Method for analyzing irreversible apneic coma (IAC)

• US 7,706,870 B2
• Filed: 07/10/2007
• Issued: 04/27/2010
• Est. Priority Date: 07/10/2007
• Status: Expired due to Fees

• Current Assignee: Yuan Ze University
• Original Assignee: Yuan Ze University
• Inventors: Hu, Bo-Kai, Huang, Sheng-Jean, Kao, Ming-Chien, Shieh, Jiann-Shing
• Primary Examiner(s): Layno; Carl H
• Assistant Examiner(s): Kimball; Jeremiah T
• Application Number:
  US11/775,781
• Publication Number:
  US 20090018460A1
• Time in Patent Office: 1,022 Days
• Field of Search: 600/521
• US Class Current: 600/521
• CPC Class Codes: A61B 5/364 Detecting abnormal ECG interval, e.g. extrasystoles, ectopic heartbeats
• CPC Class Codes: A61B 5/4064 Evaluating the brain A61B5/031, A61B5/369, A61B5/14553 take precedence

Abstract

An method for analyzing irreversible apneic coma (IAC) for determining the presence of irreversible apneic coma (IAC) by analyzing the heart rate variability of a brain traumatic patient, thereby providing a physician a reference index to determine whether brain death has occurred. This method includes, at first, recording an electrocardiogram (ECG) from a subject. Then, analyzing R-R interval in said electrocardiogram (ECG), and plotting said R-R interval into Poincaré plot, wherein the X coordinate in said Poincaré plot represents R-R interval(n), and n is a 1˜data number. Y coordinate in said Poincaré plot represents RR(n+1). And, finally, quantifying said Poincaré plot, and obtaining semi-major axis (SD1), semi-minor axis (SD2), and SD1/SD2 of said Poincaré plot, as well as Poincaré plot area.

Claims

1. A method of analyzing heart rate variability for the presence of irreversible apneic coma (IAC), comprising following steps:

step 1 recording electrocardiogram (ECG) from a subject using a patient monitor;

step 2 analyzing R-R interval in said electrocardiogram (ECG);

step 3 plotting said R-R interval into Poincaré

plot, wherein the X coordinate of said Poincaré

plot represents R-R interval(n), n is a 1˜

data number; and

Y coordinate of said Poincaré

plot represents RR(n+1); and

step 4 quantifying said Poincaré

plot, and obtaining semi-major axis (SD1), semi-minor axis (SD2), SD1/SD2 of said Poincaré

plot, as well as Poincaré

plot area;

wherein the semi-major axis (SD1) and semi-minor axis (SD2) of said Poincaré

plot are calculated as following;

defining a new axis as X1 and X2;

$\left[\begin{array}{c}x<br><br><br><br>1\\ x<br><br><br><br>2\end{array}\right]=\left[\begin{array}{cc}\cos <br><br><br><br>\mathrm{\theta <br><br>}& -\sin <br><br><br><br>\mathrm{\theta <br><br>}\\ \sin <br><br><br><br>\mathrm{\theta <br><br>}& \cos <br><br><br><br>\mathrm{\theta <br><br>}\end{array}\right]<br><br>\left[\begin{array}{c}{\mathrm{RR}}_n\\ {\mathrm{RR}}_{n+1}\end{array}\right]$

defining SD1 and SD2 as;

$\begin{array}{c}\begin{array}{c}\mathrm{SD}<br><br><br><br>1^2=\mathrm{Var}<br><br>\left(x_1\right)=\mathrm{Var}\left(\frac{1}{\sqrt{2}}<br><br>{\mathrm{RR}}_n-\frac{1}{\sqrt{2}}<br><br>{\mathrm{RR}}_{n+1}\right)\\ =\frac{1}{2}<br><br>\mathrm{Var}<br><br>\left({\mathrm{RR}}_n-{\mathrm{RR}}_{n+1}\right)=\frac{1}{2}<br><br>{\mathrm{SDSD}}^2\end{array}\\ \mathrm{SD}<br><br><br><br>2^2=2<br><br>{\mathrm{SDRR}}^2-\frac{1}{2}<br><br>{\mathrm{SDSD}}^2\end{array}$

wherein SDRR is the standard deviation of R-R interval and SDSD is the standard deviation of Δ

RR_n;

wherein said Poincaré

plot area is Π

×

SD1×

SD2;

wherein said R-R intervals is detected through one of method A and method B;

wherein method A is First Derivative (FD1) method, and said FD1 method comprising;

X(n);

ECG raw data;

Y(n)=−

2X(n−

2)−

X(n−

1)+X(n+1)+2X(n+2),2<

n<

1000;

wherein, for detecting the position of R wave in Y(n), a slope threshold value is defined as;

Slope threshold=0.7max[Y(n)],2<

n<

1000

whereby if Y(i)>

slope threshold, Y(i) becomes a region for comparison, and positions of each peaks is selected from Y(i), and wherein the distance between adjacent peaks is the R-R intervals;

wherein method B is an amplitude threshold plus a First Derivative method (AF2 method), said AF2 method comprising;

amplitude threshold=0.4max [X(n)],0<

n<

1000

transforming original data into Y0(n);

Y0(n)=X(n) if X(n)≧

0,0<

n<

1000

Y0(n)=−

X(n) if X(n)<

0,0<

n<

1000

and based on said amplitude threshold, obtaining Y1(n)

Y1(n)=Y0(n) if Y0(n)≧

Amplitude threshold

Y1(n)=Amplitude threshold if Y0(n)<

Amplitude threshold

Then, by conducting First Derivative, obtaining Y2(n);

Y2(n)=Y1(n+1)−

Y1(n−

1),1<

n<

2

wherein, in order to detect the position of R wave in Y2(n), a slope threshold value is defined as;

Slope threshold=0.7max[Y(n)],2<

n<

1000

whereby if Y(i)>

slope threshold, Y(i) becomes the region for comparison, and positions of each peaks is selected from Y(i), and wherein the distance between adjacent peaks is the R-R intervals;

step 5 determining a reference index from said quantification of said Poincaré

plot and providing said reference index to a physician for determining whether brain death has occurred;

wherein steps 2-5 are done using a computing device.