Breathing state adjusting method and device and computer equipment

Abstract

The invention relates to a breathing state adjusting method and device and computer equipment. The method comprises the following steps: in a continuous positive airway pressure ventilation mode, acquiring a physiological signal of a target object in a preset historical time period, and determining a characteristic value of the physiological signal; predicting a plurality of breathing states of the feature value through a pre-constructed breathing state prediction model to obtain a breathing prediction state of the target object at the next moment; the breathing states comprise a breathing event easy-to-occur state, a stable sleep state and a micro-awakening state; and predicting the breathing state change condition of the target object according to the breathing prediction state, and adjusting the operation pressure of the breathing equipment according to the breathing state change condition. By means of the method, respiratory events can be reduced, harm to the body of a user caused by various respiratory events is reduced, and meanwhile the pressure adjustment reasonability of the respirator is improved.

Description

Technical Field

[0001] The present application relates to the field of medical device technology, and in particular to a respiratory state adjustment method, device and computer equipment. Background Art

[0002] The ventilator has an APAP (Auto-adjusting Positive Airway Pressure) mode. In APAP mode, the ventilator monitors the user's breathing in real time. When the airway is blocked or not smooth, the ventilator will actively increase the pressure to support the collapsed or fallen soft tissue through pressure to achieve airway patency. When there is no apnea, the pressure of the ventilator will automatically decrease.

[0003] In the related art, the APAP mode of the ventilator adjusts the pressure after a respiratory event occurs, when the blood oxygen level has dropped and caused damage to the human body, and the pressure adjustment method is unreasonable. Summary of the invention

[0004] Based on this, it is necessary to provide a respiratory state adjustment method, device, computer equipment and storage medium that can reduce the occurrence of respiratory events, reduce the damage to the user's body caused by various respiratory events, and improve the rationality of the pressure adjustment of the ventilator in response to the above-mentioned technical problems.

[0005] In a first aspect, the present application provides a method for adjusting a respiratory state, comprising:

[0006] When in continuous positive airway pressure mode, obtaining physiological signals of the target object within a preset historical time period and determining characteristic values ​​of the physiological signals;

[0007] The pre-built respiratory state prediction model is used to predict multiple respiratory states of the characteristic values ​​to obtain the predicted respiratory state of the target object at the next moment; the multiple respiratory states include a state prone to respiratory events, a stable sleep state, and a micro-arousal state;

[0008] The breathing state change of the target object is predicted according to the breathing prediction state, and the operating pressure of the breathing device is adjusted according to the breathing state change.

[0009] In one embodiment, the method further comprises:

[0010] When an unpredicted respiratory event occurs in a stable sleep state, the feature value before the respiratory event is stored;

[0011] After the continuous positive airway pressure mode ends, the pre-built respiratory state prediction model is trained according to the stored characteristic values ​​to obtain an optimized respiratory state prediction model;

[0012] The optimized respiratory state prediction model is updated to a pre-built respiratory state prediction model.

[0013] In one embodiment, predicting a change in the breathing state of the target object according to the predicted breathing state, and adjusting the operating pressure of the breathing device according to the change in the breathing state includes:

[0014] When the predicted respiratory state is a state prone to respiratory events, and the target subject's respiratory state is predicted to change from a stable sleep state to a state prone to respiratory events, increasing the operating pressure of the respiratory device at a first change rate until reaching a normal operating pressure corresponding to the state prone to respiratory events;

[0015] After the target object changes from a stable sleep state to a state prone to respiratory events, if it is predicted that the target object's respiratory change is changing from a state prone to respiratory events to a stable sleep state, the operating pressure of the respiratory device is reduced at a second change rate.

[0016] In one embodiment, predicting a change in the breathing state of the target object according to the predicted breathing state, and adjusting the operating pressure of the breathing device according to the change in the breathing state includes:

[0017] When the predicted breathing state is a state prone to respiratory events, and the target subject's breathing state is predicted to change from a stable sleep state to a state prone to respiratory events, increasing the operating pressure of the respiratory device at a first change rate;

[0018] When a respiratory event occurs during the process of increasing the operating pressure, a pressure value to be increased of the respiratory device is determined according to the severity of the respiratory event, and after the respiratory event ends, the operating pressure of the respiratory device is increased according to the pressure value to be increased, and the operating pressure of the respiratory device is continued to be increased to obtain a first target pressure of the respiratory device, wherein the first target pressure is greater than the normal operating pressure corresponding to the state where a respiratory event is prone to occur;

[0019] After the target subject changes from a stable sleeping state to a state prone to respiratory events, if it is predicted that the target subject's respiratory state changes to remain in a state prone to respiratory events, controlling the respiratory device to maintain a first target pressure;

[0020] When it is predicted that the target object's respiratory state changes from a state prone to respiratory events to a stable sleep state, the operating pressure of the respiratory device is reduced according to the pressure value to be increased to obtain a second target pressure of the respiratory device, and the second target pressure is greater than the minimum operating pressure.

[0021] In one embodiment, predicting a change in the breathing state of the target object according to the predicted breathing state, and adjusting the operating pressure of the breathing device according to the change in the breathing state includes:

[0022] When the predicted respiratory state is a state prone to respiratory events, and the target subject's respiratory state is predicted to change from a stable sleep state to a state prone to respiratory events, increasing the operating pressure of the respiratory device at a first change rate until reaching a normal operating pressure corresponding to the state prone to respiratory events;

[0023] After the target subject changes from a stable sleeping state to a state prone to respiratory events, if the target subject has a respiratory event in the state prone to respiratory events, a pressure value to be increased of the respiratory device is determined according to the severity of the respiratory event, and after the respiratory event ends, the operating pressure of the respiratory device is increased according to the pressure value to be increased to obtain a first target pressure of the respiratory device;

[0024] When it is predicted that the change in the respiratory state of the target subject is to maintain a state prone to respiratory events, controlling the respiratory device to maintain a first target pressure;

[0025] When it is predicted that the target object's respiratory state changes from a state prone to respiratory events to a stable sleep state, the operating pressure of the respiratory device is reduced according to the pressure value to be increased to obtain a second target pressure of the respiratory device, and the second target pressure is greater than the minimum operating pressure.

[0026] In one embodiment, predicting a change in the breathing state of the target object according to the predicted breathing state, and adjusting the operating pressure of the breathing device according to the change in the breathing state includes:

[0027] When the predicted breathing state is a stable sleeping state, and the predicted breathing state change of the target object is to maintain a stable sleeping state, reducing the operating pressure of the breathing device;

[0028] When an unpredicted respiratory event occurs during a stable sleep state, the pressure value to be increased by the respiratory device is determined according to the severity of the respiratory event;

[0029] After the respiratory event is finished, the operating pressure of the respiratory device is increased according to the pressure value to be increased, and the operating pressure of the respiratory device is further decreased until the minimum operating pressure is reached.

[0030] In one embodiment, predicting a change in the breathing state of the target object according to the predicted breathing state, and adjusting the operating pressure of the breathing device according to the change in the breathing state includes:

[0031] When the predicted breathing state is a micro-arousal state, and the predicted breathing state change of the target object is from a stable sleep state to a micro-arousal state, the respiratory device is controlled to reduce the operating pressure during the exhalation phase of the target object, and maintain the current operating pressure during the inhalation phase of the target object.

[0032] In one embodiment, predicting a change in the breathing state of the target object according to the predicted breathing state, and adjusting the operating pressure of the breathing device according to the change in the breathing state includes:

[0033] When the predicted breathing state is a micro-arousal state, and the target object's breathing state is predicted to change from a state prone to respiratory events to a micro-arousal state, after the transition to the micro-arousal state, the respiratory device is controlled to reduce the operating pressure during the target object's exhalation phase, and maintain the current operating pressure during the target object's inhalation phase.

[0034] In a second aspect, the present application also provides a breathing state adjustment device, comprising:

[0035] A characteristic value acquisition module is used to acquire the physiological signal of the target object within a preset historical time period when in a continuous positive airway pressure ventilation mode, and determine the characteristic value of the physiological signal;

[0036] The state prediction module is used to predict multiple respiratory states of the characteristic values ​​through a pre-built respiratory state prediction model to obtain the predicted respiratory state of the target object at the next moment; the multiple respiratory states include a state prone to respiratory events, a stable sleep state, and a micro-arousal state;

[0037] The pressure adjustment module is used to predict the change of the breathing state of the target object according to the breathing prediction state, and adjust the operating pressure of the breathing device according to the change of the breathing state.

[0038] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0039] When in continuous positive airway pressure mode, obtaining physiological signals of the target object within a preset historical time period and determining characteristic values ​​of the physiological signals;

[0040] The pre-built respiratory state prediction model is used to predict multiple respiratory states of the characteristic values ​​to obtain the predicted respiratory state of the target object at the next moment; the multiple respiratory states include a state prone to respiratory events, a stable sleep state, and a micro-arousal state;

[0041] The breathing state change of the target object is predicted according to the breathing prediction state, and the operating pressure of the breathing device is adjusted according to the breathing state change.

[0042] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the following steps are implemented:

[0043] When in continuous positive airway pressure mode, obtaining physiological signals of the target object within a preset historical time period and determining characteristic values ​​of the physiological signals;

[0044] The pre-built respiratory state prediction model is used to predict multiple respiratory states of the characteristic values ​​to obtain the predicted respiratory state of the target object at the next moment; the multiple respiratory states include a state prone to respiratory events, a stable sleep state, and a micro-arousal state;

[0045] The breathing state change of the target object is predicted according to the breathing prediction state, and the operating pressure of the breathing device is adjusted according to the breathing state change.

[0046] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0047] When in continuous positive airway pressure mode, obtaining physiological signals of the target object within a preset historical time period and determining characteristic values ​​of the physiological signals;

[0048] The pre-built respiratory state prediction model is used to predict multiple respiratory states of the characteristic values ​​to obtain the predicted respiratory state of the target object at the next moment; the multiple respiratory states include a state prone to respiratory events, a stable sleep state, and a micro-arousal state;

[0049] The breathing state change of the target object is predicted according to the breathing prediction state, and the operating pressure of the breathing device is adjusted according to the breathing state change.

[0050] The above-mentioned respiratory state adjustment method, device, computer equipment, storage medium and computer program product, when in continuous positive airway pressure ventilation mode, predicts the characteristic values ​​of the target object's physiological signals in the state prone to respiratory events, stable sleep state and micro-arousal state through the pre-constructed respiratory state prediction model, and obtains the target object's predicted respiratory state at the next moment, which can not only predict multiple states of the sleep stage, but also predict the state prone to respiratory events. Predicting the changes in the target object's respiratory state according to the respiratory prediction state, and adjusting the operating pressure of the respiratory equipment in advance according to the changes in the respiratory state can reduce the occurrence of respiratory events, reduce the damage caused to the target object by respiratory events, and reasonably adjust the operating pressure of the respiratory equipment. At the same time, when the micro-arousal state is predicted, the operating pressure of the respiratory equipment is adjusted to make the operating pressure more in line with the breathing law of the human body. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0052] FIG1 is a diagram showing an application environment of a method for adjusting a respiratory state according to an embodiment;

[0053] FIG2 is a schematic flow chart of a method for adjusting a respiratory state in one embodiment;

[0054] FIG3 is a flow chart of a model optimization step after the continuous positive airway pressure mode ends in one embodiment;

[0055] FIG4 is a schematic diagram of the structure of the forward propagation stage of the BP neural network in one embodiment;

[0056] FIG5 is a schematic diagram of a neuron computing process in one embodiment;

[0057] FIG6 is a schematic diagram of adjusting the treatment pressure in a state prone to respiratory events without respiratory events occurring in one embodiment;

[0058] FIG7 is a schematic diagram of treatment pressure adjustment under continuous state changes in one embodiment;

[0059] FIG8 is a schematic diagram of adjusting treatment pressure when a respiratory event occurs during a state transition in one embodiment;

[0060] FIG9 is a schematic diagram of adjusting treatment pressure when a respiratory event occurs in a state prone to respiratory events in one embodiment;

[0061] FIG10 is a schematic diagram of adjusting the treatment pressure of a respiratory device in a continuous stable sleep state in one embodiment;

[0062] FIG11 is a schematic diagram of adjusting the treatment pressure of a respiratory device when a respiratory event occurs in a stable sleep state in one embodiment;

[0063] FIG12 is a schematic diagram of adjusting the treatment pressure when a micro-awakening state occurs in one embodiment;

[0064] FIG13 is a schematic diagram of adjusting the treatment pressure when a state prone to respiratory events is transformed into a state of micro-arousal in one embodiment;

[0065] FIG. 14 is a structural block diagram of a breathing state adjustment device in one embodiment. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0067] In the related art, the APAP mode of the ventilator adjusts the pressure after a respiratory event occurs, when the blood oxygen level has dropped and damage has been caused to the human body. This has had a negative impact on users, with a relatively delayed response. Most respiratory events are caused by increased airway resistance. At the same time, the pressure adjustment method in the related art is unreasonable.

[0068] Based on the above problems, a respiratory state adjustment method is proposed, which can predict a state prone to respiratory events due to increased airway resistance, adjust the pressure in advance, reduce the occurrence of respiratory events, reduce the impact of adverse consequences caused by various respiratory events, and reasonably adjust the pressure.

[0069] The respiratory state adjustment method provided in the embodiment of the present application can be applied to the respiratory device shown in Figure 1. Among them, the respiratory device includes a respiratory pressure support device, a sensor, a control system, a display screen and a storage device. The user represents the target object. The display screen can be used to display the parameters of the continuous positive airway pressure ventilation mode, such as the minimum treatment pressure, the maximum treatment pressure, the pressure adjustment sensitivity, the pressure reduction gear in the micro-arousal state, the pressure increase gear in the state prone to respiratory events, etc. The continuous positive airway pressure ventilation mode in the present application can adjust the treatment pressure based on the respiratory prediction state. The sensor is used to obtain the physiological signal of the target object in a preset historical time period when in the continuous positive airway pressure ventilation mode, and send it to the control system. The control system is used to determine the characteristic value of the physiological signal, and predict the characteristic value of multiple respiratory states through a pre-constructed respiratory state prediction model to obtain the target object's respiratory prediction state at the next moment; the multiple respiratory states include a state prone to respiratory events, a stable sleep state and a micro-arousal state. According to the respiratory prediction state, the change of the respiratory state of the target object is predicted, and the operating pressure provided by the respiratory pressure support device, that is, the treatment pressure, is adjusted according to the change of the respiratory state. The storage device is used to store the usage data and the characteristic values ​​used for model training during the respiratory adjustment process. The respiratory device in this embodiment may be, but is not limited to, a sleep apnea machine.

[0070] In an exemplary embodiment, as shown in FIG2 , a method for adjusting a respiratory state is provided, which is described by taking the method applied to the respiratory device in FIG1 as an example, and includes the following steps 202 to 206. Among them:

[0071] Step 202 : When in the continuous positive airway pressure mode, a physiological signal of the target object within a preset historical time period is obtained to determine a characteristic value of the physiological signal.

[0072] The target object refers to a user of a respiratory device, and the physiological signal refers to a parameter related to the respiratory state of the target object.

[0073] Optionally, when the respiratory device is in continuous positive airway pressure mode, the physiological signals of the target object within a preset historical time period are collected through sensors, and the physiological signals of the target object within the preset historical time period are transmitted to the control system. The preset historical time period is a fixed-length time window, that is, a sliding time window. For example, the amplitude of the pressure and flow signals in the last minute is collected and stored as two one-dimensional arrays of 1000 sampling points, and the characteristic values ​​of these two arrays are calculated. The physiological signals may include flow changes and pressure changes during the sleep stage. Furthermore, the physiological signals may also include blood oxygen, pulse, etc. The control system determines the characteristic values ​​of the physiological signals. The characteristic values ​​include but are not limited to the mean value, variance, difference between adjacent peaks, zero crossing, deviation mean value, peak-to-valley difference, autocorrelation coefficient, etc.

[0074] Exemplarily, the calculation process of the eigenvalue is as follows:

[0075] average value:

[0076]

[0077] in, is the number of sampling points in the sliding time window, is the sampling point.

[0078] variance:

[0079]

[0080] in, is the number of sampling points in the sliding time window, is the sampling point, is the average value of the sampling points in the sliding time window.

[0081] Difference between adjacent peaks:

[0082]

[0083] in, is the number of peaks in the sliding time window, is the amplitude of the ith peak, is the amplitude of the i+1th peak.

[0084] Zero crossing:

[0085] ZCP

[0086] in, is the i-th sampling point, is the i+1th sampling point.

[0087] Deviation Mean:

[0088]

[0089] in, is the number of sampling points in the sliding time window, is the sampling point, is the average value of the sampling points in the sliding time window.

[0090] Peak to valley difference:

[0091]

[0092] in, is the number of peaks and valleys in the sliding time window, For the crest, For the trough.

[0093] Autocorrelation coefficient:

[0094] R = ∑ i=1 N-k [ x i × x i+k ] / [ ∑ i=1 N-k x i 2 × x i+k 2 ]

[0095] Where k is the time delay, is the i-th sampling point, is the i+kth sampling point.

[0096] Optionally, the sensor may include a flow sensor and a pressure sensor, which are respectively used to collect flow changes and pressure changes of the target object within a preset historical time period.

[0097] Step 204, predicting multiple respiratory states of the characteristic values ​​through a pre-built respiratory state prediction model to obtain the predicted respiratory state of the target object at the next moment; the multiple respiratory states include a state prone to respiratory events, a stable sleep state, and a micro-arousal state.

[0098] This application divides the predicted states of the target object when using a respiratory device into: a state prone to respiratory events, a stable sleep state, and a micro-arousal state. Among them, the state prone to respiratory events is due to the prediction that the target object's airway resistance is in a very high state during sleep, and it is very easy to have respiratory events caused by excessive airway resistance, such as obstructive sleep apnea events, hypopnea events, airflow limitation events, etc. The stable sleep state is a stage in which breathing is relatively stable during sleep, with normal blood oxygen concentration and stable breathing. The micro-arousal state is a brief, partial brain awakening of the target object during the sleep stage, but it is not enough to cause full wakefulness. However, if the treatment pressure is too high when using a respiratory device, it may also cause the target object to wake up.

[0099] Optionally, the control system inputs the characteristic value of the physiological signal into a pre-built respiratory state prediction model, predicts multiple respiratory states, and obtains the predicted respiratory state of the target object at the next moment. Among them, the pre-built respiratory state prediction model can be but is not limited to a BP neural network (Back Propagation Neural Network), a convolutional neural network, a recurrent neural network, etc. Taking the BP neural network as an example, the BP neural network can include an input layer, a hidden layer, and an output layer. The input layer is used to receive the characteristic value of the physiological signal. The hidden layer is used to extract and transform the characteristic value. The output layer is used to output the prediction result of the network, that is, the predicted respiratory state of the target object at the next moment. The layers are fully connected, that is, each neuron in the input layer is connected to each neuron in the hidden layer, and each neuron in the hidden layer is connected to each neuron in the output layer.

[0100] Optionally, when setting the hidden layer, three hidden layers are set by comprehensively considering factors such as performance and accuracy. The hidden layer contains a maximum of 30 neurons, and after nonlinear transformation, an output signal is generated to the output layer, so as to achieve a smaller number of layers and performance occupancy to meet the accuracy requirements of respiratory state prediction.

[0101] Step 206, predicting a change in the breathing state of the target object according to the predicted breathing state, and adjusting the operating pressure of the breathing device according to the change in the breathing state.

[0102] Optionally, after obtaining the predicted respiratory state, the target object's respiratory state change may also be determined based on the target object's current respiratory state. Different respiratory state changes may correspond to different operating pressure adjustment methods. The operating pressure of the respiratory device is adjusted accordingly according to different respiratory state changes. Operating pressure refers to treatment pressure.

[0103] Optionally, when the predicted breathing state is a state prone to respiratory events, the operating pressure of the respiratory device is increased. When the predicted breathing state is a stable sleep state, the operating pressure of the respiratory device is reduced. When the predicted breathing state is a slightly awake state, the operating pressure is reduced during the exhalation phase of the target subject.

[0104] In the above-mentioned respiratory state adjustment method, when in continuous positive airway pressure mode, the characteristic values ​​of the target object's physiological signals are predicted by a pre-constructed respiratory state prediction model to predict the state prone to respiratory events, stable sleep state and micro-arousal state, and the target object's predicted respiratory state at the next moment is obtained, which can not only predict multiple states of the sleep stage, but also predict the state prone to respiratory events. Predicting the changes in the target object's respiratory state according to the respiratory prediction state, and adjusting the operating pressure of the respiratory equipment in advance according to the changes in the respiratory state can reduce the occurrence of respiratory events, reduce the damage caused to the target object by respiratory events, and reasonably adjust the operating pressure of the respiratory equipment. At the same time, when a micro-arousal state is predicted, the operating pressure of the respiratory equipment is adjusted to make the operating pressure more in line with the breathing law of the human body.

[0105] In an exemplary embodiment, as shown in FIG3 , the method further includes: a model optimization step after the CPAP mode ends, which includes steps 302 to 306. Among them:

[0106] Step 302: When an unpredicted respiratory event occurs in a stable sleep state, the feature value before the respiratory event is stored.

[0107] Step 304: After the continuous positive airway pressure mode ends, the pre-built respiratory state prediction model is trained according to the stored characteristic values ​​to obtain an optimized respiratory state prediction model.

[0108] Step 306: Update the optimized respiratory state prediction model to a pre-built respiratory state prediction model.

[0109] Optionally, if an unpredicted respiratory event occurs in a stable sleep state, the characteristic values ​​before the respiratory event will be stored for model training. After the treatment is completed, that is, after the continuous positive airway pressure mode ends, the respiratory state prediction model is trained using the stored characteristic values ​​to obtain a respiratory prediction result. The respiratory prediction result is compared with the actual result through the output layer of the respiratory state prediction model to obtain the error between the respiratory prediction result and the actual result. When the training end condition is not met, the model parameters are updated through the back propagation algorithm so that the model can better fit the characteristic values. After multiple iterative training, when the training end condition is met, an optimized respiratory state prediction model is obtained. The optimized respiratory state prediction model is updated to a pre-built respiratory state prediction model to perform respiratory state prediction.

[0110] For example, when the pre-built respiratory state prediction model is a BP neural network, the working process of the BP neural network is mainly divided into two stages: forward propagation and backward propagation. The input data of the forward propagation stage passes through the hidden layer from the input layer and finally reaches the output layer, as shown in Figure 4, where x includes x1, x2, ..., x m , is the input data, y includes y1, y2 and y3, and is the output breathing prediction result. The neurons in each layer perform weighted summation on the input data and generate output through the activation function, as shown in Figure 5. The activation function can be expressed as:

[0111]

[0112] Among them, x i For input data, is the weight, is the activation function, The output breathing prediction result. In this application, the activation function uses ReLU (Rectified Linear Unit) and softmax function (normalized exponential function).

[0113] In the back propagation stage, the error between the respiratory prediction result output by the respiratory state prediction model and the actual result is calculated, the error is propagated in the reverse direction of the network connection in the respiratory state prediction model, and the weight and threshold of the respiratory state prediction model are adjusted according to the error. Among them, the weight adjustment can use the gradient descent method to gradually reduce the total error of the respiratory state prediction model. The error between the output of the respiratory state prediction model and the actual result is calculated by the following loss function:

[0114]

[0115] Among them, Loss is the loss function, For the real result, It is the breathing prediction result output in the forward propagation.

[0116] In order to minimize the error between the respiratory prediction results output by the respiratory state prediction model and the actual results, it is necessary to find the minimum value of the above loss function. The iterative method to find the minimum value of the loss function is to find a numerical solution by gradient descent plus iteration. The iterative method generally requires multiple times, because the search for the minimum value of the loss function may require multiple iterations, and in each iteration, the weights between the nodes in each layer will also be continuously iterated and updated. The iterative process of the weight is as follows:

[0117]

[0118] in, represents the weight of the next iteration, represents the weight of the current iteration, is the learning rate, Represents the gradient of the loss function Loss with respect to the parameter ω.

[0119] The present application proposes an intelligent adjustment of continuous positive airway pressure ventilation mode, which implements a respiratory state prediction model only on the respiratory device and continuously optimizes the model, saves data during treatment, and trains the respiratory state prediction model after the treatment is completed. As the target subject continues to use the ventilator equipment, the model will be more adapted to the target subject and provide more accurate respiratory state predictions.

[0120] Among the state prone to respiratory events, the stable sleep state and the micro-arousal state, the stable sleep state is the basic state and lasts the longest. During the treatment process, the treatment pressure will be adjusted according to different future states.

[0121] In the state prone to respiratory events, since the target object's airway resistance will continue to increase in this state, which is very likely to cause respiratory events, it is necessary to increase the treatment pressure based on the current treatment pressure to offset the airway resistance and maintain the airway patency. In the stable sleep state, the respiratory state prediction model predicts that the target object's respiratory state has changed, and the state has changed from a stable sleep state to a state prone to respiratory events. At this time, the treatment pressure of the respiratory equipment is adjusted. There are the following situations: no respiratory events, continuous state changes, respiratory events during state transitions, and respiratory events in the stage of prone to respiratory events.

[0122] In an exemplary embodiment, predicting changes in the respiratory state of a target object according to a respiratory prediction state, and controlling the operating pressure of a respiratory device according to the changes in the respiratory state include: when the respiratory prediction state is a state prone to respiratory events, and when it is predicted that the change in the respiratory state of the target object is changing from a stable sleep state to a state prone to respiratory events, increasing the operating pressure of the respiratory device at a first change rate until it reaches a normal operating pressure corresponding to the state prone to respiratory events; after the target object changes from a stable sleep state to a state prone to respiratory events, if it is predicted that the change in the respiratory state of the target object is to remain in a state prone to respiratory events, controlling the respiratory device to maintain a normal operating pressure corresponding to the state prone to respiratory events; when it is predicted that the change in the respiratory state of the target object is changing from a state prone to respiratory events to a stable sleep state, reducing the operating pressure of the respiratory device at a second change rate until it reaches a minimum operating pressure.

[0123] The first rate of change refers to the rate of increase of the treatment pressure when the patient changes from a stable sleep state to a state prone to respiratory events. The normal operating pressure corresponding to the state prone to respiratory events refers to the treatment pressure when no respiratory events occur. The second rate of change refers to the rate of decrease of the treatment pressure when the state prone to respiratory events changes to a stable sleep state.

[0124] This embodiment adjusts the treatment pressure for a state prone to respiratory events without respiratory events. As shown in FIG6 , a sliding window is used for eigenvalue calculation and input into the input layer of the respiratory state prediction model. When the respiratory prediction state is a state prone to respiratory events, and the target object's respiratory state change is predicted to be from a stable sleep state to a state prone to respiratory events (②→①), the treatment pressure is gradually increased in advance according to the first change rate, so that the respiratory airway remains unobstructed due to the higher treatment pressure, thereby eliminating the occurrence of respiratory events. At this time, the respiratory events may be caused by sleeping posture or different sleep stages.

[0125] After the target subject changes from a stable sleeping state to a state prone to respiratory events, if it is predicted that the target subject's respiratory state changes to maintain a state prone to respiratory events, the respiratory device is controlled to maintain a normal treatment pressure corresponding to the state prone to respiratory events.

[0126] After the target subject ends the state prone to respiratory events and returns to a stable sleep state (①→②), the treatment pressure is slowly reduced at a second change rate to return to the treatment pressure before the increase.

[0127] In an exemplary embodiment, predicting changes in the respiratory state of a target object based on a respiratory prediction state, and adjusting the operating pressure of the respiratory equipment based on the changes in the respiratory state include: when the respiratory prediction state is a state prone to respiratory events, and the target object's respiratory state change is predicted to be from a stable sleep state to a state prone to respiratory events, increasing the operating pressure of the respiratory equipment at a first change rate until reaching the normal operating pressure corresponding to the state prone to respiratory events; after the target object changes from a stable sleep state to a state prone to respiratory events, if it is predicted that the target object's respiratory change is from a state prone to respiratory events to a stable sleep state, reducing the operating pressure of the respiratory equipment at a second change rate.

[0128] This embodiment adjusts the treatment pressure for continuous state changes. As shown in FIG7 , when the predicted breathing state is a state prone to respiratory events, and the predicted breathing state change of the target object is from a stable sleep state to a state prone to respiratory events (②→①), the treatment pressure of the respiratory device is increased at a first change rate. After the stable sleep state is changed to a state prone to respiratory events, it is changed to a stable sleep state (①→②) in a short time. At this time, the treatment pressure will also be reduced at a second change rate according to the state conversion. The adjustment of the treatment pressure in different states is to increase or decrease slowly, and the whole process of increasing or decreasing the treatment pressure will last for several minutes.

[0129] In an exemplary embodiment, predicting a change in the respiratory state of a target object according to a respiratory prediction state, and adjusting the operating pressure of a respiratory device according to the change in the respiratory state includes: when the respiratory prediction state is a state prone to respiratory events, and when it is predicted that the change in the respiratory state of the target object is a change from a stable sleep state to a state prone to respiratory events, increasing the operating pressure of the respiratory device at a first change rate; when a respiratory event occurs during the process of increasing the operating pressure, determining a pressure value to be increased for the respiratory device according to the severity of the respiratory event, and after the respiratory event ends, increasing the operating pressure of the respiratory device according to the pressure value to be increased, and continuing to increase the operating pressure of the respiratory device to obtain a first target pressure of the respiratory device, the first target pressure being greater than the normal operating pressure corresponding to the state prone to respiratory events; after the target object changes from a stable sleep state to a state prone to respiratory events, if it is predicted that the change in the respiratory state of the target object is to maintain the state prone to respiratory events, controlling the respiratory device to maintain the first target pressure; when it is predicted that the change in the respiratory state of the target object is a change from a state prone to respiratory events to a stable sleep state, reducing the operating pressure of the respiratory device according to the pressure value to be increased to obtain a second target pressure of the respiratory device, the second target pressure being greater than the minimum operating pressure.

[0130] The first target pressure refers to the treatment pressure required for the respiratory device to switch to a state prone to respiratory events when a respiratory event occurs during the state transition. The second target pressure refers to the treatment pressure required to return to a stable sleep state when a respiratory event occurs during the state transition.

[0131] This embodiment is to adjust the treatment pressure when a respiratory event occurs during the state transition. As shown in FIG8 , when the respiratory prediction state is a state prone to respiratory events, and the target object's respiratory state change is predicted to be from a stable sleep state to a state prone to respiratory events (②→①), the treatment pressure of the respiratory device is increased at a first change rate.

[0132] When a respiratory event occurs during the process of slowly increasing the treatment pressure, the respiratory device determines the pressure value to be increased according to the severity of the respiratory event. After the respiratory event is over, as shown in FIG8 , the treatment pressure of the pressure value to be increased is increased, and the slow increase in pressure is not affected, but the first target pressure reached will be higher than the normal treatment pressure when no respiratory event occurs.

[0133] After the transition from a state prone to respiratory events back to a stable sleep state (①→②), the slowly reduced and then stabilized treatment pressure will also increase a certain treatment pressure value based on the previous one. In Figure 8, taking a 0.5 cm H2O increase as an example, in the previous stable sleep state, the treatment pressure was 4 cm H2O. After the intermediate state transition and respiratory events, the treatment pressure maintained in the stable sleep state was 4.5 cm H2O.

[0134] In an exemplary embodiment, predicting a change in the respiratory state of a target object according to a respiratory prediction state, and adjusting the operating pressure of a respiratory device according to the change in the respiratory state includes: when the respiratory prediction state is a state prone to respiratory events, and when it is predicted that the change in the respiratory state of the target object is a change from a stable sleep state to a state prone to respiratory events, increasing the operating pressure of the respiratory device at a first change rate until the normal operating pressure corresponding to the state prone to respiratory events is reached; after the target object changes from a stable sleep state to a state prone to respiratory events, if the target object has a respiratory event in the state prone to respiratory events, determining a pressure value to be increased of the respiratory device according to the severity of the respiratory event, and after the respiratory event ends, increasing the operating pressure of the respiratory device according to the pressure value to be increased to obtain a first target pressure of the respiratory device; when it is predicted that the change in the respiratory state of the target object is to maintain a state prone to respiratory events, controlling the respiratory device to maintain the first target pressure; when it is predicted that the change in the respiratory state of the target object is a change from a state prone to respiratory events to a stable sleep state, reducing the operating pressure of the respiratory device according to the pressure value to be increased to obtain a second target pressure of the respiratory device, and the second target pressure is greater than the minimum operating pressure.

[0135] This embodiment is to adjust the treatment pressure when a respiratory event occurs in a state prone to respiratory events. As shown in FIG9 , when the predicted respiratory state is a state prone to respiratory events, and the target object's respiratory state is predicted to change from a stable sleep state to a state prone to respiratory events (②→①), the treatment pressure of the respiratory device is increased at a first change rate until it reaches the normal treatment pressure corresponding to the state prone to respiratory events.

[0136] When a respiratory event occurs during the process of slowly increasing the treatment pressure, the respiratory device determines the pressure value to be increased according to the severity of the respiratory event. After the respiratory event ends, such as after the event occurs in FIG9 , the treatment pressure is increased to the pressure value to be increased.

[0137] After changing from a state prone to respiratory events back to a stable sleep state (①→②), the slowly reduced and stabilized treatment pressure will also increase by a certain treatment pressure value based on the previous one. And the characteristic values ​​used to predict the respiratory state before the respiratory event will be stored in the storage device. After the treatment is completed, the model is optimized based on the data stored in the storage device to make the model prediction more accurate.

[0138] In the above embodiment, corresponding treatment pressure adjustment strategies are adopted for different situations where respiratory events are prone to occur, which can better reduce the AHI index (Apnea Hypopnea Index, the average number of apnea plus hypopnea occurring per hour of sleep), reduce the number of respiratory events occurring during sleep, and thus reduce the damage to the target subject's body caused by respiratory events.

[0139] For the stable sleep state, the target subject's airway is continuously unobstructed in this state, and respiratory events are not likely to occur. It is sufficient that the current treatment pressure can maintain the unobstructed airway. In the stable sleep state, the following situations may occur: continuous stable sleep state and respiratory events in the stable sleep state.

[0140] In an exemplary embodiment, changes in the breathing state of a target object are predicted based on the breathing prediction state, and the operating pressure of the respiratory device is controlled based on the breathing state changes, including: when the breathing prediction state is a stable sleep state, and the breathing state changes of the target object are predicted to maintain a stable sleep state, reducing the operating pressure of the respiratory device until a minimum operating pressure is reached.

[0141] This embodiment adjusts the treatment pressure of the respiratory device in a continuous stable sleep state. As shown in Figure 10, when the target object is in a stable sleep state for a long time, the treatment pressure of the respiratory device will decrease until it reaches the minimum treatment pressure, and the decrease process is a slow decrease. Some feature values ​​used to predict the respiratory state in the stable sleep state will also be stored in the storage device for optimizing the model to make the prediction of other states more accurate.

[0142] In an exemplary embodiment, predicting changes in the breathing state of a target object based on a breathing prediction state, and adjusting the operating pressure of the respiratory apparatus based on the changes in the breathing state include: when the breathing prediction state is a stable sleep state, and the breathing state change of the target object is predicted to maintain a stable sleep state, reducing the operating pressure of the respiratory apparatus; when an unpredicted respiratory event occurs in the stable sleep state, determining a pressure value to be increased for the respiratory apparatus based on the severity of the respiratory event; after the respiratory event ends, increasing the operating pressure of the respiratory apparatus based on the pressure value to be increased, and continuing to reduce the operating pressure of the respiratory apparatus until the minimum operating pressure is reached.

[0143] This embodiment is to adjust the treatment pressure of the respiratory device when a respiratory event occurs in a stable sleep state. As shown in Figure 11, when the predicted respiratory state is a stable sleep state and the predicted respiratory state change of the target object is to maintain a stable sleep state, the treatment pressure of the respiratory device is reduced.

[0144] When an unpredicted respiratory event occurs in a stable sleep state, the pressure value to be increased is determined according to the severity of the respiratory event. After the respiratory event ends, the treatment pressure of the pressure value to be increased is increased, and the treatment pressure of the respiratory device continues to be reduced until the minimum treatment pressure is reached. The characteristic values ​​used to predict the respiratory state before the respiratory event occurs will be stored in the storage device. After the treatment is completed, the model is optimized based on the data stored in the storage device.

[0145] In the above embodiment, corresponding treatment pressure adjustment strategies are adopted according to different situations of the stable sleeping state, so that the treatment pressure can be adjusted more reasonably.

[0146] A microarousal state refers to a brief, partial awakening of the brain during sleep, but not enough to cause full wakefulness. The following situations may occur during a microarousal state: a microarousal state and a state prone to respiratory events turning into a microarousal state.

[0147] In an exemplary embodiment, predicting changes in the breathing state of a target object based on a breathing prediction state, and adjusting the operating pressure of the respiratory device based on the changes in the breathing state include: when the breathing prediction state is a micro-arousal state, and the breathing state change of the target object is predicted to be a transition from a stable sleep state to a micro-arousal state, controlling the respiratory device to reduce the operating pressure during the exhalation phase of the target object, and maintaining the current operating pressure during the inhalation phase of the target object.

[0148] This embodiment adjusts the treatment pressure when a micro-awakening state occurs. As shown in Figure 12, the breathing prediction state model predicts that the target object is about to enter a micro-awakening state. In the micro-awakening state, it is easy to reduce the comfort of the target object due to the high treatment pressure, and there is a possibility that the target object will wake up. Therefore, after predicting the micro-awakening state (②→③), the treatment pressure will be adjusted according to the target object's inhalation and exhalation. The current treatment pressure is still maintained during the inhalation stage, and the treatment pressure will be reduced to a certain extent during the exhalation stage. When it is predicted that the target object changes from a micro-awakening state to a stable sleep state, the treatment pressure is restored to the inhalation stage. Taking Figure 12 as an example, the inhalation stage is 5 cm of water column, and the exhalation stage is 4 cm of water column. Reducing the treatment pressure during the exhalation stage will make the target object smoother when exhaling, improve the comfort of the target object, and reduce the possibility of the target object being awakened by high treatment pressure.

[0149] In an exemplary embodiment, predicting changes in the breathing state of a target object based on a breathing prediction state, and adjusting the operating pressure of the respiratory device based on the changes in the breathing state include: when the breathing prediction state is a micro-arousal state, and it is predicted that the breathing state of the target object changes from a state prone to respiratory events to a micro-arousal state, after the transition to the micro-arousal state, controlling the respiratory device to reduce the operating pressure during the exhalation phase of the target object, and maintaining the current operating pressure during the inhalation phase of the target object.

[0150] This embodiment adjusts the treatment pressure when the state prone to respiratory events changes to the micro-arousal state. As shown in Figure 13, if the target object changes from the state prone to respiratory events to the micro-arousal state (①→③), after the micro-arousal state changes, the treatment pressure slowly decreases and the pressure is adjusted according to the target object's inhalation and exhalation. The current treatment pressure is maintained during the inhalation stage, and the treatment pressure is reduced during the exhalation stage.

[0151] In this embodiment, when it is predicted that the target object enters a state of micro-awakening, the treatment pressure is adjusted according to the switching of the respiratory phases, the current treatment pressure is maintained for the inhalation phase of each breath, and the treatment pressure is appropriately reduced during the exhalation phase. This can improve the comfort of the target object when using the respiratory device, and enable the respiratory device to accurately adjust the treatment pressure according to the breathing pattern of the human body.

[0152] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0153] Based on the same inventive concept, the embodiment of the present application also provides a breathing state adjustment device for implementing the breathing state adjustment method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more breathing state adjustment device embodiments provided below can refer to the limitations of the breathing state adjustment method above, and will not be repeated here.

[0154] In an exemplary embodiment, as shown in FIG. 14 , a breathing state adjustment device is provided, comprising: a feature value acquisition module 1402 , a state prediction module 1404 and a pressure adjustment module 1406 , wherein:

[0155] The characteristic value acquisition module 1402 is used to acquire the physiological signal of the target object within a preset historical time period when in the continuous positive airway pressure mode, and determine the characteristic value of the physiological signal.

[0156] The state prediction module 1404 is used to predict multiple respiratory states of the characteristic values ​​through a pre-built respiratory state prediction model to obtain the predicted respiratory state of the target object at the next moment; the multiple respiratory states include a state prone to respiratory events, a stable sleep state, and a micro-arousal state.

[0157] The pressure adjustment module 1406 is used to predict the change of the breathing state of the target object according to the breathing prediction state, and adjust the operating pressure of the breathing device according to the change of the breathing state.

[0158] In an exemplary embodiment, the above device further includes:

[0159] The model optimization module is used to store the characteristic values ​​before the respiratory event when an unpredicted respiratory event occurs in a stable sleep state; after the continuous positive airway pressure ventilation mode ends, the pre-constructed respiratory state prediction model is trained according to the stored characteristic values ​​to obtain an optimized respiratory state prediction model; and the optimized respiratory state prediction model is updated to the pre-constructed respiratory state prediction model.

[0160] In an exemplary embodiment, the pressure adjustment module 1406 is also used to increase the operating pressure of the respiratory equipment at a first change rate until the normal operating pressure corresponding to the state prone to respiratory events is reached when the predicted respiratory state is a state prone to respiratory events and the target object's respiratory state is predicted to change from a stable sleep state to a state prone to respiratory events; after the target object changes from a stable sleep state to a state prone to respiratory events, if it is predicted that the target object's respiratory change is from a state prone to respiratory events to a stable sleep state, the operating pressure of the respiratory equipment is reduced at a second change rate.

[0161] In an exemplary embodiment, the pressure adjustment module 1406 is also used to increase the operating pressure of the respiratory device at a first change rate when the predicted respiratory state is a state prone to respiratory events and the target object's respiratory state change is predicted to change from a stable sleep state to a state prone to respiratory events; when a respiratory event occurs during the process of increasing the operating pressure, determine the pressure value to be increased of the respiratory device according to the severity of the respiratory event, and after the respiratory event ends, increase the operating pressure of the respiratory device according to the pressure value to be increased, and continue to increase the operating pressure of the respiratory device to obtain a first target pressure of the respiratory device, and the first target pressure is greater than the normal operating pressure corresponding to the state prone to respiratory events; after the target object changes from a stable sleep state to a state prone to respiratory events, if it is predicted that the target object's respiratory state changes to maintain a state prone to respiratory events, control the respiratory device to maintain the first target pressure; when it is predicted that the target object's respiratory state changes to change from a state prone to respiratory events to a stable sleep state, reduce the operating pressure of the respiratory device according to the pressure value to be increased to obtain a second target pressure of the respiratory device, and the second target pressure is greater than the minimum operating pressure.

[0162] In an exemplary embodiment, the pressure adjustment module 1406 is also used to increase the operating pressure of the respiratory device at a first change rate until the normal operating pressure corresponding to the state prone to respiratory events is reached when the respiratory prediction state is a state prone to respiratory events and the target object's respiratory state change is predicted to be from a stable sleep state to a state prone to respiratory events; after the target object changes from a stable sleep state to a state prone to respiratory events, if the target object has a respiratory event in the state prone to respiratory events, determine the pressure value to be increased of the respiratory device according to the severity of the respiratory event, and after the respiratory event ends, increase the operating pressure of the respiratory device according to the pressure value to be increased to obtain a first target pressure of the respiratory device; when it is predicted that the target object's respiratory state change is to remain in a state prone to respiratory events, control the respiratory device to maintain the first target pressure; when it is predicted that the target object's respiratory state change is from a state prone to respiratory events to a stable sleep state, reduce the operating pressure of the respiratory device according to the pressure value to be increased to obtain a second target pressure of the respiratory device, and the second target pressure is greater than the minimum operating pressure.

[0163] In an exemplary embodiment, the pressure adjustment module 1406 is also used to reduce the operating pressure of the respiratory device when the predicted respiratory state is a stable sleep state and the predicted respiratory state change of the target object is to maintain a stable sleep state; when an unpredicted respiratory event occurs in the stable sleep state, determine the pressure value of the respiratory device to be increased according to the severity of the respiratory event; after the respiratory event ends, increase the operating pressure of the respiratory device according to the pressure value to be increased, and continue to reduce the operating pressure of the respiratory device until the minimum operating pressure is reached.

[0164] In an exemplary embodiment, the pressure adjustment module 1406 is also used to control the respiratory device to reduce the operating pressure during the exhalation phase of the target object, and to maintain the current operating pressure during the inhalation phase of the target object, when the predicted respiratory state is a micro-arousal state and the target object's respiratory state is predicted to change from a stable sleep state to a micro-arousal state.

[0165] In an exemplary embodiment, the pressure adjustment module 1406 is also used to control the respiratory device to reduce the operating pressure during the exhalation phase of the target object and to maintain the current operating pressure during the inhalation phase of the target object after the transition to the micro-arousal state when the predicted respiratory state is a micro-arousal state and the target object's respiratory state is predicted to change from a state prone to respiratory events to a micro-arousal state.

[0166] Each module in the above-mentioned breathing state adjustment device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0167] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0168] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0169] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0170] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0171] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0172] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0173] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for adjusting a breathing state, characterized in that: The method comprises: When in continuous positive airway pressure mode, obtaining a physiological signal of a target object within a preset historical time period, and determining a characteristic value of the physiological signal; Predicting multiple respiratory states of the characteristic value through a pre-built respiratory state prediction model to obtain the predicted respiratory state of the target object at the next moment; the multiple respiratory states include a state prone to respiratory events, a stable sleep state, and a micro-arousal state; The breathing state change of the target object is predicted according to the breathing prediction state, and the operating pressure of the breathing device is adjusted according to the breathing state change.

2. The method according to claim 1, characterized in that The method further comprises: When an unpredicted respiratory event occurs in a stable sleep state, the feature value before the respiratory event is stored; After the continuous positive airway pressure mode ends, the pre-constructed respiratory state prediction model is trained according to the stored characteristic values ​​to obtain an optimized respiratory state prediction model; The optimized respiratory state prediction model is updated to the pre-constructed respiratory state prediction model.

3. The method according to claim 1, characterized in that: Predicting the change of the breathing state of the target object according to the predicted breathing state, and adjusting the operating pressure of the breathing device according to the change of the breathing state includes: When the predicted respiratory state is a state prone to respiratory events, and the target subject's respiratory state is predicted to change from a stable sleep state to a state prone to respiratory events, increasing the operating pressure of the respiratory device at a first change rate until reaching a normal operating pressure corresponding to the state prone to respiratory events; After the target object changes from a stable sleep state to a state prone to respiratory events, if it is predicted that the target object's respiratory change is from a state prone to respiratory events to a stable sleep state, the operating pressure of the respiratory device is reduced at a second change rate.

4. The method according to claim 1, characterized in that: Predicting the change of the breathing state of the target object according to the predicted breathing state, and adjusting the operating pressure of the breathing device according to the change of the breathing state includes: When the predicted respiratory state is a state prone to respiratory events, and the target subject's respiratory state is predicted to change from a stable sleep state to a state prone to respiratory events, increasing the operating pressure of the respiratory device at a first change rate; When a respiratory event occurs during the process of increasing the operating pressure, a pressure value to be increased of the respiratory device is determined according to the severity of the respiratory event, and after the respiratory event ends, the operating pressure of the respiratory device is increased according to the pressure value to be increased, and the operating pressure of the respiratory device is continued to be increased to obtain a first target pressure of the respiratory device, wherein the first target pressure is greater than the normal operating pressure corresponding to the state where a respiratory event is prone to occur; After the target subject changes from a stable sleeping state to a state prone to respiratory events, if it is predicted that the change in the respiratory state of the target subject is to maintain a state prone to respiratory events, controlling the respiratory device to maintain the first target pressure; When it is predicted that the respiratory state of the target object changes from a state prone to respiratory events to a stable sleep state, the operating pressure of the respiratory device is reduced according to the pressure value to be increased to obtain a second target pressure of the respiratory device, and the second target pressure is greater than the minimum operating pressure.

5. The method according to claim 1, characterized in that Predicting the change of the breathing state of the target object according to the predicted breathing state, and adjusting the operating pressure of the breathing device according to the change of the breathing state includes: When the predicted respiratory state is a state prone to respiratory events, and the target subject's respiratory state is predicted to change from a stable sleep state to a state prone to respiratory events, increasing the operating pressure of the respiratory device at a first change rate until reaching a normal operating pressure corresponding to the state prone to respiratory events; After the target subject changes from a stable sleeping state to a state prone to respiratory events, if the target subject has a respiratory event in the state prone to respiratory events, a pressure value to be increased of the respiratory device is determined according to the severity of the respiratory event, and after the respiratory event ends, the operating pressure of the respiratory device is increased according to the pressure value to be increased to obtain a first target pressure of the respiratory device; When it is predicted that the change in the respiratory state of the target object is to maintain a state prone to respiratory events, controlling the respiratory device to maintain the first target pressure; When it is predicted that the respiratory state of the target object changes from a state prone to respiratory events to a stable sleep state, the operating pressure of the respiratory device is reduced according to the pressure value to be increased to obtain a second target pressure of the respiratory device, and the second target pressure is greater than the minimum operating pressure.

6. The method according to claim 1, characterized in that Predicting the change of the breathing state of the target object according to the predicted breathing state, and adjusting the operating pressure of the breathing device according to the change of the breathing state includes: When the predicted breathing state is a stable sleeping state, and the predicted breathing state change of the target object is to maintain a stable sleeping state, reducing the operating pressure of the breathing device; When an unpredicted respiratory event occurs in a stable sleep state, determining a pressure value to be increased for the respiratory device according to the severity of the respiratory event; After the respiratory event ends, the operating pressure of the respiratory device is increased according to the pressure value to be increased, and the operating pressure of the respiratory device continues to be reduced until the minimum operating pressure is reached.

7. The method according to claim 1, characterized in that Predicting the change of the breathing state of the target object according to the predicted breathing state, and adjusting the operating pressure of the breathing device according to the change of the breathing state includes: When the predicted breathing state is a micro-arousal state, and the breathing state of the target object is predicted to change from a stable sleep state to a micro-arousal state, the respiratory device is controlled to reduce the operating pressure during the exhalation phase of the target object, and to maintain the current operating pressure during the inhalation phase of the target object.

8. The method according to claim 1, characterized in that Predicting the change of the breathing state of the target object according to the predicted breathing state, and adjusting the operating pressure of the breathing device according to the change of the breathing state includes: When the predicted respiratory state is a micro-arousal state, and the target object's respiratory state is predicted to change from a state prone to respiratory events to a micro-arousal state, after the transition to the micro-arousal state, the respiratory device is controlled to reduce the operating pressure during the exhalation phase of the target object, and maintain the current operating pressure during the inhalation phase of the target object.

9. A breathing state adjustment device, characterized in that: The device comprises: A characteristic value acquisition module, used to acquire the physiological signal of the target object within a preset historical time period when in a continuous positive airway pressure ventilation mode, and determine the characteristic value of the physiological signal; A state prediction module, used to predict multiple respiratory states of the characteristic value through a pre-built respiratory state prediction model to obtain the predicted respiratory state of the target object at the next moment; the multiple respiratory states include a state prone to respiratory events, a stable sleep state, and a micro-arousal state; The pressure adjustment module is used to predict the change of the breathing state of the target object according to the predicted breathing state, and adjust the operating pressure of the breathing device according to the change of the breathing state.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

Images