System and method for cardiopulmonary resuscitation

• US 10,426,695 B2
• Filed: 09/08/2016
• Issued: 10/01/2019
• Est. Priority Date: 09/08/2015
• Status: Active Grant

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: Covidien LP (Medtronic Plc)
• Inventors: Addison, Paul S., Watson, James N.
• Primary Examiner(s): Fletcher, Jerry-Daryl
• Application Number:
  US15/259,668
• Publication Number:
  US 20170065484A1
• Time in Patent Office: 1,118 Days
• CPC Class Codes: A61B 2562/02 Details of sensors specially adapted for in-vivo measurements
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/0261 using optical means, e.g. infrared light
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/4848 Monitoring or testing the effects of treatment, e.g. of medication
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61H 2201/5043 Displays
• CPC Class Codes: A61H 2201/5048 Audio interfaces, e.g. voice or music controlled
• CPC Class Codes: A61H 2201/5092 Optical sensor
• CPC Class Codes: A61H 2230/04 Heartbeat characteristics, e.g. E.G.C., blood pressure modulation
• CPC Class Codes: A61H 2230/06 Heartbeat rate
• CPC Class Codes: A61H 2230/207 partial O2-value
• CPC Class Codes: A61H 2230/40 Respiratory characteristics
• CPC Class Codes: A61H 31/005 with feedback for the user
• CPC Class Codes: A61N 1/3925 Monitoring; Protecting

Abstract

A method for determining an efficacy of cardiopulmonary resuscitation (CPR) includes receiving a plethysmography signal from an oximetry sensor and an electrocardiogram (ECG) signal from an ECG sensor at a processor associated with a patient monitor, the oximetry sensor, or the ECG sensor. The method includes determining a first indicator related to the efficacy of CPR based on the plethysmography signal, using the processor. The method also includes determining a second indicator related to the efficacy of CPR based on the ECG signal, using the processor. The method further includes combining the first indicator and the second indicator to determine a combination metric indicative of the efficacy of CPR, using the processor.

Claims

1. A method for determining an efficacy of cardiopulmonary resuscitation (CPR), the method comprising, using a processor configured to determine the efficacy of CPR, wherein the processor is associated with a patient monitor, an oximetry sensor, and an electrocardiogram (ECG) sensor, and wherein determining the efficacy of CPR comprises:

receiving, at the processor, a plethysmography signal from the oximetry sensor;

receiving, at the processor, an ECG signal from the ECG sensor;

determining a first indicator related to the efficacy of CPR based on the plethysmography signal, using the processor;

determining a second indicator related to the efficacy of CPR based on the ECG signal, using the processor;

combining the first indicator and the second indicator to determine a combination metric indicative of the efficacy of CPR, using the processor; and

adjusting parameters controlling one or both of a rate or depth of compressions applied by a CPR device based on the combination metric.

2. The method of claim 1, wherein the first indicator comprises an amplitude of a non-cardiac pulse, an oxygen saturation (SpO₂), a regional oxygen saturation (rSO₂), a perfusion index, a characteristic of a baseline of the plethysmography signal, or any combination thereof, and wherein the second indicator comprises a characteristic measure of the ECG signal, a cardioversion outcome prediction (COP) metric, or any combination thereof.

3. The method of claim 1, wherein the first indicator comprises an amplitude of a non-cardiac pulse and wherein the second indicator comprises a characteristic measure of the ECG signal, a cardioversion outcome prediction (COP) metric.

4. The method of claim 3, wherein combining the first and second indicators comprises assigning weights to the first and second indicators, and wherein the COP metric is assigned a higher weight than the amplitude of the non-cardiac pulse.

5. The method of claim 1, comprising determining, using the processor, an indication of the efficacy of CPR based on the combination metric, and providing, using the processor, the indication of the efficacy of CPR on a display or via a speaker.

6. The method of claim 1, comprising determining a probability of a return of spontaneous circulation upon application of a defibrillation shock, wherein determining the probability comprises:

determining a combination cardioversion outcome prediction (COP) metric indicative of the probability based at least in part on a perfusion index derived from the plethysmography signal and a COP metric derived from the ECG signal, using the processor;

and

providing, using the processor, an indication of the probability on a display or via a speaker.

7. The method of claim 1, wherein the adjusting comprises increasing a depth or frequency of the compressions responsive to the combination metric being below a threshold.

8. The method of claim 1, wherein the adjusting comprises increasing a depth or frequency of the compressions responsive to the combination metric decreasing over time.

9. A system, comprising:

a processor associated with an oximetry sensor and an electrocardiogram (ECG) sensor, or with a patient monitor that is configured to be communicatively coupled to the oximetry sensor and the ECG sensor, wherein the processor is configured to execute instructions stored on a memory to;

determine a first indicator related to an efficacy of CPR based on a plethysmography signal generated by the oximetry sensor;

determine a second indicator related to the efficacy of CPR based on an ECG signal generated by the ECG sensor;

input the first indicator and the second indicator into a trained classifier to output a metric indicative of an efficacy of CPR;

output an indication of the efficacy of CPR based on the metric on a display or via a speaker of the patient monitor, the oximetry sensor, or the ECG sensor; and

determine a probability of a return of spontaneous circulation upon application of a defibrillation shock by determining a combination cardioversion outcome prediction (COP) metric indicative of the probability based at least in part on a perfusion index derived from the plethysmography signal and a COP metric derived from the ECG signal; and

provide an indication of the probability on a display or via a speaker, wherein the indication of the probability comprises a displayed or an audible message instructing an operator to apply the defibrillation shock responsive to a determination that the combination COP metric exceeds a threshold value.

10. The system of claim 9, wherein the first indicator comprises an amplitude of a non-cardiac pulse of the plethysmography signal, a regional oxygen saturation (rSO₂) value, an oxygen saturation value (SpO₂), a perfusion index, a baseline of the plethysmography signal, or any combination thereof.

11. The system of claim 9, wherein the second indicator comprises a characteristic measure of the ECG signal or a cardioversion outcome prediction (COP) metric.

12. The system of claim 9, wherein the first indicator comprises an amplitude of a non-cardiac pulse of the plethysmography signal and the second indicator comprises at least one of a characteristic measure of the ECG signal or a cardioversion outcome prediction (COP) metric.

13. The system of claim 9, wherein the second indicator comprises a cardioversion outcome prediction (COP) metric, and the processor is configured to assign a first weight to the COP metric and a second weight to the first indicator during determination of the efficacy of CPR, and the first weight is greater than the second weight.

14. The system of claim 9, wherein the trained classifier comprises a neural network.

15. A system, comprising:

an oximetry sensor configured to be applied to a patient and to generate a plethysmography signal;

an electrocardiogram (ECG) sensor configured to be applied to the patient and to generate an ECG signal;

a processor associated with the oximetry sensor and the ECG sensor, or with a patient monitor that is configured to be communicatively coupled to the oximetry sensor and the ECG sensor, wherein the processor is configured to execute instructions stored on a memory to;

determine a first indicator based on the plethysmography signal;

determine a second indicator based on the ECG signal;

determine an efficacy of CPR based at least in part on the first indicator and the second indicator; and

provide an indication of the efficacy of CPR on a display or via a speaker until the probability exceeds a threshold value, and to provide instructions on the display or via the speaker to stop CPR and apply a defibrillation shock if the probability exceeds the threshold value.

16. The system of claim 15, wherein the first indicator comprises an amplitude of a non-cardiac pulse, an oxygen saturation (SpO₂), a regional oxygen saturation (rSO₂), a perfusion index, a characteristic of a baseline of the plethysmography signal, or any combination thereof, and wherein the second indicator comprises a characteristic measure of the ECG signal, a cardioversion outcome prediction (COP) metric, or any combination thereof.

17. The system of claim 15, wherein the processor is configured to provide an indication of the efficacy of CPR on a display or via a speaker.

18. The system of claim 17, wherein the processor is configured to provide an audible indication, and wherein a characteristic of the audible indication varies based on the efficacy of the CPR.

19. The system of claim 15, wherein the processor is configured to determine a probability of a return of spontaneous circulation upon application of shock therapy based at least in part on the first indicator and the second indicator.