CN116801944A - Rhythm analysis and decision method, device and storage medium for defibrillator - Google Patents
Rhythm analysis and decision method, device and storage medium for defibrillator Download PDFInfo
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- 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]
- A61B5/346—Analysis of electrocardiograms
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- 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
Abstract
A method, apparatus and storage medium for rhythm analysis and decision-making for a defibrillator, the method comprising: acquiring an electrocardiosignal of a target object in the process of carrying out cardiopulmonary resuscitation on the target object; dividing the electrocardiosignal into a plurality of analysis areas on a time sequence, and determining the state corresponding to each analysis area; for each analysis region, determining a segment rhythm analysis mode based on the corresponding state, and performing rhythm analysis to obtain the segment rhythm state of the analysis region; performing long-time rhythm analysis based on the segment rhythm states of a plurality of analysis areas in a first preset time period from the rhythm decision moment to obtain long-time rhythm state characteristics; performing short-time rhythm analysis based on the segment rhythm state of at least one analysis area in a second preset time period from the rhythm decision moment to obtain short-time rhythm state characteristics; a rhythm decision is determined and output based on the long-time rhythm state feature and the short-time rhythm state feature. The application can obtain more reliable rhythm decision.
Description
Description
The present application relates to the technical field of defibrillators, and more particularly to a method, apparatus and storage medium for rhythm analysis and decision making of a defibrillator.
The defibrillator is a medical instrument for eliminating arrhythmia by using stronger pulse current to pass through the heart, so that the defibrillator restores sinus rhythm, and is necessary first-aid equipment for an operating room. Defibrillation is one of the important steps for performing cardiopulmonary resuscitation. A combination of Electrocardiographic (ECG) signals is required for rhythm analysis in cardiopulmonary resuscitation (Cardiopulmonary Resuscitation, CPR) compressions, where reliable rhythm analysis relies primarily on reliable segment rhythm analysis and reliable multiple time segment rhythm state synthesis decisions.
At present, the comprehensive decision method of rhythms in CPR process mainly focuses on two aspects: one is to output a rhythm decision comprehensively using a short-time rhythm analysis state, and the other is to output a rhythm decision comprehensively using a long-time rhythm analysis state. However, the comprehensive decision is made only by using the short-time rhythm analysis state, which is easily affected by local interference, so that the rhythm is misjudged; the comprehensive decision is carried out only by means of the long-time rhythm analysis state, and the long-time stable rhythm state is reflected, is insensitive to local rhythm fluctuation and is not timely in rhythm conversion response.
Disclosure of Invention
In one aspect of the application, a method of rhythm analysis and decision making for a defibrillator is provided, the method comprising: acquiring an electrocardiosignal of a target object in the process of carrying out cardiopulmonary resuscitation on the target object; dividing the electrocardiosignal into a plurality of analysis areas on a time sequence, and determining a state corresponding to each analysis area, wherein the state comprises an emergency treatment state and/or a filtering state; for each analysis region, determining a fragment rhythm analysis mode of the analysis region based on a state corresponding to the analysis region, and performing rhythm analysis on the analysis region based on the fragment rhythm analysis mode to obtain a fragment rhythm state of the analysis region; performing long-time rhythm analysis based on the segment rhythm states of a plurality of analysis areas in a first preset time period from the rhythm decision moment to obtain long-time rhythm state characteristics; performing short-time rhythm analysis based on the segment rhythm state of at least one analysis region in a second preset time period from the rhythm decision moment to obtain a short-time rhythm state characteristic, wherein the first preset time period is larger than the second preset time period; determining a rhythm decision based on the long-term rhythm state feature and the short-term rhythm state feature and outputting the rhythm decision.
In another aspect of the application, a method of rhythm analysis and decision making for a defibrillator is provided, the method comprising: acquiring a reference signal and an original electrocardiosignal of a target object in the process of carrying out cardiopulmonary resuscitation on the target object; performing compression detection on the reference signal to obtain a time domain compression event mark of the reference signal; determining an instantaneous compression interval based on the time-domain compression event markers, and filtering the original electrocardiosignals based on the instantaneous compression interval to obtain filtered electrocardiosignals; dividing the electrocardiosignals of the target object into a plurality of analysis areas on a time sequence, and carrying out rhythm analysis on each analysis area to obtain a segment rhythm state of each analysis area, wherein the electrocardiosignals of the target object only comprise the filtered electrocardiosignals, or the electrocardiosignals of the target object comprise the original electrocardiosignals and the filtered electrocardiosignals; performing long-time rhythm analysis based on the segment rhythm states of a plurality of analysis areas in a first preset time period from the rhythm decision moment to obtain long-time rhythm state characteristics; performing short-time rhythm analysis based on the segment rhythm state of at least one analysis region in a second preset time period from the rhythm decision moment to obtain a short-time rhythm state characteristic, wherein the first preset time period is larger than the second preset time period; determining a rhythm decision based on the long-term rhythm state feature and the short-term rhythm state feature and outputting the rhythm decision.
In a further aspect of the application there is provided a rhythm analysis and decision-making apparatus comprising a memory and a processor, said memory having stored thereon a computer program for execution by said processor, said computer program when executed by said processor performing the rhythm analysis and decision-making method for a defibrillator as described above.
In yet another aspect of the present application, a storage medium having stored thereon a computer program which, when run, performs the above-described rhythm analysis and decision-making method for a defibrillator.
The method and the device for analyzing and deciding the rhythm of the defibrillator, which are provided by the embodiment of the application, combine the long-time rhythm state characteristics and the short-time rhythm state characteristics to determine the rhythm decision, so that local interference can be avoided, insensitivity to local rhythm fluctuation can be avoided, and more reliable rhythm decision can be obtained. In addition, as different rhythm analysis modes are selected according to the electrocardiosignals in different states, the accuracy of the rhythm analysis result, namely the segment rhythm state, can be further improved, and the reliability of the rhythm decision can be further improved.
Fig. 1 shows a schematic flow chart of a rhythm analysis and decision method for a defibrillator according to one embodiment of the present application.
Fig. 2 illustrates an exemplary flow diagram of a method for rhythm analysis and decision making for a defibrillator according to one embodiment of the present application.
Fig. 3 shows a process schematic of a rhythm analysis and decision methodology for a defibrillator according to one embodiment of the present application.
Fig. 4 shows a schematic flow chart of a rhythm analysis and decision method for a defibrillator according to another embodiment of the present application.
Fig. 5 shows an exemplary flow diagram of a method for rhythm analysis and decision making for a defibrillator according to another embodiment of the present application.
Fig. 6 illustrates an exemplary flow diagram of a method for rhythm analysis and decision making for a defibrillator according to yet another embodiment of the present application.
Fig. 7 shows a schematic block diagram of a rhythm analysis and decision device for a defibrillator according to an embodiment of the present application.
In order to make the objects, technical solutions and advantages of the present application more apparent, exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are only some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited by the example embodiments described herein. Based on the embodiments of the application described in the present application, all other embodiments that a person skilled in the art would have without inventive effort shall fall within the scope of the application.
In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the present application. It will be apparent, however, to one skilled in the art that the application may be practiced without one or more of these details. In other instances, well-known features have not been described in detail in order to avoid obscuring the application.
It should be understood that the present application may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the application to those skilled in the art.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term "and/or" includes any and all combinations of the associated listed items.
In order to provide a thorough understanding of the present application, detailed steps and detailed structures will be presented in the following description in order to explain the technical solution presented by the present application. Preferred embodiments of the present application are described in detail below, however, the present application may have other embodiments in addition to these detailed descriptions.
First, a rhythm analysis and decision method for a defibrillator according to one embodiment of the present application is described with reference to fig. 1. Fig. 1 shows a schematic flow chart of a method 100 for rhythm analysis and decision making for a defibrillator according to one embodiment of the present application. As shown in fig. 1, a rhythm analysis and decision method 100 for a defibrillator may include the steps of:
in step S110, an electrocardiographic signal of a target object during cardiopulmonary resuscitation of the target object is obtained.
In step S120, the electrocardiographic signal is divided into a plurality of analysis regions in time series, and a state corresponding to each analysis region is determined, where the state includes an emergency treatment state and/or a filtering state.
In step S130, for each analysis region, a segment rhythm analysis mode of the analysis region is determined based on a state corresponding to the analysis region, and a rhythm analysis is performed on the analysis region based on the segment rhythm analysis mode to obtain a segment rhythm state of the analysis region.
In step S140, a long-term rhythm analysis is performed based on the segment rhythm states of the plurality of analysis regions within a first preset time period from the rhythm decision time to obtain a long-term rhythm state feature.
In step S150, a short-time rhythm analysis is performed based on the segment rhythm status of at least one analysis region in a second preset time period from the rhythm decision time, so as to obtain a short-time rhythm status feature, where the first preset time period is greater than the second preset time period.
In step S160, a rhythm decision is determined based on the long-term rhythm state feature and the short-term rhythm state feature, and the rhythm decision is output.
In the embodiment of the application, after the electrocardiosignals of the target object in the cardiopulmonary resuscitation process of the target object are divided into a plurality of analysis areas on a time sequence, the state (emergency treatment state and/or filtering state) corresponding to each analysis area is determined, the analysis areas with different states are subjected to rhythm analysis by adopting different segment rhythm analysis modes, the segment rhythm state of each analysis area is obtained, and finally, the long-time rhythm state analysis and the long-time short-time rhythm state analysis are carried out according to the segment rhythm state of each analysis area, and the rhythm decision is determined by combining the long-time rhythm state characteristics and the short-time rhythm state characteristics, so that the local interference can be avoided, the insensitivity to the local rhythm fluctuation can be avoided, and more reliable rhythm decision can be obtained. In addition, as different rhythm analysis modes are selected according to the electrocardiosignals in different states, the accuracy of the rhythm analysis result, namely the segment rhythm state, can be further improved, and the reliability of the rhythm decision can be further improved.
In an embodiment of the present application, the electrocardiographic signal of the target object acquired in step S110 may be an original electrocardiographic signal and/or a filtered electrocardiographic signal. The filtered electrocardiosignals are obtained based on reference signals and original electrocardiosignals which are related to chest compression in the cardiopulmonary resuscitation process. Specifically, the detection and identification of the compression event can be performed on reference signals (such as chest impedance signals, blood oxygen signals, respiratory signals, signals sensed by a CPR sensor and the like acquired by defibrillation through chest electrodes), or the detection of the compression event can be assisted by combining frequency domain components of the reference signals, CPR interference of an original electrocardiosignal waveform can be filtered by adopting an adaptive filtering model, CPR chest compression detection and filtering can be realized, and a filtered electrocardiosignal can be obtained.
In an embodiment of the present application, the electrocardiographic signal is divided into a plurality of analysis regions in time series in step S120, and each analysis region may have the same time length; alternatively, the length of time for each analysis region may be varied as desired. Furthermore, for two adjacent analysis areas, they may be continuous in time or intermittent. Furthermore, for two adjacent analysis areas, they may or may not overlap in time.
In an embodiment of the application, the status of each analysis area includes an emergency treatment status and/or a filtering status. The emergency treatment state reflects the emergency operation state of emergency personnel on the target object in a time period corresponding to the analysis area; the filtering state reflects whether the electrocardiosignal in the time period corresponding to the analysis area needs filtering or not. Because the different emergency operation states and the condition of whether the electrocardiosignal needs to be filtered reflect whether the electrocardiosignal is interfered by CPR in a time period and whether the electrocardiosignal is interfered by CPR affects the rhythm analysis and decision, in the embodiment of the application, the state of each analysis area of the electrocardiosignal is determined, and a proper (corresponding) segment rhythm analysis mode is determined according to the state of each analysis area of the electrocardiosignal, so that the rhythm analysis of each analysis area is more accurately carried out, the more accurate segment rhythm state is obtained, and the more reliable rhythm decision is obtained.
In the embodiment of the present application, the emergency treatment state may further include a press progress state (may also be simply referred to as a press state), a press transition state, and a press suspension state. The filter states may further include a filter-required state and a filter-not-required state. In an embodiment of the present application, determining a segment rhythm analysis mode of an analysis region based on a state corresponding to the analysis region may include: when the emergency treatment state of the analysis area is a pressing suspension state and/or the filtering state of the analysis area is a filtering-free state, determining that the fragment rhythm analysis mode of the analysis area is an interference-free mode; and when the emergency treatment state of the analysis area is a pressing progress state or a pressing transition state and the filtering state of the analysis area is a filtering-needed state, determining that the fragment rhythm analysis mode of the analysis area is an interference mode.
As previously mentioned, the different emergency operating conditions and whether the electrocardiographic signal needs to be filtered reflect whether the electrocardiographic signal is disturbed by CPR over a period of time, which in turn affects rhythm analysis and decision-making. Therefore, when the emergency treatment state of one analysis area is determined to be the compression suspension state, it is indicated that the electrocardiographic signal is less disturbed by CPR at this time, and therefore, the analysis of the segment rhythms is performed in a non-disturbance mode. Similarly, when the filtering state of one analysis area is determined to be the filtering-free state, the fact that the electrocardiosignals are disturbed by CPR is indicated to be small, and therefore the analysis of the segment rhythms is carried out by adopting a non-disturbance mode. In the non-interference mode, both the original electrocardiosignal and the filtered electrocardiosignal can be used for rhythm analysis, so that the rhythm analysis can be performed by adopting a non-interference rhythm strategy based on the original electrocardiosignal and/or the filtered electrocardiosignal.
When the emergency treatment state of one analysis area is determined to be the compression progress state or the compression transition state, it is indicated that the electrocardiographic signal is greatly disturbed by CPR at this time, and therefore, it is necessary to perform the segment rhythm analysis in the disturbed mode. Similarly, when the filter status of an analysis area is determined to be the required filter status, it is indicated that the cardiac signal is greatly disturbed by CPR at this time, and thus the analysis of the segment rhythms is required by using the disturbed mode. In the interference mode, because the electrocardiosignals are interfered by CPR, the rhythm analysis can be carried out by adopting an interference rhythm strategy only based on the filtered electrocardiosignals; alternatively, a disturbed rhythm strategy may be used for the rhythm analysis in combination with the original and filtered electrocardiographic signals.
In an embodiment of the present application, the emergency treatment status may further include a shock status, and the determining a segment rhythm analysis mode of the analysis area based on the status corresponding to the analysis area may further include: and when the emergency treatment state of the analysis area is a shock state, determining the fragment rhythm analysis mode of the analysis area as an initialization mode. In the electric shock state, a new round of pressing cycle can be started by default, the rhythm analysis is initialized, the first analysis after the electric shock is used as the initial state of the rhythm analysis, and the pre-electric shock rhythm information is not considered any more. For example, a shock condition may be sensed when an emergency personnel presses a shock confirm button.
In an embodiment of the present application, determining the state corresponding to each analysis area in step S120 may further include: acquiring a reference signal related to chest compression in the process of carrying out cardiopulmonary resuscitation on a target object; dividing the reference signal into a plurality of sub-analysis areas on a time sequence, and determining the pressing condition corresponding to each sub-analysis area; for each analysis region of the electrocardiograph signal, determining an emergency treatment status of each analysis region based on a compression condition of one or more of the sub-analysis regions corresponding to the analysis region. In this embodiment, a reference signal (such as a chest impedance signal acquired by defibrillation via chest electrodes, a blood oxygen signal, a respiration signal, and a signal sensed by a CPR sensor, etc.) is acquired and divided into a plurality of sub-analysis regions, one or more of which corresponds to one analysis region of an electrocardiograph signal, and thus, the emergency treatment state of the analysis region is determined according to the compression condition of the one or more sub-analysis regions corresponding to the one analysis region.
In one example, the determining the emergency treatment status of each of the analysis areas based on the pressing condition of one or more of the sub-analysis areas corresponding to the analysis areas may include: when the pressing condition of each sub-analysis area corresponding to the analysis area is a pressing event, determining that the emergency treatment state of the analysis area is a pressing progress state; when the pressing condition of part of the sub-analysis areas corresponding to the analysis areas is a pressing event, and the pressing condition of the rest of the sub-analysis areas is a pressing event, determining that the emergency treatment state of the analysis areas is a pressing transition state; and when the pressing condition of each sub-analysis area corresponding to the analysis area is that no pressing event exists, determining that the emergency treatment state of the analysis area is a pressing pause state.
In an embodiment of the present application, the determining the pressing condition corresponding to each sub-analysis area may include: performing time domain analysis and/or frequency domain analysis on the reference signal to obtain time domain pressing characteristics and/or frequency domain pressing characteristics; and performing compression detection on each sub-analysis region of the reference signal based on the time domain compression characteristic and/or the frequency domain compression characteristic to determine whether a compression event exists in each sub-analysis region. In this embodiment, determining whether a compression event is present for each sub-analysis region may be performed based on time-domain compression features, frequency-domain compression features, or a combination of time-domain frequency-domain compression features to more accurately determine whether a compression event is present for each sub-analysis region.
The above is an example description of determining the emergency treatment status of each analysis area. The determination of the filter state for each analysis region is described below. In an embodiment of the present application, determining the state corresponding to each analysis area may include: acquiring a reference signal in the process of carrying out cardiopulmonary resuscitation on the target object; dividing the reference signal into a plurality of sub-analysis areas in a time sequence; and for each analysis region of the electrocardiosignal, carrying out correlation analysis on the noise of the analysis region and the reference signals of one or more sub analysis regions corresponding to the analysis region, determining a filtering mode of the analysis region according to the result of the correlation analysis, and determining the filtering state of the analysis region according to the filtering mode of the analysis region.
In this embodiment, a reference signal (such as a chest impedance signal, a blood oxygen signal, a respiration signal, and a CPR sensor-sensed signal acquired by defibrillation via a chest electrode) is acquired and divided into a plurality of sub-analysis regions, one or more of which corresponds to one analysis region of an electrocardiograph signal, and thus, based on both a reference signal portion corresponding to one or more of the sub-analysis regions corresponding to one analysis region and a noise condition of the analysis region, a filtering manner of the analysis region can be determined, thereby determining a filtering state of the analysis region. For example, when the ECG filtering mode of one analysis area is determined to be low-order filtering or high-order filtering through correlation analysis, the filtering state of the analysis area may be determined to be a desired filtering state. When the ECG filtering mode of one analysis area is determined to be the filtering-free mode through the correlation analysis, the filtering state of the analysis area can be determined to be the filtering-free state.
In an embodiment of the present application, after determining the status of each analysis region and thus determining the segment rhythm analysis mode of each analysis region, segment rhythm analysis is performed on each analysis region using the segment rhythm analysis mode corresponding to each analysis region, thereby obtaining the segment rhythm status of each analysis region, as described in step S130. After that, long-term rhythm analysis and short-term rhythm analysis are performed in step S140 and step S150, respectively, according to the resulting segment rhythm state, which will be described in detail below.
In the embodiment of the application, long-time rhythm analysis is performed based on the segment rhythm states of a plurality of analysis areas in a first preset time period from the rhythm decision time to obtain long-time rhythm state characteristics. That is, the long-term rhythm state is obtained by performing a rhythm analysis on the segment rhythm states of a plurality of analysis regions, which are a plurality of analysis regions within a first preset period from the rhythm decision time. Here, the first preset time period refers to a time period from a decision time to a time point of a first preset time back to a rhythm decision time point, and an end point of the time period may be the rhythm decision time or may be a certain time from the decision time point instead of the rhythm decision time. In one example, the analysis duration of the long-term rhythm analysis is a time range of more than 10 seconds closest to the rhythm decision time instant, but does not exceed the current compression period (typically 2 minutes or 3 minutes), including at least the segment rhythm state of 5 analysis regions. It is typically possible to analyze a plurality of segment rhythm states 2 minutes closest to the rhythm decision instant and calculate a long-term rhythm state feature, in this example the first preset time period described above being equal to 2 minutes.
In an embodiment of the application, the long-term rhythmic state characteristics may include at least one of: in the collection of the respective segment rhythm states of the plurality of analysis areas, the proportion of each segment rhythm state is calculated; when the segment rhythm states of the analysis areas are ordered according to time, the proportion of the segment rhythm states is the same continuously for a plurality of times; in the corresponding state sets of the analysis areas, the time ratio of different states and/or the proportion of each segment rhythm state in different states; and in the set of the segment rhythm states of each of the plurality of analysis areas, the weight score of each segment rhythm state of each analysis area depends on the time distance between the analysis area and the rhythm decision moment and/or the state corresponding to the analysis area.
In an embodiment of the application, for one analysis region: the closer the analysis area is to the rhythm decision time, the greater the weight allocated to the fragment rhythm state of the analysis area; and when the emergency treatment state of the analysis area is a pressing pause state or a filtering state is a filtering-free state, assigning a first weight to the segment rhythm state of the analysis area; when the emergency treatment state of the analysis area is a pressing progress state and the filtering state is a filtering-needed state, assigning a second weight to the segment rhythm state of the analysis area, wherein the second weight is smaller than the first weight; and when the emergency treatment state of the analysis area is a pressing transition state and the filtering state is a filtering-needed state, assigning a third weight to the segment rhythm state of the analysis area, wherein the third weight is smaller than the second weight.
In this embodiment, the closer to the rhythm decision time instant in the time dimension, the greater the weight assigned to the segment rhythm state at the corresponding time instant. From the signal reliability dimension, if the emergency treatment state is a compression pause state or a filtering state is a state without filtering, analyzing an ECG signal without CPR interference, wherein the analysis result of the segment rhythm state is relatively reliable, and distributing a first weight coefficient to the segment rhythm state at the corresponding moment; if the emergency treatment state is a compression progress state and the filtering state is a filtering-needed state, analyzing an ECG signal interfered by CPR at the moment, wherein the reliability of the analysis result of the segment rhythm state is reduced, and distributing a second weight coefficient (the second weight coefficient is smaller than the first weight coefficient) to the segment rhythm state at the corresponding moment; if the compression state of the current analysis region is a compression transition state and the filtering state is a filtering state, at this time, the analyzed signal includes an ECG signal interfered by CPR and an ECG signal without CPR interference, and because of the CPR filtering effect, a large difference may occur between the amplitude and the morphology of the CPR filtered ECG signal and the ECG signal without CPR filtering in the compression transition region, and the analysis result of the segment rhythm state is unreliable, and a third weight coefficient (the third weight coefficient is smaller than the second weight coefficient) is allocated to the segment rhythm state at the corresponding time. In the embodiment of the application, the rhythm state weight distribution criteria of the signal reliability dimension and the time dimension can be integrated, the respective weights are distributed to the segment rhythm states of different analysis areas, and the weighted combination is carried out to calculate the weighted score of each rhythm state. If the emergency treatment state of the current analysis area is the electric shock state, entering an initialization mode, initializing long-time rhythm analysis, starting a new round of pressing cycle by default, taking the first-time fragment rhythm analysis after electric shock as the initial fragment rhythm state of the long-time rhythm analysis, and not considering the rhythm information before electric shock.
In the embodiment of the application, the short-time rhythm analysis is performed based on the segment rhythm state of at least one analysis area in a second preset time period from the rhythm decision time to obtain the short-time rhythm state characteristics. That is, the long-term rhythm state is obtained by performing a rhythm analysis on a segment rhythm state of at least one analysis region that is at least one analysis region within a second preset time period from a rhythm decision time instant. Here, the second preset time period refers to a time period from a decision time to a time point of a second preset time back to a rhythm decision time point, and an end point of the time period may be the rhythm decision time or may be a certain time from the decision time point instead of the rhythm decision time. In one example, the analysis duration of the short-time rhythm analysis is a time range within 10 seconds of the nearest to the rhythm decision time instant, including at least the segment rhythm states of 1 analysis region. The one or more segment rhythm states that are 10 seconds closest to the moment of the rhythm decision may typically be analyzed to calculate a short-time rhythm state feature. In this example, the second preset period of time is equal to 10 seconds.
In an embodiment of the application, the short-time rhythmic state characteristics may include at least one of: in the collection of the respective segment rhythm states of the plurality of analysis areas, the proportion of each segment rhythm state is calculated; when the segment rhythm states of the analysis areas are ordered according to time, the proportion of the segment rhythm states is the same continuously for a plurality of times; in the corresponding state sets of the analysis areas, the time ratio of different states and/or the proportion of each segment rhythm state in different states; the method comprises the steps that in a set of the respective segment rhythm states of a plurality of analysis areas, the weight value of each segment rhythm state depends on the time distance between the analysis area and the rhythm decision moment and/or the state corresponding to the analysis area; the state is the time distance between the analysis area nearest to the rhythm decision time and the percentage of the segment rhythm state in the analysis area in the pressing pause state or the analysis area without filtering state.
In embodiments of the present application, similar to the long-term rhythm analysis described above, in short-term rhythm analysis, for one analysis region: the closer the analysis area is to the rhythm decision time, the greater the weight allocated to the fragment rhythm state of the analysis area; and when the emergency treatment state of the analysis area is a pressing pause state or a filtering state is a filtering-free state, assigning a first weight to the segment rhythm state of the analysis area; when the emergency treatment state of the analysis area is a pressing progress state and the filtering state is a filtering-needed state, assigning a second weight to the segment rhythm state of the analysis area, wherein the second weight is smaller than the first weight; and when the emergency treatment state of the analysis area is a pressing transition state and the filtering state is a filtering-needed state, assigning a third weight to the segment rhythm state of the analysis area, wherein the third weight is smaller than the second weight.
In this embodiment, the closer to the rhythm decision time instant in the time dimension, the greater the weight assigned to the segment rhythm state at the corresponding time instant. From the signal reliability dimension, if the emergency treatment state is a compression pause state or a filtering state is a state without filtering, analyzing an ECG signal without CPR interference, wherein the analysis result of the segment rhythm state is relatively reliable, and distributing a first weight coefficient to the segment rhythm state at the corresponding moment; if the emergency treatment state is a compression progress state and the filtering state is a filtering-needed state, analyzing an ECG signal interfered by CPR at the moment, wherein the reliability of the analysis result of the segment rhythm state is reduced, and distributing a second weight coefficient (the second weight coefficient is smaller than the first weight coefficient) to the segment rhythm state at the corresponding moment; if the compression state of the current analysis region is a compression transition state and the filtering state is a filtering state, at this time, the analyzed signal includes an ECG signal interfered by CPR and an ECG signal without CPR interference, and because of the CPR filtering effect, a large difference may occur between the amplitude and the morphology of the CPR filtered ECG signal and the ECG signal without CPR filtering in the compression transition region, and the analysis result of the segment rhythm state is unreliable, and a third weight coefficient (the third weight coefficient is smaller than the second weight coefficient) is allocated to the segment rhythm state at the corresponding time. In the embodiment of the application, the rhythm state weight distribution criteria of the signal reliability dimension and the time dimension can be integrated, the respective weights are distributed to the segment rhythm states of different analysis areas, and the weighted combination is carried out to calculate the weighted score of each rhythm state. If the emergency treatment state of the current analysis area is the electric shock state, entering an initialization mode, initializing the short-time rhythm analysis, and starting a new round of pressing cycle by default without considering the pre-electric shock rhythm information.
After the long-term and short-term rhythm state features are obtained, a rhythm decision is determined in combination with the two. In an embodiment of the present application, the determining a rhythm decision based on the long-term rhythm state feature and the short-term rhythm state feature may include: when the distribution conditions of the segment rhythm states reflected by the long-time rhythm state characteristics and the short-time rhythm state characteristics are consistent, determining a rhythm decision according to the distribution conditions of the segment rhythm states reflected by the long-time rhythm state characteristics or the short-time rhythm state characteristics; and when the distribution conditions of the segment rhythm states reflected by the long-time rhythm state characteristics and the short-time rhythm state characteristics are inconsistent, determining a rhythm decision according to one of the two distribution conditions with higher reliability, or determining a rhythm decision according to the distribution conditions of the segment rhythm states reflected by the short-time rhythm state characteristics, or outputting an uncertain rhythm decision. Wherein, as described in the aspect of signal reliability dimension, the ECG signals corresponding to the analysis areas of different states are different, and the reliability of the analysis results of the segment rhythm states is also different. Accordingly, the reliability of the distribution of the segment rhythm states represented by the long-time rhythm state characteristics and the short-time rhythm state characteristics is correlated with the state of the analysis region employed in each of the long-time rhythm analysis and the short-time rhythm analysis.
In this embodiment, a decision whether or not defibrillation is to be made is made based on a judgment criterion formulated by the distribution characteristics of the long-time rhythm state and the short-time rhythm state. If the distribution characteristics of the long-time rhythm state are consistent with those of the short-time rhythm state, outputting a defibrillation decision according to the rhythm state represented by the distribution characteristics; if the distribution characteristics of the long-time rhythm state are inconsistent with those of the short-time rhythm state, outputting a defibrillation decision according to the rhythm state represented by the more reliable distribution characteristics measured from the time dimension and the signal reliability dimension; if the distribution characteristics of the long-time rhythm state are inconsistent with those of the short-time rhythm state, the distribution characteristics of the long-time rhythm state and the short-time rhythm state are unreliable, and an uncertain rhythm decision is output. For example, if the weighted score feature in the long-term rhythm analysis indicates that the long-term rhythm state is a higher weighted score for defibrillation, and there is no time period for which compression is suspended or filtering is not needed in the short-term rhythm analysis, and the specific gravity of the defibrillation rhythm state is higher, outputting a defibrillation rhythm decision; if the characteristics such as the percentage of the rhythm state, the weighted score and the like in the long-time rhythm analysis are not large in degree of distinguishing whether the rhythm state can be defibrillated, but a time period in which pressing is suspended or filtering is not needed exists in the short-time rhythm analysis, the proportion of the defibrillatable rhythm state in the time period closest to the moment of the rhythm decision is large, and the defibrillatable rhythm decision can be output.
In another embodiment of the present application, the determining a rhythm decision based on the long-term rhythm state feature and the short-term rhythm state feature may include: for each segment rhythm state, obtaining a weighted score of the segment rhythm state according to a weighted combination of the characteristic corresponding to the segment rhythm state of the long-time rhythm state characteristic and the characteristic corresponding to the segment rhythm state of the short-time rhythm state characteristic; a rhythm decision is determined based on the weighted scores for each segment's rhythm state. In this embodiment, the decision of the rhythm is performed according to the weighted score obtained by the weighted combination of the distribution characteristics of the long-time rhythm state and the short-time rhythm state, and can be expressed as the following formula:
RhythmScore＝A*LongTimeScore+B*ShortTimeScore+C，
wherein, the RhythmScare is a weighted score of a certain rhythm state, and the decision of defibrillation, unreliability or uncertainty is made according to the weighted score of the rhythm state. LongTimeScore is a value that measures the long-term rhythm state distribution characteristics of a certain rhythm state, and may be a value that measures one long-term rhythm state distribution characteristic or a combined value that measures a plurality of long-term rhythm state distribution characteristics. For example, longTimeScore may be a distribution value (e.g., a percentage) of the different rhythm states in the long-term rhythm state feature, or may be a distribution value (e.g., a normalized value of a weighted score) converted from a distribution value of the different rhythm states in the long-term rhythm state feature. The combination method may be, for example, performing calculation such as normalization, averaging, weighted averaging, etc. on the distribution characteristics of the rhythmic states for a plurality of long time periods to obtain a combination value, etc. Shorttime score is a value that measures the short-time rhythm state distribution characteristics of a certain rhythm state, and may be a value that measures the short-time rhythm state distribution characteristics of one kind or a combined value that measures the short-time rhythm state distribution characteristics of a plurality of kinds. A. B, C the weight coefficient obtained by regression analysis.
After determining the rhythm decision, the rhythm decision may be output, for example, at the end of a compression cycle, and emergency personnel may be instructed to perform an emergency treatment based on the rhythm decision result. And if the rhythm decision output can defibrillate the rhythm decision, indicating the emergency personnel to shock, if the rhythm decision output can not defibrillate the rhythm decision, indicating the emergency personnel to continue pressing, and if the rhythm decision output is uncertain, indicating the emergency personnel to pause pressing, and confirming the rhythm of the ECG signal without pressing interference.
The rhythm analysis and decision method 100 for a defibrillator according to an embodiment of the present application is described above as being used in a fixed CPR operation mode, which is a mode in which an emergency personnel performs cardiopulmonary resuscitation in accordance with a fixed compression period set by the system, and a rhythm decision is given after the compression period ends, instructing the emergency personnel to perform emergency treatment. The method 100 may also be used in a continuous CPR mode of operation, where the continuous CPR mode of operation refers to no fixed compression period during cardiopulmonary resuscitation by an emergency personnel, continuous rhythm decisions during CPR, immediate indication of shock treatment by the emergency personnel once the rhythm decision outputs a defibrillatable rhythm, or active initiation of a rhythm analysis request by the emergency personnel, delivery of a rhythm decision, and indication of emergency treatment by the emergency personnel.
In an embodiment for a continuous CPR mode of operation, in one example, the analysis duration of the long-term rhythm analysis may be a time range of more than 10 seconds, but no more than 3 minutes, including at least the segment rhythm states of 5 analysis regions, nearest to the rhythm decision instant; the analysis duration of the short-time rhythm analysis is within 10 seconds of the nearest time range of the rhythm decision time, and at least comprises the segment rhythm states of 1 analysis area, and the rhythm decision is continuously carried out in the CPR process. If the analysis time length or the number of analysis areas before the rhythm decision time does not meet the analysis conditions of long-time rhythm analysis, the long-time rhythm state keeps a default initial state (uncertain rhythm), and when the rhythm decision is made, the characteristic of the long-time default initial rhythm state and the characteristic of the short-time rhythm state are combined, and a rhythm decision strategy is utilized to output a defibrillation, unreliability or uncertain rhythm decision. The rhythm decision strategy at this time includes, but is not limited to, the following ways: directly outputting the uncertain rhythm decision; making a defibrillation decision according to a judgment criterion formulated by the short-time rhythm state characteristics, if the defibrillation decision is measured from the time dimension and the signal reliability dimension, outputting the defibrillation decision according to the rhythm state represented by the corresponding distribution characteristics, wherein the short-time rhythm state is more reliable; outputting an uncertain rhythm decision if the short-time rhythm state is unreliable (e.g., outputting a defibrillatable rhythm decision if there is a pause in compressions or a period of time without filtering in the short-time rhythm analysis, and wherein the defibrillatable rhythm state of the period of time closest to the moment of the rhythm decision has a higher specific gravity); and according to the characteristics of the long-term default initial rhythm state and the short-term rhythm state, carrying out a weighted score obtained by weighted combination, and carrying out a rhythm decision, wherein the method can be expressed as the following formula:
RhythmScore＝A*LongTimeScore+B*ShortTimeScore+C，
Wherein, the RhythmScare is a weighted score of a certain rhythm state, and defibrillation, unreflectable or uncertain rhythm decision is carried out according to the weighted score of the rhythm state; longTimeScore is a value that measures the default initial rhythmic state for long periods of time; the shorttime score is a value for measuring the short-time rhythm state distribution characteristic of a certain rhythm state, and can be a value for measuring the short-time rhythm state distribution characteristic or a combined value for measuring the short-time rhythm state distribution characteristics; A. b, C the weight coefficient obtained by regression analysis.
And according to the rhythm decision result, indicating emergency personnel to carry out emergency treatment. When the emergency personnel do not actively initiate the rhythm analysis request, once the rhythm decision output can defibrillate the rhythm, the emergency personnel is immediately instructed to shock, and if the rhythm decision output other rhythms, the emergency personnel is not instructed or instructed to continue pressing. When the first-aid staff initiatively initiates a rhythm analysis request, a rhythm decision is given, if the rhythm decision output can defibrillate the rhythm, the first-aid staff is immediately instructed to perform electric shock, if the rhythm decision output cannot defibrillate the rhythm, the first-aid staff is instructed to continuously press, if the rhythm decision output does not determine the rhythm, the first-aid staff is instructed to pause pressing, and the ECG signal without pressing interference is subjected to rhythm confirmation.
The foregoing illustrates a method 100 for analyzing and deciding a rhythm for a defibrillator according to an embodiment of the present application, and in order to better understand the method, fig. 2 illustrates an exemplary flow chart of the rhythm analysis and decision according to an embodiment of the present application (in which links and trends thereof in the entire flow are mainly illustrated), fig. 3 illustrates a schematic diagram of the process of the rhythm analysis and decision according to an embodiment of the present application (in which various signals, states at different moments, and rhythm state analysis considerations, weight assignments, etc. are mainly illustrated), and the foregoing may be better understood according to fig. 2 and 3, which are not repeated herein.
Generally, the rhythm analysis and decision method 100 for a defibrillator according to embodiments of the present application considers not only a short-term rhythm state before a rhythm decision time, but also a long-term rhythm state before the rhythm decision time, and the rhythm state is generally relatively stable in a CPR compression period, and acquires a stable rhythm state in the CPR compression period by focusing on the rhythm state in a long time before the rhythm decision time in the CPR compression period, and simultaneously, in order to timely respond to local rhythm fluctuations, focuses on the rhythm state in a short time before the rhythm decision time in the CPR compression period, acquires a short-term transient rhythm state, synthesizes the long-term stable rhythm state and the short-term transient rhythm state, makes a rhythm decision, and instructs emergency personnel to perform emergency treatment.
Based on the above description, the method 100 for analyzing and deciding a rhythm for a defibrillator according to an embodiment of the present application determines a rhythm decision in combination with long-time rhythm state features and short-time rhythm state features, and can avoid being subjected to local disturbance and insensitive to local rhythm fluctuations, thereby enabling more reliable rhythm decisions. In addition, as different rhythm analysis modes are selected according to the electrocardiosignals in different states, the accuracy of the rhythm analysis result, namely the segment rhythm state, can be further improved, and the reliability of the rhythm decision can be further improved.
A method 400 of rhythm analysis and decision making for a defibrillator according to another embodiment of the present application is described below in conjunction with fig. 4. As shown in fig. 4, a rhythm analysis and decision method 400 for a defibrillator may include the steps of:
in step S410, a reference signal during cardiopulmonary resuscitation of a target object and an original electrocardiographic signal of the target object are obtained.
In step S420, the reference signal is subjected to compression detection, so as to obtain a time-domain compression event flag of the reference signal.
In step S430, an instantaneous compression interval is determined based on the time-domain compression event markers, and the original electrocardiograph signal is filtered based on the instantaneous compression interval to obtain a filtered electrocardiograph signal.
In step S440, the electrocardiographic signal of the target object is divided into a plurality of analysis regions in a time sequence, and each analysis region is subjected to rhythm analysis to obtain a segment rhythm state of each analysis region, where the electrocardiographic signal of the target object only includes the filtered electrocardiographic signal, or the electrocardiographic signal of the target object includes the original electrocardiographic signal and the filtered electrocardiographic signal.
In step S450, long-term rhythm analysis is performed based on the segment rhythm states of the plurality of analysis regions within a first preset time period from the rhythm decision time to obtain long-term rhythm state characteristics.
In step S460, a short-time rhythm analysis is performed based on the segment rhythm status of at least one analysis region in a second preset time period from the rhythm decision time, so as to obtain a short-time rhythm status feature, where the first preset time period is greater than the second preset time period.
In step S470, a rhythm decision is determined based on the long-term rhythm state feature and the short-term rhythm state feature, and the rhythm decision is output.
In this embodiment, the time-domain compression event markers are obtained by performing compression detection on the reference signal, and the instantaneous compression interval can be determined based on the time-domain compression event markers, so that the original electrocardiograph signal is filtered based on the instantaneous compression interval, and the filtered electrocardiograph signal is obtained. Similar to the previous embodiment, in this embodiment, the electrocardiographic signal of the target object (where the electrocardiographic signal of the target object may include only the filtered electrocardiographic signal, or the electrocardiographic signal of the target object may include the original electrocardiographic signal and the filtered electrocardiographic signal) is still divided into a plurality of analysis regions in a time sequence, and long-term rhythm state analysis and long-short-term rhythm state analysis are performed according to the segment rhythm states of each analysis region, and a rhythm decision is determined by combining the long-term rhythm state feature and the short-term rhythm state feature, so that local disturbance can be avoided, insensitivity to local rhythm fluctuation can be avoided, and thus a more reliable rhythm decision can be obtained. The difference is that in this embodiment, the state corresponding to each analysis region is not required to be determined, but the rhythm analysis is directly performed on each analysis region to obtain the segment rhythm state of each analysis region. Therefore, the present embodiment is partially similar to the foregoing embodiments, only some steps are omitted, and only the operations in the present embodiment are summarized here for brevity, and details of these operations may be found in the foregoing embodiments.
In an embodiment of the present application, performing time-domain compression detection on the reference signal in step S420 to obtain a time-domain compression event flag of the reference signal may include: performing time domain analysis and/or frequency domain analysis on the reference signal to obtain time domain pressing characteristics and/or frequency domain pressing characteristics; and performing compression detection on the reference signal based on the time domain compression characteristic and/or the frequency domain compression characteristic to obtain a time domain compression event marker of the reference signal. In this embodiment, compression detection may be performed based on time domain features, frequency domain features, or a combination of both to derive time domain compression event signatures of the reference signal.
In an embodiment of the present application, similar to the previous embodiment, the long-term rhythm state feature and the short-term rhythm state feature obtained in each of step S450 and step S460 may each include at least one of the following: in the collection of the respective segment rhythm states of the plurality of analysis areas, the proportion of each segment rhythm state is calculated; when the segment rhythm states of the analysis areas are ordered according to time, the proportion of the segment rhythm states is the same continuously for a plurality of times; in the corresponding state sets of the analysis areas, the time ratio of different states and/or the proportion of each segment rhythm state in different states; and in the set of the segment rhythm states of each of the plurality of analysis areas, the weight score of each segment rhythm state of each analysis area depends on the time distance between the analysis area and the rhythm decision moment and/or the state corresponding to the analysis area.
In an embodiment of the present application, similar to the previous embodiment, determining a rhythm decision in step S470 based on the long-term rhythm state feature and the short-term rhythm state feature may include: when the distribution conditions of the segment rhythm states reflected by the long-time rhythm state characteristics and the short-time rhythm state characteristics are consistent, determining a rhythm decision according to the distribution conditions of the segment rhythm states reflected by the long-time rhythm state characteristics or the short-time rhythm state characteristics; and when the distribution conditions of the segment rhythm states reflected by the long-time rhythm state characteristics and the short-time rhythm state characteristics are inconsistent, determining a rhythm decision according to one of the two distribution conditions with higher reliability, or determining a rhythm decision according to the distribution conditions of the segment rhythm states reflected by the short-time rhythm state characteristics, or outputting an uncertain rhythm decision. Alternatively, determining a rhythm decision based on the long-term rhythm state feature and the short-term rhythm state feature in step S470 may include: for each segment rhythm state, obtaining a weighted score of the segment rhythm state according to a weighted combination of the characteristic corresponding to the segment rhythm state of the long-time rhythm state characteristic and the characteristic corresponding to the segment rhythm state of the short-time rhythm state characteristic; a rhythm decision is determined based on the weighted scores for each segment's rhythm state.
In an embodiment of the present application, similar to the previously described embodiments, the method 400 can be applied to both a fixed cardiopulmonary resuscitation mode of operation and a continuous cardiopulmonary resuscitation mode of operation, where when applied to the continuous cardiopulmonary resuscitation mode of operation, if the analysis area prior to the timing of the rhythm decision is insufficient for long-term rhythm analysis, the long-term rhythm analysis is not performed, and the rhythm decision is determined from the default initial rhythm state for a preset length and the short-term rhythm state characteristics.
The foregoing illustrates an exemplary method 400 for analyzing and deciding a rhythm for a defibrillator according to an embodiment of the present application, and in order to better understand the method, fig. 5 illustrates an exemplary flow chart (in which links and directions thereof in the entire flow are mainly illustrated) of the rhythm analysis and deciding according to the embodiment, and the content of the foregoing method 400 may be better understood according to the flow chart, which is not described herein. In addition, in still another embodiment of the present application, the above method 400 may omit steps S410 to S430, and directly starts from step S440, where the electrocardiograph signal in step S440 may refer to a conventional ECG band-pass filtered electrocardiograph signal or a CPR filtered electrocardiograph signal. In this embodiment, the electrocardiographic signal may be analyzed as a compression reference signal, as shown in the exemplary flow diagram of fig. 6, which may be a variation of method 400.
Based on the above description, the method 400 for analyzing and deciding a rhythm for a defibrillator and its modification according to the embodiment of the present application determine a rhythm decision in combination with a long-time rhythm state feature and a short-time rhythm state feature, and can avoid being subjected to local disturbance and insensitive to local rhythm fluctuation, thereby enabling a more reliable rhythm decision to be obtained.
The above exemplarily describes a rhythm analysis and decision method for a defibrillator according to an embodiment of the present application. A rhythm analysis and decision device for a defibrillator according to another aspect of the present application is described below in connection with fig. 7. Fig. 7 shows a schematic block diagram of a rhythm analysis and decision device 700 for a defibrillator according to an embodiment of the present application. As shown in fig. 7, a rhythm analysis and decision device 700 for a defibrillator may include a memory 710 and a processor 720, the memory 710 having stored thereon a computer program for execution by the processor 720, which when executed by the processor 720 performs the rhythm analysis and decision method for a defibrillator according to an embodiment of the present application described hereinabove. In a further embodiment of the present application, the rhythm analysis and decision device 700 for a defibrillator may further comprise a signal acquisition component 730 which may be used to acquire an electrocardiographic signal and/or a reference signal related to chest compressions during cardiopulmonary resuscitation of a target subject and to communicate to the processor 720 for execution of the previously described rhythm analysis and decision method for a defibrillator according to embodiments of the present application. In an embodiment of the present application, the device 700 may be a defibrillator. Those skilled in the art will appreciate the structure and operation of the components of the rhythm analysis and decision device 700 for a defibrillator according to embodiments of the present application in conjunction with the foregoing description, and for brevity, will not be described in detail herein.
Furthermore, according to an embodiment of the present application, there is provided a storage medium having stored thereon program instructions for performing the respective steps of the method for rhythm analysis and decision-making of a defibrillator of the embodiments of the present application when the program instructions are executed by a computer or processor. The storage medium may include, for example, a memory card of a smart phone, a memory component of a tablet computer, a hard disk of a personal computer, read-only memory (ROM), erasable programmable read-only memory (EPROM), portable compact disc read-only memory (CD-ROM), USB memory, or any combination of the foregoing storage media. The computer-readable storage medium may be any combination of one or more computer-readable storage media.
Furthermore, according to an embodiment of the present application, there is also provided a computer program, which may be stored on a cloud or local storage medium. Which when executed by a computer or processor is adapted to carry out the respective steps of the method for rhythm analysis and decision making of a defibrillator of an embodiment of the present application.
Based on the above description, the method and the device for analyzing and deciding the rhythm of the defibrillator according to the embodiment of the application combine the long-time rhythm state characteristics and the short-time rhythm state characteristics to determine the rhythm decision, thereby avoiding local disturbance and insensitive to local rhythm fluctuation, and further obtaining more reliable rhythm decision. In addition, the method and the device for analyzing and deciding the rhythm of the defibrillator according to the embodiment of the application can select different rhythm analysis modes according to the electrocardiosignals in different states, and can further improve the accuracy of the rhythm analysis result, namely the segment rhythm state, so as to further improve the reliability of the rhythm decision.
Although the illustrative embodiments have been described herein with reference to the accompanying drawings, it is to be understood that the above illustrative embodiments are merely illustrative and are not intended to limit the scope of the present application thereto. Various changes and modifications may be made therein by one of ordinary skill in the art without departing from the scope and spirit of the application. All such changes and modifications are intended to be included within the scope of the present application as set forth in the appended claims.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical function division, and there may be additional divisions in actual implementation, e.g., multiple elements or components may be combined or integrated into another apparatus, or some features may be omitted, or not performed.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the application may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in order to streamline the application and aid in understanding one or more of the various inventive aspects, various features of the application are sometimes grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of the application. However, the method of the present application should not be construed as reflecting the following intent: i.e., the claimed application requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this application.
It will be understood by those skilled in the art that all of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be combined in any combination, except combinations where the features are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the application and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
Various component embodiments of the application may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functions of some of the modules according to embodiments of the present application may be implemented in practice using a microprocessor or Digital Signal Processor (DSP). The present application can also be implemented as an apparatus program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the present application may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The application may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names.
The above description is merely illustrative of the embodiments of the present application and the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes or substitutions are covered by the protection scope of the present application. The protection scope of the application is subject to the protection scope of the claims.
Claims (26)
- A method of rhythm analysis and decision making for a defibrillator, the method comprising:Acquiring an electrocardiosignal of a target object in the process of carrying out cardiopulmonary resuscitation on the target object;dividing the electrocardiosignal into a plurality of analysis areas on a time sequence, and determining a state corresponding to each analysis area, wherein the state comprises an emergency treatment state and/or a filtering state;for each analysis region, determining a fragment rhythm analysis mode of the analysis region based on a state corresponding to the analysis region, and performing rhythm analysis on the analysis region based on the fragment rhythm analysis mode to obtain a fragment rhythm state of the analysis region;performing long-time rhythm analysis based on the segment rhythm states of a plurality of analysis areas in a first preset time period from the rhythm decision moment to obtain long-time rhythm state characteristics;performing short-time rhythm analysis based on the segment rhythm state of at least one analysis region in a second preset time period from the rhythm decision moment to obtain a short-time rhythm state characteristic, wherein the first preset time period is larger than the second preset time period;determining a rhythm decision based on the long-term rhythm state feature and the short-term rhythm state feature and outputting the rhythm decision.
- The method of claim 1, wherein the emergency treatment states include a compression progress state, a compression transition state, and a compression pause state, the filtering states include a filtering-required state and a filtering-unnecessary state, the determining a segment rhythm analysis mode of the analysis region based on the state corresponding to the analysis region includes:when the emergency treatment state of the analysis area is a pressing suspension state and/or the filtering state of the analysis area is a filtering-free state, determining that the fragment rhythm analysis mode of the analysis area is an interference-free mode;and when the emergency treatment state of the analysis area is a pressing progress state or a pressing transition state and the filtering state of the analysis area is a filtering-needed state, determining that the fragment rhythm analysis mode of the analysis area is an interference mode.
- The method of claim 2, wherein the emergency treatment status further comprises a shock status, the determining a segment rhythm analysis mode for the analysis region based on the status corresponding to the analysis region further comprising:and when the emergency treatment state of the analysis area is a shock state, determining the fragment rhythm analysis mode of the analysis area as an initialization mode.
- The method according to claim 2, wherein the electrocardiographic signal comprises an original electrocardiographic signal and a filtered electrocardiographic signal, and in the non-interference mode, a non-interference rhythm strategy is adopted for rhythm analysis based on the original electrocardiographic signal and/or the filtered electrocardiographic signal; and in the interference mode, performing rhythm analysis by adopting an interference rhythm strategy based on the filtered electrocardiosignal only or based on the original electrocardiosignal and the filtered electrocardiosignal.
- The method of claim 2, wherein determining the state corresponding to each analysis region comprises:acquiring a reference signal related to chest compression in the process of carrying out cardiopulmonary resuscitation on a target object;dividing the reference signal into a plurality of sub-analysis areas on a time sequence, and determining the pressing condition corresponding to each sub-analysis area;for each analysis region of the electrocardiograph signal, determining an emergency treatment status of each analysis region based on a compression condition of one or more of the sub-analysis regions corresponding to the analysis region.
- The method of claim 5, wherein the determining the emergency treatment status of each of the analysis areas based on the pressing of one or more of the sub-analysis areas corresponding to the analysis areas comprises:When the pressing condition of each sub-analysis area corresponding to the analysis area is a pressing event, determining that the emergency treatment state of the analysis area is a pressing progress state;when the pressing condition of part of the sub-analysis areas corresponding to the analysis areas is a pressing event, and the pressing condition of the rest of the sub-analysis areas is a pressing event, determining that the emergency treatment state of the analysis areas is a pressing transition state;and when the pressing condition of each sub-analysis area corresponding to the analysis area is that no pressing event exists, determining that the emergency treatment state of the analysis area is a pressing pause state.
- The method of claim 5, wherein determining the compression condition for each sub-analysis area comprises:performing time domain analysis and/or frequency domain analysis on the reference signal to obtain time domain pressing characteristics and/or frequency domain pressing characteristics;and performing compression detection on each sub-analysis region of the reference signal based on the time domain compression characteristic and/or the frequency domain compression characteristic to determine whether a compression event exists in each sub-analysis region.
- The method of claim 2, wherein determining the state corresponding to each analysis region comprises:acquiring a reference signal in the process of carrying out cardiopulmonary resuscitation on the target object;dividing the reference signal into a plurality of sub-analysis areas in a time sequence;and for each analysis region of the electrocardiosignal, carrying out correlation analysis on the noise of the analysis region and the reference signals of one or more sub analysis regions corresponding to the analysis region, determining a filtering mode of the analysis region according to the result of the correlation analysis, and determining the filtering state of the analysis region according to the filtering mode of the analysis region.
- The method of claim 2, wherein the long-term and short-term rhythm state features each comprise at least one of:in the collection of the respective segment rhythm states of the plurality of analysis areas, the proportion of each segment rhythm state is calculated;when the segment rhythm states of the analysis areas are ordered according to time, the proportion of the segment rhythm states is the same continuously for a plurality of times;in the corresponding state sets of the analysis areas, the time ratio of different states and/or the proportion of each segment rhythm state in different states;And in the set of the segment rhythm states of each of the plurality of analysis areas, the weight score of each segment rhythm state of each analysis area depends on the time distance between the analysis area and the rhythm decision moment and/or the state corresponding to the analysis area.
- The method of claim 9, wherein the short-time rhythmic state feature further comprises: the state is the time distance between the analysis area nearest to the rhythm decision time and the percentage of the segment rhythm state in the analysis area in the pressing pause state or the analysis area without filtering state.
- The method of claim 9, wherein for an analysis region:the closer the analysis area is to the rhythm decision time, the greater the weight allocated to the fragment rhythm state of the analysis area; andwhen the emergency treatment state of the analysis area is a pressing pause state or a filtering state is a filtering-free state, a first weight is distributed to the fragment rhythm state of the analysis area;when the emergency treatment state of the analysis area is a pressing progress state and the filtering state is a filtering-required state, assigning a second weight to the segment rhythm state of the analysis area, wherein the second weight is smaller than the first weight;And when the emergency treatment state of the analysis area is a pressing transition state and the filtering state is a filtering-needed state, assigning a third weight to the segment rhythm state of the analysis area, wherein the third weight is smaller than the second weight.
- The method of claim 1, wherein the determining a rhythm decision based on the long-term rhythm state feature and the short-term rhythm state feature comprises:when the distribution conditions of the segment rhythm states reflected by the long-time rhythm state characteristics and the short-time rhythm state characteristics are consistent, determining a rhythm decision according to the distribution conditions of the segment rhythm states reflected by the long-time rhythm state characteristics or the short-time rhythm state characteristics;and when the distribution conditions of the segment rhythm states reflected by the long-time rhythm state characteristics and the short-time rhythm state characteristics are inconsistent, determining a rhythm decision according to one of the two distribution conditions with higher reliability, or determining a rhythm decision according to the distribution conditions of the segment rhythm states reflected by the short-time rhythm state characteristics, or outputting an uncertain rhythm decision.
- The method of claim 12, wherein the reliability of the distribution of the segment rhythm states represented by each of the long-term rhythm state features and the short-term rhythm state features is related to the state of an analysis region employed in each of the long-term rhythm analysis and the short-term rhythm analysis.
- The method of claim 1, wherein the determining a rhythm decision based on the long-term rhythm state feature and the short-term rhythm state feature comprises:for each segment rhythm state, obtaining a weighted score of the segment rhythm state according to the characteristic corresponding to the long-term rhythm state characteristic and the characteristic corresponding to the segment rhythm state and the weighted combination of the short-term rhythm state characteristic and the characteristic corresponding to the segment rhythm state;a rhythm decision is determined based on the weighted scores for each segment's rhythm state.
- The method according to claim 1, wherein the method is applicable to a fixed cardiopulmonary resuscitation mode of operation and a continuous cardiopulmonary resuscitation mode of operation, and when applied to the continuous cardiopulmonary resuscitation mode of operation, if the analysis area prior to the rhythm decision time is not sufficient for the long-term rhythm analysis, the long-term rhythm analysis is not performed, and the rhythm decision is determined from a preset long-term default initial rhythm state and the short-term rhythm state characteristics.
- The method of claim 1, wherein the analysis region has at least one of the following properties:each of the analysis areas has the same length of time or can be changed as desired;Any two of the analysis areas are continuous or intermittent in time;any two of the analysis regions partially overlap in time or do not overlap.
- A method of rhythm analysis and decision making for a defibrillator, the method comprising:acquiring a reference signal and an original electrocardiosignal of a target object in the process of carrying out cardiopulmonary resuscitation on the target object;performing compression detection on the reference signal to obtain a time domain compression event mark of the reference signal;determining an instantaneous compression interval based on the time-domain compression event markers, and filtering the original electrocardiosignals based on the instantaneous compression interval to obtain filtered electrocardiosignals;dividing the electrocardiosignals of the target object into a plurality of analysis areas on a time sequence, and carrying out rhythm analysis on each analysis area to obtain a segment rhythm state of each analysis area, wherein the electrocardiosignals of the target object only comprise the filtered electrocardiosignals, or the electrocardiosignals of the target object comprise the original electrocardiosignals and the filtered electrocardiosignals;performing long-time rhythm analysis based on the segment rhythm states of a plurality of analysis areas in a first preset time period from the rhythm decision moment to obtain long-time rhythm state characteristics;Performing short-time rhythm analysis based on the segment rhythm state of at least one analysis region in a second preset time period from the rhythm decision moment to obtain a short-time rhythm state characteristic, wherein the first preset time period is larger than the second preset time period;determining a rhythm decision based on the long-term rhythm state feature and the short-term rhythm state feature and outputting the rhythm decision.
- The method of claim 17, wherein compression detection of the reference signal to obtain a time-domain compression event signature of the reference signal comprises:performing time domain analysis and/or frequency domain analysis on the reference signal to obtain time domain pressing characteristics and/or frequency domain pressing characteristics;and performing compression detection on the reference signal based on the time domain compression characteristic and/or the frequency domain compression characteristic to obtain a time domain compression event marker of the reference signal.
- The method of claim 17, wherein the long-term and short-term rhythm state features each comprise at least one of:in the collection of the respective segment rhythm states of the plurality of analysis areas, the proportion of each segment rhythm state is calculated;When the segment rhythm states of the analysis areas are ordered according to time, the proportion of the segment rhythm states is the same continuously for a plurality of times;in the corresponding state sets of the analysis areas, the time ratio of different states and/or the proportion of each segment rhythm state in different states;and in the set of the segment rhythm states of each of the plurality of analysis areas, the weight score of each segment rhythm state of each analysis area depends on the time distance between the analysis area and the rhythm decision moment and/or the state corresponding to the analysis area.
- The method of claim 17, wherein the determining a rhythm decision based on the long-term rhythm state feature and the short-term rhythm state feature comprises:when the distribution conditions of the segment rhythm states reflected by the long-time rhythm state characteristics and the short-time rhythm state characteristics are consistent, determining a rhythm decision according to the distribution conditions of the segment rhythm states reflected by the long-time rhythm state characteristics or the short-time rhythm state characteristics;and when the distribution conditions of the segment rhythm states reflected by the long-time rhythm state characteristics and the short-time rhythm state characteristics are inconsistent, determining a rhythm decision according to one of the two distribution conditions with higher reliability, or determining a rhythm decision according to the distribution conditions of the segment rhythm states reflected by the short-time rhythm state characteristics, or outputting an uncertain rhythm decision.
- The method of claim 17, wherein the determining a rhythm decision based on the long-term rhythm state feature and the short-term rhythm state feature comprises:for each segment rhythm state, obtaining a weighted score of the segment rhythm state according to the characteristic corresponding to the long-term rhythm state characteristic and the characteristic corresponding to the segment rhythm state and the weighted combination of the short-term rhythm state characteristic and the characteristic corresponding to the segment rhythm state;a rhythm decision is determined based on the weighted scores for each segment's rhythm state.
- The method according to claim 17, wherein the method is applicable to a fixed cardiopulmonary resuscitation mode of operation and a continuous cardiopulmonary resuscitation mode of operation, and when applied to the continuous cardiopulmonary resuscitation mode of operation, if the analysis area prior to the rhythm decision time is insufficient for the long-term rhythm analysis, the long-term rhythm analysis is not performed, and the rhythm decision is determined from a preset long-term default initial rhythm state and the short-term rhythm state characteristics.
- A rhythm analysis and decision device characterized in that it comprises a memory and a processor, said memory having stored thereon a computer program to be run by said processor, said computer program, when run by said processor, performing the rhythm analysis and decision method for a defibrillator according to any of claims 1-22.
- The apparatus of claim 23, further comprising a signal acquisition component for acquiring a reference signal associated with chest compressions during cardiopulmonary resuscitation of a target subject.
- The device of claim 24, wherein the device is a defibrillator.
- A storage medium having stored thereon a computer program which, when run, performs the rhythm analysis and decision method for a defibrillator according to any one of claims 1-22.
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| PCT/CN2021/140965 WO2023115482A1 (en) | 2021-12-23 | 2021-12-23 | Rhythm analysis and decision-making method and apparatus for defibrillator, and storage medium |
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| US6961612B2 (en) * | 2003-02-19 | 2005-11-01 | Zoll Medical Corporation | CPR sensitive ECG analysis in an automatic external defibrillator |
| GB2446826A (en) * | 2007-02-20 | 2008-08-27 | Laerdal Medical As | Resuscitation decision support |
| US9308383B2 (en) * | 2010-03-12 | 2016-04-12 | Schiller Medical S.A.S. | Method, apparatus and computer program for defibrillation delivery decision |
| US9126055B2 (en) * | 2012-04-20 | 2015-09-08 | Cardiac Science Corporation | AED faster time to shock method and device |
| US9919160B2 (en) * | 2013-03-13 | 2018-03-20 | Koninklijke Philips N.V. | Method and apparatus for scoring the reliability of shock advisory during cardiopulmonary resuscitation |
| CN108025179A (en) * | 2015-06-30 | 2018-05-11 | 皇家飞利浦有限公司 | The device determined for the electric shock cancelled in automated external defibrillator |
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