WO2025229059A1 - Resuscitation event analysis/annotations of an electrocardiogram - Google Patents
Resuscitation event analysis/annotations of an electrocardiogramInfo
- Publication number
- WO2025229059A1 WO2025229059A1 PCT/EP2025/061831 EP2025061831W WO2025229059A1 WO 2025229059 A1 WO2025229059 A1 WO 2025229059A1 EP 2025061831 W EP2025061831 W EP 2025061831W WO 2025229059 A1 WO2025229059 A1 WO 2025229059A1
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- WO
- WIPO (PCT)
- Prior art keywords
- patient
- signal associated
- ecg data
- ecg
- defibrillator
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
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Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N1/00—Electrotherapy; Circuits therefor
- A61N1/18—Applying electric currents by contact electrodes
- A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
- A61N1/38—Applying electric currents by contact electrodes alternating or intermittent currents for producing shock effects
- A61N1/39—Heart defibrillators
- A61N1/3904—External heart defibrillators [EHD]
- A61N1/39044—External heart defibrillators [EHD] in combination with cardiopulmonary resuscitation [CPR] therapy
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N1/00—Electrotherapy; Circuits therefor
- A61N1/18—Applying electric currents by contact electrodes
- A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
- A61N1/38—Applying electric currents by contact electrodes alternating or intermittent currents for producing shock effects
- A61N1/39—Heart defibrillators
- A61N1/3993—User interfaces for automatic external defibrillators
Definitions
- the present disclosure generally relates to a resuscitation of a patient.
- the present disclosure particularly relates to annotations by a defibrillator of an electrocardiogram of the patient during a resuscitation of the patient and post-resuscitation of the patient.
- Cardiopulmonary resuscitation is a lifesaving intervention that is provided when a patient is in cardiac arrest (e.g., with no or ineffective mechanical activity of the patient’s heart) and primarily consists of chest compressions often combined with ventilation.
- a defibrillator may be used during CPR to deliver a high-amplitude current impulse to the heart in order to restore normal rhythm and contractile function in a patient experiencing an arrhythmia (e.g., ventricular fibrillation (VF) and ventricular tachycardia (VT)) that is not accompanied by a palpable pulse.
- VF ventricular fibrillation
- VT ventricular tachycardia
- defibrillators there are several classes of defibrillators that are particularly useful during CPR of a patient including a monitor/defibrillator, an automatic external defibrillator, a semiautomatic external defibrillator, a manual external defibrillator, and an advanced life support defibrillator.
- the CPR/defibrillation industry is constantly striving to improve upon CPR/defibrillation technology, particularly as related to information exchanges between a responder and a defibrillator that facilitates an effective CPR application and recovery treatment of the patient, and as related to information indications of a degree of defibrillation effectiveness of the defibrillator.
- the present disclosure is directed to an analysis and annotations by a defibrillator of resuscitation events from patients suffering sudden cardiac arrest (SCA) and receiving cardiopulmonary resuscitation.
- SCA sudden cardiac arrest
- resuscitation events in accordance with the present disclosure include a diagnostic defibrillation event, a diagnostic ventilation event and a diagnostic CPR event as set forth in the present disclosure.
- the present disclosure may be embodied as (1) a defibrillator (e.g., a monitor/defibrillator, an automatic external defibrillator, a semi-automatic external defibrillator, a manual external defibrillator, and an advanced life support defibrillator) and (2) a defibrillation controller incorporated within a defibrillator or in communication with a defibrillator.
- a defibrillator e.g., a monitor/defibrillator, an automatic external defibrillator, a semi-automatic external defibrillator, a manual external defibrillator, and an advanced life support defibrillator
- a defibrillation controller incorporated within a defibrillator or in communication with a defibrillator.
- a defibrillator of the present disclosure employ an ECG generator operable to generate ECG data, and a diagnostic defibrillation module configured to analyze one or more biological signals associated with the ECG data, and to annotate the ECG data with one or more diagnostic defibrillation events indicated by the biological signal(s).
- a defibrillation controller of the present disclosure employ a non-transitory machine-readable storage medium encoded with instructions for execution by one or more processors to generate ECG data, to analyze one or more biological signals associated with the ECG data, and to annotate the ECG data with one or more diagnostic defibrillation events indicated by the biological signal(s).
- FIG. 1 illustrates an exemplary embodiment of defibrillator in accordance with the present disclosure
- FIG. 2 illustrates an exemplary annotated electrocardiogram generated by the defibrillator of FIG. 1 in accordance with the present disclosure
- FIG. 4 illustrates an exemplary annotated electrocardiogram generated by the defibrillator of FIG. 3 in accordance with the present disclosure
- FIG. 5 illustrates an exemplary embodiment of a defibrillation controller in accordance with the present disclosure.
- FIG. 1-5 teaches exemplary embodiments of defibrillators and defibrillation controllers in accordance with the present disclosure. From the following description of FIGS. 1-5, those having ordinary skill in the art of the present disclosure will appreciate how to apply the present disclosure to make and use additional embodiments of defibrillators and defibrillation controllers in accordance with the present disclosure.
- an exemplary defibrillator 10 of the present disclosure incorporates an ECG generator 20 for generating ECG data/display during and after CPR as known in the art of the present disclosure or hereinafter conceived, and further incorporates resuscitation event modules 30 for annotating generated ECG data with resuscitation events in accordance with the present disclosure.
- Non-limiting examples of patient cardiac data 40 includes ECG lead signals, monitoring electrode signals, and photoplethysmography (PPG) signals as known in the art of the present disclosure or hereinafter conceived.
- ECG lead signals monitoring electrode signals
- PPG photoplethysmography
- Non-limiting examples of patient respiratory data 50 includes capnography signals and ventilation signals as known in the art of the present disclosure or hereinafter conceived.
- Defibrillator 10 processes data 40, 50, 60 to ascertain resuscitation event(s) that occur during and/or after the CPR.
- diagnostic defibrillation events derived from a defibrillation process implemented by defibrillator 10 as known in the art of the present disclosure or hereinafter conceived.
- diagnostic defibrillation events include rhythm classification, a vitality of a shockable rhythm, a shockable advisory and a return of spontaneous circulation.
- a second exemplary embodiment of resuscitation events includes diagnostic ventilation events derived from a ventilation process monitored by defibrillator 10 as known in the art of the present disclosure or hereinafter conceived.
- diagnostic ventilation events include ventilation quality derived from a ventilation rate, an inhaling/exhaling speed and/or a ventilation volume.
- a third exemplary embodiment of resuscitation events includes diagnostic CPR events derived from a CPR process monitored by defibrillator 10 as known in the art of the present disclosure or hereinafter conceived.
- diagnostic CPR events include compression depth, compression rate, recoil, etc.
- FIG. 2 illustrates an example of an annotated ECG by defibrillator 10 in accordance with the present disclosure.
- the ECG occurs over a cardiac arrest/arrythmia phase 71 of the CPR and a cardiac resuscitation phase 72 of the CPR.
- cardiac arrest/arrythmia phase 71 is annotated with a beginning of CPR 31, a CPR quality 32, a detection 33 of a shockable rhythm, and shockable rhythm analysis 34.
- cardiac resuscitation phase 72 is annotated with a normal rhythm analysis 36, a return of spontaneous circulation detection 37 and a ventilation analysis 38.
- FIG. 3 illustrates an exemplary embodiment 10a of the defibrillator 10 of FIG. 1.
- defibrillator 10a employs an ECG generator not shown (e.g., ECG generator 20 of FIG. 1) and resuscitation event modules (e.g., resuscitation event modules 30 of FIG. 1) including a rhythm classification module 11, a ROCS detection module 12, a VF vitality algorithm 13, a ventilation quality algorithm 14 and a CPR quality algorithm 15.
- ECG generator 20 of FIG. 1 ECG generator 20 of FIG. 1
- resuscitation event modules e.g., resuscitation event modules 30 of FIG. 1
- rhythm classification module 11 e.g., a ROCS detection module 12
- VF vitality algorithm 13 e.g., VF vitality algorithm 13
- ventilation quality algorithm 14 e.g., a ventilation quality algorithm
- Rhythm classification module 11 processes ECG lead signals 41 to execute an algorithm for classifying a heart rhythm at any given moment of time as a shockable rhythm (e.g., VF, polymorphic VT) or a non-shockable, and then for further classifying a non-shockable rhythm into organized (including normal sinus rhythm and other ORS rhythms) or asystole.
- a shockable rhythm e.g., VF, polymorphic VT
- non-shockable rhythm e.g., VF, polymorphic VT
- the heart rate of the patient can also be detected by this algorithm.
- Rhythm classification module 11 may work during CPR and/or post-CPR.
- ROSC detection algorithm 12 processes ECG lead signals 41, impedance signals 42, PPG signals 44 and capnography signals 41 to execute an algorithm for detecting a return of spontaneous circulation (ROSC).
- ROSC detection algorithm 12 may work during CPR and/or post-CPR.
- VF vitality module 13 process ECG lead signals 41 to execute an algorithm for returning a VF vitality score which can be a predictor of shock efficacy, ROSC and survival during CPR and/or post-CPR.
- an AMS A of the ECG data may be utilized to derive a VF vitality score.
- Ventilation quality module 14 processes impedance signal 41, capnography signals 51 and ventilation sensing signals 52 to execute an algorithm for deriving ventilation quality metrics such as ventilation rate, inhaling/exhaling speed and ventilation volume, primarily post-CPR.
- CPR quality module 15 processes impedance signal 41 and common mode current signal 42 to execute an algorithm for deriving CPR quality metrices, such as compression depth, compression rate, recoil, etc.
- CPR quality metrices such as compression depth, compression rate, recoil, etc.
- U.S. Patent Application Publication US20180140857A1 hereby incorporated by reference may be implemented by CPR quality module 15.
- defibrillator 10a further employs a machine learning module 16 for utilizing the resuscitation event annotation(s) as training data and/or testing data for the ECG generator and the resuscitation modules 11-15 as would be appreciated by those having ordinary skill in the art of the present disclosure.
- the machine learning module 16 may be any type of machine learning model as known in the art of the present disclosure and hereinafter conceived.
- FIG. 4 illustrates an example of an annotated ECG by defibrillator 1 Oa in accordance with the present disclosure.
- a cardiac arrest/arrythmia phase of the ECG is annotated with a beginning of CPR 31a, a CPR quality 32a, a detection 33a of the VF rhythm, and a shockable rhythm analysis 34a.
- a cardiac resuscitation phase of the ECG is annotated with a normal rhythm analysis 36a, a return of spontaneous circulation detection 37a and a ventilation analysis 38a.
- controller 100 includes one or more processor(s) 101, memory 102, a user interface 103, a network interface 104, and a storage 105 interconnected via one or more system bus(es) 106.
- the memory 102 can include various memories, as known in the art of the present disclosure or hereinafter conceived, including, but not limited to, LI, L2, or L3 cache or system memory.
- the memory 102 can include static random access memory (SRAM), dynamic RAM (DRAM), flash memory, read only memory (ROM), or other similar memory devices.
- SRAM static random access memory
- DRAM dynamic RAM
- ROM read only memory
- the user interface 103 can include one or more devices, as known in the art of the present disclosure or hereinafter conceived, for enabling communication with a user such as an administrator.
- the user interface can include a command line interface or graphical user interface that can be presented to a remote terminal via the network interface 104.
- the network interface 104 can include one or more devices, as known in the art of the present disclosure or hereinafter conceived, for enabling communication other components of a medical device.
- the network interface 104 can include a network interface card (NIC) configured to communicate according to the Ethernet protocol.
- NIC network interface card
- the network interface 104 may implement a TCP/IP stack for communication according to the TCP/IP protocols.
- TCP/IP protocols Various alternative or additional hardware or configurations for the network interface 104 will be apparent.
- the storage 105 can include one or more machine-readable storage media, as known in the art of the present disclosure or hereinafter conceived, including, but not limited to, read-only memory (ROM), random-access memory (RAM), magnetic disk storage media, optical storage media, flash-memory devices, or similar storage media.
- ROM read-only memory
- RAM random-access memory
- magnetic disk storage media magnetic disk storage media
- optical storage media flash-memory devices
- similar storage media can store instructions for execution by the processor(s) 101 or data upon with the processor(s) 101 may operate.
- the storage 105 may store a base operating system for controlling various basic operations of the hardware.
- the storage 105 can also store an application modules in the form of executable software/firmware for implementing the principles as previously described in the present disclosure.
- storage 105 stores application modules 107 including annotation modules 108 (e.g., modules 11-15 of FIG. 3) and a machine learning module 109 (e.g., module 16 of FIG. 3).
- annotation modules 108 e.g., modules 11-15 of FIG. 3
- machine learning module 109 e.g., module 16 of FIG. 3
- controller 100 may be incorporated into or linked with a defibrillator.
- controller 100 may be in communication with ECG leads 110, monitoring electrodes 111, a PPG sensor 112, a capnography sensor 113, a ventilation sensor 114 and/or a CPR meter 115 as known in the art of the present disclosure and hereinafter conceived. From the description of FIGS. 1-5 herein, those having ordinary skill in the art will appreciate the numerous benefits of the present disclosure including, but not limited to, information exchanges between a responder and a defibrillator that facilitates an effective CPR application and recovery treatment of the patient, and information indications of a degree of defibrillation effectiveness of the defibrillator.
- features, elements, components, etc. disclosed and described in the present disclosure/specification and/or depicted in the appended Figures and/or recited in the claims can be implemented in various combinations of hardware and software, and provide functions which may be combined in a single element or multiple elements.
- the functions of the various features, elements, components, etc. shown/illustrated/depicted in the Figures and/or recited in the claims can be provided through the use of dedicated hardware as well as hardware capable of executing software in association with appropriate software.
- processor When provided by a processor, the functions can be provided by a single dedicated processor, by a single shared processor, or by a plurality of individual processors, some of which can be shared and/or multiplexed.
- explicit use of the term “processor” or “controller” should not be construed to refer exclusively to hardware capable of executing software, and can implicitly include, without limitation, digital signal processor (“DSP”) hardware, memory (e.g., read only memory (“ROM’) for storing software, random access memory (“RAM”), non-volatile storage, etc.) and virtually any means and/or machine (including hardware, software, firmware, combinations thereof, etc.) which is capable of (and/or configurable) to perform and/or control a process.
- DSP digital signal processor
- ROM read only memory
- RAM random access memory
- non-volatile storage etc.
- any flow charts, flow diagrams and the like can represent various processes which can be substantially represented in computer readable storage media and so executed by a computer, processor or other device with processing capabilities, whether or not such computer or processor is explicitly shown.
- corresponding and/or related systems incorporating and/or implementing the device or such as may be used/implemented in a device in accordance with the present disclosure are also contemplated and considered to be within the scope of the present disclosure.
- corresponding and/or related method for manufacturing and/or using a device and/or system in accordance with the present disclosure are also contemplated and considered to be within the scope of the present disclosure.
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Abstract
A defibrillator (10) employing an ECG generator (20) operable to generate ECG data, and a diagnostic defibrillation module configured to analyze one or more biological signals associated with the ECG data, and to annotate the ECG data with one or more diagnostic defibrillation events indicated by the biological signal(s).
Description
RESUSCITATION EVENT ANALYSIS/ANNOTATIONS OF AN ELECTROCARDIOGRAM
FIELD OF THE INVENTION
The present disclosure generally relates to a resuscitation of a patient. The present disclosure particularly relates to annotations by a defibrillator of an electrocardiogram of the patient during a resuscitation of the patient and post-resuscitation of the patient.
BACKGROUND OF THE INVENTION
Cardiopulmonary resuscitation (CPR) is a lifesaving intervention that is provided when a patient is in cardiac arrest (e.g., with no or ineffective mechanical activity of the patient’s heart) and primarily consists of chest compressions often combined with ventilation. A defibrillator may be used during CPR to deliver a high-amplitude current impulse to the heart in order to restore normal rhythm and contractile function in a patient experiencing an arrhythmia (e.g., ventricular fibrillation (VF) and ventricular tachycardia (VT)) that is not accompanied by a palpable pulse. There are several classes of defibrillators that are particularly useful during CPR of a patient including a monitor/defibrillator, an automatic external defibrillator, a semiautomatic external defibrillator, a manual external defibrillator, and an advanced life support defibrillator. The CPR/defibrillation industry is constantly striving to improve upon CPR/defibrillation technology, particularly as related to information exchanges between a responder and a defibrillator that facilitates an effective CPR application and recovery treatment of the patient, and as related to information indications of a degree of defibrillation effectiveness of the defibrillator.
SUMMARY OF THE INVENTION
The present disclosure is directed to an analysis and annotations by a defibrillator of resuscitation events from patients suffering sudden cardiac arrest (SCA) and receiving cardiopulmonary resuscitation. Examples of resuscitation events in accordance with the present disclosure include a diagnostic defibrillation event, a diagnostic ventilation event and a diagnostic CPR event as set forth in the present disclosure.
The present disclosure may be embodied as (1) a defibrillator (e.g., a monitor/defibrillator, an automatic external defibrillator, a semi-automatic external defibrillator,
a manual external defibrillator, and an advanced life support defibrillator) and (2) a defibrillation controller incorporated within a defibrillator or in communication with a defibrillator.
Various exemplary embodiments of a defibrillator of the present disclosure employ an ECG generator operable to generate ECG data, and a diagnostic defibrillation module configured to analyze one or more biological signals associated with the ECG data, and to annotate the ECG data with one or more diagnostic defibrillation events indicated by the biological signal(s).
Various exemplary embodiments of a defibrillation controller of the present disclosure employ a non-transitory machine-readable storage medium encoded with instructions for execution by one or more processors to generate ECG data, to analyze one or more biological signals associated with the ECG data, and to annotate the ECG data with one or more diagnostic defibrillation events indicated by the biological signal(s).
The foregoing exemplary embodiments and other embodiments of the present disclosure as well as various structures and advantages of the present disclosure will become further apparent to those having ordinary skill in the art from the following detailed description of various embodiments of the present disclosure read in conjunction with the accompanying drawings. The detailed description and drawings are merely illustrative of the present disclosure rather than limiting, the scope of the present disclosure being defined by the appended claims and equivalents thereof.
BRIEF DESCRIPTION OF THE DRAWINGS
The present disclosure will present in detail the following description of exemplary embodiments with reference to the following figures wherein:
FIG. 1 illustrates an exemplary embodiment of defibrillator in accordance with the present disclosure;
FIG. 2 illustrates an exemplary annotated electrocardiogram generated by the defibrillator of FIG. 1 in accordance with the present disclosure;
FIG. 3 illustrates an exemplary embodiment of the defibrillator of FIG. 1 in accordance with the present disclosure;
FIG. 4 illustrates an exemplary annotated electrocardiogram generated by the defibrillator of FIG. 3 in accordance with the present disclosure; and
FIG. 5 illustrates an exemplary embodiment of a defibrillation controller in accordance with the present disclosure.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
To facilitate an understanding of the present disclosure, the following description of FIG. 1-5 teaches exemplary embodiments of defibrillators and defibrillation controllers in accordance with the present disclosure. From the following description of FIGS. 1-5, those having ordinary skill in the art of the present disclosure will appreciate how to apply the present disclosure to make and use additional embodiments of defibrillators and defibrillation controllers in accordance with the present disclosure.
Referring to FIG. 1, an exemplary defibrillator 10 of the present disclosure incorporates an ECG generator 20 for generating ECG data/display during and after CPR as known in the art of the present disclosure or hereinafter conceived, and further incorporates resuscitation event modules 30 for annotating generated ECG data with resuscitation events in accordance with the present disclosure.
To this end, defibrillator 10 inputs patient cardiac data 40 for generating the ECG data, and further inputs patient cardiac data 40, patient respiratory data 50 and/or patient CPR data 60 for displaying/communicating the ECG data/display with annotations of one or more resuscitation events in accordance with the present disclosure.
Non-limiting examples of patient cardiac data 40 includes ECG lead signals, monitoring electrode signals, and photoplethysmography (PPG) signals as known in the art of the present disclosure or hereinafter conceived.
Non-limiting examples of patient respiratory data 50 includes capnography signals and ventilation signals as known in the art of the present disclosure or hereinafter conceived.
Non-limiting examples of patient CPR data 60 includes CPR quality data such as compression depth, rate and recoil as known in the art of the present disclosure or hereinafter conceived.
Defibrillator 10 processes data 40, 50, 60 to ascertain resuscitation event(s) that occur during and/or after the CPR.
One exemplary embodiment of resuscitation events includes diagnostic defibrillation events derived from a defibrillation process implemented by defibrillator 10 as known in the art
of the present disclosure or hereinafter conceived. Non-limiting examples of diagnostic defibrillation events include rhythm classification, a vitality of a shockable rhythm, a shockable advisory and a return of spontaneous circulation.
A second exemplary embodiment of resuscitation events includes diagnostic ventilation events derived from a ventilation process monitored by defibrillator 10 as known in the art of the present disclosure or hereinafter conceived. Non-limiting examples of diagnostic ventilation events include ventilation quality derived from a ventilation rate, an inhaling/exhaling speed and/or a ventilation volume.
A third exemplary embodiment of resuscitation events includes diagnostic CPR events derived from a CPR process monitored by defibrillator 10 as known in the art of the present disclosure or hereinafter conceived. Non-limiting examples of diagnostic CPR events include compression depth, compression rate, recoil, etc.
FIG. 2 illustrates an example of an annotated ECG by defibrillator 10 in accordance with the present disclosure.
Referring to FIG. 2, the ECG occurs over a cardiac arrest/arrythmia phase 71 of the CPR and a cardiac resuscitation phase 72 of the CPR.
Specifically, cardiac arrest/arrythmia phase 71 is annotated with a beginning of CPR 31, a CPR quality 32, a detection 33 of a shockable rhythm, and shockable rhythm analysis 34.
Upon an annotation of a delivery of a shock 35, cardiac resuscitation phase 72 is annotated with a normal rhythm analysis 36, a return of spontaneous circulation detection 37 and a ventilation analysis 38.
Still referring to FIG. 2, those having ordinary skill in the art that the ECG of FIG. 2 has been provided in a simplified version to best illustrate the principles of the present disclosure. Nonetheless, in practice, those having ordinary skill in the art of the present disclosure will appreciate the ECG of a patient during and after CPR will follow the cardiac status of the patient, which may be extremely volatile.
FIG. 3 illustrates an exemplary embodiment 10a of the defibrillator 10 of FIG. 1.
Referring to FIG. 3, defibrillator 10a employs an ECG generator not shown (e.g., ECG generator 20 of FIG. 1) and resuscitation event modules (e.g., resuscitation event modules 30 of
FIG. 1) including a rhythm classification module 11, a ROCS detection module 12, a VF vitality algorithm 13, a ventilation quality algorithm 14 and a CPR quality algorithm 15.
Rhythm classification module 11 processes ECG lead signals 41 to execute an algorithm for classifying a heart rhythm at any given moment of time as a shockable rhythm (e.g., VF, polymorphic VT) or a non-shockable, and then for further classifying a non-shockable rhythm into organized (including normal sinus rhythm and other ORS rhythms) or asystole. The heart rate of the patient can also be detected by this algorithm. Rhythm classification module 11 may work during CPR and/or post-CPR.
ROSC detection algorithm 12 processes ECG lead signals 41, impedance signals 42, PPG signals 44 and capnography signals 41 to execute an algorithm for detecting a return of spontaneous circulation (ROSC). ROSC detection algorithm 12 may work during CPR and/or post-CPR.
VF vitality module 13 process ECG lead signals 41 to execute an algorithm for returning a VF vitality score which can be a predictor of shock efficacy, ROSC and survival during CPR and/or post-CPR. In practice, an AMS A of the ECG data may be utilized to derive a VF vitality score.
Ventilation quality module 14 processes impedance signal 41, capnography signals 51 and ventilation sensing signals 52 to execute an algorithm for deriving ventilation quality metrics such as ventilation rate, inhaling/exhaling speed and ventilation volume, primarily post-CPR.
CPR quality module 15 processes impedance signal 41 and common mode current signal 42 to execute an algorithm for deriving CPR quality metrices, such as compression depth, compression rate, recoil, etc. In practice, U.S. Patent Application Publication US20180140857A1, hereby incorporated by reference may be implemented by CPR quality module 15.
Still referring to FIG. 3, defibrillator 10a further employs a machine learning module 16 for utilizing the resuscitation event annotation(s) as training data and/or testing data for the ECG generator and the resuscitation modules 11-15 as would be appreciated by those having ordinary skill in the art of the present disclosure. In practice, the machine learning module 16 may be any type of machine learning model as known in the art of the present disclosure and hereinafter conceived.
FIG. 4 illustrates an example of an annotated ECG by defibrillator 1 Oa in accordance with the present disclosure.
Referring to FIG. 4, the ECG consists of a VF rhythm, a shock delivery and a return to a normal rhythm as would be appreciated by those having ordinary skill in the art.
Specifically, a cardiac arrest/arrythmia phase of the ECG is annotated with a beginning of CPR 31a, a CPR quality 32a, a detection 33a of the VF rhythm, and a shockable rhythm analysis 34a.
Upon an annotation of a delivery of a shock 35a, a cardiac resuscitation phase of the ECG is annotated with a normal rhythm analysis 36a, a return of spontaneous circulation detection 37a and a ventilation analysis 38a.
Still referring to FIG. 4, those having ordinary skill in the art that the ECG of FIG. 4 has been provided in a simplified version to best illustrate the principles of the present disclosure. Nonetheless, in practice, those having ordinary skill in the art of the present disclosure will appreciate the ECG of a patient during and after CPR will follow the cardiac status of the patient, which may be extremely volatile.
Referring to FIG. 5, shown is an exemplary embodiment of controller 100 that includes one or more processor(s) 101, memory 102, a user interface 103, a network interface 104, and a storage 105 interconnected via one or more system bus(es) 106.
Each processor 101 can be any hardware device, as known in the art of the present disclosure or hereinafter conceived, capable of executing instructions stored in memory 102 or storage or otherwise processing data. In a non-limiting example, the processor(s) 101 can include a microprocessor, field programmable gate array (FPGA), application-specific integrated circuit (ASIC), or other similar devices.
The memory 102 can include various memories, as known in the art of the present disclosure or hereinafter conceived, including, but not limited to, LI, L2, or L3 cache or system memory. In a non-limiting example, the memory 102 can include static random access memory (SRAM), dynamic RAM (DRAM), flash memory, read only memory (ROM), or other similar memory devices.
The user interface 103 can include one or more devices, as known in the art of the present disclosure or hereinafter conceived, for enabling communication with a user such as an
administrator. In a non-limiting example, the user interface can include a command line interface or graphical user interface that can be presented to a remote terminal via the network interface 104.
The network interface 104 can include one or more devices, as known in the art of the present disclosure or hereinafter conceived, for enabling communication other components of a medical device. In a non-limiting example, the network interface 104 can include a network interface card (NIC) configured to communicate according to the Ethernet protocol. Additionally, the network interface 104 may implement a TCP/IP stack for communication according to the TCP/IP protocols. Various alternative or additional hardware or configurations for the network interface 104 will be apparent.
The storage 105 can include one or more machine-readable storage media, as known in the art of the present disclosure or hereinafter conceived, including, but not limited to, read-only memory (ROM), random-access memory (RAM), magnetic disk storage media, optical storage media, flash-memory devices, or similar storage media. In various non-limiting embodiments, the storage 105 can store instructions for execution by the processor(s) 101 or data upon with the processor(s) 101 may operate. For example, the storage 105 may store a base operating system for controlling various basic operations of the hardware.
The storage 105 can also store an application modules in the form of executable software/firmware for implementing the principles as previously described in the present disclosure.
In one exemplary embodiment as shown, storage 105 stores application modules 107 including annotation modules 108 (e.g., modules 11-15 of FIG. 3) and a machine learning module 109 (e.g., module 16 of FIG. 3).
Still referring to FIG. 5, in practice, controller 100 may be incorporated into or linked with a defibrillator.
Additionally, to receive and process applicable signals, controller 100 may be in communication with ECG leads 110, monitoring electrodes 111, a PPG sensor 112, a capnography sensor 113, a ventilation sensor 114 and/or a CPR meter 115 as known in the art of the present disclosure and hereinafter conceived.
From the description of FIGS. 1-5 herein, those having ordinary skill in the art will appreciate the numerous benefits of the present disclosure including, but not limited to, information exchanges between a responder and a defibrillator that facilitates an effective CPR application and recovery treatment of the patient, and information indications of a degree of defibrillation effectiveness of the defibrillator.
The present disclosure has been described with reference to the preferred embodiments. Modifications and alterations may occur to others upon reading and understanding the preceding detailed description. It is intended that the invention be construed as including all such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Further, as one having ordinary skill in the art shall appreciate in view of the teachings provided herein, features, elements, components, etc. disclosed and described in the present disclosure/specification and/or depicted in the appended Figures and/or recited in the claims can be implemented in various combinations of hardware and software, and provide functions which may be combined in a single element or multiple elements. For example, the functions of the various features, elements, components, etc. shown/illustrated/depicted in the Figures and/or recited in the claims can be provided through the use of dedicated hardware as well as hardware capable of executing software in association with appropriate software. When provided by a processor, the functions can be provided by a single dedicated processor, by a single shared processor, or by a plurality of individual processors, some of which can be shared and/or multiplexed. Moreover, explicit use of the term “processor” or “controller” should not be construed to refer exclusively to hardware capable of executing software, and can implicitly include, without limitation, digital signal processor (“DSP”) hardware, memory (e.g., read only memory (“ROM’) for storing software, random access memory (“RAM”), non-volatile storage, etc.) and virtually any means and/or machine (including hardware, software, firmware, combinations thereof, etc.) which is capable of (and/or configurable) to perform and/or control a process.
Moreover, all statements herein reciting principles, aspects, and exemplary embodiments of the present disclosure, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents
include both currently known equivalents as well as equivalents developed in the future (e.g., any elements developed that can perform the same or substantially similar functionality, regardless of structure). Thus, for example, it will be appreciated by one having ordinary skill in the art in view of the teachings provided herein that any block diagrams presented herein can represent conceptual views of illustrative system components and/or circuitry embodying the principles of the invention. Similarly, one having ordinary skill in the art should appreciate in view of the teachings provided herein that any flow charts, flow diagrams and the like can represent various processes which can be substantially represented in computer readable storage media and so executed by a computer, processor or other device with processing capabilities, whether or not such computer or processor is explicitly shown.
Having described preferred and exemplary embodiments of the present disclosure, which embodiments are intended to be illustrative and not limiting, it is noted that modifications and variations can be made by persons having ordinary skill in the art in view of the teachings provided herein, including the appended Figures and claims. It is therefore to be understood that changes can be made in/to the preferred and exemplary embodiments of the present disclosure which are within the scope of the present disclosure and exemplary embodiments disclosed, described and taught herein.
Moreover, it is contemplated that corresponding and/or related systems incorporating and/or implementing the device or such as may be used/implemented in a device in accordance with the present disclosure are also contemplated and considered to be within the scope of the present disclosure. Further, corresponding and/or related method for manufacturing and/or using a device and/or system in accordance with the present disclosure are also contemplated and considered to be within the scope of the present disclosure.
Claims
1. A defibrillator (10), comprising: an ECG generator (20) operable to generate ECG data associated with a patient; and a diagnostic defibrillation module configured to analyze at least one biological signal associated with the ECG data, and to annotate the ECG data with at least one diagnostic defibrillation event indicated by the at least one biological signal.
2. The defibrillator (10) of claim 1, wherein the diagnostic defibrillation module is a rhythm classification module (11) configured to analysis at least one ECG lead signal associated with the patient to classify at least one cardiac rhythm within the ECG data and to annotate the ECG data with a classification of the at least one cardiac rhythm within the ECG data.
3. The defibrillator (10) of claim 1, wherein the diagnostic defibrillation module is a return of spontaneous circulation module (12) configured to analyze at least one ECG lead signal associated with the patient, at least one impedance signal associated with the patient, at least one PPG signal associated with the patient and at least one capnography signal associated with the patient for detecting a return of spontaneous circulation and to annotate the ECG data with an indication of a detected ROSC.
4. The defibrillator (10) of claim 1, wherein the diagnostic defibrillation module is a VF vitality module (13) configured to analyze at least one ECG lead signal associated with the patient for returning a VF vitality score and to annotate the ECG data with an indication of the VF vitality score.
5. The defibrillator (10) of claim 1, further comprising: a diagnostic ventilation module (14) configured to analyze at least one impedance signal associated with the patient, at least one capnography signal associated with the patient and at least one ventilation sensing signal associated with the patient for deriving ventilation quality
metrics and to annotate the ECG data with at least one indication of the ventilation quality metrics.
6. The defibrillator (10) of claim 1, further comprising: a diagnostic CPR module (15) configured to analyze at least one impedance signal associated with the patient and at least one common mode current associated with the patient for deriving CPR quality metrics and to annotate the ECG data with at least one indication of the CPR quality metrics.
7. The defibrillator (10) of claim 1, further comprising: a machine learning module (16) configured to generate at least one of training data and testing data from at least one annotation of the ECG data.
8. A defibrillation controller (100), comprising: a non-transitory machine-readable storage medium (105) encoded with instructions for execution by one or more processors (101), the non-transitory machine-readable storage medium (105) including the instructions to: generate ECG data associated with a patient; analyze at least one biological signal associated with the ECG data, and annotate the ECG data with at least one diagnostic defibrillation event indicated by the at least one biological signal.
9. The defibrillation controller (100) of claim 8, wherein the at least one biological signal includes at least one ECG lead signal associated with the patient to classify at least one cardiac rhythm within the ECG data and to annotate the ECG data with a classification of the at least one cardiac rhythm within the ECG data.
10. The defibrillation controller (100) of claim 8, wherein the at least one biological signal includes at least one ECG lead signal associated with the patient, at least one impedance signal associated with the patient, at least one PPG signal associated with the patient and at least one
capnography signal associated with the patient for detecting a return of spontaneous circulation and to annotate the ECG data with an indication of a detected ROSC.
11. The defibrillation controller (100) of claim 8, wherein the at least one biological signal includes at least one ECG lead signal associated with the patient for returning a VF vitality score and to annotate the ECG data with an indication of the VF vitality score.
12. The defibrillation controller (100) of claim 8, wherein the at least one biological signal includes at least one impedance signal associated with the patient, at least one capnography signal associated with the patient and at least one ventilation sensing signal associated with the patient for deriving ventilation quality metrics and to annotate the ECG data with at least one indication of the ventilation quality metrics.
13. The defibrillation controller (100) of claim 8, wherein the at least one biological signal includes at least one impedance signal associated with the patient and at least one common mode current associated with the patient for deriving CPR quality metrics and to annotate the ECG data with at least one indication of the CPR quality metrics.
14. The defibrillator (10) controller (100) of claim 8, wherein the non-transitory machine- readable storage medium (105) further includes instructions to generate at least one of training data and testing data from at least one annotation of the ECG data.
15. The defibrillation controller (100) of claim 8, wherein the defibrillation controller (100) is installed within a defibrillator (10) or operable to be in communication with the defibrillator (10).
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| US202463641639P | 2024-05-02 | 2024-05-02 | |
| US63/641,639 | 2024-05-02 |
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| WO2025229059A1 true WO2025229059A1 (en) | 2025-11-06 |
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| PCT/EP2025/061831 Pending WO2025229059A1 (en) | 2024-05-02 | 2025-04-30 | Resuscitation event analysis/annotations of an electrocardiogram |
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| US20140047314A1 (en) * | 2012-08-10 | 2014-02-13 | Physio-Control, Inc | Automatically evaluating likely accuracy of event annotations in field data |
| US20150352368A1 (en) * | 2013-09-27 | 2015-12-10 | Zoll Medical Corporation | Electrocardiogram identification |
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| US20220157418A1 (en) * | 2019-03-29 | 2022-05-19 | Zoll Medical Corporation | Systems and methods for documenting emergency care |
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| US20140047314A1 (en) * | 2012-08-10 | 2014-02-13 | Physio-Control, Inc | Automatically evaluating likely accuracy of event annotations in field data |
| US20150352368A1 (en) * | 2013-09-27 | 2015-12-10 | Zoll Medical Corporation | Electrocardiogram identification |
| US20180140857A1 (en) | 2015-06-05 | 2018-05-24 | Koninklijke Philips N.V. | Method and apparatus for detecting a status of cpr chest compressions without using a stand-alone compression meter |
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