WO2022141119A1 - 生理信号处理方法、装置、监护仪及计算机可读存储介质 - Google Patents

生理信号处理方法、装置、监护仪及计算机可读存储介质 Download PDF

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WO2022141119A1
WO2022141119A1 PCT/CN2020/141082 CN2020141082W WO2022141119A1 WO 2022141119 A1 WO2022141119 A1 WO 2022141119A1 CN 2020141082 W CN2020141082 W CN 2020141082W WO 2022141119 A1 WO2022141119 A1 WO 2022141119A1
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signal
patient
physiological signal
physiological
information
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PCT/CN2020/141082
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English (en)
French (fr)
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何先梁
金星亮
张飞
冯一鸣
肖礼飞
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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 CN202080108006.4A priority Critical patent/CN116669625A/zh
Priority to PCT/CN2020/141082 priority patent/WO2022141119A1/zh
Publication of WO2022141119A1 publication Critical patent/WO2022141119A1/zh

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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
    • A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs

Definitions

  • the present application relates to the technical field of medical equipment, and in particular, to a physiological signal processing method, device, monitor, and computer-readable storage medium.
  • the type of the patient's respiratory disease can be determined by detecting a variety of different information such as the patient's heart rate, pulse oxygen saturation, and respiratory status.
  • ECG electrocardiogram
  • PPG photoplethysmograph
  • CO2 carbon dioxide
  • the ECG signal detects whether the patient's heart rate is stable, detects the patient's pulse oxygen saturation (SpO2, Peripheral Capillary Oxygen Saturation) based on the PPG signal, so as to reflect the patient's current blood oxygen state through the pulse oxygen saturation, and the CO2 signal detects the patient of breathing.
  • the patient's respiratory disease may be determined based on the detected information such as heart rate, pulse oxygen saturation, and breathing conditions.
  • the present application provides a physiological signal processing method, device, monitor and computer-readable storage medium, which can improve the convenience and efficiency of physiological signal processing.
  • an embodiment of the present application provides a physiological signal processing method, including:
  • the breathing state of the patient is determined according to the characteristic information.
  • an embodiment of the present application provides a physiological signal processing device, including:
  • Acquisition equipment for acquiring physiological signals of patients
  • Display used to display the prompt information of the patient's breathing state
  • the processor is used to run the computer program stored in the memory, and implement the aforementioned physiological signal processing method when the computer program is executed.
  • an embodiment of the present application provides a monitor, including:
  • a parameter measurement circuit for connecting the sensor accessories and obtaining the patient's physiological parameter signal
  • Display used to display the prompt information of the patient's breathing state
  • the processor is used to run the computer program stored in the memory, and implement the aforementioned physiological signal processing method when the computer program is executed.
  • an embodiment of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements the foregoing method.
  • the embodiments of the present application provide a physiological signal processing method, device, monitor, and computer-readable storage medium, which can acquire a patient's physiological signal and obtain characteristic information of the physiological signal, and at this time, the patient's breathing state can be determined according to the characteristic information .
  • the solution only needs to determine the patient's breathing state based on the characteristic information of the patient's physiological signal, and does not need to collect multiple signals and detect the multiple signals separately, which improves the convenience and efficiency of the physiological signal processing.
  • FIG. 1 is a schematic flowchart of a physiological signal processing method provided by an embodiment of the present application
  • FIG. 2 is a schematic block diagram of a physiological signal processing apparatus provided by an embodiment of the present application.
  • FIG. 3 is a schematic block diagram of a monitor provided by an embodiment of the present application.
  • FIG. 1 is a schematic flowchart of a physiological signal processing method provided by an embodiment of the present application.
  • the physiological signal processing method can be applied in a physiological signal processing device to determine the patient's breathing state and other processes according to the patient's physiological signal; the type of the physiological signal processing device can be flexibly set according to actual needs, for example, the physiological signal processing method
  • the signal processing device may be a monitor or the like.
  • the physiological signal processing method of the embodiment of the present application includes: acquiring a physiological signal of a patient; acquiring characteristic information of the physiological signal; and determining a breathing state of the patient according to the characteristic information.
  • the patient's breathing state can be determined only based on the characteristic information of the patient's physiological signals, without the need to collect multiple signals and detect the multiple signals separately, which improves the convenience and efficiency of the physiological signal processing.
  • the physiological signal processing method includes steps S110 to S130.
  • the physiological signal processing apparatus such as a monitor
  • a collection device for collecting the physiological signal of the patient, or can be connected in communication with the collection device.
  • the acquisition device may include a photoelectric volume acquisition device, an electrocardiogram acquisition device, and an electromyography acquisition device, but of course, it is not limited thereto.
  • a photoelectric volume acquisition device Through the photoelectric volume acquisition device, the patient's photoelectric volume signal can be collected; through the ECG acquisition device, the patient's ECG signal can be collected; through the electromyography acquisition device, the patient's electromyographic signal can be collected.
  • the photoplethysmographic acquisition device can collect the photoplethysmographic signal of the patient's finger, forehead, ear, wrist or neck through the photovolume sensor, or it can be called photoplethysmograph (PPG).
  • PPG photoplethysmograph
  • the photoplethysmographic signals collected at the corresponding parts may be respectively referred to as finger-end photoplethysmography signals, ear photoplethysmography signals, forehead photoplethysmography signals, and the like.
  • the ECG acquisition device may acquire the ECG signal (ECG, Electrocardiogram) of the patient through an ECG acquisition chip and/or an ECG acquisition circuit.
  • ECG acquisition device can collect the patient's electromyography signal (EMG) or surface electromyography signal (SEMG) through needle electrodes or electrode patches.
  • ECG electromyography signal
  • SEMG surface electromyography signal
  • a single channel of physiological signals from a patient can be acquired.
  • the acquiring a single-channel physiological signal of the patient includes acquiring a photovolume signal of the patient.
  • a photovolume acquisition device For example, through a photovolume acquisition device, the photovolume signal of the corresponding part of the patient's finger end, ear, or forehead is collected.
  • photovolume signals are more convenient to collect and have less impact on patients.
  • the breathing state of the patient can be determined according to the characteristic information of the photovolume signal, which can improve the efficiency and be more friendly to the patient.
  • dual-channel physiological signals of the patient can be acquired.
  • the patient's electrocardiogram signal may also be acquired.
  • the dual-channel physiological signals include photoplethysmographic signals and electrocardiographic signals. Determining the patient's breathing state by fusing the dual-channel physiological signals can improve the accuracy of the breathing state, and the complexity of signal acquisition and data processing is relatively low.
  • the ECG signal of the preset part of the patient may be collected by an ECG collecting device.
  • the ECG acquisition device may collect ECG signals from the preset part of the patient through the chest electrode pads.
  • the current state of the patient may be detected; if the current state does not satisfy a preset state, prompt information for adjusting the state is output, so as to adjust the state of the patient based on the prompt information.
  • prompt information for adjusting the state is output, so as to adjust the state of the patient based on the prompt information.
  • the requirements for the patient's state are relatively low, for example, when the patient is not in a motion state, the photovolume signal and/or ECG signal can be acquired more accurately. signal signal. Therefore, when the patient is in an exercise state, prompt information of the adjustment state can be output to prompt the patient to stop exercising.
  • the physiological signal of the patient after adjusting the posture can be acquired by the acquisition device, for example, the single-channel physiological signal or the dual-channel physiological signal of the patient after the adjustment state is obtained, and the obtained physiological signal based on the adjusted state can be obtained.
  • the received physiological signal determines the breathing state of the patient.
  • prompt information for adjusting the state is output, such as prompting the patient to remain still, or to adjust the position of the clipping finger of the acquisition device.
  • the detecting the current state of the patient includes: collecting motion information of the patient, and determining the current state of the patient according to the motion information; or, collecting an image including the patient, and according to the image The current status of the patient is determined.
  • the current state of the patient in the image is determined by machine learning methods. If the current state of the patient is not conducive to the accurate acquisition of the physiological signal, prompt information may be output.
  • the characteristic information of the physiological signal can be understood as the key information contained in the physiological signal, for example, the characteristic information may include signal frequency, amplitude, and the like.
  • the characteristic information generally does not include useless information such as noise, and the patient's breathing state is determined according to the characteristic information of the physiological signal, which can obtain a more accurate breathing state with less calculation and reduce the complexity of breathing state detection.
  • the characteristic information of the preprocessed physiological signal can be obtained by preprocessing the physiological signal.
  • the acquiring the characteristic information of the physiological signal includes: preprocessing the physiological signal, and performing denoising processing on the preprocessed physiological signal to obtain a denoised physiological signal; and acquiring the physiological signal. Characteristic information of denoised physiological signals.
  • the preprocessing may include at least one of the following: hardware filtering, signal amplification, and analog-to-digital (A/D) conversion.
  • the denoising process may include digital filtering of adaptive filters.
  • the hardware filtering may include, for example, low-pass filtering and high-pass filtering (baseline drift, high frequency, and low frequency removal).
  • characteristic information such as peak amplitude, valley amplitude, peak position, and valley position is extracted from the denoised physiological signal.
  • the amplitude of the valley, the position of the peak and/or the position of the valley may be the time corresponding to the peak and/or the valley in the signal.
  • the light absorption state may also be extracted from the denoised photovolume signal to obtain characteristic information.
  • the light absorption state includes, for example, a red light absorption amount and/or an infrared light absorption amount.
  • the blood oxygen saturation (SpO2, Peripheral Capillary Oxygen Saturation) of the patient can be determined, and the blood oxygen saturation is used to indicate the current blood oxygen state of the patient.
  • the respiratory status of the patient includes a normal status, a respiratory oxygenation status (ABD Event, which may also be referred to as a respiratory oxygenation event).
  • a respiratory oxygenation event usually refers to the phenomenon of bradycardia and/or hypoxemia caused by apnea. Apnea can be called event A, bradycardia (eg, heart rate below 60 beats/min) can be called event B, and hypoxemia (eg, oxygen drop below 88%) can be called event D.
  • the detection of respiratory oxygenation events is mainly for patients with apnea.
  • the patient's breathing state may be determined based on the patient's breathing information, pulse rate, and blood oxygen saturation.
  • the respiration information may be determined according to the photovolume signal and/or the electrocardiogram signal of the patient.
  • the respiration information can be separated from the ECG signal directly by means of signal extraction.
  • the changes in the impedance of the thoracic cavity when the human body is breathing can be detected through the ECG electrode pads to obtain breathing information.
  • the respiration information can be obtained by fusing the photovolume signal and the ECG signal.
  • thoracic impedance detection can calculate respiratory information, such as respiration rate, according to Ohm's law. For example, there is a certain voltage U1 and U2 between the three leads of the ECG signal. When a person breathes, the thoracic cavity rises and falls back and forth, which can be detected. To the change of the thoracic impedance (that is, the resistance R) in the process of ups and downs, keeping U constant and R changing, then the detected current I also changes. Therefore, the respiration wave can be determined by detecting the change of the current I, that is, the change of the current I can reflect the respiration signal, for example, the respiration rate can be calculated according to the change of the current I.
  • the respiration wave can be determined by detecting the change of the current I, that is, the change of the current I can reflect the respiration signal, for example, the respiration rate can be calculated according to the change of the current I.
  • the pulse rate may be determined from the patient's photovolume signal and/or electrocardiogram signal.
  • the photoplethysmographic signal can be used to indicate changes in the pulsatile state of the blood vessel, so that the patient's pulse rate can be determined from the photoplethysmographic signal (PPG signal).
  • the pulse rate of the patient can be determined according to the PR interval of the electrocardiographic signal.
  • the pulse rate of the patient can be determined by fusing the photovolume signal and the ECG signal, for example, the pulse rate of the patient can be obtained by weighted summation of the pulse rate determined according to the PPG signal and the pulse rate determined according to the ECG signal.
  • SpO2 Blood oxygen saturation
  • SpO2 is the percentage of the oxygen-bound oxyhemoglobin in the blood to the total bindable hemoglobin capacity, that is, the blood oxygen concentration in the blood.
  • the photoplethysmographic signal determines blood oxygen saturation.
  • the patient's breathing information, pulse rate, and blood oxygen saturation can be determined according to the photovolume signal, so that the patient's breathing state can be determined according to the single-channel physiological signal.
  • determining the breathing state of the patient according to the breathing information, pulse rate, and blood oxygen saturation includes at least one of the following: when it is determined based on the breathing information that the patient's apnea starts, the first Within a preset time or within a second preset time after the apnea ends, when the pulse rate is lower than the first preset threshold, determine that the patient's breathing state is the first respiratory oxygenation event; when based on the breathing information When it is determined that the blood oxygen saturation is lower than the second preset threshold within the third preset time after the start of the patient's apnea or the fourth preset time after the end of the apnea, the breathing state of the patient is determined to be the first Two respiratory oxygenation events; when it is determined based on the respiration information that the pulse rate is lower than the first preset threshold within a fifth preset time after the start of apnea of the patient or a sixth preset time after the apnea ends, and the pulse rate is
  • the first respiratory oxygenation event may also be referred to as an AB event.
  • AB event when bradycardia occurs within 50 s after apnea starts or bradycardia occurs within 25 s after apnea ends, it is determined that the patient's breathing state is the first respiratory oxygenation event. event.
  • the second respiratory oxygenation event can also be referred to as an AD event.
  • a hypoxemia event occurs within 55s after the apnea starts or a hypoxemia event occurs within 38s after the apnea ends
  • the patient's breathing state is determined to be the second respiratory oxygenation event.
  • Coincidence event when a hypoxemia event occurs within 55s after the apnea starts or a hypoxemia event occurs within 38s after the apnea ends, the patient's breathing state is determined to be the second respiratory oxygenation event.
  • coincidence event when a hypoxemia event occurs within 55s after the apnea starts or a
  • the patient's respiratory state is the third respiratory oxygenation event.
  • the fourth respiratory oxygenation event can be referred to as the A event
  • the fifth respiratory oxygenation event can be referred to as the B event
  • the sixth respiratory oxygenation event can be referred to as the D event; the A event, the B event, and the D event occur independently, indicating that a Associated events can be called ordinary events.
  • the determining the breathing state of the patient according to the characteristic information includes: acquiring, according to the characteristic information, a signal quality index corresponding to a signal segment of each time window in the physiological signal; The signal quality index is used to filter out the signal segments that meet the conditions to obtain a target signal; the breathing state of the patient is determined according to the target signal.
  • the quality of the physiological signals (which may be called signal segments) collected in different time periods (which may be called time windows) can be evaluated to screen out
  • the higher quality physiological signal and the determination of the patient's breathing state according to the higher quality physiological signal can improve the accuracy of the determination of the breathing state.
  • time domain analysis and/or frequency domain analysis may be performed on the physiological signal according to characteristic information of the physiological signal, and the determination of the The signal quality index corresponding to the signal segment of each time window in the physiological signal.
  • the variation of the peak-to-valley difference, the variation of the peak-to-peak interval and/or the variation of the baseline deviation corresponding to the signal segment of each time window in the physiological signal may be obtained according to the characteristic information of the physiological signal, and According to the peak-to-valley difference variability, the peak-to-peak interval variability and/or the baseline deviation variability, a signal quality index corresponding to a signal segment of each time window in the physiological signal is determined.
  • the mean value of peak values and the mean value of valley values corresponding to the signal segments of each time window in the physiological signal may be obtained according to the characteristic information of the physiological signal, so as to obtain the peak-to-valley difference variability.
  • the peak-valley difference variability is determined according to the difference between the mean value of the peaks and the mean value of the valleys.
  • the mean value of the interval between adjacent wave peaks corresponding to the signal segments of each time window in the physiological signal may be obtained to obtain the peak-to-peak interval variability.
  • the reference baseline in the physiological signal can be obtained, and the mean value of the amplitude values of the discrete points corresponding to the signal segments of each time window in the physiological signal can be obtained to obtain the target baseline; the reference baseline in the physiological signal can be obtained The deviation between the baseline and the target baseline, the baseline deviation variability is obtained.
  • the reference baseline may be determined from a stable value of the physiological signal of a healthy person.
  • determining the signal quality index corresponding to the signal segment of each time window in the physiological signal according to the peak-to-valley difference variability, the peak-to-peak interval variability and/or the baseline deviation variability including: Obtain the weight value of the variation of the peak-valley difference, the variation of the peak-to-peak interval, and the variation of the baseline deviation corresponding to the physiological signal; according to the weight value, and the variation of the peak-to-valley difference, the peak-to-peak interval
  • the variability and the baseline deviation variability are used to determine the signal quality index corresponding to the signal segment of each time window in the physiological signal. For example, according to a preset weight value, the signal quality index is obtained by weighting and summing the peak-to-valley difference variability, the peak-to-peak interval variability, and/or the baseline deviation variability.
  • frequency domain analysis is performed on the physiological signal respectively, and according to the analysis result of the frequency domain analysis, the corresponding signal segment of each time window in the physiological signal is determined.
  • the signal quality index includes: performing correlation analysis between different frequency bands on the signal segments of each time window in the physiological signal according to the characteristic information of the physiological signal; determining the physiological signal according to the correlation analysis results between different frequency bands The signal quality index corresponding to the signal segment of each time window in the signal.
  • the photovolumetric signal can be decomposed into waves of multiple frequency bands by methods such as wavelet transform (WT), wherein the waves in the range of 1 Hz to 2 Hz correspond to the normal pulse rate of a person, which is 60 to 120 beats/min. In between, waves in the range of 0.17 to 1.2 Hz correspond to respiration rates of 40 to 70. If the correlation analysis determines that the wave in the range of 1 Hz to 2 Hz has a high correlation with the wave in the range of 0.17 to 1.2 Hz, it can be determined that the signal quality index of the photovolumetric signal is good.
  • WT wavelet transform
  • the target signal includes a signal segment of the photovolume signal.
  • the determining of the breathing state of the patient according to the target signal includes: acquiring breathing information, pulse rate, and blood oxygen saturation based on a signal segment of the photovolume signal; Saturation, which determines the breathing state of the patient.
  • the photoplethysmographic signal can be used to indicate changes in the pulsatile state of the blood vessel, so that the patient's pulse rate can be determined from the photoplethysmographic signal (PPG signal).
  • PPG signal photoplethysmographic signal
  • the number of times the peak appears in the signal segment of the photovolume signal is acquired, and the pulse rate is determined according to the number of times and the duration of the time window.
  • an interpolation process is performed on the signal segment of the photovolume signal to reconstruct a respiration waveform, and respiration information is determined based on the respiration waveform. For example, a wave in the range of 0.17 to 1.2 Hz is extracted from the signal segment, and interpolation processing is performed on the wave in the range of 0.17 to 1.2 Hz to reconstruct the respiratory waveform.
  • pulse rate and respiration information are demodulated in the signal segment of the photovolume signal by at least one of digital filtering method, wavelet transform method, and power spectrum method.
  • the signal segment of the photovolume signal is acquired, and the blood oxygen saturation is determined according to the ratio of the red light absorption amount and the infrared light absorption amount in the signal segment.
  • the patient's breathing information, pulse rate, and blood oxygen saturation can be determined according to the photovolume signal, so that the patient's breathing state can be determined according to the single-channel physiological signal.
  • the target signal includes a signal segment of the photoelectric volume signal and a signal segment of the electrocardiogram signal
  • the determining the breathing state of the patient according to the target signal includes: based on the photoelectric signal
  • the signal segment of the volume signal acquires pulse rate and blood oxygen saturation; based on the signal segment of the ECG signal, respiration information is acquired; according to the respiration information, pulse rate, and blood oxygen saturation, the breathing state of the patient is determined. Therefore, the respiration state can be determined according to the physiological signals of the patient's dual channels.
  • the respiration information can be separated from the signal segment of the ECG signal directly by means of signal extraction.
  • the target signal includes a signal segment of the photoelectric volume signal and a signal segment of the electrocardiogram signal
  • the determining the breathing state of the patient according to the target signal includes: based on the photoelectric signal Obtaining pulse rate and blood oxygen saturation from the signal segment of the volume signal; obtaining respiration information based on the signal segment of the photovolume signal and the signal segment of the ECG signal; , to determine the breathing state of the patient.
  • the respiration information can be obtained by fusing the two signals of the photovolume signal and the electrocardiogram signal, and the obtained respiration information is more accurate.
  • the acquiring the respiration information based on the signal segment of the photovolume signal and the signal segment of the ECG signal includes: acquiring a first weight value of the photovolume signal, and acquiring a first weight value of the ECG signal.
  • Two weight values first respiration information is acquired based on the signal segment of the photovolume signal, and second respiration information is acquired based on the signal segment of the ECG signal; according to the first weight value, the first respiration information, and the second weight value and the second respiration information, and determine the respiration information, for example, weighted and summed the first respiration information and the second respiration information according to the first weight value and the second weight value to obtain the patient's respiration information.
  • the sum of the first weight value and the second weight value is 1.
  • the physiological signal processing method further includes: outputting prompt information of the respiration state.
  • the physiological signal processing device may output the prompt information of the breathing state through a display device and/or a speaker, and the patient and/or medical staff may obtain the breathing state of the patient.
  • the outputting prompt information of the respiratory state includes: acquiring a timestamp when the respiratory oxygenation event occurs, and displaying the timestamp through a voice broadcast or a screen. And the prompt information of the respiratory oxygenation event, prompting medical staff to deal with it in time.
  • the patient may be classified into a state level based on the respiratory oxygenation event, and prompt information of the time stamp, the respiratory oxygenation event and the state level of the patient may be displayed through voice broadcast or screen display.
  • prompt information of the time stamp, the respiratory oxygenation event and the state level of the patient may be displayed through voice broadcast or screen display.
  • the physiological signal processing method further includes: when the respiration state conforms to a respiration oxygenation event, determining the respiration state based on the respiration oxygenation event.
  • the physiological signals are marked, and the marked physiological signals are stored, so that the physiological signals of the patient when the respiratory oxygenation event occurs can be traced back.
  • the marking the physiological signal based on the respiratory oxygenation event includes: acquiring the type of the respiratory oxygenation event; determining a marking strategy according to the type of the respiratory oxygenation event; according to the marking strategy Annotate the physiological signal. For example, if the respiratory oxygenation event determined according to the physiological signal is an ABD event, the physiological signal is marked as an ABD event, and if the respiratory oxygenation event determined according to the physiological signal is an A event, the physiological signal is marked as ordinary event.
  • the physiological signal processing method provided by the embodiment of the present application obtains the physiological signal of the patient, obtains characteristic information of the physiological signal, and determines the breathing state of the patient according to the characteristic information.
  • the patient's breathing state can be determined only based on the characteristic information of the patient's physiological signals, without the need to collect multiple signals and detect the multiple signals separately, which improves the convenience and efficiency of the physiological signal processing.
  • FIG. 2 is a schematic block diagram of a physiological signal processing apparatus 600 provided by an embodiment of the present application.
  • the physiological signal processing apparatus 600 includes: a collection device 610 , a display 620 , a memory 630 and a processor 640 .
  • the collecting device 610 is used for collecting physiological signals of the patient, and the display 620 is used for displaying prompt information of the breathing state of the patient.
  • the memory 630 stores a computer program, and the processor 640 is configured to run the computer program stored in the memory 630, and implement the steps of the aforementioned physiological signal processing method when the computer program is executed.
  • the processor 640 and the memory 430 are connected through a bus 601, and the bus 601 is, for example, an I2C (Inter-integrated Circuit) bus.
  • I2C Inter-integrated Circuit
  • the processor 640 may be a micro-controller unit (Micro-controller Unit, MCU), a central processing unit (Central Processing Unit, CPU), or a digital signal processor (Digital Signal Processor, DSP) or the like.
  • MCU Micro-controller Unit
  • CPU Central Processing Unit
  • DSP Digital Signal Processor
  • the memory 630 may be a Flash chip, a read-only memory (ROM, Read-Only Memory) magnetic disk, an optical disk, a U disk, a mobile hard disk, and the like.
  • ROM Read-Only Memory
  • the memory 630 may be a Flash chip, a read-only memory (ROM, Read-Only Memory) magnetic disk, an optical disk, a U disk, a mobile hard disk, and the like.
  • the processor 640 is configured to run the computer program stored in the memory 630, and implement the following steps when executing the computer program:
  • the breathing state of the patient is determined according to the characteristic information.
  • FIG. 3 is a schematic block diagram of a monitor 700 provided by an embodiment of the present application.
  • the monitor 700 includes: a parameter measurement circuit 710 , a display 720 , a memory 730 and a processor 740 .
  • the parameter measurement circuit 710 is used to collect the physiological signals of the patient.
  • the monitor 700 further includes the sensor attachment 10 , and the parameter measurement circuit 710 is used for connecting the sensor attachment 10 and obtaining the physiological parameter signals of the patient collected by the sensor attachment 10 .
  • the parameter measurement circuit 710 can be connected to one or more sensor attachments 10 , for example, for obtaining various physiological signals of the patient through various sensor attachments 10 , such as a photoplethysmographic signal (PPG signal), the electrocardiographic signal (ECG signal), and the electromyographic signal (EMG signal) and the like.
  • PPG signal photoplethysmographic signal
  • ECG signal electrocardiographic signal
  • EMG signal electromyographic signal
  • the display 720 is used to display prompt information of the breathing state of the patient.
  • the memory 730 stores a computer program, and the processor 740 is configured to execute the computer program stored in the memory 730, and implement the steps of the aforementioned physiological signal processing method when the computer program is executed.
  • the processor 740 and the memory 430 are connected through a bus 701, and the bus 701 is, for example, an I2C (Inter-integrated Circuit) bus.
  • I2C Inter-integrated Circuit
  • the processor 740 may be a micro-controller unit (Micro-controller Unit, MCU), a central processing unit (Central Processing Unit, CPU) or a digital signal processor (Digital Signal Processor, DSP) or the like.
  • MCU Micro-controller Unit
  • CPU Central Processing Unit
  • DSP Digital Signal Processor
  • the memory 730 may be a Flash chip, a read-only memory (ROM, Read-Only Memory) magnetic disk, an optical disk, a U disk, a mobile hard disk, and the like.
  • ROM Read-Only Memory
  • the memory 730 may be a Flash chip, a read-only memory (ROM, Read-Only Memory) magnetic disk, an optical disk, a U disk, a mobile hard disk, and the like.
  • the processor 740 is configured to run the computer program stored in the memory 730, and implement the following steps when executing the computer program:
  • the breathing state of the patient is determined according to the characteristic information.
  • Embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the processor enables the processor to implement the physiological signal processing method provided by the foregoing embodiments A step of.
  • the computer-readable storage medium may be the physiological signal processing apparatus described in any of the foregoing embodiments, such as an internal storage unit of a monitor, such as a hard disk or memory of the monitor.
  • the computer-readable storage medium can also be an external storage device of the physiological signal processing device, such as a plug-in hard disk equipped on the monitor, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital) , SD) card, flash memory card (Flash Card), etc.

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  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

一种生理信号处理方法，包括：获取患者的生理信号(S110)；获取生理信号的特性信息(S120)；根据特征信息确定患者的呼吸状态(S130)，需要基于患者的生理信号的特性信息即可确定患者的呼吸状态，提高了对生理信号处理的便捷性和效率。还提供了生理信号处理装置、监护仪及计算机可读存储介质。

Description

生理信号处理方法、装置、监护仪及计算机可读存储介质 技术领域
本申请涉及医疗设备技术领域，具体涉及一种生理信号处理方法、装置、监护仪及计算机可读存储介质。
背景技术
针对患有呼吸疾病的患者，可以通过检测患者的心率、脉搏血氧饱和度、以及呼吸状态等多种不同信息，来确定患者的呼吸疾病的类型。
目前，在对多种不同信息获取的过程中，需要通过不同的采集设备分别采集心电图(ECG，electrocardiogram)、光电容积描记(PPG，photoplethysmograph)、以及二氧化碳(CO2，carbon dioxide)等，然后，基于ECG信号检测患者的心率是否稳定，基于PPG信号检测患者的脉搏血氧饱和度(SpO2，Peripheral Capillary Oxygen Saturation)，以便通过脉搏血氧饱和度来反映患者当前的血氧状态，以及CO2信号检测患者的呼吸情况。此时，可以基于检测出的心率、脉搏血氧饱和度、以及呼吸情况等信息确定患者的呼吸疾病。
由于需要通过复杂的采集方式分别获取多种不同信号，并对多种信号分别进行检测，因此，一方面，对于患者进行长期监测，会影响患者的休息及恢复过程中的活动范围，不利于患者的康复，以及降低了医护人员的工作效率；另一方面，检测过程的复杂度较高，降低了检测的便捷性。
发明内容
本申请提供了一种生理信号处理方法、装置、监护仪及计算机可读存储介质，可以提高对生理信号处理的便捷性和效率。
第一方面，本申请实施例提供了一种生理信号处理方法，包括：
获取患者的生理信号；
获取所述生理信号的特性信息；
根据所述特征信息确定所述患者的呼吸状态。
第二方面，本申请实施例提供了一种生理信号处理装置，包括：
采集设备，用于采集患者的生理信号；
显示器，用于显示患者呼吸状态的提示信息；
存储器，存储有计算机程序；
处理器，用于运行存储在所述存储器中的计算机程序，并在执行所述计算机程序时实现前述的生理信号处理方法。
第三方面，本申请实施例提供了一种监护仪，包括：
传感器附件；
参数测量电路，用于连接传感器附件，以及获得患者的生理参数信号；
显示器，用于显示患者呼吸状态的提示信息；
存储器，存储有计算机程序；
处理器，用于运行存储在所述存储器中的计算机程序，并在执行所述计算机程序时实现前述的生理信号处理方法。
第四方面，本申请实施例提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时使所述处理器实现上述的方法。
本申请实施例提供了一种生理信号处理方法、装置、监护仪及计算机可读存储介质，可以获取患者的生理信号，以及获取生理信号的特性信息，此时可以根据特征信息确定患者的呼吸状态。该方案仅需要基于患者的生理信号的特性信息即可确定患者的呼吸状态，而不需要采集多种信号并对多种信号分别进行检测，提高了对生理信号处理的便捷性和效率。
应当理解的是，以上的一般描述和后文的细节描述仅是示例性和解释性的，并不能限制本申请实施例的公开内容。
附图说明
为了更清楚地说明本申请实施例的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本申请实施例提供的一种生理信号处理方法的流程示意图；
图2是本申请实施例提供的一种生理信号处理装置的示意性框图；
图3是本申请实施例提供的一种监护仪的示意性框图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
附图中所示的流程图仅是示例说明，不是必须包括所有的内容和操作/步骤，也不是必须按所描述的顺序执行。例如，有的操作/步骤还可以分解、组合或部分合并，因此实际执行的顺序有可能根据实际情况改变。
下面结合附图，对本申请的一些实施方式作详细说明。在不冲突的情况下，下述的实施例及实施例中的特征可以相互组合。
请参阅图1，图1是本申请实施例提供的一种生理信号处理方法的流程示意图。所述生理信号处理方法可以应用在生理信号处理装置中，用于根据患者的生理信号确定患者的呼吸状态等过程；其中该生理信号处理装置的类型可以根据实际需要进行灵活设置，例如，该生理信号处理装置可以是监护仪等。
本申请实施例的生理信号处理方法包括：获取患者的生理信号；获取所述生理信号的特性信息；根据所述特征信息确定所述患者的呼吸状态。仅需要基于患者的生理信号的特性信息即可确定患者的呼吸状态，而不需要采集多种信号并对多种信号分别进行检测，提高了对生理信号处理的便捷性和效率。
如图1所示，本申请实施例的生理信号处理方法包括步骤S110至步骤S130。
S110、获取患者的生理信号。
示例性的，所述生理信号处理装置，如监护仪搭载用于采集患者所述生理 信号的采集设备，或者能够与采集设备通信连接。
示例性的，采集设备可以包括光电容积采集设备、心电采集设备、以及肌电采集设备，当然也不限于此。通过光电容积采集设备，可以采集患者的光电容积信号；通过心电采集设备，可以采集患者的心电信号；通过肌电采集设备，可以采集患者的肌电信号。
其中，光电容积采集设备可以通过光电容积传感器采集患者手指、额头、耳部、腕部或者脖颈等处的光电容积信号，或者可以称为光体积描记波(PPG，Photoplethysmograph)。其中，在相应部位采集的光电容积信号可以分别称为指端光电容积脉搏信号、耳部光电容积脉搏波信号、额头光电容积脉搏波信号等。心电采集设备可以通过心电采集芯片和/或心电采集电路采集所述患者的心电信号(ECG，Electrocardiogram)。肌电采集设备可以通过针电极或电极贴片采集患者的肌电信号(EMG)或表面肌电信号(SEMG)。
在一些实施方式中，可以获取患者单通道的生理信号。
示例性的，所述获取患者单通道的生理信号包括获取患者的光电容积信号。例如通过光电容积采集设备，采集所述患者指端、耳部、或额头对应部位的光电容积信号。
光电容积信号相较于心电信号、肌电信号等，更方便采集，对患者的影响也比较小。通过根据光电容积信号的特性信息即可确定患者的呼吸状态，可以提高效率，对患者也更友好。
在一些实施方式中，可以获取所述患者双通道的生理信号。
示例性的，除了获取患者的光电容积信号，还可以获取患者的心电信号。可以理解的，所述双通道的生理信号包括光电容积信号和心电信号。通过融合双通道的生理信号确定患者的呼吸状态，可以提高呼吸状态的准确性，而且信号采集、数据处理的复杂度也比较低。
示例性的，可以通过心电采集设备，采集所述患者预设部位的心电信号。例如，心电采集设备可以通过胸部电极片，采集所述患者预设部位的心电信号。
在一些实施方式中，可以检测所述患者的当前状态；若所述当前状态不满足预设状态，则输出调整状态的提示信息，以基于所述提示信息调整所述患者的状态。患者处于运动状态，或者躺卧姿态不准确或压到采集设备时，获取的生理信号不够准确。可以提示调整所述患者的状态。
示例性的，在获取患者的光电容积信号和/或心电信号信号时，对患者状态的要求比较低，例如当患者未处于运动状态时均可以较为准确的获取光电容积信号和/或心电信号信号。因此可以在患者处于运动状态时，输出调整状态的提示信息，以提示患者停止运动。
在患者调整状态之后，可以通过采集设备获取调整姿态后的所述患者的所述生理信号，例如获取调整状态后的所述患者单通道的生理信号或双通道的生理信号，以及基于调整后获取到的所述生理信号确定所述患者的呼吸状态。
示例性的，若检测到患者处于运动状态，或者躺卧姿态不准确或压到采集设备时，输出调整状态的提示信息，例如提示患者保持静止，或者调整采集设备的夹手指的位置等。
示例性的，所述检测所述患者的当前状态包括：采集所述患者的运动信息，根据所述运动信息确定所述患者的当前状态；或者，采集包含所述患者的图像，根据所述图像确定所述患者的当前状态。
例如，通过机器学习方法确定图像中患者的当前状态。若患者的当前状态不利于所述生理信号的准确采集，则可以输出提示信息。
S120、获取所述生理信号的特性信息。
生理信号的特性信息可以理解为是生理信号所包含的关键信息，例如特性信息可以包括信号频率、幅值等。特性信息一般不包括噪音等无用信息，根据生理信号的特性信息确定患者的呼吸状态，可以通过较少的计算量得到更准确的呼吸状态，降低呼吸状态检测的复杂度。
在一些实施方式中，可以通过对所述生理信号进行预处理，获取预处理后的所述生理信号的特性信息。
示例性的，所述获取所述生理信号的特性信息包括：对所述生理信号进行预处理，并对预处理后的生理信号进行去噪处理，得到去噪后的生理信号；以及获取所述去噪后的生理信号的特性信息。
其中，所述预处理可以包括以下至少一种：硬件滤波、信号放大、模数(A/D)转换。去噪处理可以包括自适应滤波器的数字滤波处理。硬件滤波例如可以包括低通滤波、高通滤波(基线漂移，频率比较高，去低频)。
示例性的，从所述去噪后的生理信号中提取峰值幅度、谷值幅度、峰值位置、谷值位置等特性信息。其中，谷值幅度，峰值位置和/或谷值位置可以为信 号中峰值和/或谷值对应的时间。
示例性的，当获取的生理信号包括患者的光电容积信号时，还可以从去噪后的光电容积信号中提取光吸收状态，得到特性信息。光吸收状态例如包括红光吸收量和/或红外光吸收量。根据光吸收状态能够确定患者的血氧饱和度(SpO2，Peripheral Capillary Oxygen Saturation)，血氧饱和度用于指示患者当前的血氧状态。
S130、根据所述特征信息确定所述患者的呼吸状态。
在一些实施方式中，患者的呼吸状态包括正常状态、呼吸氧合状态(ABD Event，也可称为呼吸氧合事件)。呼吸氧合事件通常指由呼吸暂停导致的心动过缓和/或血氧过低的现象。其中呼吸暂停可以称为A事件，心动过缓(例如心率低于60次/分)可以称为B事件，血氧过低(例如血氧下降到88％以下)可以称为D事件。
呼吸氧合事件的检测主要是针对患有呼吸暂停性疾病的患者。在一些实施方式中，可以根据患者的呼吸信息、脉率、以及血氧饱和度，确定所述患者的呼吸状态。
示例性的，呼吸信息可以根据患者的光电容积信号和/或心电信号确定。其中，基于心电信号(ECG信号)获取呼吸信息，可以直接采用信号提取的方式将呼吸信息从ECG信号中进行分离。或者可以通过心电电极片检测人体呼吸时胸腔阻抗的变化进而获取呼吸信息。或者可以将光电容积信号和心电信号两种信号融合求取呼吸信息。
示例性的，胸阻抗法检测可以根据欧姆定律计算呼吸信息，如呼吸率，例如心电信号的三导联之间有一定的电压U1、U2，人呼吸的时候胸腔是来回起伏的，可以检测到在起伏的过程中胸阻抗(即电阻R)的变化，保持U是恒定的，R在变化，那么检测的电流I也是变化的。从而可以通过检测电流I的变化来确定呼吸波，即电流I的变化能反映呼吸信号，例如可以根据电流I的变化计算呼吸率。
示例性的，脉率可以根据患者的光电容积信号和/或心电信号确定。
光电容积信号可以用于指示血管的搏动状态变化，从而可以根据光电容积信号(PPG信号)确定患者的脉率。示例性的，可以根据心电信号的PR间期确定患者的脉率。或者可以将光电容积信号和心电信号两种信号融合确定患者的 脉率，例如将根据PPG信号确定的脉率和根据心电信号确定的脉率加权求和得到患者的脉率。
血氧饱和度(SpO2)用于指示患者的血氧状态，SpO2是血液中被氧结合的氧合血红蛋白的容量占全部可结合的血红蛋白容量的百分比，即血液中血氧的浓度，可以根据患者的光电容积信号确定血氧饱和度。
可以理解的，根据光电容积信号可以确定患者的呼吸信息、脉率、以及血氧饱和度，从而可以根据单通道的生理信号确定所述患者的呼吸状态。
举例而言，所述根据所述呼吸信息、脉率、以及血氧饱和度，确定所述患者的呼吸状态包括一下至少一种：当基于所述呼吸信息确定所述患者呼吸暂停开始后第一预设时间内或呼吸暂停结束后第二预设时间内，所述脉率低于第一预设阈值时，确定所述患者的呼吸状态为第一呼吸氧合事件；当基于所述呼吸信息确定所述患者呼吸暂停开始后第三预设时间内或吸暂停结束后第四预设时间内，所述血氧饱和度低于第二预设阈值时，确定所述患者的呼吸状态为第二呼吸氧合事件；当基于所述呼吸信息确定所述患者呼吸暂停开始后第五预设时间内或吸暂停结束后第六预设时间内，所述脉率低于第一预设阈值且所述血氧饱和度低于第二预设阈值时，确定所述患者的呼吸状态为第三呼吸氧合事件；当基于所述呼吸信息确定所述患者存在呼吸暂停时，确定所述患者的呼吸状态为第四呼吸氧合事件；当所述脉率低于第一预设阈值时，确定所述患者的呼吸状态为第五呼吸氧合事件；当所述血氧饱和度低于第二预设阈值时，确定所述患者的呼吸状态为第六呼吸氧合事件。
其中，第一呼吸氧合事件也可以称为AB事件，例如在呼吸暂停开始后50s内发生心动过缓或者呼吸暂停结束后25s内发生心动过缓时确定患者的呼吸状态为第一呼吸氧合事件。第二呼吸氧合事件也可以称为AD事件，例如在呼吸暂停开始后55s内发生了低血氧事件或者呼吸暂停结束后38s内发生低血氧事件时确定患者的呼吸状态为第二呼吸氧合事件。第三呼吸氧合事件也可以称为ABD事件，例如在呼吸暂停后心动过缓和血氧过低同时发生时确定患者的呼吸状态为第三呼吸氧合事件。第四呼吸氧合事件可以称为A事件，第五呼吸氧合事件可以称为B事件，第六呼吸氧合事件可以称为D事件；A事件、B事件、D事件单独发生，表示一次未关联事件，可以称为普通事件。
在一些实施方式中，所述根据所述特征信息确定所述患者的呼吸状态，包 括：根据所述特征信息获取所述生理信号中，每个时间窗的信号段对应的信号质量指数；根据所述信号质量指数筛选出满足条件的信号段，得到目标信号；根据所述目标信号确定所述患者的呼吸状态。
基于单通道的生理信号或者基于双通道的生理信号确定患者的呼吸状态时，可以通过对不同时间段(可以称为时间窗)采集的生理信号(可以称为信号段)进行质量评估，筛选出质量较高的生理信号，以及根据质量较高的生理信号确定患者的呼吸状态，可以提高呼吸状态确定的准确性。
在一些实施方式中，可以根据所述生理信号的特性信息，对所述生理信号进行时域分析和/或频域分析，以及根据时域分析和/或频域分析的分析结果，确定所述生理信号中每个时间窗的信号段对应的信号质量指数。
示例性的，可以根据所述生理信号的特征信息获取所述生理信号中，每个时间窗的信号段对应的峰谷差值变异度、峰峰间隔变异度和/或基线偏离变异度，以及根据所述峰谷差值变异度、峰峰间隔变异度和/或基线偏离变异度，确定所述生理信号中每个时间窗的信号段对应的信号质量指数。
举例而言，可以根据所述生理信号的特征信息获取所述生理信号中，每个时间窗的信号段对应的峰值的均值以及谷值的均值，得到峰谷差值变异度。例如根据所述峰值的均值以及所述谷值的均值之间的差值确定峰谷差值变异度。
举例而言，可以获取所述生理信号中每个时间窗的信号段对应的相邻波峰与波峰之间间隔的均值，得到峰峰间隔变异度。
举例而言，可以获取所述生理信号中的参考基线，以及获取所述生理信号中每个时间窗的信号段对应离散点的幅度值的均值，得到目标基线；获取所述生理信号中的参考基线与目标基线之间的偏差，得到基线偏离变异度。例如，参考基线可以根据健康人的所述生理信号的稳定值确定。
示例性的，所述根据所述峰谷差值变异度、峰峰间隔变异度和/或基线偏离变异度，确定所述生理信号中每个时间窗的信号段对应的信号质量指数,包括：获取所述生理信号对应的所述峰谷差值变异度、峰峰间隔变异度、以及基线偏离变异度的权重值；根据所述权重值，以及所述峰谷差值变异度、峰峰间隔变异度、以及基线偏离变异度，确定所述生理信号中所述每个时间窗的信号段对应的信号质量指数。例如，根据预设的权重值，对所述峰谷差值变异度、峰峰间隔变异度和/或基线偏离变异度加权求和，得到所述信号质量指数。
在一些实施方式中，所述根据所述生理信号的特性信息，分别对所述生理信号进行频域分析，根据频域分析的分析结果，确定所述生理信号中每个时间窗的信号段对应的信号质量指数，包括：根据所述生理信号的特征信息分别对所述生理信号中每个时间窗的信号段进行不同频段间关联性分析；根据不同频段间关联性分析结果，确定所述生理信号中每个时间窗的信号段对应的信号质量指数。
示例性的，光电容积信号可以通过例如小波变换(wavelet transform，WT)等方法分解出多个频段的波，其中1Hz到2Hz范围内的波对应人的正常脉率，为60至120次/分之间，0.17到1.2Hz范围内的波对应呼吸率，为40至70。如果通过关联性分析确定信号中1Hz到2Hz范围内的波与0.17到1.2Hz范围内的波的关联度较高，则可以确定光电容积信号的信号质量指数较好。其中光电容积信号中1Hz到2Hz范围内和0.17到1.2Hz范围内的波的占比越高，可以确定光电容积信号中其他频段的波较少，则信号质量指数较好。
筛选出质量较高的生理信号，即满足条件的信号段，得到目标信号，根据质量较高的目标信号确定患者的呼吸状态，可以提高呼吸状态确定的准确性。
在一些实施方式中，所述目标信号包括所述光电容积信号的信号段。所述根据所述目标信号确定所述患者的呼吸状态包括：基于所述光电容积信号的信号段获取呼吸信息、脉率、以及血氧饱和度；根据所述呼吸信息、脉率、以及血氧饱和度，确定所述患者的呼吸状态。
光电容积信号可以用于指示血管的搏动状态变化，从而可以根据光电容积信号(PPG信号)确定患者的脉率。示例性的，获取所述光电容积信号的信号段中峰值出现的次数，根据所述次数和所述时间窗的时长确定脉率。
示例性的，对所述光电容积信号的信号段进行插值处理，以重构呼吸波形，以及基于所述呼吸波形确定呼吸信息。例如在信号段提取0.17到1.2Hz范围内的波，对0.17到1.2Hz范围内的波进行插值处理，以重构呼吸波形。
示例性的，通过数字滤波法、小波变换法、功率谱法中的至少一种在光电容积信号的信号段解调出脉率和呼吸信息，如呼吸频率。
示例性的，获取所述光电容积信号的信号段，根据信号段中红光吸收量和红外光吸收量的比值，确定血氧饱和度。
可以理解的，根据光电容积信号可以确定患者的呼吸信息、脉率、以及血 氧饱和度，从而可以根据单通道的生理信号确定所述患者的呼吸状态。
在另一些实施方式中，所述目标信号包括所述光电容积信号的信号段和所述心电信号的信号段，所述根据所述目标信号确定所述患者的呼吸状态包括：基于所述光电容积信号的信号段获取脉率和血氧饱和度；基于所述心电信号的信号段获取呼吸信息；根据所述呼吸信息、脉率、以及血氧饱和度，确定所述患者的呼吸状态。从而可以实现根据患者双通道的生理信号确定呼吸状态。
示例性的，可以直接采用信号提取的方式将呼吸信息从心电信号的信号段中进行分离。
在其他一些实施方式中，所述目标信号包括所述光电容积信号的信号段和所述心电信号的信号段，所述根据所述目标信号确定所述患者的呼吸状态包括：基于所述光电容积信号的信号段获取脉率和血氧饱和度；基于所述光电容积信号的信号段和所述心电信号的信号段获取呼吸信息；根据所述呼吸信息、脉率、以及血氧饱和度，确定所述患者的呼吸状态。从而可以将光电容积信号和心电信号两种信号融合求取呼吸信息，得到的呼吸信息更准确。
示例性的，所述基于所述光电容积信号的信号段和所述心电信号的信号段获取呼吸信息包括：获取所述光电容积信号的第一权重值，以及获取所述心电信号的第二权重值；基于所述光电容积信号的信号段获取第一呼吸信息，基于所述心电信号的信号段获取第二呼吸信息；根据所述第一权重值、第一呼吸信息、第二权重值和第二呼吸信息，确定所述呼吸信息，例如根据第一权重值和第二权重值对第一呼吸信息和第二呼吸信息进行加权求和，得到患者的呼吸信息。示例性的，第一权重值和第二权重值的和为1。
可选的，所述根据所述特征信息确定所述患者的呼吸状态之后，所述生理信号处理方法还包括：输出所述呼吸状态的提示信息。
示例性的，生理信号处理装置可以通过显示装置和/或扬声器输出所述呼吸状态的提示信息，患者和/或医护人员可以获取患者的呼吸状态。
示例性的，当所述呼吸状态符合呼吸氧合事件时，所述输出所述呼吸状态的提示信息包括：获取所述呼吸氧合事件发生的时间戳，通过语音播报或屏幕显示所述时间戳及所述呼吸氧合事件的提示信息，提示医护人员及时处理。
示例性的，可以基于所述呼吸氧合事件对所述患者进行状态等级划分，通过语音播报或屏幕显示所述时间戳、所述呼吸氧合事件和所述患者的状态等级 的提示信息。其中，患者的状态等级越高，如发生ABD事件，则提示信息越强，例如语音播报的音量越大，或者屏幕显示的闪烁频率越高。
可选的，所述根据所述特征信息确定所述患者的呼吸状态之后，所述生理信号处理方法还包括：当所述呼吸状态符合呼吸氧合事件时，基于所述呼吸氧合事件对所述生理信号进行标注，存储标注后的生理信号，从而可以回溯呼吸氧合事件发生时患者的生理信号。
示例性的，所述基于所述呼吸氧合事件对所述生理信号进行标注包括：获取所述呼吸氧合事件的类型；根据所述呼吸氧合事件的类型确定标注策略；根据所述标注策略对所述生理信号进行标注。例如，若根据生理信号确定的呼吸氧合事件为ABD事件，则将所述生理信号标注为ABD事件，若根据生理信号确定的呼吸氧合事件为A事件，则将所述生理信号标注为普通事件。
本申请实施例提供的生理信号处理方法，通过获取患者的生理信号，获取所述生理信号的特性信息，以及根据所述特征信息确定所述患者的呼吸状态。仅需要基于患者的生理信号的特性信息即可确定患者的呼吸状态，而不需要采集多种信号并对多种信号分别进行检测，提高了对生理信号处理的便捷性和效率。
请结合上述实施例参阅图2，图2是本申请实施例提供的生理信号处理装置600的示意性框图。该生理信号处理装置600包括：采集设备610、显示器620、存储器630和处理器640。
其中，采集设备610用于采集患者的生理信号，显示器620用于显示患者呼吸状态的提示信息。存储器630存储有计算机程序，处理器640用于运行存储在所述存储器630中的计算机程序，并在执行所述计算机程序时实现前述的生理信号处理方法的步骤。
示例性的，处理器640和存储器430通过总线601连接，该总线601比如为I2C(Inter-integrated Circuit)总线。
具体的，处理器640可以是微控制单元(Micro-controller Unit，MCU)、中央处理单元(Central Processing Unit，CPU)或数字信号处理器(Digital Signal Processor，DSP)等。
具体的，存储器630可以是Flash芯片、只读存储器(ROM，Read-Only Memory)磁盘、光盘、U盘或移动硬盘等。
示例性的，所述处理器640用于运行存储在存储器630中的计算机程序，并在执行所述计算机程序时实现如下步骤：
获取患者的生理信号；
获取所述生理信号的特性信息；
根据所述特征信息确定所述患者的呼吸状态。
本申请实施例提供的生理信号处理装置的具体原理和实现方式均与前述实施例的生理信号处理方法类似，此处不再赘述。
请结合上述实施例参阅图3，图3是本申请实施例提供的监护仪700的示意性框图。该监护仪700包括：参数测量电路710、显示器720、存储器730和处理器740。
其中，参数测量电路710用于采集患者的生理信号。
示例性的，监护仪700还包括传感器附件10，参数测量电路710用于连接传感器附件10，以及获得传感器附件10采集的患者的生理参数信号。示例性的，参数测量电路710能够连接一种或多种传感器附件10，例如用于通过多种传感器附件10获取患者的多种生理信号，如光电容积信号(PPG信号)、所述心电信号(ECG信号)、以及所述肌电信号(EMG信号)等。
显示器720用于显示患者呼吸状态的提示信息。存储器730存储有计算机程序，处理器740用于运行存储在所述存储器730中的计算机程序，并在执行所述计算机程序时实现前述的生理信号处理方法的步骤。
示例性的，处理器740和存储器430通过总线701连接，该总线701比如为I2C(Inter-integrated Circuit)总线。
具体的，处理器740可以是微控制单元(Micro-controller Unit，MCU)、中央处理单元(Central Processing Unit，CPU)或数字信号处理器(Digital Signal Processor，DSP)等。
具体的，存储器730可以是Flash芯片、只读存储器(ROM，Read-Only Memory)磁盘、光盘、U盘或移动硬盘等。
示例性的，所述处理器740用于运行存储在存储器730中的计算机程序，并在执行所述计算机程序时实现如下步骤：
获取患者的生理信号；
获取所述生理信号的特性信息；
根据所述特征信息确定所述患者的呼吸状态。
本申请实施例提供的监护仪的具体原理和实现方式均与前述实施例的生理信号处理方法类似，此处不再赘述。
本申请实施例还提供一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时使所述处理器实现上述实施例提供的生理信号处理方法的步骤。
其中，所述计算机可读存储介质可以是前述任一实施例所述的生理信号处理装置，如监护仪的内部存储单元，例如所述监护仪的硬盘或内存。所述计算机可读存储介质也可以是所述生理信号处理装置的外部存储设备，例如所述监护仪上配备的插接式硬盘，智能存储卡(Smart Media Card，SMC)，安全数字(Secure Digital，SD)卡，闪存卡(Flash Card)等。
应当理解，在此本申请中所使用的术语仅仅是出于描述特定实施例的目的而并不意在限制本申请。
还应当理解，在本申请和所附权利要求书中使用的术语“和/或”是指相关联列出的项中的一个或多个的任何组合以及所有可能组合，并且包括这些组合。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以权利要求的保护范围为准。

Claims (24)

  1. 一种生理信号处理方法，其特征在于，包括：
    获取患者的生理信号；
    获取所述生理信号的特性信息；
    根据所述特征信息确定所述患者的呼吸状态。
  2. 根据权利要求1所述的生理信号处理方法，其特征在于，所述根据所述特征信息确定所述患者的呼吸状态包括：
    根据所述特征信息获取所述生理信号中，每个时间窗的信号段对应的信号质量指数；
    根据所述信号质量指数筛选出满足条件的信号段，得到目标信号；
    根据所述目标信号确定所述患者的呼吸状态。
  3. 根据权利要求2所述的生理信号处理方法，其特征在于，所述根据所述特征信息获取所述生理信号中，每个时间窗的信号段对应的信号质量指数包括：
    根据所述特征信息对所述生理信号进行时域分析和/或频域分析；
    根据时域分析和/或频域分析的分析结果，确定所述生理信号中每个时间窗的信号段对应的信号质量指数。
  4. 根据权利要求2所述的生理信号处理方法，其特征在于，获取患者的生理信号包括：
    获取患者单通道的生理信号，或者获取所述患者双通道的生理信号。
  5. 根据权利要求4所述的生理信号处理方法，其特征在于，所述获取患者单通道的生理信号，或者获取所述患者双通道的生理信号包括：
    检测所述患者的当前状态；
    若所述当前状态为运动状态，则输出调整状态的提示信息，以基于所述提示信息调整所述患者的状态；
    获取调整状态后的所述患者单通道的生理信号或双通道的生理信号。
  6. 根据权利要求5所述的生理信号处理方法，其特征在于，所述检测所述患者的当前状态包括：
    采集所述患者的运动信息，根据所述运动信息确定所述患者的当前状态；或者，
    采集包含所述患者的图像，根据所述图像确定所述患者的当前状态。
  7. 根据权利要求4所述的生理信号处理方法，其特征在于，所述生理信号包括光电容积信号，所述获取患者单通道的生理信号包括：
    通过光电容积采集设备，采集所述患者指端、耳部、或额头对应部位的光电容积信号。
  8. 根据权利要求4所述的生理信号处理方法，其特征在于，所述生理信号包括光电容积信号和心电信号，所述获取所述患者双通道的生理信号包括：
    通过光电容积采集设备，采集所述患者指端、耳部、或额头对应部位的光电容积信号；以及，
    通过心电采集设备，采集所述患者预设部位的心电信号。
  9. 根据权利要求7所述的生理信号处理方法，其特征在于，所述目标信号包括所述光电容积信号的信号段，所述根据所述目标信号确定所述患者的呼吸状态包括：
    基于所述光电容积信号的信号段获取呼吸信息、脉率、以及血氧饱和度；
    根据所述呼吸信息、脉率、以及血氧饱和度，确定所述患者的呼吸状态。
  10. 根据权利要求9所述的生理信号处理方法，其特征在于，基于所述光电容积信号的信号段获取呼吸信息、脉率、以及血氧饱和度包括：
    获取所述光电容积信号的信号段中峰值出现的次数，根据所述次数和所述时间窗的时长确定脉率；以及，
    对所述光电容积信号的信号段进行插值处理，以重构呼吸波形，基于所述呼吸波形确定呼吸信息；以及，
    获取所述光电容积信号的信号段，根据信号段中红光吸收量和红外光吸收量的比值，确定血氧饱和度。
  11. 根据权利要求8所述的生理信号处理方法，其特征在于，所述目标信号包括所述光电容积信号的信号段和所述心电信号的信号段，所述根据所述目标信号确定所述患者的呼吸状态包括：
    基于所述光电容积信号的信号段获取脉率和血氧饱和度；
    基于所述心电信号的信号段获取呼吸信息；
    根据所述呼吸信息、脉率、以及血氧饱和度，确定所述患者的呼吸状态。
  12. 根据权利要求8所述的生理信号处理方法，其特征在于，所述目标信号包括所述光电容积信号的信号段和所述心电信号的信号段，所述根据所述目标 信号确定所述患者的呼吸状态包括：
    基于所述光电容积信号的信号段获取脉率和血氧饱和度；
    基于所述光电容积信号的信号段和所述心电信号的信号段获取呼吸信息；
    根据所述呼吸信息、脉率、以及血氧饱和度，确定所述患者的呼吸状态。
  13. 根据权利要求12所述的生理信号处理方法，其特征在于，所述基于所述光电容积信号的信号段和所述心电信号的信号段获取呼吸信息包括：
    获取所述光电容积信号的第一权重值，以及获取所述心电信号的第二权重值；
    基于所述光电容积信号的信号段获取第一呼吸信息，基于所述心电信号的信号段获取第二呼吸信息；
    根据所述第一权重值、第一呼吸信息、第二权重值和第二呼吸信息，确定所述呼吸信息。
  14. 根据权利要求9至13任一项所述的生理信号处理方法，其特征在于，所述根据所述呼吸信息、脉率、以及血氧饱和度，确定所述患者的呼吸状态包括：
    当基于所述呼吸信息确定所述患者呼吸暂停开始后第一预设时间内或呼吸暂停结束后第二预设时间内，所述脉率低于第一预设阈值时，确定所述患者的呼吸状态为第一呼吸氧合事件；
    当基于所述呼吸信息确定所述患者呼吸暂停开始后第三预设时间内或吸暂停结束后第四预设时间内，所述血氧饱和度低于第二预设阈值时，确定所述患者的呼吸状态为第二呼吸氧合事件；
    当基于所述呼吸信息确定所述患者呼吸暂停开始后第五预设时间内或吸暂停结束后第六预设时间内，所述脉率低于第一预设阈值且所述血氧饱和度低于第二预设阈值时，确定所述患者的呼吸状态为第三呼吸氧合事件；
    当基于所述呼吸信息确定所述患者存在呼吸暂停时，确定所述患者的呼吸状态为第四呼吸氧合事件；
    当所述脉率低于第一预设阈值时，确定所述患者的呼吸状态为第五呼吸氧合事件；
    当所述血氧饱和度低于第二预设阈值时，确定所述患者的呼吸状态为第六呼吸氧合事件。
  15. 根据权利要求1至13任一项所述的生理信号处理方法，其特征在于，所述获取所述生理信号的特性信息包括：
    对所述生理信号进行预处理，并对预处理后的生理信号进行去噪处理，得到去噪后的生理信号；
    获取所述去噪后的生理信号的特性信息。
  16. 根据权利要求15所述的生理信号处理方法，其特征在于，所述获取所述去噪后的生理信号的特性信息包括：
    从所述去噪后的生理信号中提取峰值幅度、谷值幅度、峰值位置、谷值位置、以及光吸收状态，得到特性信息。
  17. 根据权利要求1至13任一项所述的生理信号处理方法，其特征在于，所述根据所述特征信息确定所述患者的呼吸状态之后，所述生理信号处理方法还包括：
    输出所述呼吸状态的提示信息。
  18. 根据权利要求17所述的生理信号处理方法，其特征在于，当所述呼吸状态符合呼吸氧合事件时，所述输出所述呼吸状态的提示信息包括：
    获取所述呼吸氧合事件发生的时间戳，通过语音播报或屏幕显示所述时间戳及所述呼吸氧合事件的提示信息。
  19. 根据权利要求18所述的生理信号处理方法，其特征在于，所述通过语音播报或屏幕显示所述时间戳及所述呼吸氧合事件的提示信息包括：
    基于所述呼吸氧合事件对所述患者进行状态等级划分，通过语音播报或屏幕显示所述时间戳、所述呼吸氧合事件和所述患者的状态等级的提示信息。
  20. 根据权利要求1至13任一项所述的生理信号处理方法，其特征在于，所述根据所述特征信息确定所述患者的呼吸状态之后，所述生理信号处理方法还包括：
    当所述呼吸状态符合呼吸氧合事件时，基于所述呼吸氧合事件对所述生理信号进行标注，存储标注后的生理信号。
  21. 根据权利要求20所述的生理信号处理方法，其特征在于，所述基于所述呼吸氧合事件对所述生理信号进行标注包括：
    获取所述呼吸氧合事件的类型；
    根据所述呼吸氧合事件的类型确定标注策略；
    根据所述标注策略对所述生理信号进行标注。
  22. 一种生理信号处理装置，其特征在于，包括：
    采集设备，用于采集患者的生理信号；
    显示器，用于显示患者呼吸状态的提示信息；
    存储器，存储有计算机程序；
    处理器，用于运行存储在所述存储器中的计算机程序，并在执行所述计算机程序时实现如权利要求1至21任一项所述的生理信号处理方法。
  23. 一种监护仪，其特征在于，包括：
    传感器附件；
    参数测量电路，用于连接传感器附件，以及获得患者的生理参数信号；
    显示器，用于显示患者呼吸状态的提示信息；
    存储器，存储有计算机程序；
    处理器，用于运行存储在所述存储器中的计算机程序，并在执行所述计算机程序时实现如权利要求1至21任一项所述的生理信号处理方法。
  24. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时使所述处理器实现如权利要求1至21任一项所述的生理信号处理方法。
PCT/CN2020/141082 2020-12-29 2020-12-29 生理信号处理方法、装置、监护仪及计算机可读存储介质 WO2022141119A1 (zh)

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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2005020809A1 (en) * 2003-09-02 2005-03-10 Medtronic Emergency Response Systems, Inc. Pulse detection using patient physiological signals
US20120041279A1 (en) * 2010-08-13 2012-02-16 Respiratory Motion, Inc. Devices and methods for respiratory variation monitoring by measurement of respiratory volumes, motion and variability
CN106255449A (zh) * 2014-05-05 2016-12-21 思勘度股份有限公司 具有用于生命体征扫描的多个集成传感器的便携式装置
CN107072565A (zh) * 2014-09-30 2017-08-18 深圳市大耳马科技有限公司 生命体征光纤传感器系统及方法
CN107743374A (zh) * 2015-07-27 2018-02-27 谷歌有限责任公司 基于患者移动改变生理信号
CN109414204A (zh) * 2016-06-22 2019-03-01 皇家飞利浦有限公司 用于确定针对对象的呼吸信息的方法和装置

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2005020809A1 (en) * 2003-09-02 2005-03-10 Medtronic Emergency Response Systems, Inc. Pulse detection using patient physiological signals
US20120041279A1 (en) * 2010-08-13 2012-02-16 Respiratory Motion, Inc. Devices and methods for respiratory variation monitoring by measurement of respiratory volumes, motion and variability
CN106255449A (zh) * 2014-05-05 2016-12-21 思勘度股份有限公司 具有用于生命体征扫描的多个集成传感器的便携式装置
CN107072565A (zh) * 2014-09-30 2017-08-18 深圳市大耳马科技有限公司 生命体征光纤传感器系统及方法
CN107743374A (zh) * 2015-07-27 2018-02-27 谷歌有限责任公司 基于患者移动改变生理信号
CN109414204A (zh) * 2016-06-22 2019-03-01 皇家飞利浦有限公司 用于确定针对对象的呼吸信息的方法和装置

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