ECG rhythm advisory method

• US 9,642,547 B2
• Filed: 04/24/2014
• Issued: 05/09/2017
• Est. Priority Date: 05/12/2004
• Status: Active Grant

• Current Assignee: Zoll Medical Corporation (Asahi Kasei Corporation)
• Original Assignee: Zoll Medical Corporation (Asahi Kasei Corporation)
• Inventors: Tan, Qing, Freeman, Gary A., Geheb, Frederick J., Brewer, James E.
• Primary Examiner(s): KAHELIN, MICHAEL WILLIAM
• Application Number:
  US14/260,534
• Publication Number:
  US 20140236030A1
• Time in Patent Office: 1,111 Days
• CPC Class Codes: A61B 5/347 Detecting the frequency distribution of signals
• CPC Class Codes: A61B 5/361 Detecting fibrillation
• CPC Class Codes: A61B 5/363 Detecting tachycardia or bradycardia
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61H 2201/5015 using specific interfaces or standards, e.g. USB, serial, parallel
• CPC Class Codes: A61H 2230/04 Heartbeat characteristics, e.g. E.G.C., blood pressure modulation
• CPC Class Codes: A61H 31/005 with feedback for the user
• CPC Class Codes: A61N 1/39 Heart defibrillators
• CPC Class Codes: A61N 1/3904 External heart defibrillators [EHD]
• CPC Class Codes: A61N 1/39044 in combination with cardiopulmonary resuscitation [CPR] therapy
• CPC Class Codes: A61N 1/3925 Monitoring; Protecting

Abstract

A method of automatically determining which type of treatment is most appropriate for a cardiac arrest victim, the method comprising transforming one or more time domain electrocardiogram (ECG) signals into a frequency domain representation comprising a plurality of discrete frequency bands, combining the discrete frequency bands into a plurality of analysis bands, wherein there are fewer analysis bands than discrete frequency bands,

• • determining the content of the analysis bands, and determining the type of treatment based on the content of the analysis bands.

Claims

1. An apparatus for automatically determining which type of treatment is most appropriate for a cardiac arrest victim, the apparatus comprising processing circuitry configured to:

transform one or more time domain ECG signals into frequency domain data, wherein the one or more time domain ECG signals being processed are from electrodes applied externally to the cardiac arrest victim and include periods of time when cardiopulmonary resuscitation (CPR) is being delivered to the cardiac arrest victim;

process the frequency domain data to determine at least one peak;

determine a parameter set of at least two parameters characteristic of the at least one peak, wherein the parameter set is calculated at more than two points in time, and wherein a sequence of parameter sets defines a trajectory, and wherein the trajectory is analyzed using a recursive filter to predict an estimated value for the parameter set; and

determine the type of treatment based on the estimated value for the parameter set.

2. The apparatus of claim 1 wherein the processing circuitry is configured to determine a measure of a width of the at least one peak.

3. The apparatus of claim 2, wherein the processing circuitry is configured to determine the type of treatment based at least in part on the measure of the width of the at least one peak.

4. The apparatus of claim 1 wherein the recursive filter is a Kalman filter.

5. The apparatus of claim 1 wherein the analysis method involves use of a Particle Filter.

6. The apparatus of claim 1 wherein the analysis of the trajectory is used to predict defibrillation success.

7. The apparatus of claim 1 wherein the analysis of the trajectory is used to determine whether it is appropriate to defibrillate or deliver an alternative therapy such as chest compressions, drugs such as epinephrine, constitutive nutrients such as glucose, or other electrical therapy such as pacing.

8. The apparatus of claim 1 wherein a mathematical transformation is performed on the trajectory.

9. The apparatus of claim 8 wherein the mathematical transformation is a projection of the trajectory onto a plane within a parameter space based on a number of parameters in the parameter set and a number of determined peaks.

10. The apparatus of claim 9 wherein image mensuration algorithms are employed to evaluate features of the projection of the trajectory.

11. The apparatus of claim 1 wherein the processing circuitry is configured to generate analysis frequency bands based on the determined at least one peak and to quantify an energy within the analysis frequency bands.

12. The apparatus of claim 11 wherein quantifying the energy within the analysis frequency bands comprises one or more of determining at least one number characterizing an energy of a highest peak within the analysis frequency bands and determining an overall or average energy for the analysis frequency bands.

13. The apparatus of claim 11 wherein the processing circuitry is configured to analyze a variation over time corresponding to the analysis frequency bands.

14. The apparatus of claim 11 wherein the analysis frequency bands are characterized by widths of about 0.5 Hz.

15. The apparatus of claim 11 wherein the analysis frequency bands are characterized by unequal widths such that widths of the analysis frequency bands with frequencies less than 3 Hz are larger than widths of the analysis frequency bands with frequencies in a 6-12 Hz frequency range.

16. The apparatus of claim 11 wherein each analysis frequency band is composed of an aggregation of multiple spectral measurements.

17. The apparatus of claim 16 wherein characteristics of the multiple spectral measurements within each analysis frequency band include at least one of:

mean spectral energy, spectral energy variance, median spectral energy, maximum spectral energy, and minimum spectral energy.