WO2023283935A1 - 用于医疗通气设备的心源性干扰识别方法和医疗通气设备 - Google Patents

用于医疗通气设备的心源性干扰识别方法和医疗通气设备 Download PDF

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WO2023283935A1
WO2023283935A1 PCT/CN2021/106785 CN2021106785W WO2023283935A1 WO 2023283935 A1 WO2023283935 A1 WO 2023283935A1 CN 2021106785 W CN2021106785 W CN 2021106785W WO 2023283935 A1 WO2023283935 A1 WO 2023283935A1
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signal
fluctuation
cardiogenic
disturbance
flow velocity
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French (fr)
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朱锋
刘京雷
姚普林
周小勇
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Shenzhen Mindray Bio Medical Electronics Co Ltd
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Shenzhen Mindray Bio Medical Electronics Co Ltd
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Priority to CN202180100255.3A priority Critical patent/CN117615808A/zh
Priority to EP21949719.5A priority patent/EP4371596A4/en
Priority to PCT/CN2021/106785 priority patent/WO2023283935A1/zh
Publication of WO2023283935A1 publication Critical patent/WO2023283935A1/zh
Priority to US18/412,582 priority patent/US20240157073A1/en
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Definitions

  • the present application relates to the technical field of medical equipment, and more specifically relates to a cardiogenic interference identification method for medical ventilation equipment and the medical ventilation equipment.
  • Medical ventilation equipment with an inspiratory trigger function improves the man-machine synchronicity of the spontaneous breathing process of the ventilated subject.
  • the inspiratory trigger means that when the ventilated subject makes an inhalation action, the medical ventilation device senses the inspiratory effort of the ventilated subject and starts to deliver air.
  • Pipeline leaks, pipeline vibrations, cardiogenic interference and other factors may cause false triggering of medical ventilation equipment.
  • false triggering may lead to hyperventilation of the patient, causing lung injury and respiratory alkalosis; on the other hand, it may be considered as the patient's real inspiratory triggering, leading to clinical misdiagnosis.
  • the first aspect of the embodiment of the present application provides a cardiogenic interference identification method for medical ventilation equipment, including:
  • a fluctuation characteristic of the fluctuation is obtained, and a cardiogenic disturbance in the fluctuation is identified based on the fluctuation characteristic of the fluctuation.
  • the second aspect of the embodiment of the present application provides a cardiogenic interference identification method for medical ventilation equipment, including:
  • a fluctuation characteristic of the fluctuation is obtained, and a cardiogenic disturbance in the fluctuation is identified based on the fluctuation characteristic of the fluctuation.
  • the third aspect of the embodiment of the present application provides a cardiogenic interference identification method for medical ventilation equipment, including:
  • the first signal and the second signal are two signals capable of reflecting the heartbeat signal of the ventilated subject;
  • a fluctuation characteristic of the fluctuation is obtained, and a cardiogenic disturbance in the fluctuation is identified based on the fluctuation characteristic of the fluctuation.
  • the fourth aspect of the embodiment of the present application provides a medical ventilation device, which includes:
  • a ventilation unit for providing ventilation to a ventilated subject
  • a measuring unit configured to monitor the ventilated subject during the process of providing ventilation to the ventilated subject, so as to obtain a first signal and a second signal;
  • a processor connected to the measurement unit, configured to acquire the first signal and the second signal, and the processor is also configured to execute the cardiogenic disturbance identification method as described above.
  • the fifth aspect of the embodiment of the present application provides a cardiogenic interference identification method for medical ventilation equipment, including:
  • the first signal includes a flow velocity signal or a pressure signal obtained by monitoring the ventilated object by the medical ventilation equipment
  • the second signal includes a flow rate signal or a pressure signal obtained by monitoring the ventilated object by the external device human signal
  • Fluctuations in the first signal are identified, and cardiogenic disturbances in the fluctuations are identified based on the second signal.
  • the sixth aspect of the embodiment of the present application provides a medical ventilation device, which includes:
  • a ventilation unit for providing ventilation to a ventilated subject
  • a measuring unit configured to monitor the ventilated subject during the process of providing ventilation to the ventilated subject, so as to obtain a first signal
  • a processor connected to the measurement unit and external equipment, for acquiring the first signal, and acquiring a second signal obtained by the external equipment monitoring the ventilated subject; the processor is also used for executing Cardiac disturbance identification method as described above.
  • the cardiogenic interference identification method for medical ventilation equipment and the medical ventilation equipment identify cardiogenic interference based on the physiological signals collected by the medical ventilation equipment itself, without the need for physiological signals from external equipment, and has obvious clinical use value .
  • FIG. 1 shows a schematic flow chart of a method for identifying cardiogenic disturbances in medical ventilation equipment according to an embodiment of the present application
  • Fig. 2 shows a schematic diagram of a flow velocity signal, a pressure signal and their cross-correlation signals according to an embodiment of the present application
  • Fig. 3 shows a schematic diagram of a flow velocity fluctuation signal according to an embodiment of the present application
  • Fig. 4 shows a schematic diagram of assessing the magnitude of cardiogenic interference according to an embodiment of the present application
  • Fig. 5 shows a schematic diagram of adjusting an inhalation trigger threshold according to an embodiment of the present application
  • Fig. 6 shows a schematic block diagram of a medical ventilation device according to an embodiment of the present application
  • Fig. 7 shows a schematic flowchart of a method for identifying cardiogenic disturbances in medical ventilation equipment according to another embodiment of the present application
  • Fig. 8 shows a schematic flowchart of a method for identifying cardiogenic disturbances in medical ventilation equipment according to another embodiment of the present application
  • Fig. 9 shows a schematic flowchart of a method for identifying cardiogenic disturbances in medical ventilation equipment according to yet another embodiment of the present application.
  • Fig. 10 shows a schematic diagram of identifying cardiogenic interference based on electrocardiographic signals according to an embodiment of the present application.
  • FIG. 1 is a schematic flow chart of a method 100 for identifying cardiogenic interference according to an embodiment of the present application.
  • the cardiogenic interference identification method 100 of the embodiment of the present application includes the following steps:
  • step S110 the first signal and the second signal obtained by monitoring the ventilated object by the medical ventilation equipment are obtained, and the first signal includes a flow rate signal;
  • step S120 identifying the fluctuation of the flow velocity signal according to the flow velocity signal and the second signal
  • step S130 the fluctuation characteristic of the fluctuation is obtained, and the cardiogenic disturbance in the fluctuation is identified based on the fluctuation characteristic of the fluctuation.
  • the cardiogenic interference identification method 100 of the embodiment of the present application identifies cardiogenic interference based on the signal collected by the medical ventilation equipment itself, and then can suppress false triggers caused by cardiogenic interference. When there is no external device for monitoring heartbeat information It can also realize the identification of cardiogenic interference, and has obvious clinical use value.
  • the medical ventilation equipment can be implemented as a device that provides mechanical ventilation to the ventilated object, and the ventilated object can specifically refer to an injured patient who needs to breathe with the help of the medical ventilation equipment due to respiratory failure or spontaneous breathing difficulty.
  • the respiratory system of the ventilated subject cannot complete normal spontaneous breathing, mechanical ventilation is performed through medical ventilation equipment to provide respiratory support.
  • the medical ventilation equipment in the embodiment of the present application can be implemented as a medical equipment with a mechanical ventilation function such as a ventilator and an anesthesia machine.
  • the mechanical ventilation of medical ventilation equipment to complete a breathing cycle needs to go through inhalation trigger, inhalation process, inhalation-exhalation switching and exhalation process.
  • the ventilator takes the initiative to inhale, which causes the pressure drop or flow rate change in the airway, and the medical ventilation equipment senses the inhalation action of the ventilator and starts to deliver air, which is called inspiratory triggering.
  • inspiratory triggering The higher the sensitivity of the inspiratory trigger, the faster the medical ventilation equipment can perceive the inspiratory effort of the ventilated subject, and the smaller the work of breathing required for the inspiratory trigger of the ventilated subject.
  • the higher the sensitivity of the inspiratory trigger function the greater the possibility of false triggering of the medical ventilation device.
  • the cardiogenic interference identification method 100 in this embodiment is based on the medical ventilation
  • the first signal and the second signal collected by monitoring the ventilated subject by the device itself identify cardiogenic interference.
  • Inspiratory triggering methods of medical ventilation equipment include but are not limited to flow rate triggering and pressure triggering.
  • flow rate trigger mode when the medical ventilation device detects that the airway flow rate or the change of the flow rate is greater than the preset flow rate trigger threshold, it is determined that the ventilator triggers inhalation.
  • pressure trigger mode when the medical ventilation device detects that the airway pressure is lower than the preset pressure trigger threshold, it is determined that the ventilator triggers inhalation.
  • the cardiogenic interference identification method 100 of this embodiment can identify cardiogenic interference in the flow velocity signal, and is mainly applicable to the flow velocity trigger mode.
  • Cardiogenic interference is the interference caused by the beating of the heart. During the contraction and relaxation of the heart, changes in the thoracic pressure are caused by changes in the volume of the heart and the swing of its position, which in turn causes gradient changes in the airway pressure and the generation of airflow. Causes fluctuations in flow rate, causing false triggering.
  • the identification method of cardiogenic interference in the embodiment of the present application can effectively identify cardiogenic interference in the flow rate signal, and then suppress false triggering caused by cardiac interference by adjusting the trigger threshold, thereby avoiding hyperventilation caused by false triggering And other issues.
  • the first signal and the second signal are signals obtained by the medical ventilation device monitoring the ventilated subject during mechanical ventilation.
  • the first signal and the second signal can reflect the inspiratory effort of the ventilated subject.
  • the first signal includes a flow rate signal, which may specifically be an airway flow rate obtained by monitoring a ventilated object by a flow rate sensor of a medical ventilation device.
  • the second signal may be other signals except the flow rate signal obtained by monitoring the medical ventilation equipment.
  • the second signal can be The obtained pressure signal may specifically be a pressure signal reflecting the inspiratory effort of the subject to be ventilated.
  • the pressure signal reflecting the inspiratory effort of the ventilated subject includes at least one of an intrapulmonary pressure signal, an airway pressure signal, an esophageal pressure signal, a transdiaphragmatic pressure signal, a gastric intragastric pressure signal, and a carina pressure signal.
  • the pressure signal can be measured by a pressure sensor of the medical ventilation device.
  • the second signal may also be a signal of the respiratory system obtained by the medical ventilation device monitoring the ventilated subject during mechanical ventilation, reflecting the inspiratory effort of the ventilated subject.
  • the signal of the respiratory system reflecting the inspiratory effort of the ventilated subject includes at least one of a lung ultrasound imaging signal, a diaphragm muscle ultrasound imaging signal, an electrical impedance imaging signal, and a diaphragm muscle electrical signal.
  • the electrical impedance imaging signal includes but not limited to chest electrical impedance imaging signal.
  • the second signal can also be the hemodynamic signal obtained by the medical ventilation equipment monitoring the ventilated object during the mechanical ventilation process.
  • the hemodynamic signal has a more direct correlation with cardiogenic interference, which is beneficial to Identify cardiogenic disturbances in the flow signal.
  • the hemodynamic signal includes at least one of invasive blood pressure, arterial blood pressure, central venous pressure and pulse wave.
  • the fluctuation of the flow velocity signal is identified according to the flow velocity signal and the second signal. Since cardiogenic interference can cause fluctuations in both the flow velocity signal and the second signal, the fluctuation feature in the flow velocity signal can be amplified by the second signal, and then the fluctuation can be identified. After the moment when the flow velocity signal fluctuates is identified according to the amplified fluctuation characteristics, the cardiogenic interference in the fluctuations is subsequently identified based on the fluctuation characteristics of the fluctuations.
  • various signal processing methods can be used to amplify the fluctuation characteristics in the flow velocity signal based on the second signal.
  • the cross-correlation signal between the flow velocity signal and the second signal can be obtained according to the flow velocity signal and the second signal, and the fluctuation can be determined according to the cross-correlation signal. time of occurrence.
  • Cross-correlation can enhance the response of cardiogenic disturbances on the signal.
  • the cross-correlation signal between the flow velocity signal and the second signal includes a second-order differential cross-correlation signal between the flow velocity signal and the second signal, that is, a cross-correlation signal between the second-order differential signal of the flow velocity signal and the second-order differential signal of the second signal , it is clearer and more intuitive to explain fluctuations through second-order difference signals.
  • the flow rate signal be F(t)
  • the pressure signal be P(t)
  • the second-order differential signals of the flow rate signal and the pressure signal be ⁇ ( ⁇ F) and ⁇ ( ⁇ P) respectively
  • the flow rate signal and The second-order differential cross-correlation signal of the pressure signal is defined as:
  • N is the length of the pressure signal and flow velocity signal used in the calculation of the cross-correlation signal.
  • Fig. 2 shows an example of a flow velocity signal, a pressure signal and their second-order differential cross-correlation signals. It can be seen from Figure 2 that the cross-correlation signal amplifies the fluctuation characteristics of the flow velocity signal, and in the cross-correlation signal, corresponding to each fluctuation, a peak will be generated. Through clinical data analysis, it is found that the peak of the cross-correlation signal generally appears at a certain time after the moment when the flow velocity signal begins to increase significantly, generally about 200ms after this moment.
  • the fluctuation moment of the flow velocity signal can be identified.
  • a trough may also be generated corresponding to each fluctuation, and at this time, the fluctuation moment of the flow velocity signal can be identified according to the time when the trough of the cross-correlation signal appears.
  • step S130 the fluctuation characteristic of the fluctuation is obtained, and the cardiogenic disturbance in the fluctuation is identified based on the fluctuation characteristic of the fluctuation. Since the heartbeat cycle has a certain regularity, the cardiogenic interference can be identified according to whether the fluctuation characteristics of the fluctuations have corresponding regularity; further, based on the fluctuation characteristics of the fluctuations, it can also be identified that the fluctuations are invalid triggers, pipelines, etc. Fluids are also fluctuations caused by cardiogenic disturbances.
  • the fluctuation characteristic of the fluctuation may include the time characteristic of the fluctuation, the shape characteristic of the fluctuation, and the like.
  • the time characteristic of the fluctuation may include the duration of each fluctuation. For example, when the duration of the detected fluctuation is within a preset range, it may be determined that the fluctuation is cardiogenic disturbance. Since the duration of cardiogenic interference is significantly longer than the duration of the fluctuation caused by water accumulation in the pipeline, but significantly shorter than the duration of the invalid trigger, it can be judged according to the duration of the fluctuation that the time corresponding to the peak value of the second-order differential cross-correlation signal appears Whether the fluctuation is cardiogenic interference, avoid misidentifying the fluctuation of the flow rate signal caused by pipeline water, invalid triggering, etc. as cardiogenic interference.
  • the duration of each fluctuation can be determined according to the difference between the actual flow rate and the estimated flow rate. Specifically, determine the estimated flow velocity of the ventilated object, obtain the flow velocity fluctuation signal according to the difference between the actual flow velocity in the flow velocity signal and the estimated flow velocity at the same moment, and then obtain the duration of each fluctuation according to the flow velocity fluctuation signal, for example, according to the flow velocity fluctuation signal The duration of each fluctuation is obtained by the time difference between two adjacent peaks or two adjacent troughs corresponding to each fluctuation.
  • the flow velocity fluctuation amplitude describes the non-stationarity of the flow velocity signal, and the greater the fluctuation amplitude, the more obvious the sudden change of the flow velocity signal.
  • the flow velocity fluctuation amplitude F d F actu - F esti , so a peak is generated in the flow velocity fluctuation signal after the start moment and end moment of each fluctuation, according to two adjacent The time difference between peaks gives the duration of each fluctuation.
  • the flow velocity fluctuation amplitude F d is defined as F esti -F actu , then a trough will be generated in the flow velocity fluctuation signal after the start and end of each fluctuation. At this time, two adjacent The time difference between the two troughs is used to obtain the duration of each fluctuation.
  • a method for calculating the estimated flow velocity F esti includes: based on the actual flow velocity at a preset moment before the current moment, determining the estimated flow velocity at the current moment according to a respiratory mechanics model.
  • a respiratory mechanics model since the human respiratory system is modeled using R (resistance) and C (compliance), it is a typical first-order RC model.
  • the actual flow velocity 100ms before the current moment can be used to estimate the current estimated flow velocity using the above formula, and the estimated flow velocity thus obtained is more accurate than using the flow velocity at the initial time point to estimate the flow velocity at each subsequent moment .
  • Another calculation method of the estimated flow velocity F esti is: performing linear fitting based on the actual flow velocity within a preset time period before the current moment to determine the estimated flow velocity at the current moment.
  • the temporal characteristics of the fluctuation may also include the rhythm of the fluctuation, that is, the rhythm and regularity of the occurrence time of multiple fluctuations.
  • the rhythm of multiple fluctuations may include the average time interval of multiple fluctuations, the variance of multiple time intervals of multiple fluctuations, and the like.
  • the rhythm of multiple fluctuations can be determined according to the occurrence time of each fluctuation determined in step S120; The signal determines a rhythm that fluctuates multiple times.
  • the cardiogenic disturbances in the fluctuations may also be jointly determined according to the duration of each fluctuation and the rhythms of multiple fluctuations. For example, when multiple fluctuations conform to a preset rhythm, and the duration of each fluctuation is within a preset range, the multiple fluctuations are determined to be cardiogenic disturbances.
  • the heartbeat cycle is generally stable, and when the moment of this cardiogenic disturbance is identified, the moment when the next cardiogenic disturbance will occur can be predicted based on the heartbeat cycle.
  • the heartbeat cycle can be obtained from the rhythm of cardiogenic disturbances, or it can be obtained by other means.
  • the heartbeat period can be predicted according to the time interval between at least two cardiogenic disturbances, and the predicted time of the next cardiogenic disturbance can be obtained according to the occurrence time of the current cardiogenic disturbance and the heartbeat period.
  • cardiogenic interference In general, the characteristics of cardiogenic interference on the flow rate signal and pressure signal are more obvious in the expiratory phase than in the inspiratory phase. Since the heartbeat is regular, the heartbeat characteristics of the expiratory phase can reflect the heartbeat characteristics of the entire ventilation cycle. Therefore, cardiogenic interference can be identified during the expiratory phase. Based on the identified results and the known heartbeat cycle, Predict the timing of cardiogenic disturbances during the inspiratory phase.
  • the size of the cardiac interference can be determined, and the trigger sensitivity can be adjusted according to the size of the cardiac interference, so as to avoid false triggering caused by the cardiac interference.
  • Adjusting the trigger sensitivity according to the size of the cardiogenic interference can realize the automatic adjustment of the trigger sensitivity according to the interference situation, without manual adjustment by the user; at the same time, adjusting the trigger sensitivity according to the size of the cardiogenic interference can improve the accuracy of the adjustment and avoid excessively increasing the trigger sensitivity , to ensure trigger sensitivity while avoiding false triggering caused by cardiogenic interference.
  • the trigger sensitivity includes inspiratory trigger sensitivity or exhalation trigger sensitivity, and its characterization forms include but not limited to flow rate, pressure, change speed of flow rate and change speed of pressure.
  • the flow velocity fluctuation amplitude F d at the occurrence time of the cardiogenic disturbance may be taken as the magnitude of the cardiogenic disturbance.
  • the magnitude of cardiogenic interference may also be determined according to other signal characteristics such as the waveform area of the flow velocity fluctuation.
  • determine the estimated flow velocity of the ventilated object obtain the flow velocity fluctuation signal according to the difference between the actual flow velocity in the flow velocity signal and the estimated flow velocity at the same moment, and determine the cardiogenicity according to the flow velocity fluctuation signal corresponding to the occurrence time of the cardiogenic disturbance.
  • the size of the disturbance For example, referring to FIG. 4 , the occurrence time of cardiogenic interference can be determined according to the cross-correlation signal, and the peak value of the flow velocity fluctuation signal corresponding to this moment can be determined as the magnitude of the cardiogenic interference. If the duration of each fluctuation is determined according to the flow velocity fluctuation signal in step S120, the size of the cardiogenic disturbance can be determined according to the flow velocity fluctuation signal obtained in step S120.
  • step S130 only the fluctuation amplitude of the flow velocity at the occurrence time of the cardiogenic disturbance may be calculated, so as to obtain the magnitude of the cardiogenic disturbance.
  • the flow velocity fluctuation amplitude F d is the difference between the actual flow velocity F actu and the estimated flow velocity F esti .
  • the actual flow velocity F actu can be directly extracted from the flow velocity signal.
  • the calculation method of the estimated flow velocity F esti can be referred to above, and will not be repeated here.
  • the maximum value of multiple peaks in the flow velocity fluctuation signal can be used as the magnitude of cardiogenic interference, so as to avoid false triggering caused by cardiogenic interference as much as possible.
  • the average value of multiple peaks in the flow velocity fluctuation signal can also be used as the magnitude of the cardiac interference, so as to reduce errors.
  • the multiple peaks can be multiple peaks in the same breathing cycle, that is, the size of the cardiogenic interference is calculated according to multiple cardiogenic interferences in the same breathing cycle, and the size of the cardiogenic interference is performed once per breathing cycle and adjust the trigger sensitivity in real time according to the measurement results.
  • the multiple peaks are not limited to multiple peaks in the same respiratory cycle, and can also be multiple peaks in at least two respiratory cycles, or a preset number of multiple peaks.
  • the size of the cardiac disturbance is calculated once.
  • the trigger sensitivity can be adjusted to be greater than or equal to the trigger signal caused by the cardiogenic disturbance.
  • the trigger threshold Strig can be adjusted to be greater than or equal to the magnitude Fd of cardiac disturbance, so as to avoid false triggering caused by cardiac disturbance.
  • the trigger sensitivity at any moment during the ventilation process can be finally adjusted to be greater than or equal to the magnitude of cardiac interference, so as to avoid false triggering as much as possible.
  • the adjustment object is the inspiratory trigger threshold
  • the trigger sensitivity at any time during the ventilation process can also be understood as the inspiratory trigger threshold at any time during the inspiratory trigger phase.
  • the predicted time of the next cardiogenic interference can be obtained according to the occurrence time of the current cardiogenic interference and the heartbeat cycle, and the Prediction of the next cardiogenic disturbance
  • the trigger sensitivity in the vicinity of the prediction is adjusted to be greater than or equal to the size of the cardiac disturbance, which can also avoid false triggering caused by cardiac disturbance, and at the same time, it is also conducive to ensuring the sensitivity of the inspiratory trigger .
  • the vicinity of the predicted time of the next cardiogenic disturbance refers to a period of time before and after the predicted time of the next cardiogenic disturbance predicted according to the heartbeat cycle.
  • the trigger sensitivity can be increased according to the preset step size until the trigger sensitivity is greater than or equal to the trigger signal caused by the cardiogenic disturbance, thereby avoiding sudden changes in the trigger sensitivity.
  • the trigger sensitivity can be increased by a preset step in each respiratory cycle, and each preset step is the size F d of the cardiogenic disturbance multiplied by a certain coefficient.
  • the preset step length can be adjusted in real time according to the magnitude of the cardiac disturbance.
  • FIG. 5 it shows the synchronously collected pressure signal, flow velocity signal and electrocardiographic signal, and the electrocardiographic signal is used to illustrate the moment when central source interference of the flow velocity signal occurs.
  • the inspiratory triggering time is consistent with the cardiogenic interference time, that is, the inspiratory triggering at this time is a false trigger caused by cardiogenic interference, so the inspiratory triggering threshold is increased according to the size of the cardiogenic interference; in the next In the respiratory cycle, the inspiratory triggering time T2 is still consistent with the cardiogenic interference time, and the inspiratory triggering threshold continues to increase; until the inspiratory triggering threshold at T3 and T4 is greater than the size of the cardiogenic interference, the inspiratory triggering is no longer consistent with the cardiogenic interference. related to source interference.
  • the user interaction interface of the medical ventilation device may also be used to prompt the cardiogenic interference in the flow rate signal, and the user can manually adjust it based on the cardiogenic interference.
  • the adjustment can be guided according to the relationship between the inspiratory trigger state of the medical ventilator and the moment at which the cardiogenic disturbance occurs.
  • the correlation between the moment of inhalation trigger and the moment of cardiogenic interference can be judged. If the correlation between the two is found to be high, it means that the inhalation trigger is caused by cardiac interference.
  • the user can judge whether the adjustment is completed according to the time of cardiogenic interference displayed on the interface, or the medical ventilation equipment can judge whether the correlation between the inspiration trigger time and the time of cardiogenic interference has been reduced to the preset requirement, And prompt the user whether to complete the adjustment.
  • the cardiogenic interference identification method 100 for medical ventilation equipment identifies cardiogenic interference based on the signal collected by the medical ventilation equipment itself, without the need for external equipment signals, and has obvious clinical use value .
  • the medical ventilation device 600 of the embodiment of the present application includes a ventilation unit 610, a measurement unit 620 and a processor 630.
  • the ventilation unit 610 is used to provide ventilation to the ventilation object; the measurement unit 620 is used to provide ventilation to the ventilation object.
  • the medical ventilation device 600 can be implemented as a medical device with a mechanical ventilation function such as a ventilator or anesthesia machine.
  • the ventilation unit 610 includes an air source and an air circuit, and the air circuit includes an inspiratory branch and an expiratory branch.
  • the gas source is used to provide gas during mechanical ventilation, and the inspiratory branch is connected to the gas source to provide an inspiratory path during mechanical ventilation; the expiratory branch is used to provide exhalation during mechanical ventilation path.
  • the gas provided by the ventilation unit 610 to the ventilated object may be oxygen, or a mixed gas of air and oxygen.
  • the gas can be the compressed gas provided by the gas supply system, or the gas from the environment.
  • the measurement unit 620 includes sensors for measuring the first signal and the second signal during mechanical ventilation.
  • the first signal includes a flow rate signal
  • the sensor includes at least a flow rate sensor for measuring the flow rate signal.
  • the second signal may include a pressure signal
  • the pressure signal includes a pressure signal reflecting the inspiratory effort of the ventilated subject, specifically including a pulmonary pressure signal, an airway pressure signal, an esophageal pressure signal, a transdiaphragmatic pressure signal, a gastric pressure signal, and a carina pressure signal. at least one of the signals.
  • the sensors also include pressure sensors for measuring pressure signals.
  • the flow rate sensor is arranged at the exhalation end and the inhalation end of the air circuit, and the pressure sensor is arranged at the connection end with the ventilated object.
  • the second signal may also include a hemodynamic signal, and the hemodynamic signal includes at least one of invasive blood pressure, arterial blood pressure, central venous pressure, and pulse wave; the measurement unit 620 includes a device for measuring the hemodynamic signal measuring device.
  • the second signal may also include a signal of the respiratory system reflecting the inspiratory effort of the ventilated subject, specifically including at least one of a lung ultrasound imaging signal, a diaphragm muscle ultrasound imaging signal, an electrical impedance imaging signal, and a diaphragm muscle electrical signal;
  • the measurement unit 620 includes a A measuring device for measuring signals of the respiratory system reflecting the inspiratory effort of a ventilated subject.
  • the processor 630 is connected to the measurement unit 620, and is used to: receive the first signal and the second signal measured by the measurement unit 620, the first signal includes the flow velocity signal; identify the fluctuation of the flow velocity signal according to the flow velocity signal and the second signal; obtain the fluctuation Fluctuation characteristics, and identify cardiogenic disturbances in fluctuations based on the fluctuation characteristics of the fluctuations.
  • the processor 630 can be implemented by software, hardware, firmware or any combination thereof, and can use circuits, single or multiple application-specific integrated circuits, single or multiple general-purpose integrated circuits, single or multiple microprocessors, single or multiple programmable
  • the logic device, or any combination of the foregoing circuits and/or devices, or other suitable circuits or devices is programmed, and the processor 630 may control other components in the medical ventilation device 600 to perform desired functions.
  • the processor 630 is further configured to: determine the magnitude of the cardiogenic disturbance; and adjust the trigger sensitivity according to the magnitude of the cardiogenic disturbance.
  • identifying the fluctuation of the flow velocity signal according to the flow velocity signal and the second signal includes: obtaining a cross-correlation signal between the flow velocity signal and the second signal according to the flow velocity signal and the second signal; and determining the occurrence time of the fluctuation according to the cross-correlation signal.
  • the cross-correlation signal includes a second-order differential cross-correlation signal.
  • the fluctuation characteristic comprises a temporal characteristic of the fluctuation.
  • the time characteristics of the fluctuation include at least one of the following: the duration of each fluctuation, and the rhythm of the fluctuation.
  • identifying the cardiogenic interference in the fluctuation based on the duration of each fluctuation includes: determining that the fluctuation is a cardiogenic interference when the duration of the fluctuation is within a preset range; identifying the cardiac interference in the fluctuation based on the rhythm of the fluctuation Sexual interference, including: when multiple fluctuations conform to the preset rhythm, it is determined that the fluctuations are cardiogenic interference.
  • obtaining the duration of each fluctuation includes: determining the estimated flow velocity of the ventilated subject; obtaining the flow velocity fluctuation signal according to the difference between the actual flow velocity in the flow velocity signal and the estimated flow velocity at the same moment; The duration of the fluctuation.
  • determining the magnitude of cardiogenic interference includes: determining the estimated flow velocity of the ventilated subject; obtaining a flow velocity fluctuation signal according to the difference between the actual flow velocity in the flow velocity signal and the estimated flow velocity at the same moment; The time-corresponding flow velocity fluctuation signal determines the size of the cardiogenic disturbance.
  • determining the estimated flow rate of the ventilation subject includes: based on the actual flow rate at a preset time before the current time, determining the estimated flow rate at the current time according to a respiratory mechanics model.
  • linear fitting is performed based on the actual flow velocity within a preset time period before the current moment, so as to determine the estimated flow velocity at the current moment.
  • adjusting the inspiratory trigger threshold according to the magnitude of the cardiogenic disturbance includes: increasing the trigger sensitivity according to a preset step size until the trigger sensitivity is greater than or equal to the trigger signal caused by the cardiogenic disturbance. Further, the preset step size can be adjusted in real time according to the size of the cardiogenic disturbance.
  • adjusting the trigger sensitivity according to the magnitude of the cardiogenic disturbance includes: adjusting the trigger sensitivity at any moment during the ventilation process to be greater than or equal to the magnitude of the cardiogenic disturbance, or adjusting the trigger sensitivity according to the current
  • the occurrence time of the disturbance determines the prediction time of the next occurrence of the cardiac disturbance, and adjusts the trigger sensitivity around the prediction time of the next occurrence of the cardiogenic disturbance to be greater than or equal to the size of the cardiogenic disturbance.
  • the medical ventilation device 600 identifies cardiogenic interference in the flow rate signal based on the signal collected by itself, without the need for signals from external devices, and has obvious clinical use value.
  • FIG. 7 is a schematic flow chart of a method 700 for identifying cardiogenic interference according to an embodiment of the present application.
  • the cardiogenic interference identification method 700 of the embodiment of the present application includes the following steps:
  • step S710 obtain a first signal and a second signal obtained by monitoring the ventilated object by the medical ventilation equipment, the first signal includes a pressure signal;
  • step S720 identifying fluctuations in the pressure signal according to the pressure signal and the second signal
  • step S730 the fluctuation characteristic of the fluctuation is obtained, and the cardiogenic disturbance in the fluctuation is identified based on the fluctuation characteristic of the fluctuation.
  • the inspiratory triggering methods of medical ventilation equipment include flow rate triggering and pressure triggering.
  • the cardiogenic interference identification method 100 in the previous embodiment can identify cardiac source interference in the flow rate signal, and is mainly applicable to flow rate triggering;
  • the cardiogenic interference identification method 700 of the embodiment can identify cardiogenic interference in pressure signals, and is mainly applicable to pressure triggers. The following only describes the main steps of the cardiogenic interference identification method 700, and more details can be referred to above.
  • the second signal acquired in step S710 may include a flow velocity signal.
  • the second signal may be used to amplify the fluctuation caused by the central source interference of the pressure signal, so as to identify the fluctuation in the pressure signal.
  • a cross-correlation signal between the flow velocity signal and the pressure signal can be obtained according to the second signal and the pressure signal; and the occurrence time of the fluctuation can be determined according to the cross-correlation signal.
  • the cross-correlation signal includes a second-order differential cross-correlation signal of the flow velocity signal and the pressure signal.
  • the fluctuation characteristic of the fluctuation is obtained, and the cardiogenic disturbance is identified based on the fluctuation characteristic of the fluctuation.
  • the fluctuation feature may include the time feature of the fluctuation.
  • the time characteristics of the fluctuations include at least one of the following: the duration of each fluctuation, and the rhythm of the fluctuations. For example, when the duration of the fluctuation is within a preset range, it is determined that the fluctuation is cardiogenic disturbance. Alternatively, when the multiple fluctuations conform to the preset rhythm, it is determined that the multiple fluctuations are multiple cardiogenic disturbances.
  • the rhythm of multiple fluctuations can be determined directly according to the peak or trough of the cross-correlation signal, and the duration of each fluctuation can be determined by: determining the estimated pressure of the ventilated object; according to the actual pressure in the pressure signal and the same moment
  • the pressure fluctuation signal is obtained by the difference of the estimated pressure; according to the pressure fluctuation signal, the duration of each fluctuation can be obtained, for example, according to the difference between two adjacent peaks or two adjacent troughs corresponding to each of the fluctuations in the pressure fluctuation signal
  • the time difference between gives the duration of each fluctuation.
  • one manner of determining the estimated pressure of the ventilated object is: based on the actual pressure at a preset time before the current time, and according to the respiratory mechanics model, the estimated pressure at the current time is determined.
  • Another way of determining the estimated pressure of the ventilation subject is: performing linear fitting based on the actual pressure within a preset time period before the current moment, so as to determine the estimated pressure at the current moment.
  • the magnitude of the cardiac disturbance can be further determined, and the trigger sensitivity can be adjusted according to the magnitude of the cardiogenic disturbance, where the trigger sensitivity is the trigger sensitivity of the pressure trigger.
  • the magnitude of cardiogenic interference can be determined according to the above-mentioned pressure fluctuation signal.
  • the magnitude of cardiogenic disturbance includes the maximum or average value of multiple peaks in the pressure fluctuation signal.
  • the trigger sensitivity when the trigger sensitivity is adjusted according to the magnitude of the cardiogenic disturbance, the trigger sensitivity may be increased according to a preset step size until the trigger sensitivity is greater than or equal to the trigger signal caused by the cardiogenic disturbance.
  • the preset step size can be adjusted in real time according to the size of the cardiogenic disturbance.
  • the trigger sensitivity at any moment during the ventilation process can be adjusted to be greater than or equal to the magnitude of the cardiac disturbance, or it can be determined according to the occurrence time of the current cardiac disturbance
  • the predicted time of the occurrence of the next cardiogenic disturbance adjusting the trigger sensitivity near the predicted time of the next occurrence of the cardiogenic disturbance to be greater than or equal to the magnitude of the cardiogenic disturbance.
  • the heartbeat cycle can be predicted according to the time interval between at least two cardiogenic disturbances, and The time of occurrence and the heartbeat cycle get the predicted time of the next cardiogenic disturbance.
  • the medical ventilation device 600 of the embodiment of the present application includes a ventilation unit 610, a measurement unit 620 and a processor 630.
  • the ventilation unit 610 is used to provide ventilation to the ventilation object; the measurement unit 620 is used to provide ventilation to the ventilation object.
  • the processor 630 is connected to the measurement unit 620 for obtaining the first signal signal and the second signal, the processor 630 is also used to execute the above-mentioned cardiogenic interference identification method 700, that is: acquire the first signal and the second signal, the first signal includes a pressure signal; according to the pressure signal and the second signal Identify fluctuations in the pressure signal; acquire fluctuation characteristics of the fluctuations, and identify cardiogenic disturbances in the fluctuations based on the fluctuation characteristics of the fluctuations.
  • the cardiogenic interference identification method 700 of this embodiment and the medical ventilation equipment identify the cardiogenic interference in the pressure signal based on the signal obtained by the medical ventilation equipment itself from monitoring the ventilated object, and can also identify it when there is no external device for monitoring heartbeat information Cardiac interference, so as to avoid false triggering caused by cardiac interference.
  • FIG. 8 is a schematic flowchart of a method 800 for identifying cardiogenic disturbances according to an embodiment of the present application.
  • the cardiogenic interference identification method 800 of the embodiment of the present application includes the following steps:
  • step S810 the first signal and the second signal obtained by the medical ventilation equipment monitoring the ventilated subject are obtained, and the first signal and the second signal are two kinds of signals that can reflect the heartbeat signal of the ventilated subject ;
  • step S820 identifying fluctuations of the first signal according to the first signal and the second signal
  • step S830 the fluctuation characteristic of the fluctuation is obtained, and the cardiogenic disturbance in the fluctuation is identified based on the fluctuation characteristic of the fluctuation.
  • the first signal and the second signal are any two signals obtained by the medical ventilation equipment monitoring the ventilated subject, which can reflect the heartbeat signal of the ventilated subject, including but not limited to flow rate signal, pressure signal, Hemodynamic signals, signals of the respiratory system that reflect the inspiratory effort of the ventilated subject, etc.
  • pressure signals include but not limited to intrapulmonary pressure signals, airway pressure signals, esophageal pressure signals, transdiaphragmatic pressure signals, intragastric pressure signals , carina pressure signals
  • hemodynamic signals include but not limited to invasive blood pressure, arterial blood pressure, central venous pressure and pulse wave
  • signals of the respiratory system reflecting the inspiratory effort of the ventilated subject include but not limited to lung ultrasound imaging signals, Diaphragm ultrasound imaging signal, electrical impedance imaging signal and diaphragm muscle electrical signal.
  • identifying the fluctuation of the first signal according to the first signal and the second signal includes: obtaining a cross-correlation signal between the first signal and the second signal according to the first signal and the second signal, and determining the occurrence of the fluctuation according to the cross-correlation signal time.
  • the cardiogenic interference in the fluctuation is identified according to the fluctuation characteristic of the fluctuation.
  • the fluctuation characteristic includes a fluctuation time characteristic, and the fluctuation time characteristic includes at least one of the following: each time the fluctuation The duration of the fluctuation, the rhythm of the fluctuation. For example, when the duration of the fluctuations is within a preset range, it is determined that the fluctuations are cardiogenic disturbances; or, when multiple fluctuations conform to a preset rhythm, it is determined that the fluctuations are cardiogenic disturbances.
  • the method further includes: determining the magnitude of the cardiogenic disturbance; adjusting the trigger sensitivity of the medical ventilation device according to the magnitude of the cardiogenic disturbance.
  • the trigger sensitivity of the medical device is the trigger sensitivity related to the first signal.
  • the medical ventilation device 600 of the embodiment of the present application includes a ventilation unit 610, a measurement unit 620 and a processor 630.
  • the ventilation unit 610 is used to provide ventilation to the ventilation object; the measurement unit 620 is used to provide ventilation to the ventilation object.
  • the ventilated subject is monitored to obtain the first signal and the second signal, which are two kinds of signals capable of reflecting the heartbeat signal of the ventilated subject; the processor 630 is connected with the measuring unit 620 for Acquire the first signal and the second signal, and the processor 630 is also configured to execute the above-mentioned cardiogenic interference identification method 800, that is: acquire the first signal and the second signal; identify the first signal according to the first signal and the second signal Fluctuation; Obtain the fluctuation characteristic of the fluctuation, and identify the cardiogenic disturbance in the fluctuation based on the fluctuation characteristic of the fluctuation.
  • the cardiogenic interference identification method 800 that is: acquire the first signal and the second signal; identify the first signal according to the first signal and the second signal Fluctuation; Obtain the fluctuation characteristic of the fluctuation, and identify the cardiogenic disturbance in the fluctuation based on the fluctuation characteristic of the fluctuation.
  • the cardiogenic interference identification method 800 of this embodiment and the medical ventilation equipment identify the cardiogenic interference in one of the signals based on the two signals that can reflect the heartbeat signal of the ventilation subject obtained by the medical ventilation equipment itself from monitoring the ventilation subject. Cardiogenic interference can also be identified when there is an external device that monitors heartbeat information, thereby avoiding false triggers caused by cardiac interference.
  • the cardiogenic interference identification method 900 includes the following steps:
  • step S910 a first signal and a second signal are acquired, the first signal includes the flow rate signal or the pressure signal obtained by monitoring the ventilation object by the medical ventilation equipment, and the second signal includes the external device monitoring the ventilation object monitor the resulting human body signal;
  • step S920 fluctuations in the flow rate signal are identified, and cardiogenic disturbances in the fluctuations are identified based on the second signal.
  • the cardiogenic interference identification method 900 of this embodiment acquires a second signal from an external device, and identifies cardiogenic interference in a flow velocity signal or a pressure signal based on the second signal.
  • the cardiac interference after the cardiac interference is identified, it further includes: determining the size of the cardiac interference, and adjusting the trigger sensitivity according to the size of the cardiac interference, which does not require the user to manually adjust the trigger sensitivity, and can avoid cardiac interference.
  • sexual interference causes false triggers while ensuring the sensitivity of inspiratory triggers.
  • identifying cardiogenic interference based on the second signal includes: obtaining a predicted time range for occurrence of cardiogenic interference based on the second signal; and determining fluctuations within the predicted time range as cardiogenic interference.
  • the second signal may be a physiological signal related to a heartbeat.
  • the second signal may be a signal capable of directly reflecting the characteristics of the ventilated subject's heartbeat, such as at least one of an electrocardiogram (ECG), a pulse wave signal, and an invasive blood pressure signal. Since the second signal can directly reflect the characteristics of the heartbeat, the moment and duration of the heartbeat can be identified according to the characteristics of the second signal reflecting the heartbeat, so as to obtain the predicted time range of cardiogenic interference.
  • ECG electrocardiogram
  • a series of waveforms will be recorded on the ECG during one cardiac cycle, including P waves, QRS complexes and T waves. It is generally believed that within 30-60 ms after the end of a QRS complex, that is, between time periods 1 and 2 in Figure 10, there will be an obvious fluctuation in the flow velocity signal that first increases and then decreases, that is, cardiogenic interference. The increased flow rate of this process is prone to false triggering. Therefore, according to the moment when the QRS complex in the electrocardiographic signal ends, the predicted time range of cardiogenic interference can be obtained, and the flow velocity fluctuation within the predicted time range is determined as cardiogenic interference.
  • the second signal may be a signal of the respiratory system collected by an external device reflecting the inspiratory effort of the ventilated subject, specifically including a lung ultrasound imaging signal, a diaphragm muscle ultrasound imaging signal, an electrical impedance imaging signal, and a diaphragm muscle electrical signal. at least one of .
  • determining the magnitude of cardiogenic interference includes: determining the estimated flow velocity of the ventilated subject; obtaining a flow velocity fluctuation signal according to the difference between the actual flow velocity in the flow velocity signal and the estimated flow velocity at the same moment; The flow rate fluctuation signal determines the magnitude of cardiogenic disturbance.
  • determining the estimated flow rate of the ventilated object includes: based on the actual flow rate at a preset time before the current time, determining the estimated flow rate at the current time according to the respiratory mechanics model; or performing linear fitting based on the actual flow rate within a preset time period before the current time , to determine the estimated flow velocity at the current moment.
  • Adjusting the trigger sensitivity according to the magnitude of the cardiogenic disturbance includes: increasing the trigger sensitivity according to a preset step size until the trigger sensitivity is greater than or equal to the trigger signal caused by the cardiogenic disturbance.
  • the preset step size can be adjusted in real time according to the size of the cardiogenic disturbance.
  • the trigger sensitivity at any moment during the ventilation process can be adjusted to be greater than or equal to the magnitude of the cardiac disturbance, or the trigger sensitivity near the predicted moment of the cardiac disturbance can be adjusted to Adjust to be greater than or equal to the magnitude of the cardiogenic disturbance.
  • the trigger sensitivity at any moment during the ventilation process can be adjusted to be greater than or equal to the magnitude of the cardiac disturbance, or the trigger sensitivity near the predicted moment of the cardiac disturbance can be adjusted to Adjust to be greater than or equal to the magnitude of the cardiogenic disturbance.
  • the medical ventilation device 600 of the embodiment of the present application includes a ventilation unit 610, a measurement unit 620 and a processor 630, wherein the ventilation unit 610 is used to provide ventilation to the ventilation object; the measurement unit 620 is used to provide ventilation to the ventilation object. Monitor the ventilated object during the ventilation process to obtain a first signal; the processor 630 is connected with the measurement unit 620 and external equipment to obtain the first signal and obtain the first signal obtained by the external device monitoring the ventilated object. Two signals, the processor 630 is also used to execute the cardiogenic disturbance identification method 800 .
  • the cardiogenic interference identification method 900 of this embodiment and the medical ventilation equipment identify the cardiogenic interference in the flow velocity signal based on the signal obtained by monitoring the ventilated object by the external device, thereby improving the accuracy of the identification of the cardiogenic interference.
  • the disclosed devices and methods may be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components can be combined or May be integrated into another device, or some features may be omitted, 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

一种用于医疗通气设备的心源性干扰识别方法（100）和医疗通气设备（600），该方法包括：获取医疗通气设备（600）对通气对象进行监测所得到的第一信号和第二信号，第一信号包括流速信号；根据流速信号和第二信号识别流速信号的波动；获取波动的波动特征，并基于波动的波动特征识别波动中的心源性干扰。该方法基于医疗通气设备（600）自身采集的信号识别心源性干扰，无需外部设备的生理信号，具有明显的临床使用价值。

Description

用于医疗通气设备的心源性干扰识别方法和医疗通气设备
说明书
技术领域
本申请涉及医疗设备技术领域，更具体地涉及一种用于医疗通气设备的心源性干扰识别方法和医疗通气设备。
背景技术
带有吸气触发功能的医疗通气设备提升了通气对象自主呼吸过程的人机同步性。吸气触发即当通气对象产生吸气动作时，医疗通气设备感知到通气对象的吸气努力而开始送气。管道漏气、管道震动、心源性干扰等因素可能引起医疗通气设备的误触发。误触发一方面可能导致病人过度通气，引起肺损伤和呼吸碱中毒；另一方面可能被认为是病人真实的吸气触发，导致临床的误诊断。
为了提升医疗通气设备的可靠性，目前的医疗通气设备通常具有泄露补偿功能，通过自动适应不同大小的泄漏进而避免由于泄漏导致的误触发。然而针对心源性干扰导致的误触发，只能通过手动调节吸气触发的灵敏度来防止误触发，而此操作的前提是医护人员能够及时识别到心源性干扰导致的误触发。由于心源性干扰导致的误触发与通气对象真实的吸气触发比较相似，绝大部分情况下，一般经验的医护人员难以对其进行识别。
发明内容
在发明内容部分中引入了一系列简化形式的概念，这将在具体实施方式部分中进一步详细说明。本发明的发明内容部分并不意味着要试图限定出所要求保护的技术方案的关键特征和必要技术特征，更不意味着试图确定所要求保护的技术方案的保护范围。
本申请实施例第一方面提供了一种用于医疗通气设备的心源性干扰识别方法，包括：
获取所述医疗通气设备对通气对象进行监测所得到的第一信号和第二信号，所述第一信号包括流速信号；
根据所述流速信号和所述第二信号识别所述流速信号的波动；
获取所述波动的波动特征，并基于所述波动的波动特征识别所述波动中的心源性干扰。
本申请实施例第二方面提供了一种用于医疗通气设备的心源性干扰识别方法，包括：
获取所述医疗通气设备对通气对象进行监测所得到的第一信号和第二信号，所述第一信号包括压力信号；
根据所述压力信号和所述第二信号识别所述压力信号的波动；
获取所述波动的波动特征，并基于所述波动的波动特征识别所述波动中的心源性干扰。
本申请实施例第三方面提供了一种用于医疗通气设备的心源性干扰识别方法，包括：
获取所述医疗通气设备对通气对象进行监测所得到的第一信号和第二信号，所述第一信号和所述第二信号为两种能够反映所述通气对象心跳信号的信号；
根据所述第一信号和所述第二信号识别所述第一信号的波动；
获取所述波动的波动特征，并基于所述波动的波动特征识别所述波动中的心源性干扰。
本申请实施例第四方面提供了一种医疗通气设备，所述医疗通气设备包括：
通气单元，用于向通气对象提供通气；
测量单元，用于在向所述通气对象提供通气的过程中对所述通气对象进行监测，以得到第一信号和第二信号；
处理器，与所述测量单元连接，用于获取所述第一信号和所述第二信号，所述处理器还用于执行如上所述的心源性干扰识别方法。
本申请实施例第五方面提供了一种用于医疗通气设备的心源性干扰识别方法，包括：
获取第一信号和第二信号，所述第一信号包括医疗通气设备对通气对象进行监测所得到的流速信号或压力信号，所述第二信号包括外部设备对所述通气对象进行监测所得到的人体信号；
识别所述第一信号的波动，并基于所述第二信号识别所述波动中的心源性干扰。
本申请实施例第六方面提供了一种医疗通气设备，所述医疗通气设备包 括：
通气单元，用于向通气对象提供通气；
测量单元，用于在向所述通气对象提供通气的过程中对所述通气对象进行监测，以得到第一信号；
处理器，与所述测量单元和外部设备连接，用于获取所述第一信号，以及获取所述外部设备对所述通气对象进行监测所得到的第二信号，所述处理器还用于执行如上所述的心源性干扰识别方法。
根据本申请实施例的用于医疗通气设备的心源性干扰识别方法和医疗通气设备基于医疗通气设备自身采集的生理信号识别心源性干扰，无需外部设备的生理信号，具有明显的临床使用价值。
附图说明
为了更清楚地说明本申请实施例中的技术方案，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，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
在附图中：
图1示出根据本申请一实施例的用于医疗通气设备的心源性干扰识别方法的示意性流程图；
图2示出根据本申请一实施例的流速信号、压力信号和二者的互相关信号的示意图；
图3示出根据本申请一实施例的流速波动信号的示意图；
图4示出根据本申请一实施例的评估心源性干扰的大小的示意图；
图5示出根据本申请一实施例的调节吸气触发阈值的示意图；
图6示出根据本申请一实施例的医疗通气设备的示意性框图
图7示出根据本申请另一实施例的用于医疗通气设备的心源性干扰识别方法的示意性流程图；
图8示出根据本申请又一实施例的用于医疗通气设备的心源性干扰识别方法的示意性流程图；
图9示出根据本申请再一实施例的用于医疗通气设备的心源性干扰识别方法的示意性流程图；
图10示出根据本申请一实施例的基于心电信号识别心源性干扰的示意 图。
具体实施方式
为了使得本申请的目的、技术方案和优点更为明显，下面将参照附图详细描述根据本申请的示例实施例。显然，所描述的实施例仅仅是本申请的一部分实施例，而不是本申请的全部实施例，应理解，本申请不受这里描述的示例实施例的限制。基于本申请中描述的本申请实施例，本领域技术人员在没有付出创造性劳动的情况下所得到的所有其它实施例都应落入本申请的保护范围之内。
在下文的描述中，给出了大量具体的细节以便提供对本申请更为彻底的理解。然而，对于本领域技术人员而言显而易见的是，本申请可以无需一个或多个这些细节而得以实施。在其他的例子中，为了避免与本申请发生混淆，对于本领域公知的一些技术特征未进行描述。
应当理解的是，本申请能够以不同形式实施，而不应当解释为局限于这里提出的实施例。相反地，提供这些实施例将使公开彻底和完全，并且将本申请的范围完全地传递给本领域技术人员。
在此使用的术语的目的仅在于描述具体实施例并且不作为本申请的限制。在此使用时，单数形式的“一”、“一个”和“所述/该”也意图包括复数形式，除非上下文清楚指出另外的方式。还应明白术语“组成”和/或“包括”，当在该说明书中使用时，确定所述特征、整数、步骤、操作、元件和/或部件的存在，但不排除一个或更多其它的特征、整数、步骤、操作、元件、部件和/或组的存在或添加。在此使用时，术语“和/或”包括相关所列项目的任何及所有组合。
为了彻底理解本申请，将在下列的描述中提出详细的结构，以便阐释本申请提出的技术方案。本申请的可选实施例详细描述如下，然而除了这些详细描述外，本申请还可以具有其他实施方式。
下面，将参考图1描述根据本申请一个实施例的用于医疗通气设备的心源性干扰识别方法。图1是本申请实施例的心源性干扰识别方法100的一个示意性流程图。
如图1所示，本申请实施例的心源性干扰识别方法100包括如下步骤：
在步骤S110，获取所述医疗通气设备对通气对象进行监测所得到的第一 信号和第二信号，所述第一信号包括流速信号；
在步骤S120，根据所述流速信号和所述第二信号识别所述流速信号的波动；
在步骤S130，获取所述波动的波动特征，并基于所述波动的波动特征识别所述波动中的心源性干扰。
本申请实施例的心源性干扰识别方法100基于医疗通气设备自身采集的信号识别心源性干扰，进而能够对心源性干扰引起的误触发进行抑制，在不存在监测心跳信息的外部设备时也能够实现对心源性干扰的识别，具有明显的临床使用价值。
具体地，医疗通气设备可以实现为向通气对象提供机械通气的设备，通气对象具体可以指因呼吸功能衰竭或自主呼吸困难而需借助医疗通气设备进行呼吸的伤病患者。当通气对象的呼吸系统无法完成正常的自主呼吸时，通过医疗通气设备进行机械通气，以提供呼吸支持。本申请实施例的医疗通气设备可以实现为呼吸机、麻醉机等具有机械通气功能的医疗设备。
医疗通气设备完成一个呼吸周期的机械通气需要经历吸气触发、吸气过程、吸呼切换及呼气过程。其中，通气对象主动吸气，引起气道内的压力下降或流速变化，医疗通气设备感知到通气对象的吸气动作而开始送气，称为吸气触发。吸气触发的灵敏度越高，医疗通气设备越能够更快地感知到通气对象的吸气努力，通气对象吸气触发需要的呼吸功越小。但与此同时，吸气触发功能的灵敏度越高，医疗通气设备发生误触发的可能性越大。在引起误触发的各种因素中，心源性干扰引起的误触发与真实的吸气触发较为相似而难以识别，针对这一问题，本申请实施例的心源性干扰识别方法100基于医疗通气设备自身对通气对象进行监测采集到的第一信号和第二信号识别心源性干扰。
医疗通气设备的吸气触发方式包括但不限于流速触发和压力触发。对于流速触发方式来说，当医疗通气设备检测到气道流速或流速变化大于预设的流速触发阈值时判断为通气对象触发吸气。对于压力触发方式来说，当医疗通气设备检测到气道压低于预设的压力触发阈值时判断为通气对象触发吸气。本实施例的心源性干扰识别方法100能够识别流速信号中的心源性干扰，主要适用于流速触发方式。与压力触发相比，流速触发更为敏感，通气对象的吸气负荷更少；而正是由于流速触发较为敏感，更容易受到心源性干扰的影 响而导致误触发。心源性干扰为心脏搏动引发的干扰，在心脏的收缩和舒张过程中，由于心脏体积的变化及其位置的摆动引起胸腔压力的变化，进而引起气道内压的梯度变化和气流的产生，而导致流速出现波动，引起误触发。本申请实施例的心源性干扰的识别方法可以有效识别流速信号中的心源性干扰，进而通过调节触发阈值来对心源性干扰引起的误触发进行抑制，从而避免误触发引起的过度通气等问题。
在步骤S110，第一信号和第二信号为医疗通气设备在机械通气过程中对通气对象进行监测所得到的信号，示例性地，第一信号和第二信号能够反映通气对象吸气努力。其中，第一信号包括流速信号，具体可以是医疗通气设备的流速传感器对通气对象进行监测所得到的气道流速。第二信号可以是由医疗通气设备监测所得的除流速信号以外的其他信号。
在一个示例中，由于心脏的收缩和舒张过程会引起胸腔压力的变化，进而引起气道内压力的变化，即压力信号能够较为明显地反映心源性干扰，因此第二信号可以是医疗通气设备测得的压力信号，具体可以是反映通气对象吸气努力的压力信号。示例性地，反映通气对象吸气努力的压力信号包括肺内压信号、气道压信号、食道压信号、跨膈压信号、胃内压信号、隆突压信号中的至少一种。示例性地，可以通过医疗通气设备的压力传感器测得压力信号。
或者，第二信号也可以是医疗通气设备在机械通气过程中对通气对象进行监测所得到的反映通气对象吸气努力的呼吸系统的信号。示例性地，反映通气对象吸气努力的呼吸系统的信号包括肺部超声成像信号、膈肌超声成像信号、电阻抗成像信号、膈肌电信号中的至少一种。其中，电阻抗成像信号包括但不限于胸部电阻抗成像信号。
又或者，第二信号也可以是医疗通气设备在机械通气过程中对通气对象进行监测所得到的血流动力学信号，血流动力学信号与心源性干扰具有更直接的相关性，有利于识别流速信号中的心源性干扰。示例性地，血流动力学信号包括有创血压、动脉血压、中心静脉压和脉搏波中的至少一种。在步骤S120中，根据流速信号和第二信号识别流速信号的波动。由于心源性干扰在流速信号和第二信号中均会造成波动，通过第二信号可以放大流速信号中的波动特征，进而对波动进行识别。在根据放大后的波动特征识别出流速信号发生波动的时刻之后，后续再基于波动的波动特征识别波动中的心源性干扰。
其中，可以通过各种信号处理的方式基于第二信号放大流速信号中的波 动特征，例如，可以根据流速信号和第二信号得到流速信号与第二信号的互相关信号，根据互相关信号确定波动的发生时间。互相关能够增强心源性干扰在信号上的响应。示例性地，流速信号与第二信号的互相关信号包括流速信号与第二信号的二阶差分互相关信号，即流速信号的二阶差分信号与第二信号的二阶差分信号的互相关信号，通过二阶差分信号解释波动更为清晰和直观。
继续以压力信号为例，设流速信号为F(t)，压力信号为P(t)，流速信号与压力信号的二阶差分信号分别为Δ(ΔF)，Δ(ΔP)，则流速信号与压力信号的二阶差分互相关信号定义为：
Figure PCTCN2021106785-appb-000001
其中，N为互相关信号计算所用的压力信号和流速信号的长度。图2示出了流速信号、压力信号及二者的二阶差分互相关信号的示例。由图2可知，互相关信号放大了流速信号的波动特征，在互相关信号中，对应于每一次波动，会对应产生一个波峰。通过临床数据分析发现，互相关信号的波峰一般出现在流速信号开始明显增加的时刻之后的一定时间，一般为该时刻后200ms左右。因此，根据压力信号和流速信号的二阶差分互相关信号的波峰出现的时刻，可以对流速信号的波动时刻进行识别。但可以理解的是，当采用其他函数计算互相关信号时，对应于每一次波动也可能对应产生一个波谷，则此时可以根据互相关信号的波谷出现的时刻对流速信号的波动时刻进行识别。
当识别到流速信号中的波动之后，在步骤S130，获取波动的波动特征，并基于波动的波动特征识别波动中的心源性干扰。由于心跳周期具有一定的规律性，根据波动的波动特征是否具有相应的规律性可以识别出其中的心源性干扰；进一步地，还可以基于波动的波动特征识别出该波动是无效触发、管路积水还是心源性干扰导致的波动。
其中，波动的波动特征可以包括波动的时间特征、波动的形状特征等。示例性地，波动的时间特征可以包括每次波动的持续时间。例如，可以在检测到波动的持续时间在预设范围内时，确定该波动为心源性干扰。由于心源性干扰的持续时间明显大于管路积水造成的波动的时间，而明显小于无效触发的持续时间，因此可以根据波动的持续时间来判断二阶差分互相关信号峰 值对应的时刻出现的波动是否为心源性干扰，避免将管路积水、无效触发等造成的流速信号的波动误识别为心源性干扰。
在一个实施例中，可以根据实际流速与估计流速的差值确定每次波动的持续时间。具体地，确定通气对象的估计流速，根据流速信号中的实际流速与同一时刻的估计流速的差值得到流速波动信号，再根据流速波动信号得到每次波动的持续时间，例如，根据流速波动信号中对应每次波动的相邻两个波峰或相邻两个波谷之间的时间差得到每次波动的持续时间。
如图3所示，设通气对象的实际流速为F actu，通气对象的估计流速为F esti，则流速波动幅度定义为：F d＝F actu-F esti。流速波动幅度描述了流速信号的非平稳性，波动幅度越大，说明流速信号的突变越明显。参见图3的流速信号和流速波动幅度(F d)波形可知，对应于流速信号的每一次波动，都会在波动开始时刻和结束时刻一段时间后分别产生一个波峰，并且两个波峰对应时刻的时间差恰好等于流速信号的波动开始时刻和结束时刻之间的时间差。因此，根据流速波动信号中对应每次波动的相邻两个波峰之间的时间差可以得到每次波动的持续时间，进而确定波动是否是心源性干扰。
需要说明的是，在图3的示例中，流速波动幅度F d＝F actu-F esti，因此流速波动信号中在每次波动的开始时刻和结束时刻之后分别产生一个波峰，根据相邻两个波峰之间的时间差可以得到每次波动的持续时间。而在其他实施例中，若将流速波动幅度F d定义为F esti-F actu，则流速波动信号中在每次波动的开始和结束时刻之后将分别产生一个波谷，此时可以根据相邻两个波谷之间的时间差得到每次波动的持续时间。
为了计算流速波动幅度F d，需要确定每个时间点的估计流速F esti。示例性地，估计流速F esti的一种计算方法包括：基于当前时刻之前预设时刻的实际流速，根据呼吸力学模型确定当前时刻的估计流速。根据呼吸力学模型，由于使用R(阻力)和C(顺应性)对人体呼吸系统进行建模所得到的是典型的一阶RC模型，根据一阶模型的特点，呼气阶段的理论估算流速为F esti(t)＝PEF×e -t/τ，其中τ为呼气时间常数，PEF为呼气峰值流速。根据指数波形的特点，可以用任意时刻的实际流速估算其后某一时刻的估计流速，即F esti(t)＝Flow(t-Δt)×e -Δt/τ。例如，可以使用当前时刻100ms前的实际流速、采用以上公式来估计当前的估计流速，由此得到的估计流速相比于完全使用起始时间点的流速估计后续每一时刻的流速来说更加准确。
估计流速F esti的另外一种计算方法为：基于当前时刻之前预设时间段内的实际流速进行线性拟合，以确定当前时刻的估计流速。该方法根据线性公式基于一段时间内的历史流速进行拟合，利用线性公式获取当前时刻的估计流速，即F esti(t)＝k×t+b。例如，可以用当前时刻之前200ms时间段内的实际流速，线性估算当前时刻的估计流速。
除了每次波动的持续时间以外，波动的时间特征还可以包括波动的节律，即多次波动的发生时间的节奏和规律。当多次波动符合预设节律时，即多次波动的发生时间具有预设规律性时，确定该多次波动为心源性干扰。例如，多次波动的节律可以包括多次波动的平均时间间隔，多次波动的多个时间间隔的方差等。在确定多次波动的节律时，可以根据步骤S120中确定的每次波动的发生时间确定多次波动的节律；或者，由于波动时刻与互相关信号的波峰的节律一致，也可以直接根据互相关信号确定多次波动的节律。
在一些实施例中，为了提高心源性干扰识别的准确性，还可以根据每次波动的持续时间和多次波动的节律共同确定波动中的心源性干扰。例如，当多次波动符合预设节律，并且其中每次波动的持续时间在预设范围内时，将该多次波动确定为心源性干扰。
此外，心跳周期一般是稳定的，在识别到本次心源性干扰的时刻时，可以根据心跳周期预测出下一次心源性干扰出现的时刻。心跳周期可以根据心源性干扰的节律获得，也可以采用其他方式获得。例如，可以根据至少两次心源性干扰之间的时间间隔预测心跳周期，并根据当次心源性干扰的发生时间和心跳周期得到下一次心源性干扰的预测时间。
一般情况下，心源性干扰在流速信号和压力信号上的特征在呼气阶段相比于吸气阶段更为明显。由于心跳是规律性的，是呼气阶段的心跳特征可以反映整个通气周期的心跳特征，因此，可以在呼气阶段对心源性干扰进行识别，基于识别到的结果和已知的心跳周期，对吸气阶段的心源性干扰的发生时间进行预测。
进一步地，在识别出流速信号中的心源性干扰之后，还可以确定心源性干扰的大小，根据心源性干扰的大小调节触发灵敏度，从而避免心源性干扰引起的误触发。根据心源性干扰的大小调节触发灵敏度能够实现触发灵敏度随干扰情况的自动调节，无需用户手动调节；同时，根据心源性干扰的大小调节触发灵敏度能够提高调节的精确性，避免过度提高触发灵敏度，在避免 心源性干扰引起误触发的同时保证触发的敏感性。示例性地，触发灵敏度包括吸气触发灵敏度或呼气触发灵敏度，其表征形式包括但不限于流速、压力、流速的变化速度和压力的变化速度。
为了根据心源性干扰的大小调节触发灵敏度，首先需要确定心源性干扰的大小。在一个实施例中，可以将心源性干扰发生时间的流速波动幅度F d作为心源性干扰的大小。在其他实施例中，也可以根据流速波动的波形面积等其他信号特征确定心源性干扰的大小。
具体地，确定通气对象的估计流速，根据流速信号中的的实际流速与同一时刻的估计流速的差值得到流速波动信号，并根据心源性干扰的发生时间对应的流速波动信号确定心源性干扰的大小。例如，参见图4，可以根据互相关信号确定心源性干扰的发生时间，并将该时刻对应的流速波动信号的峰值确定为心源性干扰的大小。若在步骤S120根据流速波动信号确定每次波动的持续时间，则可以根据步骤S120中获取的流速波动信号确定心源性干扰的大小。否则，在步骤S130中可以仅计算心源性干扰发生时间的流速波动幅度，从而得到心源性干扰的大小。流速波动幅度F d为实际流速F actu与估计流速F esti的差值，实际流速F actu可以直接从流速信号中提取，估计流速F esti的计算方式可以参见上文，在此不做赘述。
进一步地，在计算心源性干扰的大小以调节触发灵敏度时，可以将流速波动信号中多个峰值的最大值作为心源性干扰的大小，以尽可能地避免心源性干扰造成误触发。或者，也可以将流速波动信号中多个峰值的平均值作为心源性干扰的大小，以减小误差。其中，多个峰值可以是同一个呼吸周期中的多个峰值，即根据同一个呼吸周期的多个心源性干扰计算心源性干扰的大小，每个呼吸周期进行一次心源性干扰的大小的测量，并根据测量结果实时调节触发灵敏度。但需要注意的是，多个峰值不限于同一个呼吸周期中的多个峰值，也可以是至少两个呼吸周期中的多个峰值，或者预设数目的多个峰值，例如，可以在每检测到10个心源性干扰时计算一次心源性干扰的大小。
在确定心源性干扰的大小后，则可以将触发灵敏度调节为大于或等于心源性干扰导致的触发信号。例如，对于流速触发来说，可以将触发阈值S trig调节为大于或等于心源性干扰的大小F d，从而避免心源性干扰造成误触发。例如，可以将触发阈值S trig设置为S trig＝F d+k，其中，k为大于零的常量或变量。
在一实施例中，可以最终将通气过程中任意时刻的触发灵敏度均调节为 大于或等于心源性干扰的大小，以尽可能地避免产生误触发现象。当调节对象是吸气触发阈值时，通气过程中任意时刻的触发灵敏度也可以理解为吸气触发阶段任意时刻的吸气触发阈值。
或者，由于心跳具有规律性，在识别到当次心源性干扰的发生时间时，可以根据当次心源性干扰的发生时间和心跳周期得到下一次心源性干扰发生的预测时间，并将下一次心源性干扰的预测预测附近的触发灵敏度调节为大于或等于心源性干扰的大小，同样可以避免心源性干扰造成误触发，与此同时，还有利于保证吸气触发的敏感性。其中，下一次心源性干扰的预测时间附近是指根据心跳周期预测的下一次心源性干扰的预测时间前后的一段时间范围内。
在根据心源性干扰的大小调节触发灵敏度时，可以按照预设步长增大触发灵敏度，直到触发灵敏度大于或等于心源性干扰导致的触发信号，从而避免触发灵敏度发生突变。例如，可以在每个呼吸周期将触发灵敏度增大一个预设步长，每个预设步长为心源性干扰的大小F d乘以一定的系数。同时，由于在通气过程中会不断对心源性干扰的大小进行测量，因此可以根据心源性干扰的大小实时调节预设步长。
参见图5，其中示出了同步采集的压力信号、流速信号和心电信号，心电信号为了说明流速信号中心源性干扰出现的时刻。在T1时刻，吸气触发时刻与心源性干扰时刻一致，即此时的吸气触发为心源性干扰造成的误触发，因此根据心源性干扰的大小增大吸气触发阈值；在下一个呼吸周期，吸气触发时刻T2仍然与心源性干扰时刻一致，继续增大吸气触发阈值；直到T3和T4时刻的吸气触发阈值大于心源性干扰的大小，吸气触发不再与心源性干扰相关。
可选地，在识别到心源性干扰之后，也可以通过医疗通气设备的用户交互界面对流速信号中的心源性干扰进行提示，由用户基于心源性干扰进行手动调节。在根据心源性干扰的大小调节吸气触发阈值时，可以根据医疗通气设备的吸气触发状态和心源性干扰出现的时刻之间的关系来引导调节。在调节过程中，可以判断吸气触发时刻与心源性干扰时刻的相关性，若发现二者相关性较高，则说明该吸气触发是由于心源性干扰导致的，此时按照一定步长增大触发灵敏度，直到吸气触发时刻与心源性干扰时刻的相关性降低至不足以认为吸气触发是由于心源性干扰引起的误触发。其中，可以由用户根据界面上显示的心源性干扰时刻判断是否完成调节，也可以由医疗通气设备对 吸气触发时刻与心源性干扰时刻的相关性是否已降低至预设要求进行判断，并提示用户是否完成调节。
综上所述，根据本申请实施例的用于医疗通气设备的心源性干扰识别方法100基于医疗通气设备自身采集的信号识别心源性干扰，无需外部设备的信号，具有明显的临床使用价值。
本申请实施例另一方面提供一种医疗通气设备，医疗通气设备用于代替、控制或改变通气对象的呼吸，通过增加肺通气量来改善通气对象的呼吸功能并减轻通气对象的呼吸消耗。参加图6，本申请实施例的医疗通气设备600包括通气单元610、测量单元620和处理器630，通气单元610用于向通气对象提供通气；测量单元620用于在向通气对象提供通气的过程中对通气对象进行监测，以得到第一信号和第二信号；处理器630与测量单元620连接，用于获取第一信号和第二信号，处理器630还用于执行上述的心源性干扰识别方法100，以下仅对医疗通气设备600的主要功能进行描述，其他具体细节可以参见上文。医疗通气设备600可以实现为呼吸机或麻醉机等具有机械通气功能的医疗设备。
示例性地，通气单元610包括气源和气路，气路包括吸气支路和呼气支路。气源用于在机械通气的过程中提供气体，吸气支路与气源连接，用于在机械通气的过程中提供吸气路径；呼气支路用于在机械通气的过程中提供呼气路径。通气单元610向通气对象提供的气体可以是氧气，也可以是空气与氧气的混合气体。气体可以是供气系统提供的压缩气体，也可以是来源于环境中的气体。
测量单元620包括传感器，用于在机械通气过程中测量第一信号和第二信号。第一信号包括流速信号，传感器至少包括流速传感器，用于测量流速信号。第二信号可以包括压力信号，压力信号包括反映通气对象吸气努力的压力信号，具体包括肺内压信号、气道压信号、食道压信号、跨膈压信号、胃内压信号、隆突压信号中的至少一种。传感器还包括压力传感器，用于测量压力信号。示例性地，流速传感器设置在气路的呼气端和吸气端，压力传感器设置在与通气对象的连接端。第二信号还可以包括血流动力学信号，血流动力学信号包括有创血压、动脉血压、中心静脉压和脉搏波中的至少一种；测量单元620包括用于测量血流动力学信号的测量装置。第二信号还可以包括反映通气对象吸气努力的呼吸系统的信号，具体包括肺部超声成像信号、膈肌超声成像信号、电阻抗成像信号、膈肌电信号中的至少一种；测量单元 620包括用于测量反映通气对象吸气努力的呼吸系统的信号的测量装置。
处理器630与测量单元620连接，用于：接收测量单元620测得的第一信号和第二信号，第一信号包括流速信号；根据流速信号和第二信号识别流速信号的波动；获取波动的波动特征，并基于波动的波动特征识别波动中的心源性干扰。
处理器630可以通过软件、硬件、固件或其任意组合来实现，可以使用电路、单个或多个专用集成电路、单个或多个通用集成电路、单个或多个微处理器、单个或多个可编程逻辑器件、或者前述电路和/或器件的任意组合、或者其他适合的电路或器件，并且处理器630可以控制医疗通气设备600中的其它组件以执行期望的功能。
在一个实施例中，处理器630还用于：确定心源性干扰的大小；根据心源性干扰的大小调节触发灵敏度。
在一个实施例中，根据流速信号和第二信号识别流速信号的波动，包括：根据流速信号和第二信号得到流速信号与第二信号的互相关信号；根据互相关信号确定波动的发生时间。示例性地，互相关信号包括二阶差分互相关信号。
在一个实施例中，波动特征包括波动的时间特征。进一步地，波动的时间特征包括以下至少一种：每次波动的持续时间、波动的节律。其中，基于每次波动的持续时间识别波动中的心源性干扰，包括：当波动的持续时间在预设范围内时，确定波动为心源性干扰；基于波动的节律识别波动中的心源性干扰，包括：当多次波动符合预设节律时，确定波动为心源性干扰。
在一个实施例中，获取每次波动的持续时间包括：确定通气对象的估计流速；根据流速信号中的实际流速与同一时刻的估计流速的差值得到流速波动信号；根据流速波动信号得到每次波动的持续时间。
在一个实施例中，确定心源性干扰的大小包括：确定通气对象的估计流速；根据流速信号中的实际流速与同一时刻的估计流速的差值得到流速波动信号；根据心源性干扰的发生时间对应的流速波动信号确定心源性干扰的大小。
示例性地，确定通气对象的估计流速包括：基于当前时刻之前预设时刻的实际流速，根据呼吸力学模型确定当前时刻的估计流速。或者，基于当前时刻之前预设时间段内的实际流速进行线性拟合，以确定当前时刻的估计流速。
在一个实施例中，根据心源性干扰的大小调节吸气触发阈值，包括：按 照预设步长增大触发灵敏度，直到触发灵敏度大于或等于心源性干扰导致的触发信号。进一步地，可以根据心源性干扰的大小实时调节预设步长。
在一个实施例中，根据心源性干扰的大小调节触发灵敏度，包括：将通气过程中任意时刻的触发灵敏度均调节为大于或等于心源性干扰的大小，或者，根据当次将心源性干扰的发生时间确定下一次心源性干扰发生的预测时间，将下一次心源性干扰发生的预测时间附近的触发灵敏度调节为大于或等于心源性干扰的大小。
根据本申请实施例的用于医疗通气设备600基于自身采集的信号识别流速信号中的心源性干扰，无需外部设备的信号，具有明显的临床使用价值。
下面，将参考图7描述根据本申请另一个实施例的用于医疗通气设备的心源性干扰识别方法。图7是本申请实施例的心源性干扰识别方法700的一个示意性流程图。
如图7所示，本申请实施例的心源性干扰识别方法700包括如下步骤：
在步骤S710，获取医疗通气设备对通气对象进行监测所得到的第一信号和第二信号，所述第一信号包括压力信号；
在步骤S720，根据所述压力信号和所述第二信号识别所述压力信号的波动；
在步骤S730，获取所述波动的波动特征，并基于所述波动的波动特征识别所述波动中的心源性干扰。
如上所述，医疗通气设备的吸气触发方式包括流速触发和压力触发，上一实施例的心源性干扰识别方法100能够识别出流速信号中的心源性干扰，主要适用于流速触发；本实施例的心源性干扰识别方法700能够识别出压力信号中的心源性干扰，主要适用于压力触发。以下仅对心源性干扰识别方法700的主要步骤进行描述，更多的细节可以参照上文。
由于心脏的收缩和舒张会造成流速的变化，因此步骤S710中获取的第二信号可以包括流速信号。之后，在步骤S720中，可以通过第二信号放大压力信号中心源性干扰造成的波动，从而识别压力信号中的波动。例如，可以根据第二信号和压力信号得到流速信号与压力信号的互相关信号；并根据互相关信号确定波动的发生时间。示例性地，互相关信号包括流速信号与压力信号的二阶差分互相关信号。
识别到压力信号的波动之后，在步骤S730，获取波动的波动特征，并基于波动的波动特征识别其中的心源性干扰。其中，波动特征可以包括波动的 时间特征。波动的时间特征包括以下至少一种：每次波动的持续时间、波动的节律。例如，当波动的持续时间在预设范围内时，确定该波动为心源性干扰。或者，当多次波动符合预设节律时，确定该多次波动为多个心源性干扰。
其中，多次波动的节律可以直接根据互相关信号的波峰或波谷来确定，每次波动的持续时间可以通过以下方式来确定：确定通气对象的估计压力；根据压力信号中的实际压力与同一时刻的估计压力的差值得到压力波动信号；根据压力波动信号得到每次波动的持续时间，例如，可以根据压力波动信号中对应每次所述波动的相邻两个波峰或相邻两个波谷之间的时间差得到每次所述波动的持续时间。其中，确定通气对象的估计压力的一种方式为：基于当前时刻之前预设时刻的实际压力，根据呼吸力学模型确定当前时刻的估计压力。确定通气对象的估计压力的另外一种方式为：基于当前时刻之前预设时间段内的实际压力进行线性拟合，以确定当前时刻的估计压力。
在识别到心源性干扰后，可以进一步确定心源性干扰的大小，并根据心源性干扰的大小调节触发灵敏度，此处的触发灵敏度为压力触发的触发灵敏度。其中，心源性干扰的大小可以根据上述的压力波动信号来确定。示例性地，心源性干扰的大小包括压力波动信号中多个峰值的最大值或平均值。
在一个实施例中，在根据心源性干扰的大小调节触发灵敏度时，可以按照预设步长增大触发灵敏度，直到触发灵敏度大于或等于心源性干扰导致的触发信号。其中，可以根据心源性干扰的大小实时调节预设步长。
在根据心源性干扰的大小调节触发灵敏度时，可以将通气过程中任意时刻的触发灵敏度均调节为大于或等于心源性干扰的大小，或者，可以根据当次心源性干扰的发生时间确定下一次心源性干扰发生的预测时间，将下一次心源性干扰发生的预测时间附近的所述触发灵敏度调节为大于或等于所述心源性干扰的大小。在根据当次心源性干扰的发生时间确定下一次心源性干扰发生的预测时间时，可以根据至少两次心源性干扰之间的时间间隔预测心跳周期，并根据当次心源性干扰的发生时间和心跳周期得到下一次心源性干扰的预测时间。
本申请实施例另一方面提供一种医疗通气设备，该医疗通气设备可以实现上述的心源性干扰识别方法700。继续参加图6，本申请实施例的医疗通气设备600包括通气单元610、测量单元620和处理器630，通气单元610用于向通气对象提供通气；测量单元620用于在向通气对象提供通气的过程中对通气对象进行监测，以得到第一信号和第二信号，其中第一信号包括压力信号，第二信号包括但不限于流速信号；处理器630与测量单元620连接，用 于获取第一信号和第二信号，处理器630还用于执行上述的心源性干扰识别方法700，即：获取第一信号和第二信号，第一信号包括压力信号；根据压力信号和所述第二信号识别压力信号的波动；获取波动的波动特征，并基于波动的波动特征识别波动中的心源性干扰。
本实施例的心源性干扰识别方法700和医疗通气设备基于医疗通气设备自身对通气对象监测所得的信号识别压力信号中的心源性干扰，在不存在监测心跳信息的外部设备时也能够识别心源性干扰，从而避免心源性干扰引起的误触发。
下面，将参考图8描述根据本申请另一个实施例的用于医疗通气设备的心源性干扰识别方法。图8是本申请实施例的心源性干扰识别方法800的一个示意性流程图。
如图8所示，本申请实施例的心源性干扰识别方法800包括如下步骤：
在步骤S810，获取所述医疗通气设备对通气对象进行监测所得到的第一信号和第二信号，所述第一信号和所述第二信号为两种能够反映所述通气对象心跳信号的信号；
在步骤S820，根据所述第一信号和所述第二信号识别所述第一信号的波动；
在步骤S830，获取所述波动的波动特征，并基于所述波动的波动特征识别所述波动中的心源性干扰。
示例性地，在步骤S810中，第一信号和第二信号为医疗通气设备对通气对象进行监测所得到的任意两种能够反应通气对象心跳信号的信号，包括但不限于流速信号、压力信号、血流动力学信号、反映通气对象吸气努力的呼吸系统的信号等，其中，压力信号包括但不限于肺内压信号、气道压信号、食道压信号、跨膈压信号、胃内压信号、隆突压信号；血流动力学信号包括但不限于有创血压、动脉血压、中心静脉压和脉搏波；反映通气对象吸气努力的呼吸系统的信号包括但不限于肺部超声成像信号、膈肌超声成像信号、电阻抗成像信号和膈肌电信号。
示例性地，根据第一信号和第二信号识别第一信号的波动包括：根据第一信号和第二信号得到第一信号与第二信号的互相关信号，并根据互相关信号确定波动的发生时间。识别到第一信号的波动之后，根据波动的波动特征识别波动中的心源性干扰，示例性地，波动特征包括波动的时间特征，波动的时间特征包括以下至少一种：每次所述波动的持续时间、所述波动的节律。 例如，当波动的持续时间在预设范围内时，确定波动为心源性干扰；或者，当多次波动符合预设节律时，确定波动为心源性干扰。
示例性地，在识别到心源性干扰之后，还包括：确定心源性干扰的大小；根心源性干扰的大小调节医疗通气设备的触发灵敏度。示例性地，医疗设备的触发灵敏度为与第一信号相关的触发灵敏度。
本申请实施例另一方面提供一种医疗通气设备，该医疗通气设备可以实现上述的心源性干扰识别方法800。继续参加图6，本申请实施例的医疗通气设备600包括通气单元610、测量单元620和处理器630，通气单元610用于向通气对象提供通气；测量单元620用于在向通气对象提供通气的过程中对通气对象进行监测，以得到第一信号和第二信号，第一信号和第二信号为两种能够反应所述通气对象心跳信号的信号；处理器630与测量单元620连接，用于获取第一信号和第二信号，处理器630还用于执行上述的心源性干扰识别方法800，即：获取第一信号和第二信号；根据第一信号和第二信号识别第一信号的波动；获取波动的波动特征，并基于波动的波动特征识别波动中的心源性干扰。
本实施例的心源性干扰识别方法800和医疗通气设备基于医疗通气设备自身对通气对象监测所得的两种能够反映通气对象心跳信号的信号识别其中一种信号中的心源性干扰，在不存在监测心跳信息的外部设备时也能够识别心源性干扰，从而避免心源性干扰引起的误触发。
本申请实施例另一方面提供一种用于医疗通气设备的心源性干扰识别方法，参见图9，该心源性干扰识别方法900包括如下步骤：
在步骤S910，获取第一信号和第二信号，所述第一信号包括医疗通气设备对通气对象进行监测所得到的流速信号或压力信号，所述第二信号包括外部设备对所述通气对象进行监测所得到的人体信号；
在步骤S920，识别所述流速信号的波动，并基于所述第二信号识别所述波动中的心源性干扰。本实施例的心源性干扰识别方法900从外部设备获取第二信号，基于第二信号识别流速信号或压力信号中的心源性干扰。
在一个实施例中，识别到心源性干扰之后，还包括：确定心源性干扰的大小，以及根据心源性干扰的大小调节触发灵敏度，无需用户手动调节触发灵敏度，并且能够在避免心源性干扰造成误触发的同时保证吸气触发的敏感性。
在一个实施例中，基于第二信号识别心源性干扰，包括：基于第二信号得到出现心源性干扰的预测时间范围；将该预测时间范围内的波动确定为心 源性干扰。第二信号可以是与心跳相关的生理信号。进一步地，第二信号可以是能够获得直接反映通气对象心跳特征的信号，例如心电信号(ECG)、脉搏波信号、有创血压信号中的至少一种。由于第二信号能够直接反映心跳特征，因此可以根据该第二信号中反映心跳的特征识别心跳发生的时刻和持续时间，从而得到出现心源性干扰的预测时间范围。
以心电信号为例，参见图10，一次心动周期会在心电图上记录一系列波形，包括P波、QRS波群和T波。一般认为，在一个QRS波群结束后的30-60ms内，即图10中的时间段1和2之间，流速信号会出现一个明显的先增加后减小的波动，即心源性干扰，此过程的流速增加容易导致误触发。因此，根据心电信号中的QRS波群结束的时刻，可以得到出现心源性干扰的预测时间范围，并将该预测时间范围内的流速波动确定为心源性干扰。
在另一实施例中，第二信号可以是外部设备采集的反映通气对象吸气努力的呼吸系统的信号，具体包括肺部超声成像信号、膈肌超声成像信号、电阻抗成像信号、膈肌电信号中的至少一种。
在识别到心源性干扰的大小之后，还可以确定心源性干扰的大小，并根据心源性干扰的大小调节吸气触发阈值。示例性地，确定心源性干扰的大小包括：确定通气对象的估计流速；根据流速信号中的实际流速与同一时刻的估计流速的差值得到流速波动信号；根据心源性干扰的发生时间对应的流速波动信号确定心源性干扰的大小。其中，确定通气对象的估计流速包括：基于当前时刻之前预设时刻的实际流速，根据呼吸力学模型确定当前时刻的估计流速；或者，基于当前时刻之前预设时间段内的实际流速进行线性拟合，以确定当前时刻的估计流速。根据心源性干扰的大小调节触发灵敏度，包括：按照预设步长增大触发灵敏度，直到触发灵敏度大于或等于心源性干扰导致的触发信号。其中，可以根据心源性干扰的大小实时调节预设步长。在根据心源性干扰的大小调节触发灵敏度时，可以将通气过程中任意时刻的触发灵敏度均调节为大于或等于心源性干扰的大小，或者，将心源性干扰的预测时刻附近的触发灵敏度调节为大于或等于心源性干扰的大小。步骤S930和步骤S940的具体细节可以参照心源性干扰识别方法100中的相关描述，在此不做赘述。
本申请实施例另一方面提供一种医疗通气设备，该医疗通气设备可以实现上述的心源性干扰识别方法900。继续参加图6，本申请实施例的医疗通气设备600包括通气单元610、测量单元620和处理器630，其中，通气单元610用于向通气对象提供通气；测量单元620用于在向通气对象提供通气的 过程中对通气对象进行监测，以得到第一信号；处理器630与测量单元620和外部设备连接，用于获取第一信号，以及获取外部设备对所述通气对象进行监测所得到的第二信号，处理器630还用于执行心源性干扰识别方法800。
本实施例的心源性干扰识别方法900和医疗通气设备基于外部设备对通气对象监测所得的信号识别流速信号中的心源性干扰，提高了心源性干扰识别的准确性。
尽管这里已经参考附图描述了示例实施例，应理解上述示例实施例仅仅是示例性的，并且不意图将本申请的范围限制于此。本领域普通技术人员可以在其中进行各种改变和修改，而不偏离本申请的范围和精神。所有这些改变和修改意在被包括在所附权利要求所要求的本申请的范围之内。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
在本申请所提供的几个实施例中，应该理解到，所揭露的设备和方法，可以通过其它的方式实现。例如，以上所描述的设备实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个设备，或一些特征可以忽略，或不执行。
在此处所提供的说明书中，说明了大量具体细节。然而，能够理解，本申请的实施例可以在没有这些具体细节的情况下实践。在一些实例中，并未详细示出公知的方法、结构和技术，以便不模糊对本说明书的理解。
类似地，应当理解，为了精简本申请并帮助理解各个发明方面中的一个或多个，在对本申请的示例性实施例的描述中，本申请的各个特征有时被一起分组到单个实施例、图、或者对其的描述中。然而，并不应将该本申请的方法解释成反映如下意图：即所要求保护的本申请要求比在每个权利要求中所明确记载的特征更多的特征。更确切地说，如相应的权利要求书所反映的那样，其发明点在于可以用少于某个公开的单个实施例的所有特征的特征来解决相应的技术问题。因此，遵循具体实施方式的权利要求书由此明确地并入该具体实施方式，其中每个权利要求本身都作为本申请的单独实施例。
本领域的技术人员可以理解，除了特征之间相互排斥之外，可以采用任何组合对本说明书(包括伴随的权利要求、摘要和附图)中公开的所有特征以及如此公开的任何方法或者设备的所有过程或单元进行组合。除非另外明确陈述，本说明书(包括伴随的权利要求、摘要和附图)中公开的每个特征可以由提供相同、等同或相似目的的替代特征来代替。
此外，本领域的技术人员能够理解，尽管在此所述的一些实施例包括其它实施例中所包括的某些特征而不是其它特征，但是不同实施例的特征的组合意味着处于本申请的范围之内并且形成不同的实施例。例如，在权利要求书中，所要求保护的实施例的任意之一都可以以任意的组合方式来使用。
本申请的各个部件实施例可以以硬件实现，或者以在一个或者多个处理器上运行的软件模块实现，或者以它们的组合实现。本领域的技术人员应当理解，可以在实践中使用微处理器或者数字信号处理器(DSP)来实现根据本申请实施例的一些模块的一些或者全部功能。本申请还可以实现为用于执行这里所描述的方法的一部分或者全部的装置程序(例如，计算机程序和计算机程序产品)。这样的实现本申请的程序可以存储在计算机可读介质上，或者可以具有一个或者多个信号的形式。这样的信号可以从因特网网站上下载得到，或者在载体信号上提供，或者以任何其他形式提供。
应该注意的是上述实施例对本申请进行说明而不是对本申请进行限制，并且本领域技术人员在不脱离所附权利要求的范围的情况下可设计出替换实施例。在权利要求中，不应将位于括号之间的任何参考符号构造成对权利要求的限制。本申请可以借助于包括有若干不同元件的硬件以及借助于适当编程的计算机来实现。在列举了若干装置的单元权利要求中，这些装置中的若干个可以是通过同一个硬件项来具体体现。单词第一、第二、以及第三等的使用不表示任何顺序。可将这些单词解释为名称。
以上所述，仅为本申请的具体实施方式或对具体实施方式的说明，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，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。本申请的保护范围应以权利要求的保护范围为准。

Claims (41)

  1. 一种用于医疗通气设备的心源性干扰识别方法，其特征在于，包括：
    获取所述医疗通气设备对通气对象进行监测所得到的第一信号和第二信号，所述第一信号包括流速信号；
    根据所述流速信号和所述第二信号识别所述流速信号的波动；
    获取所述波动的波动特征，并基于所述波动的波动特征识别所述波动中的心源性干扰。
  2. 根据权利要求1所述的方法，其特征在于，所述波动特征包括所述波动的时间特征。
  3. 根据权利要求1所述的方法，其特征在于，还包括：
    确定所述心源性干扰的大小；
    根据所述心源性干扰的大小调节触发灵敏度。
  4. 根据权利要求1所述的方法，其特征在于，所述第二信号包括压力信号。
  5. 根据权利要求4所述的方法，其特征在于，所述第二信号包括反映所述通气对象吸气努力的压力信号，或者所述第二信号包括血流动力学信号。
  6. 根据权利要求5所述的方法，其特征在于，所述反映所述通气对象吸气努力的压力信号包括肺内压信号、气道压信号、食道压信号、跨膈压信号、胃内压信号、隆突压信号中的至少一种；所述血流动力学信号包括有创血压、动脉血压、中心静脉压和脉搏波中的至少一种。
  7. 根据权利要求1所述的方法，其特征在于，所述第二信号包括反映所述通气对象吸气努力的呼吸系统的信号。
  8. 根据权利要求7所述的方法，其特征在于，所述反映所述通气对象吸气努力的呼吸系统的信号包括肺部超声成像信号、膈肌超声成像信号、电阻抗成像信号、膈肌电信号中的至少一种。
  9. 根据权利要求1-8中任一项所述的方法，其特征在于，根据所述流速信号和所述第二信号识别所述流速信号的波动，包括：
    根据所述流速信号和所述第二信号得到所述流速信号与所述第二信号的互相关信号；
    根据所述互相关信号确定所述波动的发生时间。
  10. 根据权利要求9所述的方法，其特征在于，所述互相关信号包括二阶差分互相关信号。
  11. 根据权利要求2所述的方法，其特征在于，所述波动的时间特征包 括以下至少一种：每次所述波动的持续时间、所述波动的节律。
  12. 根据权利要求11所述的方法，其特征在于，基于所述波动的波动特征识别所述波动中的心源性干扰，包括：
    当所述波动的持续时间在预设范围内时，确定所述波动为心源性干扰；
    或者，
    基于所述波动的时间特征识别所述波动中的心源性干扰，包括：
    当多次所述波动符合预设节律时，确定所述波动为心源性干扰。
  13. 根据权利要求11所述的方法，其特征在于，获取每次所述波动的持续时间包括：
    确定所述通气对象的估计流速；
    根据所述流速信号中的实际流速与对应的估计流速的差值得到流速波动信号；
    根据所述流速波动信号得到每次所述波动的持续时间。
  14. 根据权利要求3所述的方法，其特征在于，确定所述心源性干扰的大小包括：
    确定所述通气对象的估计流速；
    根据所述流速信号中的实际流速与对应的估计流速的差值得到流速波动信号；
    确定所述心源性干扰的发生时间，根据所述心源性干扰的发生时间对应的所述流速波动信号确定所述心源性干扰的大小。
  15. 根据权利要求13或14所述的方法，其特征在于，确定所述通气对象的估计流速包括：
    基于当前时刻之前预设时刻的实际流速，根据呼吸力学模型确定当前时刻的估计流速；或者，
    基于当前时刻之前预设时间段内的实际流速进行曲线拟合，以确定当前时刻的估计流速。
  16. 根据权利要求3所述的方法，其特征在于，根据所述心源性干扰的大小调节触发灵敏度，包括：
    按照预设步长增大所述触发灵敏度，直到所述触发灵敏度大于或等于心源性干扰导致的触发信号。
  17. 根据权利要求16所述的方法，其特征在于，还包括：根据所述心源性干扰的大小实时调节所述预设步长。
  18. 根据权利要求3所述的方法，其特征在于，根据所述心源性干扰的 大小调节触发灵敏度，包括：
    将通气过程中的触发灵敏度均调节为大于或等于所述心源性干扰的大小，或者，根据当次心源性干扰的发生时间确定下一次心源性干扰发生的预测时间，将下一次心源性干扰发生的预测时间附近的所述触发灵敏度调节为大于或等于所述心源性干扰的大小。
  19. 根据权利要求18所述的方法，其特征在于，还包括：
    根据至少两次心源性干扰之间的时间间隔预测心跳周期；
    根据当次心源性干扰的发生时间和所述心跳周期得到下一次心源性干扰的所述预测时间。
  20. 一种用于医疗通气设备的心源性干扰识别方法，其特征在于，包括：
    获取医疗通气设备对通气对象进行监测所得到的第一信号和第二信号，所述第一信号包括压力信号；
    根据所述压力信号和所述第二信号识别所述压力信号的波动；
    获取所述波动的波动特征，并基于所述波动的波动特征识别所述波动中的心源性干扰。
  21. 根据权利要求20所述的方法，其特征在于，所述波动特征包括所述波动的时间特征。
  22. 根据权利要求20所述的方法，其特征在于，所述第二信号包括流速信号。
  23. 根据权利要求20所述的方法，其特征在于，还包括：
    确定所述心源性干扰的大小；
    根据所述心源性干扰的大小调节触发灵敏度。
  24. 根据权利要求20-23中任一项所述的方法，其特征在于，根据所述压力信号和所述第二信号识别所述压力信号的波动，包括：
    根据所述压力信号和所述第二信号得到所述压力信号与所述第二信号的互相关信号；
    根据所述互相关信号确定所述波动的发生时间。
  25. 根据权利要求21所述的方法，其特征在于，所述波动的时间特征包括以下至少一种：每次所述波动的持续时间、所述波动的节律。
  26. 根据权利要求25所述的方法，其特征在于，基于所述波动的波动特征识别所述波动中的心源性干扰，包括：
    当所述波动的持续时间在预设范围内时，确定所述波动为心源性干扰；
    或者，
    基于所述波动的时间特征识别所述波动中的心源性干扰，包括：
    当多次所述波动符合预设节律时，确定所述波动为心源性干扰。
  27. 根据权利要求23所述的方法，其特征在于，根据所述心源性干扰的大小调节触发灵敏度，包括：
    将通气过程中的触发灵敏度均调节为大于或等于所述心源性干扰的大小，或者，根据当次心源性干扰的发生时间确定下一次心源性干扰发生的预测时间，将下一次心源性干扰发生的预测时间附近的所述触发灵敏度调节为大于或等于所述心源性干扰的大小。
  28. 一种用于医疗通气设备的心源性干扰识别方法，其特征在于，包括：
    获取所述医疗通气设备对通气对象进行监测所得到的第一信号和第二信号，所述第一信号和所述第二信号为两种能够反应所述通气对象心跳信号的信号；
    根据所述第一信号和所述第二信号识别所述第一信号的波动；
    获取所述波动的波动特征，并基于所述波动的波动特征识别所述波动中的心源性干扰。
  29. 根据权利要求28所述的方法，其特征在于，所述波动特征包括所述波动的时间特征。
  30. 根据权利要求28所述的方法，其特征在于，还包括：
    确定所述心源性干扰的大小；
    根据所述心源性干扰的大小调节触发灵敏度。
  31. 根据权利要求28-30中任一项所述的方法，其特征在于，根据所述第一信号和所述第二信号识别所述第一信号的波动，包括：
    根据所述第一信号和所述第二信号得到所述第一信号与所述第二信号的互相关信号；
    根据所述互相关信号确定所述波动的发生时间。
  32. 根据权利要求29所述的方法，其特征在于，所述波动的时间特征包括以下至少一种：每次所述波动的持续时间、所述波动的节律。
  33. 根据权利要求32所述的方法，其特征在于，基于所述波动的波动特征识别所述波动中的心源性干扰，包括：
    当所述波动的持续时间在预设范围内时，确定所述波动为心源性干扰；
    或者，
    基于所述波动的时间特征识别所述波动中的心源性干扰，包括：
    当多次所述波动符合预设节律时，确定所述波动为心源性干扰。
  34. 一种医疗通气设备，其特征在于，所述医疗通气设备包括：
    通气单元，用于向通气对象提供通气；
    测量单元，用于在向所述通气对象提供通气的过程中对所述通气对象进行监测，以得到第一信号和第二信号；
    处理器，与所述测量单元连接，用于获取所述第一信号和所述第二信号，所述处理器还用于执行权利要求1-33中任一项所述的心源性干扰识别方法。
  35. 一种用于医疗通气设备的心源性干扰识别方法，其特征在于，包括：
    获取第一信号和第二信号，所述第一信号包括医疗通气设备对通气对象进行监测所得到的流速信号或压力信号，所述第二信号包括外部设备对所述通气对象进行监测所得到的人体信号；
    识别所述第一信号的波动，并基于所述第二信号识别所述波动中的心源性干扰。
  36. 根据权利要求35所述的方法，其特征在于，还包括：
    确定所述心源性干扰的大小；
    根据所述心源性干扰的大小调节触发灵敏度。
  37. 根据权利要求35所述的方法，其特征在于，所述基于所述第二信号识别所述波动中的心源性干扰，包括：
    基于所述第二信号得到出现所述心源性干扰的预测时间范围；
    将所述预测时间范围内的波动确定为所述心源性干扰。
  38. 根据权利要求35-37任意一项所述的方法，其特征在于，所述第二信号包括心电信号、脉搏波信号、有创血压信号中的至少一种。
  39. 根据权利要求35-37任意一项所述的方法，其特征在于，所述第二信号包括反映所述通气对象吸气努力的呼吸系统的信号。
  40. 根据权利要求39所述的方法，其特征在于，所述反映所述通气对象吸气努力的呼吸系统的信号包括肺部超声成像信号、膈肌超声成像信号、电阻抗成像信号、膈肌电信号中的至少一种。
  41. 一种医疗通气设备，其特征在于，所述医疗通气设备包括：
    通气单元，用于向通气对象提供通气；
    测量单元，用于在向所述通气对象提供通气的过程中对所述通气对象进行监测，以得到第一信号；
    处理器，与所述测量单元和外部设备连接，用于获取所述第一信号，以及获取所述外部设备对所述通气对象进行监测所得到的第二信号，所述处理器还用于执行权利要求35-40中任一项所述的心源性干扰识别方法。
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6186956B1 (en) * 1998-05-28 2001-02-13 University Of South Carolina Method and system for continuously monitoring cardiac output
US20120136222A1 (en) * 2010-11-30 2012-05-31 Nellcor Puritan Bennett Llc Methods And Systems For Monitoring A Ventilator Patient With A Capnograph
US20130025597A1 (en) * 2011-07-29 2013-01-31 Nellcor Puritan Bennett Llc Methods and systems for monitoring a ventilated patient with an oximeter
WO2013084159A1 (en) * 2011-12-06 2013-06-13 Università Campus Bio-Medico Di Roma System for the estimation of cardiac output
CN103619390A (zh) * 2011-05-23 2014-03-05 佐尔医药公司 具有通气质量反馈单元的医疗通气系统
EP3115075A1 (de) * 2015-07-07 2017-01-11 Löwenstein Medical Technology S.A. Vorrichtung zur veränderung des atemgas-druckes in abhängigkeit von einem mass der herzleistung

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2005079897A1 (en) * 2004-02-25 2005-09-01 Resmed Limited Cardiac monitoring and therapy using a device for providing pressure treatment of sleep disordered breathing
DE102007031017B3 (de) * 2007-07-04 2009-02-12 Dräger Medical AG & Co. KG Verfahren zum Betreiben einer Anästhesie- oder Beatmungsvorrichtung mit Triggerfunktion und Vorrichtung hierzu
WO2020009631A1 (en) * 2018-07-06 2020-01-09 Maquet Critical Care Ab Non-invasive estimation of pulmonary blood pressure

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6186956B1 (en) * 1998-05-28 2001-02-13 University Of South Carolina Method and system for continuously monitoring cardiac output
US20120136222A1 (en) * 2010-11-30 2012-05-31 Nellcor Puritan Bennett Llc Methods And Systems For Monitoring A Ventilator Patient With A Capnograph
CN103619390A (zh) * 2011-05-23 2014-03-05 佐尔医药公司 具有通气质量反馈单元的医疗通气系统
US20130025597A1 (en) * 2011-07-29 2013-01-31 Nellcor Puritan Bennett Llc Methods and systems for monitoring a ventilated patient with an oximeter
WO2013084159A1 (en) * 2011-12-06 2013-06-13 Università Campus Bio-Medico Di Roma System for the estimation of cardiac output
EP3115075A1 (de) * 2015-07-07 2017-01-11 Löwenstein Medical Technology S.A. Vorrichtung zur veränderung des atemgas-druckes in abhängigkeit von einem mass der herzleistung

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP4371596A4 *

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