A filtering method and filtering device for esophageal pressure signal

Abstract

The present invention provides a method for filtering an esophageal pressure signal and an esophageal pressure filtering device, the method comprising the steps of: obtaining an esophageal pressure signal of a patient; constructing a reference signal according to the esophageal pressure signal; updating a filtering parameter of an adaptive filter according to the reference signal to obtain an updated adaptive filter; and filtering out a heartbeat notch signal in the esophageal pressure signal according to the updated adaptive filter. The above-mentioned method for filtering an esophageal pressure signal can effectively filter out noise signals in the esophageal pressure signal.

Description

Technical Field

[0001] The present invention relates to the field of medical technology, and in particular to a filtering method and a filtering device for an esophageal pressure signal. Background Art

[0002] During clinical mechanical ventilation, doctors can insert a special esophageal pressure catheter with an air bag into the patient's esophagus to obtain the changes in the patient's esophageal pressure. The effectiveness of using esophageal pressure (Pes) as an approximate substitute for intra plural pressure (Ppl) has been widely recognized by doctors around the world. Doctors can use the above method to approximately obtain the patient's intra plural pressure, thereby calculating the patient's transpulmonary pressure, chest wall compliance, lung compliance, transpulmonary driving pressure and other parameters. At this point, the impact of the gas delivery pressure on the patient's lungs and chest wall during mechanical ventilation can be accurately obtained, and the patient's ventilation process can be further described and evaluated.

[0003] To obtain accurate esophageal pressure waveforms through an esophageal pressure catheter, the esophageal pressure catheter must first be placed in the correct position of the patient's esophagus. After the esophageal pressure catheter is placed, the position of the balloon in the esophagus is close to the heart, and the patient's heartbeat will also affect the pressure measured by the esophageal pressure catheter. Therefore, the esophageal pressure waveform is often interfered by the patient's heartbeat, which is usually called a cardiac notch or cardiac artifact (cardiogenic oscillation). The presence of the cardiac notch has a certain interference with the obtained esophageal pressure value, especially when the amplitude of the patient's cardiac notch is large. The noise signal brought by the cardiac notch may also cover the patient's own esophageal pressure signal, resulting in inaccurate esophageal pressure values, affecting the subsequent further calculation of the patient's lung physiological parameters. In addition, when the doctor needs to evaluate and identify the patient's inspiratory effort through the swing of esophageal pressure, the presence of the cardiac notch will affect the doctor's judgment, making it difficult for the doctor to accurately evaluate the patient's inspiratory effort, as well as to identify and analyze the patient's human-machine confrontation.

[0004] In summary, the esophageal pressure signal will be interfered by the heartbeat notch signal, so esophageal pressure filtering is very necessary and important.

[0005] At present, scholars have not done much research on esophageal pressure filtering methods. For example, Schuessler used the esophageal pressure signal after high-pass filtering and the R wave signal extracted from ECG (electrocardiogram) to construct an adaptive denoiser. Graβhoff uses the template subtraction method, which requires the introduction of ECG / EMG (electromyogram) signals to analyze the noise template, but both methods require a monitor to be installed next to the ventilator, which is inconvenient to use in clinical practice. Summary of the invention

[0006] The present invention mainly provides a filtering method for an esophageal pressure signal. The filtering method can filter the heartbeat notch signal in the esophageal pressure signal in real time without connecting the ventilation device (such as a ventilator, anesthesia machine, etc.) to other devices, thereby meeting the filtering requirements for the esophageal pressure signal in the ventilation device. The present invention also provides a corresponding filtering device.

[0007] According to a first aspect, an embodiment provides a method for filtering an esophageal pressure signal, comprising the steps of:

[0008] Acquire the patient's esophageal pressure signal;

[0009] constructing a reference signal according to the esophageal pressure signal;

[0010] Updating the filter parameters of the adaptive filter according to the reference signal to obtain an updated adaptive filter;

[0011] The heartbeat notch signal in the esophageal pressure signal is filtered out according to the updated adaptive filter.

[0012] According to a second aspect, an embodiment provides a method for filtering an esophageal pressure signal, comprising the steps of:

[0013] Obtain the patient's esophageal pressure signal and blood oxygen signal;

[0014] constructing a reference signal according to the blood oxygen signal;

[0015] Updating the filter parameters of the adaptive filter according to the reference signal to obtain an updated adaptive filter;

[0016] The heartbeat notch signal in the esophageal pressure signal is filtered out according to the updated adaptive filter.

[0017] According to a third aspect, an embodiment provides a method for filtering a physiological signal, comprising the steps of:

[0018] Obtain the patient's physiological signals that change over time;

[0019] constructing a reference signal according to the physiological signal, the reference signal having a frequency domain distribution or a time domain distribution close to that of a noise signal in the physiological signal;

[0020] Updating the filter parameters of the adaptive filter according to the reference signal to obtain an updated adaptive filter;

[0021] The noise signal in the physiological signal is filtered out according to the updated adaptive filter.

[0022] According to a fourth aspect, an embodiment provides a filtering device for an esophageal pressure signal, comprising:

[0023] a sensor interface that receives a patient's esophageal pressure value monitored by a pressure sensor;

[0024] The processor is connected to the sensor interface signal, receives the esophageal pressure value and generates an esophageal pressure signal, and constructs a reference signal according to the esophageal pressure signal, updates the filtering parameters of the adaptive filter according to the reference signal to obtain an updated adaptive filter, and filters out the heartbeat notch signal in the esophageal pressure signal according to the updated adaptive filter.

[0025] According to a fifth aspect, an embodiment provides a ventilator, comprising:

[0026] Gas source interface, connected to external gas source;

[0027] A breathing circuit connects the gas source interface to the patient's respiratory system to input the gas provided by the gas source to the patient and receive the gas exhaled by the patient;

[0028] A respiratory assistance device, which provides respiratory support power to control the gas provided by the gas source to be output to the patient, collects the gas exhaled by the patient for reuse or discharges it to the external environment, and the respiratory assistance device includes a machine-controlled ventilation module and / or a manual ventilation module; and

[0029] The filtering device for esophageal pressure signal in the fourth aspect.

[0030] According to a sixth aspect, an embodiment provides a ventilation device, comprising:

[0031] Memory, used to store programs;

[0032] A processor is used to implement the method described in the first aspect by executing the program stored in the memory.

[0033] According to a seventh aspect, an embodiment provides a medical device, comprising:

[0034] Memory, used to store programs;

[0035] A processor is used to implement the method described in the second aspect or the third aspect by executing the program stored in the memory.

[0036] According to an eighth aspect, an embodiment provides a computer-readable storage medium, comprising a program, wherein the program can be executed by a processor to implement the methods described in the first to third aspects.

[0037] The above-mentioned filtering method of the esophageal pressure signal constructs a reference signal according to the esophageal pressure signal itself during ventilation, and filters the esophageal pressure signal according to the reference signal and the adaptive filter. Only the esophageal pressure signal needs to be collected, so in the process of filtering the esophageal pressure signal, in addition to the ventilation equipment used for mechanical ventilation, no other external equipment needs to be introduced, and the adaptive filtering method is adopted, which has a good filtering effect on the esophageal pressure signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a structural schematic diagram of an adaptive noise canceller;

[0039] Figure 2 A schematic diagram of the structure of a ventilator according to an embodiment;

[0040] Figure 3 is a waveform diagram of an esophageal pressure signal of an embodiment;

[0041] Figure 4 A schematic diagram of the time interval between peaks in one cycle of an esophageal pressure signal according to an embodiment;

[0042] Figure 5 is a spectrum diagram of an esophageal pressure signal of an embodiment;

[0043] Figure 6 A spectrum diagram of a reference signal of an embodiment;

[0044] Figure 7 A spectrum diagram of a reference signal of another embodiment;

[0045] Figure 8 A schematic structural diagram of a filtering process of an adaptive filter according to an embodiment;

[0046] Fig. 9 A waveform diagram and a spectrum diagram of a filtered esophageal pressure signal according to an embodiment;

[0047] Fig.10 is a flow chart of a method for filtering an esophageal pressure signal according to an embodiment;

[0048] Fig.11 A flowchart of a method for updating an adaptive filter according to an embodiment;

[0049] 10. Gas source interface;

[0050] 20. Respiratory assistance devices;

[0051] 30. Breathing circuit;

[0052] 30a, inhalation passage; 30b, exhalation passage; 31, carbon dioxide absorber; 32, one-way valve; 33, patient interface;

[0053] 40. Sensor interface;

[0054] 50. Memory;

[0055] 60. Processor;

[0056] 70. Display;

[0057] 80. Patient. DETAILED DESCRIPTION

[0058] The present invention is further described in detail below by specific embodiments in conjunction with the accompanying drawings. Wherein similar elements in different embodiments adopt associated similar element numbers. In the following embodiments, many detailed descriptions are for making the present application better understood. However, those skilled in the art can easily recognize that some features can be omitted in different situations, or can be replaced by other elements, materials, methods. In some cases, some operations related to the present application are not shown or described in the specification, this is to avoid the core part of the present application being overwhelmed by too much description, and for those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations according to the description in the specification and the general technical knowledge in the art.

[0059] In addition, the features, operations or characteristics described in the specification can be combined in any appropriate manner to form various implementations. At the same time, the steps or actions in the method description can also be interchanged or adjusted in a manner that is obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for the purpose of clearly describing a certain embodiment and are not meant to be a required sequence, unless otherwise specified that a certain sequence must be followed.

[0060] The serial numbers of the components in this document, such as "first", "second", etc., are only used to distinguish the objects described and do not have any order or technical meaning. The "connection" and "coupling" mentioned in this application, unless otherwise specified, include direct and indirect connections (couplings).

[0061] The adaptive filter referred to in the present invention refers to an algorithm or device that automatically adjusts the filter coefficients based on the estimation of the statistical characteristics of the input and output signals to achieve the best filtering characteristics. The structure of a typical adaptive denoiser using the adaptive filtering method is as follows: Figure 1As shown in Figure 1, the structure requires two input signals: (1) the basic signal s+n, which is considered to be the superposition of the target signal s+n and the noise signal n; (2) the reference signal n0, which is associated with the noise signal n but not with the target signal s. The function of the denoiser is to obtain an output signal that is close to the target signal s from the input basic signal s+n. The specific filtering process is as follows:

[0062] Input the reference signal n0 to the adaptive filter and get the output signal of the filter The basic signal s+n is input to the denoiser and the output signal of the filter is subtracted from the basic signal s+n. This gives the output signal of the noise canceller At the same time, the basic signal s+n and the output signal of the filter are obtained The error signal ε between them is then continuously reduced by optimizing the parameters of the adaptive filter according to the adaptive filtering algorithm. Commonly used adaptive filtering algorithms include the Least Mean Square (LMS) algorithm, the Recursive Least Squares algorithm, the Kalman filter algorithm (RLS) and the neural network algorithm, as well as the improved algorithms derived from these algorithms, such as normalized LMS, variable step size LMS, fast RLS, square root RLS and RLS algorithm based on QR decomposition. Under the rules of the above filter algorithm, the filter automatically optimizes the filter parameters and / or structure according to the filtering results of the previous moment to adapt to the unpredictable and time-varying statistical characteristics of the signal and noise. The final effect is to make the filter output signal is the optimal estimate of the noise signal n under this rule, and the output signal It is also close to the target signal s. The adaptive filtering algorithm does not require prior information about the signal and noise, has a small amount of calculation, is suitable for real-time processing, and is widely used in many engineering problems.

[0063] The basic wave referred to in the present invention refers to other waveforms that can be obtained by superimposing and changing several types of waveforms. These types of waveforms are called basic waves.

[0064] The fundamental frequency referred to in the present invention is also called base frequency, which refers to the lowest frequency in the composite wave. Any periodic waveform can be decomposed into a fundamental frequency sine wave plus many higher-order frequency sine waves, where the higher-order frequency is an integer multiple of the fundamental frequency (N can only be an integer), and the higher-order frequency sine waves can be considered as harmonics referred to in the present invention.

[0065] Please refer to Figure 2 , Figure 2Shown is a schematic diagram of the structural composition of a ventilator (or also known as a ventilation device), which includes an air source interface 10, a breathing assistance device 20, a breathing circuit 30, a sensor interface 40, a memory 50, a processor 60 and a display 70.

[0066] The gas source interface 10 is used to connect to a gas source (not shown in the figure), and the gas source is used to provide gas. The gas can generally be oxygen and air. In some embodiments, the gas source can be a compressed gas cylinder or a central gas supply source, and the gas supply type is oxygen 02 and air. The gas source interface 10 may include conventional components such as a pressure gauge, a pressure regulator, a flow meter, a pressure reducing valve, and a proportional control protection device, which are respectively used to control the flow of various gases (such as oxygen and air). The gas input by the gas source interface 10 enters the breathing circuit 30 and forms a mixed gas with the original gas in the breathing circuit 30.

[0067] The breathing assistance device 20 is used to provide power for the non-spontaneous breathing of the patient 80 and maintain the patency of the airway, that is, to drive the gas input from the gas source interface 10 and the mixed gas in the breathing circuit 30 to the respiratory system of the patient 80, and to drain the gas exhaled by the patient 80 into the breathing circuit 30, thereby improving ventilation and oxygenation, and preventing the patient 80 from hypoxia and carbon dioxide from accumulating in the patient 80. In a specific embodiment, the breathing assistance device 20 generally includes a machine-controlled ventilation module, and the airflow duct of the machine-controlled ventilation module is connected to the breathing circuit 30. In the state where the patient 80 has not recovered spontaneous breathing during the operation, the machine-controlled ventilation module is used to provide the patient 80 with breathing power. In some embodiments, the breathing assistance device 20 also includes a manual ventilation module, and the airflow duct of the manual ventilation module is connected to the breathing circuit 30. During the induction stage before intubation of the patient 80 during the operation, it is usually necessary to use a manual ventilation module to assist the patient 80 in breathing. When the breathing assistance device 20 includes both a machine-controlled ventilation module and a manual ventilation module, the machine-controlled or manual ventilation mode can be switched through a machine-controlled or manual switch (e.g., a three-way valve) to connect the machine-controlled ventilation module or the manual ventilation module to the breathing circuit 30, thereby controlling the breathing of the patient 80. Those skilled in the art should understand that, according to specific needs, the ventilator may include only the machine-controlled ventilation module or the manual ventilation module.

[0068] The breathing circuit 30 includes an inhalation passage 30a, an exhalation passage 30b and a carbon dioxide absorber 31. The inhalation passage 30a and the exhalation passage 30b are connected to form a closed loop, and the carbon dioxide absorber 31 is arranged on the pipeline of the exhalation passage 30b. The mixed gas of fresh air introduced by the gas source interface 10 is input from the inlet of the inhalation passage 30a and provided to the patient 80 through the patient interface 33 arranged at the outlet of the inhalation passage 30a. The patient interface 33 can be a mask, a nasal cannula or an endotracheal cannula. In a preferred embodiment, a one-way valve 32 is arranged on the inhalation passage 30a, and the one-way valve 32 is opened during the inhalation phase and closed during the exhalation phase. A one-way valve 32 is also arranged on the exhalation passage 30b, and the one-way valve 32 is closed during the inhalation phase and opened during the exhalation phase. The inlet of the exhalation passage 30b is connected to the patient interface 33. When the patient 80 exhales, the exhaled gas enters the carbon dioxide absorber 31 through the exhalation passage 30b, and the carbon dioxide in the exhaled gas is filtered out by the substance in the carbon dioxide absorber 31. The gas after the carbon dioxide is filtered out is recirculated into the inhalation passage 30a. In some embodiments, a flow sensor and / or a pressure sensor are also provided in the breathing circuit 30, which are used to detect the gas flow and / or the pressure in the pipeline, respectively.

[0069] The sensor interface 40 is used to receive various respiratory information of the patient 80 collected by the sensor, such as the esophageal pressure value of the patient 80 under the machine-assisted ventilation state collected by the sensor. Specifically, the sensor interface 40 is connected to the signal output end of the pressure sensor. In one embodiment, the sensor interface 40 can only be used as a connector between the sensor output end and the subsequent circuit (such as the processor 60), and the signal is not processed. The sensor interface 40 can also be integrated into the processor 60 as an interface for accessing signals of the processor 60. In another embodiment, the sensor interface 40 may include an amplifier circuit, a filter circuit and an A / D conversion circuit, which are used to amplify, filter and perform analog-to-digital conversion processing on the input analog signal. Of course, the technician should understand that the connection relationship between the amplifier circuit, the filter circuit and the A / D conversion circuit can be changed according to the specific design of the circuit, and a certain circuit can be reduced, for example, the amplifier circuit or the filter circuit can be reduced, thereby reducing its corresponding function. In addition, the sensor interface 40 can also access information collected by other sensors, such as flow information and / or pressure information of the breathing circuit 30.

[0070] As a specific product, the pressure sensor for monitoring esophageal pressure values ​​may be a part of the ventilator or an external accessory independent of the ventilator.

[0071] The memory 50 may be used to store data or programs, for example, to store data collected by various sensors, data generated by the processor 60 through calculation, or image frames generated by the processor 60, which may be 2D or 3D images, or the memory 50 may store a graphical user interface, one or more default image display settings, and programming instructions for the processor 60. The memory 50 may be a tangible and non-transitory computer-readable medium, such as a flash memory, RAM, ROM, EEPROM, etc.

[0072] The processor 60 is used to execute instructions or programs, control various control valves in the respiratory assistance device 20, the gas source interface 10 and / or the respiratory circuit 30, or process the received data to generate the required calculation or judgment results, or generate visual data or graphics, and output the visual data or graphics to the display 70 for display. In this embodiment, the processor 60 is connected to the sensor interface 40 signal to obtain the esophageal pressure signal of the patient 80, and construct a reference signal based on the esophageal pressure signal. For example, the esophageal pressure signal is used as a basic signal to construct a reference signal that is close to the frequency domain distribution or time domain distribution of the heartbeat notch signal. The reason for constructing a reference signal that is close to the frequency domain distribution or time domain distribution is to obtain a signal that is close to the energy distribution of the heartbeat notch signal.

[0073] The following takes the construction of a reference signal close to the frequency domain distribution of the heartbeat notch as an example to illustrate the construction process of the reference signal:

[0074] First, the fundamental frequency of the heartbeat notch signal in the esophageal pressure signal is obtained. Two methods of obtaining the fundamental frequency are described below.

[0075] The first method is to identify the time domain characteristics and / or frequency domain characteristics of the heartbeat notch signal from the esophageal pressure signal, and calculate the fundamental frequency of the heartbeat notch signal. Figure 3 The waveform diagram of a typical esophageal pressure signal is shown. The processor 60 can identify the waveform within at least one cycle of the esophageal pressure signal, for example Figure 3 The embodiment shown in has multiple cycles, and the processor 60 can select one of the cycles and calculate the time interval between two adjacent peaks in the cycle. The time interval is the cycle of the cardiac notch signal, and the inverse of the time interval can be used as the fundamental frequency of the cardiac notch signal.

[0076] In some embodiments, the average of the time intervals between multiple consecutive peaks in a cycle can also be calculated (for example Figure 4 The dotted line in the figure represents the time interval between three consecutive peaks in one cycle), and the average is used as the average value of the cycle of the heartbeat notch signal, and the fundamental frequency of the heartbeat notch signal can be obtained based on the average value. This makes the calculation of the heartbeat notch signal more accurate.

[0077] The second method is to obtain the frequency distribution information of the heartbeat notch signal by calculating the short-time spectrum of the esophageal pressure signal, thereby obtaining the fundamental frequency of the heartbeat notch signal. Figure 5 The figure shows a spectrum diagram of a typical esophageal pressure signal. The processor 60 can identify that the frequencies of the cardiac notch signal are mainly distributed at the horizontal coordinates 1, 2, 3, 4 and 5, so 1 Hz can be used as the fundamental frequency of the cardiac notch signal.

[0078] Both of the above two methods can obtain the fundamental frequency of the heartbeat notch signal. Any one of them or a combination of the two can be used. In other embodiments, other feasible methods can also be used.

[0079] In some embodiments, after obtaining the fundamental frequency of the heartbeat notch signal, an external device may be introduced to verify the fundamental frequency of the heartbeat notch signal. For example, a monitor or an electrocardiogram device is used to obtain the pulse parameters and / or heart rate parameters of the patient 80, and the fundamental frequency of the heartbeat notch signal is verified according to the heart rate parameters and / or pulse rate parameters. For example, when the difference between the two does not exceed a preset threshold, it can be considered that the fundamental frequency of the heartbeat notch signal obtained by the ventilator is credible.

[0080] In some embodiments, the blood oxygen signal of the patient 80 can also be obtained, for example, the pulse parameter and / or heart rate parameter of the patient 80 can be obtained through a monitor or an electrocardiogram device, and then the pulse parameter and / or heart rate parameter can be used as the fundamental frequency of the heartbeat notch signal. In addition to the ventilator, this method also requires the use of other medical equipment or monitoring equipment.

[0081] After determining the fundamental frequency of the heartbeat notch signal, a related reference signal is constructed according to the fundamental frequency. The reference signal can be obtained by constructing a fundamental wave with the same frequency as the fundamental frequency of the heartbeat notch signal. The fundamental wave can be any one of a sine wave, a triangle wave, a square wave, a sawtooth wave and a Gaussian function. A reference signal can be obtained based on the fundamental wave. For example, the fundamental wave can be directly used as a reference signal. The following is an example of the construction process of the fundamental wave using a sine wave as an example. The construction method is as follows:

[0082] Noise_ref=A*sin(2*π*HeartRate / (SamplingRate*60)*t+B).

[0083] Among them, Noise_ref is the reference signal, HeartRate is the heart rate of the patient 80, Samplingrate is the sampling rate of the above-mentioned ventilator when obtaining the esophageal pressure signal of the patient 80, A is the amplitude, and B is the phase. The above-mentioned amplitude, phase and frequency of the sine wave on the right side can be adjusted to meet the structural requirements.

[0084] According to the above formula, a sine wave with a frequency equal to the fundamental frequency of the heartbeat notch signal can be constructed. Figure 3 The fundamental frequency of the heartbeat notch signal obtained from the esophageal pressure signal is used to construct a reference signal. Figure 6 The signal spectrum diagram after Fourier transformation of the constructed reference signal shows that the frequency domain energy of the signal is mainly concentrated on the fundamental frequency of the heartbeat notch signal, so the above method successfully constructs a suitable reference signal.

[0085] It should be noted that the above process of constructing a reference signal is an explanation of an implementation mode of the present invention, and the method of constructing a reference signal of the present invention is not limited to the example given.

[0086] In some embodiments, the reference signal may include not only the signal component of the fundamental frequency energy of the heartbeat notch, but also the signal component at the harmonic frequency of each heartbeat notch. For example, the reference signal may be constructed in the following manner:

[0087] Noise_ref=A1*sin(2*π*HeartRate / (SamplingRate*60)*t+B1)+

[0088] A2*sin(2*π*HeartRate*2 / (SamplingRate*60)*t+B2)+

[0089] A3*sin(2*π*HeartRate*3 / (SamplingRate*60)*t+B3)+….

[0090] This formula can represent that the fundamental wave and its 2nd to Nth harmonics are superimposed to obtain the reference signal Noise_ref, 2≤N.

[0091] Among them, A2*sin(2*π*HeartRate*2 / (SamplingRate*60)*t+B2) contains the energy of the heartbeat notch signal at the second harmonic.

[0092] A3*sin(2*π*HeartRate*3 / (SamplingRate*60)*t+B3) includes the energy of the heartbeat notch signal at the third harmonic. The meaning of each symbol in this formula has been explained above and will not be repeated here. Figure 7 The signal spectrum diagram after Fourier transformation of the reference signal constructed according to the above formula.

[0093] Through the above-mentioned construction, when filtering the esophageal pressure signal, the harmonic energy of the heartbeat notch signal can be filtered out, thereby better performing esophageal pressure filtering.

[0094] The reference signal constructed includes the harmonic energy of the heartbeat notch signal, which can be determined according to actual use requirements. For example, the reference signal can be fixedly constructed to include the third harmonic energy of the heartbeat notch signal, or to include the fifth harmonic energy of the heartbeat notch signal, so as to meet the needs of most filtering occasions.

[0095] After obtaining the reference signal, the processor 60 updates the filter parameters of the adaptive filter according to the obtained reference signal, thereby obtaining an updated adaptive filter. The classical denoiser mentioned above is a method of updating the filter parameters of the adaptive filter using the reference signal. Figure 8 The filtering parameters of the adaptive filter are updated in the manner shown, which is described in detail below.

[0096] like Figure 8 As shown, the esophageal pressure signal is used as the basic signal, and a reference signal is superimposed on it. The superimposed signal is used as the first input signal, and an adaptive filter is used to filter the first input signal to obtain an output signal. Then, the error signal between the esophageal pressure signal and the output signal is calculated. Finally, according to the error signal, an adaptive algorithm is used to update the filter parameters of the adaptive filter. For example, any one or more of the step size, order and coefficient of the adaptive filter can be updated to obtain an updated adaptive filter. The first input signal is the result of superimposing noise on the basic signal. Therefore, the result of adaptive filtering is to make the adaptive filter obtain an attenuated gain coefficient at the noise frequency, thereby reducing the noise signal in the first input signal. The method for updating the filter parameters of the adaptive filter after obtaining the error signal can use the various algorithms mentioned above when introducing the denoiser to minimize the error signal.

[0097] After obtaining the adaptive filter, the esophageal pressure signal can be filtered using the adaptive filter. One filtering method is as follows: Figure 8 As shown in FIG. 1 , the esophageal pressure signal is used as the second input signal, and the updated adaptive filter is used to filter the second input signal, thereby filtering out the heartbeat notch signal in the esophageal pressure signal. The filtering result is shown in FIG. Fig. 9 As shown, the dark solid line part is the spectrum diagram and waveform diagram after filtering, and the light solid line is the spectrum diagram and waveform diagram before filtering. It can be clearly seen that the noise signal in the esophageal pressure signal is effectively filtered out.

[0098] Based on the above-mentioned ventilator, the filtering method of the esophageal pressure signal is described below.

[0099] like Fig.10 The flowchart of the esophageal pressure filtering method according to an embodiment is shown, comprising the steps of:

[0100] Step 100 , obtaining the esophageal pressure signal of the patient 80 .

[0101] For example, when a ventilation device (such as an anesthesia machine and / or a ventilator) is ventilating the patient 80 , an esophageal pressure signal of the patient 80 is acquired through a sensor of the ventilation device itself.

[0102] Step 200: construct a reference signal according to the esophageal pressure signal.

[0103] The reference signal can be close to the frequency domain distribution of the heartbeat notch signal in the esophageal pressure signal, or it can be close to the time domain distribution of the heartbeat notch signal in the esophageal pressure signal. The reason for constructing a reference signal with a frequency domain distribution or a time domain distribution that is close is to obtain a signal that is close to the energy distribution of the heartbeat notch signal.

[0104] In some embodiments, the esophageal pressure signal is used as a basic signal to construct a reference signal with a frequency domain distribution close to that of the heartbeat notch signal, specifically comprising the following steps:

[0105] Step 210: obtaining the fundamental frequency of the heartbeat notch signal in the esophageal pressure signal according to the esophageal pressure signal.

[0106] For example, the time domain features and / or frequency domain features of the heartbeat notch signal are identified from the esophageal pressure signal, and the fundamental frequency of the heartbeat notch signal is calculated. Figure 3 The waveform diagram of a typical esophageal pressure signal is shown. With the help of a ventilator that acquires the esophageal pressure signal, the waveform within at least one cycle of the esophageal pressure signal can be identified, for example Figure 3 The embodiment shown in has multiple cycles, one of the cycles is selected, and the time interval between two adjacent peaks in the cycle is calculated. The time interval is the cycle of the heartbeat notch signal, and the reciprocal of the time interval can be used as the fundamental frequency of the heartbeat notch signal.

[0107] In some embodiments, the average of the time intervals between multiple consecutive peaks in a cycle can also be calculated (for example Figure 4 The dotted line in the figure represents the time interval between three consecutive peaks in one cycle), and the average is used as the average value of the cycle of the heartbeat notch signal, and the fundamental frequency of the heartbeat notch signal can be obtained based on the average value. This makes the calculation of the heartbeat notch signal more accurate.

[0108] In some embodiments, the frequency distribution information of the heartbeat notch signal can also be obtained by calculating the short-time spectrum of the esophageal pressure signal, thereby obtaining the fundamental frequency of the heartbeat notch signal. Figure 5 The figure shows a spectrum diagram of a typical esophageal pressure signal. With the help of an external machine, it can be identified that the frequencies of the cardiac notch signal are mainly distributed at the horizontal coordinates 1, 2, 3, 4 and 5, among which 1 Hz can be taken as the fundamental frequency of the cardiac notch signal.

[0109] Both of the above two methods can obtain the fundamental frequency of the heartbeat notch signal. Any one of them or a combination of the two can be used. In other embodiments, other feasible methods can also be used.

[0110] In some embodiments, after obtaining the fundamental frequency of the heartbeat notch signal, an external device may be introduced to verify the fundamental frequency of the heartbeat notch signal. For example, a monitor or an electrocardiogram device is used to obtain the pulse parameters and / or heart rate parameters of the patient 80, and the fundamental frequency of the heartbeat notch signal is verified according to the heart rate parameters and / or pulse rate parameters. For example, when the difference between the two does not exceed a preset threshold, it can be considered that the fundamental frequency of the heartbeat notch signal obtained by the ventilator is credible.

[0111] Step 220: construct a reference signal according to the fundamental frequency of the heartbeat notch signal.

[0112] In this step, a reference signal can be obtained by constructing a basic wave having the same frequency as the fundamental frequency of the heartbeat notch signal. The basic wave can be any one of a sine wave, a triangle wave, a square wave, a sawtooth wave, and a Gaussian function. A reference signal can be obtained based on the basic wave. For example, the basic wave can be directly used as a reference signal. The construction process of the basic wave is illustrated below using a sine wave as an example. The construction method is as follows:

[0113] Noise_ref=A*sin(2*π*HeartRate / (SamplingRate*60)*t+B).

[0114] Among them, Noise_ref is the reference signal, HeartRate is the heart rate of the patient 80, Samplingrate is the sampling rate of the above-mentioned ventilator when obtaining the esophageal pressure signal of the patient 80, A is the amplitude, and B is the phase. The above-mentioned amplitude, phase and frequency of the sine wave on the right side can be adjusted to meet the structural requirements.

[0115] According to the above formula, a sine wave with a frequency equal to the fundamental frequency of the heartbeat notch signal can be constructed. Figure 3 The fundamental frequency of the heartbeat notch signal obtained from the esophageal pressure signal is used to construct a reference signal. Figure 6 The signal spectrum diagram after Fourier transformation of the constructed reference signal shows that the frequency domain energy of the signal is mainly concentrated on the fundamental frequency of the heartbeat notch signal, so the above method successfully constructs a suitable reference signal.

[0116] It should be noted that the above process of constructing a reference signal is an explanation of an implementation mode of the present invention, and the method of constructing a reference signal of the present invention is not limited to the example given.

[0117] In some embodiments, the reference signal may include not only the signal component of the fundamental frequency energy of the heartbeat notch, but also the signal component at the harmonic frequency of each heartbeat notch. For example, the reference signal may be constructed in the following manner:

[0118] Noise_ref=A1*sin(2*π*HeartRate / (SamplingRate*60)*t+B1)+

[0119] A2*sin(2*π*HeartRate*2 / (SamplingRate*60)*t+B2)+

[0120] A3*sin(2*π*HeartRate*3 / (SamplingRate*60)*t+B3)+…

[0121] This formula can represent that the fundamental wave and its 2nd to Nth harmonics are superimposed to obtain the reference signal Noise_ref, 2≤N.

[0122] Among them, A2*sin(2*π*HeartRate*2 / (SamplingRate*60)*t+B2) contains the energy of the heartbeat notch signal at the second harmonic.

[0123] A3*sin(2*π*HeartRate*3 / (SamplingRate*60)*t+B3) includes the energy of the heartbeat notch signal at the third harmonic. The meaning of each symbol in this formula has been explained above and will not be repeated here. Figure 7 The signal spectrum diagram after Fourier transformation of the reference signal constructed according to the above formula.

[0124] Through the above-mentioned construction, when filtering the esophageal pressure signal, the harmonic energy of the heartbeat notch signal can be filtered out, thereby better performing esophageal pressure filtering.

[0125] The reference signal constructed includes the harmonic energy of the heartbeat notch signal, which can be determined according to actual use requirements. For example, the reference signal can be fixedly constructed to include the third harmonic energy of the heartbeat notch signal, or to include the fifth harmonic energy of the heartbeat notch signal, so as to meet the needs of most filtering occasions.

[0126] Step 300: Update the filter parameters of the adaptive filter according to the reference signal to obtain an updated adaptive filter.

[0127] The classic denoiser mentioned above is a way to update the filter parameters of the adaptive filter using a reference signal. Fig.11The process shown updates the filter parameters of the adaptive filter, including the steps of:

[0128] Step 310: superimpose the esophageal pressure signal and the reference signal, and use the superimposed signal as the first input signal.

[0129] Step 320: Use an adaptive filter to filter the first input signal to obtain an output signal.

[0130] Step 330: Calculate the error signal between the esophageal pressure signal and the output signal.

[0131] Step 340: According to the error signal, an adaptive algorithm is used to update the filter parameters of the adaptive filter to obtain an updated adaptive filter.

[0132] Step 340 is to change the filtering parameters of the adaptive filter in the direction of minimizing the error signal according to the various algorithms mentioned above, for example, changing any one or more of the step size, order and coefficients of the adaptive filter, so as to obtain an updated adaptive filter.

[0133] Step 400: Filter out the heartbeat notch signal in the esophageal pressure signal using the updated adaptive filter.

[0134] In some embodiments, the esophageal pressure signal is used as the second input signal, and the updated adaptive filter is used to filter the second input signal, thereby filtering out the heartbeat notch signal in the esophageal pressure signal. Fig. 9 As shown, the dark solid line part is the spectrum diagram and waveform diagram after filtering, and the light solid line is the spectrum diagram and waveform diagram before filtering. It can be clearly seen that the noise signal in the esophageal pressure signal is effectively filtered out.

[0135] In addition to the esophageal pressure signal, other physiological signals can also be filtered out of noise signals in a similar manner as described above. Specifically, first, the physiological signal of the patient 80 that changes over time is obtained; then, a reference signal that is close to the frequency domain distribution or time domain distribution of the noise signal in the physiological signal is constructed based on the physiological signal; then, the filtering parameters of the adaptive filter are updated based on the reference signal to obtain an updated adaptive filter; finally, the noise signal in the physiological signal is filtered out based on the updated adaptive filter. It should be understood that in various embodiments of the present invention, the user can decide when to enable and stop the filtering method of the adaptive filter, and does not need to always use the filtering method of the adaptive filter, and can also be used in combination with other filtering methods.

[0136] In the above embodiment, in addition to the respiratory equipment used for mechanical ventilation, no other external equipment is required; and the frequency domain distribution of the reference signal of the adaptive filter is close to the heartbeat notch signal, and the frequency domain energy distribution is consistent with the heartbeat notch, so the real-time filtering effect is better.

[0137] The above specific examples are used to illustrate the present invention, which are only used to help understand the present invention and are not used to limit the present invention. For those skilled in the art, according to the concept of the present invention, the above specific implementation methods can be changed.

Claims

1. A filtering method for esophageal pressure signal, characterized in that , comprising the steps of: Acquire the patient's esophageal pressure signal; Obtaining the fundamental frequency of the heartbeat notch signal in the esophageal pressure signal according to the esophageal pressure signal, and constructing a reference signal according to the fundamental frequency, wherein the reference signal is close to the heartbeat notch signal in frequency domain distribution; Updating the filtering parameters of the adaptive filter according to the reference signal to obtain an updated adaptive filter; filtering out the heartbeat notch signal in the esophageal pressure signal according to the updated adaptive filter; Wherein, obtaining the fundamental frequency of the heartbeat notch signal in the esophageal pressure signal according to the esophageal pressure signal includes at least one of the following methods: Identify the time domain characteristics and / or frequency domain characteristics of the heartbeat notch signal from the esophageal pressure signal, and calculate the fundamental frequency of the heartbeat notch signal; The frequency distribution information of the heartbeat notch signal is obtained by calculating the short-time spectrum of the esophageal pressure signal, thereby obtaining the fundamental frequency of the heartbeat notch signal.

2. The method according to claim 1, characterized in that The calculation of the fundamental frequency of the heartbeat notch signal includes: identifying a waveform within at least one cycle of the esophageal pressure signal; calculating a time interval between two adjacent peaks in one cycle of at least one cycle of the esophageal pressure signal; The fundamental frequency of the heartbeat notch signal is calculated according to the time interval.

3. The method according to claim 1, characterized in that The calculation of the fundamental frequency of the heartbeat notch signal includes: identifying a waveform within at least one cycle of the esophageal pressure signal; calculating at least two time intervals between a plurality of adjacent peaks in at least one cycle of the esophageal pressure signal; The fundamental frequency of the heartbeat notch signal is calculated according to the average value of at least two time intervals.

4. The method according to claim 1, characterized in that The method further comprises: The pulse rate parameter and / or heart rate parameter of the patient is obtained, and the fundamental frequency of the heartbeat notch signal is verified according to the heart rate parameter and / or pulse rate parameter.

5. The method according to claim 1, characterized in that The step of constructing the reference signal according to the fundamental frequency of the heartbeat notch signal comprises: Constructing a basic wave with the same frequency as the fundamental frequency, wherein the basic wave includes any one of a sine wave, a triangle wave, a square wave, a sawtooth wave and a Gaussian function; A reference signal is obtained according to the fundamental wave.

6. The method according to claim 5, characterized in that The obtaining of a reference signal according to the fundamental wave comprises: Using the fundamental wave as a reference signal; or Calculate and obtain the 2nd to Nth harmonics of the fundamental wave; The fundamental wave is superimposed with its 2nd to Nth harmonics to obtain a reference signal, wherein N is greater than or equal to 2.

7. The method according to claim 6, characterized in that N is equal to 3 or 5.

8. The method according to claim 1, characterized in that The method for updating the filtering parameters of the adaptive filter comprises: Superimposing the esophageal pressure signal with a reference signal, and using the superimposed signal as a first input signal; Using the adaptive filter to filter the first input signal to obtain an output signal; calculating an error signal between the esophageal pressure signal and an output signal; According to the error signal, an adaptive algorithm is used to update the filter parameters of the adaptive filter to obtain the updated adaptive filter.

9. The method according to claim 8, characterized in that The adopting an adaptive algorithm to update the filter parameters of the adaptive filter comprises: At least one of the step size, order, and coefficients of the adaptive filter is updated.

10. The method according to claim 1, characterized in that The step of filtering out the heartbeat notch signal in the esophageal pressure signal according to the updated adaptive filter comprises: using the esophageal pressure signal as a second input signal; The updated adaptive filter is used to filter the second input signal, thereby filtering out the heartbeat notch signal in the esophageal pressure signal.

11. A method for filtering physiological signals, characterized in that: Includes steps: Obtain the patient's physiological signals that change over time; Obtaining the fundamental frequency of the noise signal in the physiological signal according to the physiological signal, and constructing a reference signal close to the frequency domain distribution of the noise signal in the physiological signal according to the fundamental frequency; Updating the filter parameters of the adaptive filter according to the reference signal to obtain an updated adaptive filter; filtering out noise signals in the physiological signal according to the updated adaptive filter; Wherein, obtaining the fundamental frequency of the noise signal in the physiological signal according to the physiological signal includes at least one of the following methods: Identify the time domain characteristics and / or frequency domain characteristics of the noise signal from the physiological signal, and calculate the fundamental frequency of the noise signal; The frequency distribution information of the noise signal is obtained by calculating the short-time spectrum of the physiological signal, thereby obtaining the fundamental frequency of the noise signal.

12. A filtering device for esophageal pressure signal, characterized in that: include: a sensor interface that receives a patient's esophageal pressure value monitored by a pressure sensor; A processor is connected to the sensor interface signal, receives the esophageal pressure value and generates an esophageal pressure signal, obtains the fundamental frequency of the heartbeat notch signal in the esophageal pressure signal according to the esophageal pressure signal, constructs a reference signal according to the fundamental frequency, the reference signal is close to the frequency domain distribution of the heartbeat notch signal, updates the filter parameters of the adaptive filter according to the reference signal to obtain the updated adaptive filter, and filters out the heartbeat notch signal in the esophageal pressure signal according to the updated adaptive filter; Wherein, obtaining the fundamental frequency of the heartbeat notch signal in the esophageal pressure signal according to the esophageal pressure signal includes at least one of the following methods: Identify the time domain characteristics and / or frequency domain characteristics of the heartbeat notch signal from the esophageal pressure signal, and calculate the fundamental frequency of the heartbeat notch signal; The frequency distribution information of the heartbeat notch signal is obtained by calculating the short-time spectrum of the esophageal pressure signal, thereby obtaining the fundamental frequency of the heartbeat notch signal.

13. The esophageal pressure signal filtering device according to claim 12, characterized in that: The calculation of the fundamental frequency of the heartbeat notch signal includes: identifying a waveform within at least one cycle of the esophageal pressure signal; calculating a time interval between two adjacent peaks in one cycle of at least one cycle of the esophageal pressure signal; The fundamental frequency of the heartbeat notch signal is calculated according to the time interval.

14. The esophageal pressure signal filtering device according to claim 12, characterized in that: The calculation of the fundamental frequency of the heartbeat notch signal includes: identifying a waveform within at least one cycle of the esophageal pressure signal; calculating at least two time intervals between a plurality of adjacent peaks in at least one cycle of the esophageal pressure signal; The fundamental frequency of the heartbeat notch signal is calculated according to the average value of at least two time intervals.

15. The esophageal pressure signal filtering device according to claim 12, characterized in that: Also includes: The pulse rate parameter and / or heart rate parameter of the patient is obtained, and the fundamental frequency of the heartbeat notch signal is verified according to the heart rate parameter and / or pulse rate parameter.

16. The esophageal pressure signal filtering device according to claim 12, characterized in that: The step of constructing the reference signal according to the fundamental frequency of the heartbeat notch signal comprises: Constructing a basic wave with the same frequency as the fundamental frequency, wherein the basic wave includes any one of a sine wave, a triangle wave, a square wave, a sawtooth wave and a Gaussian function; A reference signal is obtained according to the fundamental wave.

17. The esophageal pressure signal filtering device according to claim 16, characterized in that: The obtaining of a reference signal according to the fundamental wave comprises: Using the fundamental wave as a reference signal; or Calculate and obtain the 2nd to Nth harmonics of the fundamental wave; The fundamental wave is superimposed with its 2nd to Nth harmonics to obtain a reference signal, wherein N is greater than or equal to 2.

18. The esophageal pressure signal filtering device according to claim 17, characterized in that: N is equal to 3 or 5.

19. The esophageal pressure signal filtering device according to claim 12, characterized in that: The method for updating the filtering parameters of the adaptive filter comprises: Superimposing the esophageal pressure signal with a reference signal, and using the superimposed signal as a first input signal; Using the adaptive filter to filter the first input signal to obtain an output signal; calculating an error signal between the esophageal pressure signal and an output signal; According to the error signal, an adaptive algorithm is used to update the filter parameters of the adaptive filter to obtain the updated adaptive filter.

20. The esophageal pressure signal filtering device according to claim 19, characterized in that: The adopting an adaptive algorithm to update the filter parameters of the adaptive filter comprises: At least one of the step size, order, and coefficients of the adaptive filter is updated.

21. The esophageal pressure signal filtering device according to claim 12, characterized in that: The step of filtering out the heartbeat notch signal in the esophageal pressure signal according to the updated adaptive filter comprises: using the esophageal pressure signal as a second input signal; The updated adaptive filter is used to filter the second input signal, thereby filtering out the heartbeat notch signal in the esophageal pressure signal.

22. A ventilator, characterized in that: include: Gas source interface, connected to external gas source; A breathing circuit connects the gas source interface to the patient's respiratory system to input the gas provided by the gas source to the patient and receive the gas exhaled by the patient; A respiratory assistance device, which provides respiratory support power to control the gas provided by the gas source to be output to the patient, collects the gas exhaled by the patient for reuse or discharges it to the external environment, and the respiratory assistance device includes a machine-controlled ventilation module and / or a manual ventilation module; and A filtering device for an esophageal pressure signal according to any one of claims 12 to 21.

23. A ventilation device, characterized in that: include: Memory, used to store programs; A processor, configured to implement the method according to any one of claims 1 to 11 by executing the program stored in the memory.

24. A medical device, characterized in that: include: Memory, used to store programs; A processor, configured to implement the method according to any one of claims 1 to 11 by executing the program stored in the memory.

25. A computer-readable storage medium, characterized in that: The method comprises a program which can be executed by a processor to implement the method according to any one of claims 1 to 11.

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