reflects the limit cycle of unit radius while the small circles show the
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positions of the P,Q,R,S,T events.</CAPTION>
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<TR><TD><IMG
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WIDTH="351" HEIGHT="271" BORDER="0"
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SRC="img43.png"
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ALT="\begin{figure}
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\centerline{\psfig{file=pqrst3d.eps,width=7.75cm}}
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\end{figure}"></TD></TR>
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</TABLE>
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</DIV>
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<DIV ALIGN="CENTER"><A NAME="f:pqrstcomplex"></A><A NAME="128"></A>
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<TABLE>
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<CAPTION ALIGN="BOTTOM"><STRONG>Figure 3:</STRONG>
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Morphology of one PQRST-complex of the ECG.</CAPTION>
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<TR><TD><IMG
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WIDTH="352" HEIGHT="275" BORDER="0"
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SRC="img44.png"
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ALT="\begin{figure}
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\centerline{\psfig{file=pqrstcomplex.eps,width=7.75cm}}
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\end{figure}"></TD></TR>
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</TABLE>
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</DIV>
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By contrasting the dynamical model (<A HREF="node4.html#e:pqrst">1</A>) with the mechanisms
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underlying the cardiac cycle, it is obvious that the time required to
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complete one lap of the limit cycle is equal to the RR-interval
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of the synthetic ECG signal. Variations in the length of the RR-intervals
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can be incorporated by varying the angular velocity <IMG
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WIDTH="15" HEIGHT="14" ALIGN="BOTTOM" BORDER="0"
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SRC="img28.png"
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ALT="$\omega$">.
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The effects of both RSA and Mayer waves in the power spectrum
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<IMG
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WIDTH="37" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
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SRC="img2.png"
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ALT="$S(f)$"> of the RR-intervals are incorporated
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by generating RR-intervals which have a bimodal power spectrum
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consisting of the sum of two Gaussian distributions,
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<BR>
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<DIV ALIGN="RIGHT">
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<!-- MATH
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\begin{equation}
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S(f) = \frac{\sigma_1^2}{\sqrt{2 \pi c_1^2}}
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\exp \left( \frac{(f - f_1)^2}{2 c_1^2} \right)
|
|
+ \frac{\sigma_2^2}{\sqrt{2 \pi c_2^2}}
|
|
\exp \left( \frac{(f - f_2)^2}{2 c_2^2} \right),
|
|
\end{equation}
|
|
-->
|
|
<TABLE WIDTH="100%" ALIGN="CENTER">
|
|
<TR VALIGN="MIDDLE"><TD ALIGN="CENTER" NOWRAP><A NAME="e:Sf"></A><IMG
|
|
WIDTH="423" HEIGHT="48" BORDER="0"
|
|
SRC="img45.png"
|
|
ALT="\begin{displaymath}
|
|
S(f) = \frac{\sigma_1^2}{\sqrt{2 \pi c_1^2}}
|
|
\exp \left( ...
|
|
...c_2^2}}
|
|
\exp \left( \frac{(f - f_2)^2}{2 c_2^2} \right),
|
|
\end{displaymath}"></TD>
|
|
<TD WIDTH=10 ALIGN="RIGHT">
|
|
(3)</TD></TR>
|
|
</TABLE>
|
|
<BR CLEAR="ALL"></DIV><P></P>
|
|
with means <IMG
|
|
WIDTH="41" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img46.png"
|
|
ALT="$f_1,f_2$"> and standard
|
|
deviations <IMG
|
|
WIDTH="39" HEIGHT="28" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img47.png"
|
|
ALT="$c_1,c_2$">. Power in the LF and HF bands are given by
|
|
<IMG
|
|
WIDTH="21" HEIGHT="33" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img48.png"
|
|
ALT="$\sigma_1^2$"> and <IMG
|
|
WIDTH="21" HEIGHT="33" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img49.png"
|
|
ALT="$\sigma_2^2$"> respectively whereas the variance
|
|
equals the total area <!-- MATH
|
|
$\sigma^2 = \sigma^2_1+\sigma^2_2$
|
|
-->
|
|
<IMG
|
|
WIDTH="95" HEIGHT="33" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img50.png"
|
|
ALT="$\sigma^2 = \sigma^2_1+\sigma^2_2$">,
|
|
yielding an LF/HF ratio of <!-- MATH
|
|
$\sigma^2_1/\sigma^2_2$
|
|
-->
|
|
<IMG
|
|
WIDTH="46" HEIGHT="33" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img51.png"
|
|
ALT="$\sigma^2_1/\sigma^2_2$">.
|
|
Fig. <A HREF="node4.html#f:Sf">4</A> shows the power spectrum <IMG
|
|
WIDTH="37" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img2.png"
|
|
ALT="$S(f)$"> given
|
|
by <IMG
|
|
WIDTH="61" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img52.png"
|
|
ALT="$f_1 = 0.1$">,
|
|
<IMG
|
|
WIDTH="69" HEIGHT="29" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img53.png"
|
|
ALT="$f_2 = 0.25$">, <IMG
|
|
WIDTH="68" HEIGHT="28" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img54.png"
|
|
ALT="$c_1 = 0.01$">, <IMG
|
|
WIDTH="68" HEIGHT="28" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img55.png"
|
|
ALT="$c_2 = 0.01$"> and <!-- MATH
|
|
$\sigma^2_1/\sigma^2_2 = 0.5$
|
|
-->
|
|
<IMG
|
|
WIDTH="87" HEIGHT="33" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img56.png"
|
|
ALT="$\sigma^2_1/\sigma^2_2 = 0.5$">.
|
|
The Gaussian frequency distribution is motivated by the
|
|
typical power spectrum of a real RR tachogram [<A
|
|
HREF="node8.html#malik95">7</A>].
|
|
|
|
<DIV ALIGN="CENTER"><A NAME="f:Sf"></A><A NAME="145"></A>
|
|
<TABLE>
|
|
<CAPTION ALIGN="BOTTOM"><STRONG>Figure 4:</STRONG>
|
|
Power spectrum <IMG
|
|
WIDTH="37" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img2.png"
|
|
ALT="$S(f)$"> of the RR-interval process
|
|
with a LF/HF ratio of <!-- MATH
|
|
$\sigma_1^2/\sigma_2^2 = 0.5$
|
|
-->
|
|
<IMG
|
|
WIDTH="87" HEIGHT="33" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img3.png"
|
|
ALT="$\sigma _1^2/\sigma _2^2 = 0.5$">.</CAPTION>
|
|
<TR><TD><IMG
|
|
WIDTH="352" HEIGHT="275" BORDER="0"
|
|
SRC="img57.png"
|
|
ALT="\begin{figure}
|
|
\centerline{\psfig{file=Sf.eps,width=7.75cm}}
|
|
\end{figure}"></TD></TR>
|
|
</TABLE>
|
|
</DIV>
|
|
A RR-interval time series <IMG
|
|
WIDTH="34" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img58.png"
|
|
ALT="$T(t)$"> with power spectrum <IMG
|
|
WIDTH="37" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img2.png"
|
|
ALT="$S(f)$"> is generated by
|
|
taking the inverse Fourier transform of a sequence of complex numbers with
|
|
amplitudes <IMG
|
|
WIDTH="53" HEIGHT="37" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img59.png"
|
|
ALT="$\sqrt{S(f)}$"> and phases which are randomly
|
|
distributed between 0 and <IMG
|
|
WIDTH="22" HEIGHT="14" ALIGN="BOTTOM" BORDER="0"
|
|
SRC="img60.png"
|
|
ALT="$2 \pi$">.
|
|
By multiplying this time series by an appropriate
|
|
scaling constant and adding an offset value, the resulting time series can be
|
|
given any required mean and standard deviation.
|
|
Suppose that <IMG
|
|
WIDTH="34" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img58.png"
|
|
ALT="$T(t)$"> represents the time series generated by the RR-process
|
|
with power spectrum <IMG
|
|
WIDTH="37" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img2.png"
|
|
ALT="$S(f)$">. The time-dependent
|
|
angular velocity <IMG
|
|
WIDTH="33" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img61.png"
|
|
ALT="$\omega(t)$"> of motion around the limit cycle is then given
|
|
by
|
|
<BR>
|
|
<DIV ALIGN="RIGHT">
|
|
|
|
<!-- MATH
|
|
\begin{equation}
|
|
\omega(t) = \frac{2 \pi}{T(t)}.
|
|
\end{equation}
|
|
-->
|
|
<TABLE WIDTH="100%" ALIGN="CENTER">
|
|
<TR VALIGN="MIDDLE"><TD ALIGN="CENTER" NOWRAP><IMG
|
|
WIDTH="88" HEIGHT="42" BORDER="0"
|
|
SRC="img62.png"
|
|
ALT="\begin{displaymath}
|
|
\omega(t) = \frac{2 \pi}{T(t)}.
|
|
\end{displaymath}"></TD>
|
|
<TD WIDTH=10 ALIGN="RIGHT">
|
|
(4)</TD></TR>
|
|
</TABLE>
|
|
<BR CLEAR="ALL"></DIV><P></P>
|
|
In this way the series of RR-intervals of the resultant
|
|
synthetic ECG will also have a power spectrum equal to <IMG
|
|
WIDTH="37" HEIGHT="31" ALIGN="MIDDLE" BORDER="0"
|
|
SRC="img2.png"
|
|
ALT="$S(f)$">; this will be
|
|
demonstrated in the next section.
|
|
|
|
<HR>
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<B> Next:</B> <A NAME="tex2html66"
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HREF="index.shtml">A dynamical model for</A>
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<B> Previous:</B> <A NAME="tex2html58"
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HREF="node3.html">Heart rate variability</A>
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<ADDRESS>
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2003-10-08
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</ADDRESS>
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