# US 12,201,405 B2 · Assessing effectiveness of CPR

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- Number: US 12,201,405 B2
- Document ID: US12201405B2
- Status: Granted
- Kind: B2
- Application number: 14/885,891
- Filed: 2015-10-16
- Published: 2016-02-11
- Granted: 2025-01-21
- Earliest claimed: 2008-10-29
- Assignees: Flashback Technologies, Inc.; The Regents of the University of Colorado, a body corporate
- Applicants: Flashback Technologies, Inc.; The Regents of the University of Colorado, a body corporate
- Inventors: Isobel Jane Mulligan; Gregory Zlatko Grudic; Steven L. Moulton
- Web page: https://patentgrep.com/patent/US12201405B2

## CPC

- A61B 5/02042: {Determining blood loss or bleeding, e.g. during a surgical procedure}
- A61B 5/02028: {Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction}
- A61B 5/0205: Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
- A61B 5/02108: {from analysis of pulse wave characteristics}
- A61B 5/318: Heart-related electrical modalities, e.g. electrocardiography [ECG]
- A61B 5/4848: {Monitoring or testing the effects of treatment, e.g. of medication}
- A61B 5/4875: {Hydration status, fluid retention of the body}
- A61B 5/7275: {Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor}
- A61H 31/00: Artificial respiration by a force applied to the chest; Heart stimulation, e.g. heart massage (applying electric currents by contact electrodes for stimulation, e.g. heart pace-makers, A61N1/36 {; teaching or training models, demonstration models for medical purposes G09B23/288})
- G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems
- G16H 50/50: for simulation or modelling of medical disorders
- A61B 5/002: {Monitoring the patient using a local or closed circuit, e.g. in a room or building (A61B5/0017 takes precedence)}
- A61B 5/02241: {of small dimensions, e.g. adapted to fingers}
- A61B 5/029: Measuring blood output from the heart, e.g. minute volume
- A61B 5/031: {Intracranial pressure}
- A61B 5/14551: {for measuring blood gases}
- A61B 5/4836: {Diagnosis combined with treatment in closed-loop systems or methods (A61B5/0036 takes precedence)}
- A61B 5/6826: {Finger}
- A61B 5/7246: {using correlation, e.g. template matching or determination of similarity}
- A61B 5/7267: {involving training the classification device}
- A61B 5/742: {using visual displays (displays for heart-related electrical signals, e.g. ECG, A61B5/339)}
- A61B 7/04: Electric stethoscopes
- A61B 2562/0219: Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
- A61M 1/1613: {Profiling or modelling of patient or predicted treatment evolution or outcome}
- G16H 40/20: for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
- G16H 40/63: for local operation
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- A61H: PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY (electrotherapy, magnetotherapy, radiation therapy or ultrasound therapy A61N)
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- A61M: DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY (introducing media into or onto the bodies of animals A61D7/00; means for inserting tampons A61F13/26; devices for administering food or medicines orally A61J; containers for collecting, storing or administering blood or medical fluids A61J1/05); DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY (surgery A61B; chemical aspects of surgical articles A61L); DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR {(Electrotherapy, e.g. producing anaesthesia by the use of alternating or intermittent currents A61N1/36021)}

## Abstract

Novel tools and techniques are provided for assessing, predicting and/or effectiveness of cardiopulmonary resuscitation (“CPR”), in some cases, noninvasively. In various embodiments, tools and techniques are provided for implementing rapid estimation of a patient's compensatory reserve index (“CRI”) before, during, and after CPR is performed, and using the CRI and variations in CRI values to determine, in some instances, in real-time, the effectiveness of CPR that is performed.

## Claims

### Claim 1

A method for non-invasively determining the effectiveness of cardiopulmonary resuscitation (CPR) on a patient, comprising:
retrieving, by one or more computer systems, physiological data of the patient from one or more sensors monitoring the patient during CPR, wherein the physiological data is waveform data;
transforming, by one or more computer systems, the physiological data from waveform data to one or more patient compensatory serve index (“CRI”) values thereby transforming the waveform data to a numerical value, wherein transforming the physiological data to the one or more patient CRI values includes:
accessing a data store and acquiring a plurality of reference waveforms from a model, wherein each waveform of the plurality of reference waveforms corresponds to a respective CRI value determined from a ratio of intravascular volume loss at time t and intravascular volume loss at hemodynamic decompensation;
comparing the patient waveform data against the plurality of reference waveforms of the model;
determining a similarity between patient waveform data and the plurality of reference waveforms of the model individually; and
determining the one or more patient CRI values that corresponds to the patient waveform data based at least in part on respective similarities of the patient waveform data to each of the plurality of reference waveforms of the model;
based at least in part on the one or more patient CRI values, estimating, by one or more computer systems, an effectiveness of CPR on the patient, wherein the one or more patient CRI values are compared against a CRI model configured to relate changes in CRI values to the effectiveness of CPR on the patient; and
displaying, by one or more computer systems, the effectiveness of CPR on the patient on a user interface.

### Claim 2 (depends on 1)

The method of claim 1, wherein the one or more patient CRI values are estimated based on physiological data that are at least one of received before, received during, or received after CPR.

### Claim 3 (depends on 1)

The method of claim 1, wherein the one or more patient CRI values comprise a plurality of patient CRI values, and wherein estimating effectiveness of a CPR procedure on the patient further is based at least in part on an average value of CRI over a time period or a standard deviation of at least some of the plurality of patient CRI values, a skewness of at least some of the plurality of patient CRI values, a rate of change of at least two of the plurality of patient CRI values, or a difference between two of the plurality of values of CRI.

### Claim 4 (depends on 1)

The method of claim 1, wherein the effectiveness of CPR on the patient is displayed as a number on a scale from 0 to 100.

### Claim 5 (depends on 1)

The method of claim 1, wherein the plurality of reference waveforms of the model correspond to a state of hemodynamic decompensation or near hemodynamic decompensation, or a series of states progressing towards hemodynamic decompensation.

### Claim 6 (depends on 1)

The method of claim 1, wherein determining the similarity further comprises:
producing, for each respective patient waveform of the patient waveform data, a respective similarity coefficient representing a similarity between a respective patient waveform and each of the plurality of reference waveforms of the model;
normalizing the produced, respective similarity coefficients;
summing each respective value of CRI, corresponding to each of the plurality of reference waveforms of the model, respectively weighted by the normalized respective similarity coefficient; and
determining an estimated CRI value for the patient based on the summed, weighted CRI values.

### Claim 7 (depends on 1)

The method of claim 1, wherein at least one of the one or more sensors is selected from the group consisting of a blood pressure sensor, an intracranial pressure monitor, a central venous pressure monitoring catheter, an arterial catheter, an electroencephalograph, a cardiac monitor, a transcranial Doppler sensor, a transthoracic impedance plethysmograph, a pulse oximeter, a near infrared spectrometer, a ventilator, an accelerometer, and an electronic stethoscope.

### Claim 8 (depends on 1)

The method of claim 1, wherein the physiological data comprises data representing blood pressure waveforms, plethysmograph waveforms, or photoplethysmograph (PPG) waveforms.

### Claim 9 (depends on 1)

The method of claim 1, wherein the plurality of reference waveforms are generated by inducing a test subject to enter one or more physiological states, and obtaining physiological data from the test subject while the test subject is in a respective physiological state of the one or more physiological states.

### Claim 10 (depends on 9)

The method of claim 9, further comprising:
inducing a physiological state of reduced circulatory system volume in the test subject.

### Claim 11 (depends on 10)

The method of claim 10, wherein inducing the physiological state comprises subjecting the test subject to lower body negative pressure (“LBNP”).

### Claim 12 (depends on 11)

The method of claim 11, wherein inducing the physiological state comprises subjecting the test subject to dehydration.

### Claim 13 (depends on 9)

The method of claim 9, wherein the one or more physiological states comprises a state of cardiovascular collapse or near-cardiovascular collapse.

### Claim 14 (depends on 9)

The method of claim 9, wherein the one or more physiological states comprises a state of euvolemia.

### Claim 15 (depends on 9)

The method of claim 9, wherein the one or more physiological states comprises a state of hypervolemia.

### Claim 16 (depends on 9)

The method of claim 9, wherein the one or more physiological states comprises a state of dehydration or hypovolemia.

### Claim 17 (depends on 9)

The method of claim 9, further comprising correlating the physiological data of the test subject to the respective physiological state, wherein correlating the physiological data of the test subject with the respective physiological state of the test subject further comprises:
identifying a most predictive set of signals Sk out of a set of signals s1, S2, . . . , SD for each of one or more outcomes ok, wherein the most-predictive set of signals Sk corresponds to a first data set representing a first physiological parameter of the physiological data of the test subject, and wherein each of the one or more outcomes ok represents a physiological state measurement of the one or more physiological states respectively;
autonomously learning a set of probabilistic predictive models ôk=Mk(Sk), where ôk is a prediction of outcome ok derived from a model Mk that uses as inputs values obtained from the set of signals Sk; and
repeating the operation of autonomously learning incrementally from data that contains examples of values of signals s1, s2, . . . , sD and corresponding outcomes o1, o2, . . . , oK.

### Claim 18 (depends on 1)

The method of claim 1, wherein the effectiveness of CPR on the patient is displayed as a qualitative indicator.

### Claim 19 (depends on 1)

The method of claim 1, further including outputting instructions to control a therapeutic device.

### Claim 20

A system for non-invasively assessing the health of a patient, comprising:
one or more sensors to obtain physiological data from the patient; and
a computer system in communication with the one or more sensors, the computer system comprising:
one or more processors; and
a non-transitory computer readable medium in communication with the one or more processors, the computer readable medium having encoded thereon a set of instructions executable by the one or more processors to cause the computer system to:
retrieve physiological data of the patient from one or more sensors monitoring the patient, wherein the physiological data is waveform data;
transform the physiological data from waveform data to one or more patient compensatory reserve index (“CRI”) values thereby transforming the waveform data to a numerical value, wherein transforming the physiological data to the one or more patient CRI values includes:
accessing a data store and acquiring a plurality of reference waveforms from a model, wherein each waveform of the plurality of reference waveforms corresponds to a respective CRI value determined from a ratio of intravascular volume loss at time t and intravascular volume loss at hemodynamic decompensation;
comparing the patient waveform data against the plurality of reference waveforms of the model;
determining a similarity between patient waveform data and the plurality of reference waveforms of the model individually; and
determining the one or more patient CRI values that corresponds to the patient waveform data based at least in part on respective similarities of the patient waveform data to each of the plurality of reference waveforms of the model;
based at least in part on the one or more patient CRI values, estimate the health of the patient, wherein the one or more patient CRI values are compared against a CRI model configured to relate changes in CRI values to the health of the patient; and
display the health of the patient on a user interface.

### Claim 21 (depends on 20)

The system of claim 20, wherein the one or more patient CRI values are estimated based on physiological data that are at least one of received before, received during, or received after CPR.

### Claim 22 (depends on 20)

The system of claim 20, wherein the one or more patient CRI values comprise a plurality of patient CRI values, and wherein estimating effectiveness of a CPR procedure on the patient further is based at least in part on an average value of CRI over a time period or a standard deviation of at least some of the plurality of patient CRI values, a skewness of at least some of the plurality of patient CRI values, a rate of change of at least two of the plurality of patient CRI values, or a difference between two of the plurality of values of CRI.

### Claim 23 (depends on 20)

The system of claim 20, further including displaying the effectiveness of CPR on the patient as a number on a scale from 0 to 100.

### Claim 24 (depends on 20)

The system of claim 20, wherein the plurality of reference waveforms of the model correspond to a state of hemodynamic decompensation or near hemodynamic decompensation, or a series of states progressing towards hemodynamic decompensation.

### Claim 25 (depends on 20)

The system of claim 20, wherein determining the similarity between patient waveform data and the plurality of reference waveforms of the model further comprises:
producing, for each respective patient waveform of the patient waveform data, a respective similarity coefficient representing the similarity between a respective patient waveform and each of the plurality of reference waveforms of the model;
normalizing the produced, respective similarity coefficients;
summing each respective value of CRI, corresponding to each of the plurality of reference waveforms of the model, respectively weighted by the normalized respective similarity coefficient; and
determining an estimated CRI value for the patient based on the summed, weighted CRI values.

### Claim 26 (depends on 20)

The system of claim 20, wherein at least one of the one or more sensors is selected from the group comprising of a blood pressure sensor, an intracranial pressure monitor, a central venous pressure monitoring catheter, an arterial catheter, an electroencephalograph, a cardiac monitor, a transcranial Doppler sensor, a transthoracic impedance plethysmograph, a pulse oximeter, a near infrared spectrometer, a ventilator, an accelerometer, and an electronic stethoscope.

### Claim 27 (depends on 20)

The system of claim 20, wherein the physiological data comprises data representing blood pressure waveforms, plethysmograph waveforms, or photoplethysmograph (PPG) waveforms.

### Claim 28 (depends on 20)

The method of claim 20, wherein the effectiveness of CPR on the patient is displayed as a qualitative indicator.

### Claim 29 (depends on 20)

The method of claim 20, further including outputting instructions to control a therapeutic device.

### Claim 30

A system for non-invasively determining the effectiveness of cardiopulmonary resuscitation (CPR) on a patient, comprising:
one or more sensors to obtain physiological data from the patient; and
a computer system in communication with the one or more sensors, the computer system comprising:
one or more processors; and
a non-transitory computer readable medium in communication with the one or more processors, the computer readable medium having encoded thereon a set of instructions executable by the one or more processors to cause the computer system to:
retrieve physiological data of the patient from one or more sensors monitoring the patient during CPR, wherein the physiological data is waveform data;
transform the physiological data from waveform data to one or more patient compensatory reserve index (“CRI”) values thereby transforming the waveform data to a numerical value, wherein transforming the physiological data to the one or more patient CRI values includes:
accessing a data store and acquiring a plurality of reference waveforms from a model, wherein each waveform of the plurality of reference waveforms corresponds to a respective CRI value determined from a ratio of intravascular volume loss at time t and intravascular volume loss at hemodynamic decompensation;
comparing the patient waveform data against the plurality of reference waveforms of the model;
determining a similarity between patient waveform data and the plurality of reference waveforms of the model individually; and
determining the one or more patient CRI values that corresponds to the patient waveform data based at least in part on respective similarities of the patient waveform data to each of the plurality of reference waveforms of the model;
based at least in part on the one or more patient CRI values, estimate an effectiveness of CPR on the patient, wherein the one or more patient CRI values are compared against a CRI model configured to relate changes in CRI values to the effectiveness of CPR on the patient; and
display the effectiveness of CPR on the patient on a user interface.

### Claim 31 (depends on 30)

The system of claim 30, wherein the one or more patient CRI values comprise a plurality of patient CRI values, and wherein estimating effectiveness of a CPR procedure on the patient further is based at least in part on an average value of CRI over a time period or a standard deviation of at least some of the plurality of patient CRI values, a skewness of at least some of the plurality of patient CRI values, a rate of change of at least two of the plurality of patient CRI values, or a difference between two of the plurality of values of CRI.

### Claim 32 (depends on 30)

The system of claim 30, wherein determining the similarity between patient waveform data and the plurality of reference waveforms of the model further comprises:
producing, for each respective patient waveform of the patient waveform data, a respective similarity coefficient representing the similarity between a respective patient waveform and each of the plurality of reference waveforms of the model;
normalizing the produced, respective similarity coefficients;
summing each respective value of CRI, corresponding to each of the plurality of reference waveforms of the model, respectively weighted by the normalized respective similarity coefficient; and
determining an estimated CRI value for the patient based on the summed, weighted CRI values.

### Claim 33 (depends on 30)

The system of claim 30, wherein at least one of the one or more sensors is selected from the group comprising of a blood pressure sensor, an intracranial pressure monitor, a central venous pressure monitoring catheter, an arterial catheter, an electroencephalograph, a cardiac monitor, a transcranial Doppler sensor, a transthoracic impedance plethysmograph, a pulse oximeter, a near infrared spectrometer, a ventilator, an accelerometer, and an electronic stethoscope.

### Claim 34 (depends on 30)

The system of claim 30, wherein the physiological data comprises data representing blood pressure waveforms, plethysmograph waveforms, or photoplethysmograph (PPG) waveforms.

### Claim 35 (depends on 1)

The method of claim 1, further including outputting a recommended treatment option based on the one or more patient CRI values.