WO2023115483A1 - Procédé et dispositif de détection de compression pour réanimation cardio-pulmonaire, et support de stockage - Google Patents

Procédé et dispositif de détection de compression pour réanimation cardio-pulmonaire, et support de stockage Download PDF

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WO2023115483A1
WO2023115483A1 PCT/CN2021/140966 CN2021140966W WO2023115483A1 WO 2023115483 A1 WO2023115483 A1 WO 2023115483A1 CN 2021140966 W CN2021140966 W CN 2021140966W WO 2023115483 A1 WO2023115483 A1 WO 2023115483A1
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compression
frequency
domain
pressing
time
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PCT/CN2021/140966
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English (en)
Chinese (zh)
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黄飞云
蒋浩宇
洪俊标
胡咪咪
何先梁
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深圳迈瑞生物医疗电子股份有限公司
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Priority to PCT/CN2021/140966 priority Critical patent/WO2023115483A1/fr
Priority to CN202180075062.7A priority patent/CN116801808A/zh
Publication of WO2023115483A1 publication Critical patent/WO2023115483A1/fr

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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
    • A61B5/25—Bioelectric electrodes therefor
    • A61B5/279—Bioelectric electrodes therefor specially adapted for particular uses
    • A61B5/28—Bioelectric electrodes therefor specially adapted for particular uses for electrocardiography [ECG]

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  • the present application relates to the technical field of cardiopulmonary resuscitation (CPR) compression detection, and more specifically relates to a compression detection method, device and storage medium for cardiopulmonary resuscitation.
  • CPR cardiopulmonary resuscitation
  • CPR chest compression detection and filtering technology can detect compression indicators such as compression frequency based on compression-related reference signals, and give emergency personnel feedback on compression quality.
  • Electrocardiograph (ECG for short) signal interference restores the original ECG waveform to a certain extent.
  • emergency personnel can adjust the compression operation quality in time through the compression quality feedback such as the compression frequency, and can also observe the filtered ECG waveform to obtain the patient's physical status information, reducing the interruption time of CPR, thereby improving the success of rescue Rate.
  • some rhythm analysis algorithms can also analyze the filtered ECG waveform and give suggestions for electric shock decisions.
  • the research on CPR chest compression detection and filtering technology mainly relies on the CPR sensor, which requires an additional sensor signal as a compression reference signal for compression detection and filtering.
  • some literature proposes to use one or more of the sensor signals of chest compression displacement/compression velocity/compression acceleration generated by CPR compression as the compression reference signal, and some literature also proposes the comprehensive sensor signal and chest impedance transformation as the reference signal.
  • Different filtering models perform CPR interference filtering on ECG signals.
  • the above-mentioned methods require additional sensor attachments, which increase additional costs, and the sensor has a poor feel when pressed, limited application scenarios, and poor user experience.
  • a compression detection method for cardiopulmonary resuscitation comprising: acquiring a reference signal related to chest compressions during cardiopulmonary resuscitation of a target object and an ECG signal of the target object; Performing frequency domain analysis on the reference signal to obtain frequency domain compression features; performing time domain analysis on the reference signal to obtain time domain compression features; analyzing the reference signal based on the frequency domain compression features and the time domain compression features performing time-domain compression detection to obtain a time-domain compression event marker of the reference signal; determining an instantaneous compression interval based on the time-domain compression event marker, and filtering the ECG signal based on the instantaneous compression interval, In order to obtain the filtered ECG signal.
  • the method includes: providing a first detection mode and a second detection mode; The compression frequency detected by the cardiopulmonary resuscitation sensor during the resuscitation process; when in the second detection mode, obtain a reference signal related to chest compressions during the cardiopulmonary resuscitation process for the target object, and perform frequency domain analysis on the reference signal to obtain A frequency-domain compression feature is obtained, a compression frequency is determined based on the frequency-domain compression feature, and feedback information of a compression quality related to the compression frequency is output.
  • a compression detection device for cardiopulmonary resuscitation includes a memory and a processor, the memory stores a computer program run by the processor, and the computer program is processed by the The compression detection method for performing the above-mentioned cardiopulmonary resuscitation when the device is running.
  • a storage medium where a computer program is stored on the storage medium, and the computer program executes the above compression detection method for cardiopulmonary resuscitation when running.
  • the compression event markers in the time domain are obtained through combined analysis of the time domain and the frequency domain, which can avoid the problems of compression frequency error and filtered ECG distortion caused by false detection and missed detection of compression events,
  • the CPR interference filtering of the ECG signal based on the obtained effective compression event markers can effectively improve the CPR filtering performance of the ECG signal, and better guide emergency personnel to carry out first aid.
  • Fig. 1 shows a schematic flowchart of a compression detection method for cardiopulmonary resuscitation according to an embodiment of the present application.
  • Fig. 2 shows an example time-domain diagram of reference signals related to chest compressions acquired in the compression detection method for cardiopulmonary resuscitation according to an embodiment of the present application.
  • Fig. 3 shows an example diagram in the frequency domain of a reference signal related to chest compressions obtained in the compression detection method for cardiopulmonary resuscitation according to an embodiment of the present application.
  • Fig. 4 shows an example diagram of a position of a compression event of a reference signal in a compression detection method for cardiopulmonary resuscitation according to an embodiment of the present application.
  • Fig. 5 shows an example of a display interface for displaying parameters in the compression detection method for cardiopulmonary resuscitation according to an embodiment of the present application.
  • FIG. 6 shows an exemplary flowchart of CPR chest compression detection and filtering according to the embodiment shown in FIG. 1 .
  • FIG. 7 shows another exemplary flowchart of CPR chest compression detection and filtering according to the embodiment shown in FIG. 1 .
  • Fig. 8 shows a schematic flowchart of a compression detection method for cardiopulmonary resuscitation according to another embodiment of the present application.
  • Fig. 9 shows a schematic block diagram of a compression detection device for cardiopulmonary resuscitation according to an embodiment of the present application.
  • FIG. 1 shows a schematic flowchart of a compression detection method 100 for cardiopulmonary resuscitation according to an embodiment of the present application.
  • the compression detection method 100 for cardiopulmonary resuscitation may include the following steps:
  • step S110 a reference signal related to chest compressions during cardiopulmonary resuscitation of the target object and an electrocardiographic signal of the target object are acquired.
  • step S120 a frequency-domain analysis is performed on the reference signal to obtain frequency-domain pressing features.
  • step S130 a time-domain analysis is performed on the reference signal to obtain a time-domain pressing feature.
  • step S140 time-domain compression detection is performed on the reference signal based on the frequency-domain compression feature and the time-domain compression feature, so as to obtain a time-domain compression event marker of the reference signal.
  • step S150 the instantaneous compression interval is determined based on the time-domain compression event marker, and the electrocardiographic signal is filtered based on the instantaneous compression interval to obtain a filtered electrocardiographic signal.
  • a reference signal related to chest compressions (hereinafter referred to as reference signal) during cardiopulmonary resuscitation of the target object, such as at least one of the following: chest impedance signal, blood oxygen signal, Respiration signal as well as signal sensed by the CPR sensor.
  • the signal sensed by the CPR sensor may include at least one of a pressure signal, a displacement signal, a velocity signal and an acceleration signal, for example.
  • frequency domain analysis and time domain analysis are performed on the reference signal respectively, so as to obtain frequency domain compression characteristics and time domain compression characteristics of the reference signal respectively.
  • step S120 and step S130 in FIG. 1 the order of the two is not necessarily the same, and they can be interchanged or performed at the same time.
  • the time-domain compression detection is performed on the reference signal based on the frequency-domain compression feature and the time-domain compression feature, that is, the time-domain compression event marker of the reference signal is obtained through combined analysis of the time domain and the frequency domain.
  • reference signals such as chest impedance signals are not relatively regular and stable in shape like CPR sensor signals, they are easily affected by individuals and compressions, and large morphological changes may occur in the same body or between different individuals. In some cases, compressions cause The time-domain signal of the chest impedance signal appears low-amplitude, bimodal or even multi-peak. Therefore, if the compression detection is performed on a reference signal such as the chest impedance signal only in the time domain, compression events may be missed or falsely detected.
  • the compression detection of a reference signal such as the chest impedance signal in the frequency domain is not as precise as the detection result in the time domain, and it is difficult to guarantee the performance of compression detection and filtering. Therefore, the pressing detection method according to the embodiment of the present application can avoid the occurrence of pressing events in some cases such as low amplitude, bimodal or even multimodal forms of reference signals such as chest impedance signals in the time domain through combined analysis of time domain and frequency domain. False detections and missed detections lead to compression frequency errors and ECG distortion after filtering. Based on the obtained effective compression event marks on the reference signal for CPR interference filtering, it can effectively improve the ECG signal CPR filtering performance.
  • the compression detection method 100 for cardiopulmonary resuscitation will be described in more detail below.
  • the signal of no concern outside the pressing frequency band range (for example, 100-120 times/minute (count per minute, cpm for short)) can be filtered out through a band-pass filter; Then, the filtered reference signal can be calculated in the frequency domain by Fast Fourier Transform (FFT) to obtain the band-selected spectrum, and finally the amplitude-frequency characteristics of the reference signal in the frequency band of interest can be obtained; after that, based on Such a spectrogram acquires frequency-domain pressing features, such as at least one of the following: at least one of instantaneous pressing frequency, spectral amplitude corresponding to the instantaneous pressing frequency, and pressing harmonic component features.
  • FFT Fast Fourier Transform
  • all frequency components and their corresponding amplitudes within the compression frequency band can be detected based on the spectrogram of the reference signal, frequency domain characteristics such as the frequency position and amplitude of each frequency component can be analyzed, and the fundamental frequency of the compression can be determined. That is, the instantaneous compression frequency, and the amplitude corresponding to the frequency can be called the frequency-domain compression peak amplitude.
  • the characteristics of the compression harmonic components can be obtained, and the time-domain peak shape of the obtained reference signal can be inferred (such as no compression peak, single compression peak, double compression peak, etc.). compression peaks, multiple compression peaks, etc.).
  • FIG. 2 and FIG. 3 respectively show examples of the time-domain waveform and frequency spectrum of a reference signal (taking a multimodal chest impedance signal as an example) obtained in the compression detection method according to the embodiment of the present application.
  • the reference signal is a chest impedance signal waveform collected from a cardiopulmonary resuscitation patient when the compression frequency is about 110 cpm, and the spectrogram is obtained by FFT calculation. From the time-domain waveform, one CPR compression produces multiple peaks on the impedance waveform.
  • the pressing fundamental frequency (as shown in Figure 3, the abscissa X is 1.758, and the ordinate Y is the frequency component corresponding to 0.2034), that is, the actual pressing frequency.
  • the pressing fundamental frequency As shown in Figure 3, the abscissa X is 1.758, and the ordinate Y is the frequency component corresponding to 0.2034), that is, the actual pressing frequency.
  • the pressing frequency band Within the range, it can also be seen that there are a plurality of frequency components with relatively large spectral amplitudes, and their respective frequency magnitudes are all multiples of the pressing fundamental frequency, which are called pressing harmonics (such as the abscissa X shown in Figure 3 are respectively 3.589, 5.396 and 7.19 compression harmonics).
  • the fundamental frequency and harmonic component characteristics of the compression can be determined through the frequency domain analysis, so that the frequency domain compression feature can assist the time domain compression peak detection (described below).
  • pressing peak detection in fact, pressing events may also occur at valleys instead of peaks (described below), therefore, the pressing detection in this application is described as pressing peak detection in some examples, Described in some examples as press valley detection, they are collectively referred to as press event detection.
  • the above is the acquisition process of the frequency domain pressing feature.
  • the time-domain pressing feature and the detection of the time-domain pressing event based on the time-domain pressing feature are described below.
  • the time-domain compression characteristics obtained by performing time-domain analysis on the reference signal may include at least one of the following: compression interval, compression amplitude, and single-compression duration.
  • the chest impedance signal can be preprocessed with a band-pass filter to filter out unconcerned signals outside the compression frequency range (such as impedance fluctuations caused by breathing), and the filtered
  • the chest impedance signal searches for markers of compression events (peaks or troughs) based on time-domain compression signatures.
  • compression events can be retrieved based on prior knowledge of time-domain compression characteristics, where the prior knowledge refers to the range of impedance amplitude changes caused by compressions proposed by the American Heart Association (AHA) guidelines for cardiopulmonary resuscitation, published literature, or open technologies , impedance peak width range, and recommended compression frequency and other information; in the later stage of the search, these prior knowledge can be combined to continuously learn the time-domain compression features searched in the early stage, and finally optimize and adjust the compression event search strategy to detect chest impedance signals Time-domain compression event markers for .
  • AHA American Heart Association
  • the time domain pressing event search includes time domain pressing peak search; when it is determined that the time domain pressing event occurs at the time domain trough position, the time domain Compression event searches include time-domain compression trough searches.
  • the time-domain pressing event detection strategy will also automatically distinguish the time-domain waveform of the reference signal according to the data characteristics of the reference signal (including but not limited to the time-domain peak amplitude and time-domain valley amplitude) within a period of time. Specifically, whether the peak represents the position of the pressing event or the trough represents the position of the pressing event (as mentioned above), so that the time-domain pressing event detection strategy is adjusted to search for the peak or the trough to obtain a more accurate position of the pressing event (time-domain pressing event mark).
  • the upper part of the figure is the impedance waveform, and its trough corresponds to the peak of the gold standard (the pressure signal collected by the sensor, that is, the waveform in the lower part of Figure 4), which is more accurate than the peak of the impedance waveform.
  • the time domain compression detection is performed on the reference signal based on the frequency domain compression feature and the time domain compression feature, so as to obtain the time domain compression event marker of the reference signal.
  • the time-domain compression event search may be performed based on the time-domain compression features, and the time-domain compression event search may be optimized and adjusted based on the frequency-domain compression features, so as to obtain the time-domain compression event marker of the reference signal.
  • the time-domain compression event search based on the time-domain compression features has been described above, and the optimization and adjustment of the time-domain compression event search based on the frequency-domain compression features will be described below.
  • optimizing and adjusting the search for pressing events based on frequency-domain pressing features may include at least one of the following: adjusting the threshold value of the pressing interval for time-domain pressing event search based on the instantaneous pressing frequency; The frequency-corresponding frequency spectrum amplitude adjusts the threshold value of the compression amplitude in the time-domain compression event search; adjusts the threshold value of the single-press duration in the time-domain compression event search based on the instantaneous compression frequency and the characteristics of the harmonic component of the compression.
  • the fundamental frequency adjusts the interval threshold of pressing the peak (valley) in the time domain
  • there is only one pressing event in the interval threshold time window that is, only one peak (valley) representing the compression
  • the peak amplitude adjusts the threshold value of the peak (valley) amplitude in the time domain search.
  • the peak (valley) whose amplitude is below the amplitude threshold does not represent a real pressing event, that is, an invalid peak (valley); another example, by pressing the fundamental frequency and harmonic components Adjust the threshold of the time-domain peak (valley) width.
  • the duration of a single press event should be between the upper threshold and the lower threshold, that is, the width of an effective peak (valley) should be within the upper and lower limits.
  • the instantaneous pressing interval can be determined, and the ECG signal of the target subject can be filtered based on the instantaneous pressing interval to obtain a filtered ECG signal. Since the effective compression event markers on the reference signal are obtained based on the compression features in the time domain and the compression features in the frequency domain, the CPR interference filtering based on them can effectively improve the CPR filtering performance of the ECG signal.
  • a correlation analysis can be performed on the noise of the ECG signal and the reference signal, and the filtering mode can be determined according to the result of the correlation analysis, so as to Used for filtering.
  • the ECG signal is implemented with adaptive CPR interference filtering using a least mean square (Least Mean Square, referred to as LMS) adaptive filter; wherein, before implementing adaptive CPR interference filtering, the ECG waveform noise and Correlation analysis is performed on the reference signal, and according to the noise state of the ECG waveform, it is judged which filtering mode should be used for filtering the ECG waveform, and the order of the adaptive filter is controlled to achieve a better filtering effect.
  • LMS least mean square
  • the ECG waveform after ECG anti-CPR interference filtering can be displayed on the user interface in real time, such as the ECG waveform after CPR interference filtering shown in the lower left side of Figure 5 (the waveform before filtering can also be shown in Figure 5 See, as shown in the upper left side of Figure 5), to help emergency personnel observe the patient's physical status information in real time during the compression process, and reduce the compression interruption time.
  • rhythm analysis based on the filtered ECG signal; obtain the rhythm state during compression based on the result of the rhythm analysis; output an electric shock decision based on the rhythm state.
  • the ECG waveform after ECG anti-CPR interference filtering can reflect the rhythm state of the real ECG waveform to a certain extent. Therefore, it can participate in rhythm analysis, obtain the rhythm state during the compression process, give electric shock decisions, assist emergency personnel to perform first aid operations, and reduce compression interruptions. time.
  • the compression frequency can also be determined based on the frequency-domain compression characteristics, and feedback information about the compression quality related to the compression frequency can be output, such as the numerical value of the compression frequency and/or the prompt of the compression speed, for example, as shown in 5 shows that the pressing frequency is 146 cpm on the display interface (in addition, the display interface shown in FIG. 5 also shows information related to ECG signals).
  • determining the compression frequency based on frequency-domain compression characteristics may include: determining multiple instantaneous compression frequencies based on reference signals of multiple time periods; and determining a final compression frequency based on the multiple instantaneous compression frequencies. For example, a weighted average, a geometric average, or a median is performed on multiple instantaneous pressing frequencies to obtain the final pressing frequency.
  • the compression frequency can be obtained only by using the frequency domain compression features.
  • the pressing frequency before determining the pressing frequency based on the frequency domain pressing feature, it may also be determined whether the frequency domain pressing feature satisfies a reliability threshold; when the frequency domain pressing feature satisfies the reliability threshold condition, the pressing frequency is determined based on the frequency domain pressing feature.
  • reliability detection is performed on the frequency-domain compression features first, and then the compression frequency is determined based on the frequency-domain compression features when it is determined to be reliable, which can improve the accuracy of the determination result of the compression frequency.
  • the frequency-domain compression features do not meet the reliability threshold conditions, for example, the frequency-domain compression peak amplitude is extremely small or the instantaneous compression frequency is unreasonable, these frequency-domain compression features are unreliable features, and the ECG signal of the target object can be analyzed at this time. Analyze to obtain ECG characteristics (such as heart rate, heart rate frequency peak amplitude, heart rate frequency band energy ratio, ECG frequency peak amplitude, ECG compression frequency band peak energy ratio, etc.
  • ECG characteristics such as heart rate, heart rate frequency peak amplitude, heart rate frequency band energy ratio, ECG frequency peak amplitude, ECG compression frequency band peak energy ratio, etc.
  • the pressing feature determines whether the frequency domain pressing feature that does not meet the reliability threshold condition is caused by pressing; when it is determined that the frequency domain pressing feature that does not meet the reliability threshold condition is caused by pressing, modify the frequency based on the ECG pressing feature domain pressing feature, so that the modified frequency domain pressing feature satisfies the reliability threshold condition, and the pressing frequency is determined based on the modified frequency domain pressing feature.
  • the frequency-domain pressing feature when it is determined that the frequency-domain pressing feature that does not meet the reliability threshold condition is not caused by pressing, the frequency-domain pressing feature can be deleted; when it cannot be determined whether the frequency-domain pressing feature that does not meet the reliability threshold condition is caused by pressing If so, the frequency-domain compression feature can be retained, and the compression frequency can be determined based on the frequency-domain compression feature.
  • the compression frequency may also be determined based on the frequency-domain compression features and the time-domain compression event markers, and feedback information of compression quality related to the compression frequency may be output.
  • the first instantaneous pressing frequency can be determined based on the frequency domain pressing characteristics; the second instantaneous pressing frequency can be determined based on the time domain pressing event marker; reliability analysis is performed on the first instantaneous pressing frequency and the second instantaneous pressing frequency respectively; based on The results of the reliability analysis take the first instantaneous pressing frequency, the second instantaneous pressing frequency or the combination of both as the third instantaneous pressing frequency; repeat the above process for the reference signals of multiple time periods to obtain multiple third instantaneous pressing Frequency: performing weighted average, geometric mean or median on multiple third instantaneous pressing frequencies to obtain the final pressing frequency.
  • the pressing frequency is determined based on the frequency-domain pressing feature and the time-domain pressing event marker, so that a more accurate pressing frequency can be obtained.
  • FIG. 6 shows an exemplary flow chart of CPR chest compression detection and filtering (with reference signal as The impedance signal is taken as an example, and the pressing event is described as a pressing peak as an example), and the content described above can be better understood according to the flow chart.
  • FIG. 7 shows another exemplary flowchart of CPR chest compression detection and filtering.
  • the compression detection method for cardiopulmonary resuscitation obtains time domain compression event markers through combined analysis of time domain and frequency domain, which can avoid reference signals such as chest impedance signals in the time domain.
  • reference signals such as chest impedance signals in the time domain.
  • false detection and missed detection of compression events may lead to incorrect compression frequency and ECG distortion after filtering.
  • CPR interference filtering is performed on ECG signals based on the obtained effective compression event markers, which can effectively improve The CPR filtering performance of ECG signal can better guide emergency personnel to carry out first aid.
  • a compression detection method 800 for cardiopulmonary resuscitation will be described below with reference to FIG. 8 .
  • the compression detection method 800 for cardiopulmonary resuscitation may include the following steps:
  • step S810 a first detection mode and a second detection mode are provided.
  • step S820 when in the first detection mode, acquire and output the compression frequency detected by the cardiopulmonary resuscitation sensor during the cardiopulmonary resuscitation process of the target object.
  • step S830 when in the second detection mode, acquire reference signals related to chest compressions during cardiopulmonary resuscitation of the target object, perform frequency domain analysis on the reference signals to obtain frequency domain compression features, and obtain frequency domain compression features based on frequency domain compression
  • the feature determines the frequency of compressions and outputs feedback on the quality of the compressions relative to the frequency of compressions.
  • two detection modes are provided, one detection mode obtains the compression frequency through the CPR sensor, and the other detection mode determines the compression frequency through the frequency domain compression characteristics of the reference signal (as described in the previous embodiment). Therefore, users can choose different detection modes according to their needs, and realize flexible switching.
  • a third detection mode may also be provided.
  • determining the third pressing frequency based on the first pressing frequency and the second pressing frequency may include: averaging or weighted averaging the first pressing frequency and the second pressing frequency to obtain the third pressing frequency; One of the frequency and the second pressing frequency is determined as the third pressing frequency.
  • a new pressing frequency is obtained by combining the pressing frequency obtained in the first detection mode and the pressing frequency obtained in the second detection mode, and a more accurate pressing frequency can be obtained.
  • time-domain analysis when in the second detection mode, can also be performed on the reference signal to obtain time-domain compression features; time-domain analysis is performed on the reference signal based on the frequency-domain compression features and time-domain compression features. Press detection to obtain the time-domain press event marker of the reference signal; determine the instantaneous press interval based on the time-domain press event marker, and filter the ECG signal based on the instantaneous press interval to obtain the filtered ECG signal.
  • This embodiment is the same as the embodiment described above in conjunction with FIG. 1 , and for the sake of brevity, details are not repeated here.
  • performing time-domain press detection on the reference signal based on the frequency-domain press feature and the time-domain press feature, so as to obtain a time-domain press event marker of the reference signal includes: performing Searching for a time-domain compression event, and optimizing and adjusting the time-domain compression event search based on the frequency-domain compression feature, so as to obtain a time-domain compression event marker of the reference signal.
  • the frequency-domain pressing feature includes at least one of the following: instantaneous pressing frequency, spectral amplitude corresponding to the instantaneous pressing frequency, pressing harmonic component features; the time-domain pressing feature includes at least one of the following: a single pressing lasts Time, pressing amplitude, and pressing width; said optimizing and adjusting said pressing event search based on said frequency-domain pressing feature includes at least one of the following: adjusting said time-domain pressing event search based on said instantaneous pressing frequency
  • the threshold of the compression interval adjust the threshold of the compression amplitude of the time-domain compression event search based on the frequency spectrum corresponding to the instantaneous compression frequency; adjust the time-domain compression based on the instantaneous compression frequency and the characteristics of the harmonic component of the compression Threshold for single press duration for event search.
  • the time domain press event search includes the time domain press peak search; when it is determined that the time domain press event occurs at the time domain valley position, the time domain press event search includes the time domain press event search Press the trough to search.
  • the frequency-domain pressing feature may include an instantaneous pressing frequency
  • the determining the pressing frequency based on the frequency-domain pressing feature may include: determining multiple instantaneous pressing frequencies based on the reference signals of multiple time periods; The multiple instantaneous compression rates determine the final compression rate.
  • the determining the final pressing frequency based on the multiple instantaneous pressing frequencies may include: performing a weighted average, a geometric mean or a median calculation on the multiple instantaneous pressing frequencies to obtain the final pressing frequency.
  • the reference signal includes at least one of the following: a chest impedance signal, a blood oxygen signal, a respiratory signal, and a signal sensed by a cardiopulmonary resuscitation sensor, wherein the signal sensed by the cardiopulmonary resuscitation sensor includes a pressure signal, a displacement signal, At least one of a velocity signal and an acceleration signal.
  • the filtered ECG signal can also be displayed in real time.
  • rhythm analysis based on the filtered ECG signal; obtain a rhythm state during compression based on the result of the rhythm analysis; and output an electric shock decision based on the rhythm state.
  • FIG. 9 shows a schematic block diagram of a compression detection device 900 for cardiopulmonary resuscitation according to an embodiment of the present application.
  • the compression detection device 900 for cardiopulmonary resuscitation may include a memory 910 and a processor 920.
  • the memory 910 stores a computer program run by the processor 920.
  • the cardiopulmonary resuscitation compression detection device 900 may also include a signal collection device 930, which may be used to collect reference signals related to chest compressions during the cardiopulmonary resuscitation process of the target object, and transmit them to
  • the processor 920 is configured to execute the compression detection method for cardiopulmonary resuscitation according to the embodiment of the present application.
  • the storage medium may include, for example, a memory card of a smart phone, a storage unit of a tablet computer, a hard disk of a personal computer, a read only memory (ROM), an erasable programmable read only memory (EPROM), a portable compact disk read only memory (CD), etc. -ROM), USB memory, or any combination of the above storage media.
  • the computer readable storage medium can be any combination of one or more computer readable storage medium.
  • a computer program is also provided, and the computer program may be stored in the cloud or on a local storage medium.
  • the computer program is run by a computer or a processor, it is used to execute the corresponding steps of the compression detection method for cardiopulmonary resuscitation according to the embodiment of the present application.
  • the compression event markers in the time domain can be obtained through combined analysis of the time domain and the frequency domain, which can avoid the low amplitude of reference signals such as chest impedance signals in the time domain.
  • reference signals such as chest impedance signals
  • false detection and missed detection of compression events may lead to incorrect compression frequency and ECG distortion after filtering.
  • CPR interference filtering is performed on ECG signals based on the obtained effective compression event markers, which can Effectively improve the CPR filtering performance of ECG signals, and better guide emergency personnel to carry out first aid.
  • the compression detection method and device for cardiopulmonary resuscitation can provide two detection modes, one detection mode obtains the compression frequency through the CPR sensor, and the other detection mode determines the compression frequency through the frequency domain compression characteristics of the reference signal , users can choose different detection modes according to their needs to achieve flexible switching.
  • the disclosed devices and methods may be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components can be combined or integrated. to another device, or some features may be ignored, or not implemented.
  • the various component embodiments of the present application may be realized in hardware, or in software modules running on one or more processors, or in a combination thereof.
  • a microprocessor or a digital signal processor (DSP) may be used in practice to implement some or all functions of some modules according to the embodiments of the present application.
  • DSP digital signal processor
  • the present application can also be implemented as an apparatus program (for example, a computer program and a computer program product) for performing a part or all of the methods described herein.
  • Such a program implementing the present application may be stored on a computer-readable medium, or may be in the form of one or more signals.
  • Such a signal may be downloaded from an Internet site, or provided on a carrier signal, or provided in any other form.

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Abstract

Procédé et dispositif de détection de compression pour réanimation cardio-pulmonaire, et support de stockage. Le procédé consiste à : acquérir un signal de référence associé à une compression thoracique et un signal d'électrocardiogramme d'un sujet cible lors de la mise en œuvre d'une réanimation cardio-pulmonaire chez un sujet cible (S110) ; effectuer une analyse dans le domaine fréquentiel sur le signal de référence pour obtenir une caractéristique de compression dans le domaine fréquentiel (S120) ; effectuer une analyse dans le domaine temporel sur le signal de référence pour obtenir une caractéristique de compression dans le domaine temporel (S130) ; effectuer une détection de compression dans le domaine temporel sur le signal de référence sur la base de la caractéristique de compression dans le domaine fréquentiel et de la caractéristique de compression dans le domaine temporel, de façon à obtenir un marqueur d'événement de compression dans le domaine temporel du signal de référence (S140) ; et déterminer un intervalle de compression instantanée sur la base du marqueur d'événement de compression dans le domaine temporel, et filtrer le signal d'électrocardiogramme sur la base de l'intervalle de compression instantanée pour obtenir un signal d'électrocardiogramme filtré (S150). Le procédé et le dispositif de détection de compression peuvent améliorer efficacement les performances de filtrage CPR du signal ECG.
PCT/CN2021/140966 2021-12-23 2021-12-23 Procédé et dispositif de détection de compression pour réanimation cardio-pulmonaire, et support de stockage WO2023115483A1 (fr)

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CN202180075062.7A CN116801808A (zh) 2021-12-23 2021-12-23 一种心肺复苏的按压检测方法、装置以及存储介质

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