Method for identifying hypoventilation type, computer equipment and storage medium

Abstract

The invention relates to a method for identifying a hypoventilation type, computer equipment and a storage medium. The method comprises the following steps: acquiring breathing state data of a target user; determining breathing characteristic information according to the breathing state data; the breathing characteristic information comprises a breathing peak change rate, a breathing pressure change rate and a breathing flow ratio; and according to the breathing peak change rate, the breathing pressure change rate and the breathing flow ratio, the hypoventilation type of the target user is determined. By means of the collected breathing state data, whether a hypoventilation event occurs or not can be judged, the specific hypoventilation type can be determined in combination with the characteristics of the hypoventilation type, only the breathing-related data is collected, the obtained data is not affected by motion artifacts and changes of the elastic inertia of the pipeline, and the accuracy of hypoventilation is improved. The accuracy of the data for determining the hypoventilation type is improved, so that the accuracy of identifying the hypoventilation type is improved.

Description

Technical Field

[0001] The present application relates to the technical field of ventilators, and in particular to a method, apparatus, computer device and storage medium for identifying hypoventilation types. Background Art

[0002] A hypoventilation event (HVE) occurs when ventilation drops significantly below normal levels, leading to carbon dioxide accumulation and decreased blood oxygen saturation. This condition is common in sleep apnea, neurological disorders, or certain physiological conditions and can have serious health consequences. Therefore, timely and accurate identification of the type of hypoventilation is crucial.

[0003] In traditional technology, an oscillating wave generator is used to collect pressure and flow signals and calculate the signal power spectrum to identify hypopnea; alternatively, hypopnea is identified based on airflow, snoring, and blood oxygen signals.

[0004] However, traditional hypopnea identification methods are unable to identify the hypopnea type of hypopnea events. Summary of the Invention

[0005] Based on this, it is necessary to provide a method, computer device and storage medium for accurately identifying the type of hypopnea in order to address the above technical issues.

[0006] In a first aspect, the present application provides a method for identifying a type of hypopnea, the method comprising:

[0007] Obtain the target user's breathing status data;

[0008] Determining respiratory characteristic information based on the respiratory state data; the respiratory characteristic information includes a respiratory peak change rate, a respiratory pressure change rate, and a respiratory flow ratio;

[0009] The hypopnea type of the target user is determined according to the respiratory peak change rate, the respiratory pressure change rate, and the respiratory flow ratio.

[0010] In one embodiment, determining the type of hypopnea event based on the respiratory peak change rate, the respiratory pressure change rate, and the respiratory flow ratio includes:

[0011] determining whether a hypopnea event occurs according to the peak respiratory rate of change and a first rate of change threshold;

[0012] When it is determined that the hypopnea event occurs, the hypopnea type of the target user is determined according to the respiratory pressure change rate and the respiratory flow ratio.

[0013] In one embodiment, determining the hypopnea type of the target user based on the respiratory pressure change rate and the respiratory flow ratio includes:

[0014] When the respiratory pressure change rate is less than or equal to a second change rate threshold, and the respiratory flow ratio is less than or equal to a ratio threshold, determining that the hypopnea type is central apnea;

[0015] When the respiratory pressure change rate is less than or equal to a second change rate threshold, and the respiratory flow ratio is greater than a ratio threshold, determining that the hypopnea type is obstructive apnea;

[0016] When the respiratory pressure change rate is greater than a second change rate threshold, and the respiratory flow ratio is greater than a ratio threshold, it is determined that the hypoventilation type is alveolar hypoventilation.

[0017] In one embodiment, the respiratory state data includes peak respiratory flow rate, inspiratory pressure data, and respiratory flow data of multiple breaths per unit time. Determining respiratory characteristic information based on the respiratory state data includes:

[0018] Determining the peak respiratory rate of change according to the peak respiratory flow rate;

[0019] determining the respiratory pressure change rate according to the inspiratory pressure data;

[0020] The respiratory flow ratio is determined according to the ratio of the expiratory flow to the inspiratory flow in the respiratory flow data.

[0021] In one embodiment, determining the respiratory pressure change rate based on the inspiratory pressure data includes:

[0022] Determining a difference between inspiratory pressure data corresponding to any two breaths in the plurality of breaths;

[0023] determining a maximum value and a minimum value from the differences;

[0024] The respiratory pressure change rate is determined according to the maximum value and the minimum value.

[0025] In one embodiment, determining the peak respiratory rate of change based on the peak respiratory flow rate includes:

[0026] Determining an average flow rate of peak respiratory flow rates of a plurality of breaths within the unit time;

[0027] determining a plurality of differences between the peak respiratory flow rate and the average flow rate for a plurality of breaths within the unit time;

[0028] The respiratory peak change rate is determined based on the plurality of differences and the number of the plurality of breaths.

[0029] In one embodiment, obtaining the target user's respiratory status data includes:

[0030] Obtain initial respiratory status data through the ventilator sensor;

[0031] The initial respiratory state data is subjected to denoising processing to obtain the respiratory state data; the denoising processing includes wavelet transform and Butterworth.

[0032] In a second aspect, the present application further provides a device for identifying the type of hypopnea, comprising:

[0033] An acquisition module is used to obtain the respiratory status data of the target user;

[0034] A first determining module is configured to determine respiratory characteristic information based on the respiratory state data; the respiratory characteristic information includes a respiratory peak change rate, a respiratory pressure change rate, and a respiratory flow ratio;

[0035] The second determining module is configured to determine the hypopnea type of the target user according to the respiratory peak change rate, the respiratory pressure change rate, and the respiratory flow ratio.

[0036] In a third aspect, the present application further provides a computer device comprising 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:

[0037] Obtain the target user's breathing status data;

[0038] Determining respiratory characteristic information based on the respiratory state data; the respiratory characteristic information includes a respiratory peak change rate, a respiratory pressure change rate, and a respiratory flow ratio;

[0039] The hypopnea type of the target user is determined according to the respiratory peak change rate, the respiratory pressure change rate, and the respiratory flow ratio.

[0040] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0041] Obtain the target user's breathing status data;

[0042] Determining respiratory characteristic information based on the respiratory state data; the respiratory characteristic information includes a respiratory peak change rate, a respiratory pressure change rate, and a respiratory flow ratio;

[0043] The hypopnea type of the target user is determined according to the respiratory peak change rate, the respiratory pressure change rate, and the respiratory flow ratio.

[0044] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0045] Obtain the target user's breathing status data;

[0046] Determining respiratory characteristic information based on the respiratory state data; the respiratory characteristic information includes a respiratory peak change rate, a respiratory pressure change rate, and a respiratory flow ratio;

[0047] The hypopnea type of the target user is determined according to the respiratory peak change rate, the respiratory pressure change rate, and the respiratory flow ratio.

[0048] The above-mentioned method, computer device, and storage medium for identifying hypopnea types acquire respiratory status data of a target user; determine respiratory characteristic information based on the respiratory status data; the respiratory characteristic information includes the respiratory peak rate of change, respiratory pressure rate of change, and respiratory flow ratio; and determine the target user's hypopnea type based on the respiratory peak rate of change, respiratory pressure rate of change, and respiratory flow ratio. Using the acquired respiratory status data, it is not only possible to determine whether a hypopnea event has occurred, but also to determine the specific hypopnea type by combining the characteristics of the hypopnea type. Since only respiratory-related data is acquired, the acquired data is unaffected by motion artifacts and changes in the elastic inertia of the tubing, thereby improving the accuracy of the data used to determine the hypopnea type and thus improving the accuracy of identifying the hypopnea type. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0050] Figure 1 A diagram illustrating an application environment of a method for identifying hypoventilation types in one embodiment;

[0051] Figure 2 1 is a flow chart of a method for identifying hypoventilation types in one embodiment;

[0052] Figure 3 A flowchart of a method for identifying hypoventilation types in another embodiment;

[0053] Figure 4A flowchart of a method for identifying hypoventilation types in another embodiment;

[0054] Figure 5 A flowchart of a method for identifying hypoventilation types in another embodiment;

[0055] Figure 6 A flowchart of a method for identifying hypoventilation types in another embodiment;

[0056] Figure 7 A flowchart of a method for identifying hypoventilation types in another embodiment;

[0057] Figure 8 A flowchart of a method for identifying hypoventilation types in another embodiment;

[0058] Figure 9 FIG. 1 is a structural block diagram of an apparatus for identifying hypoventilation types in one embodiment. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0060] The method for identifying the type of hypopnea provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown in FIG. , the computer device may be a ventilator, and its internal structure diagram may be as shown in FIG. Figure 1As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless means, and the wireless means can be implemented via Wi-Fi, a mobile cellular network, near field communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for identifying the type of hypopnea. The display unit of the computer device is used to form a visually visible image, and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0061] Those skilled in the art will understand that Figure 1 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0062] In one embodiment, Figure 2 As shown, a method for identifying the type of hypopnea is provided, and the method is applied to Figure 1 The following is an example of a ventilator in the figure:

[0063] S201, obtaining the target user's breathing status data.

[0064] The respiratory status data may include respiratory flow data, respiratory pressure data, etc. of the target user within a preset time period.

[0065] In this embodiment of the present application, the target user's respiratory status data can be collected through the ventilator's own sensors, eliminating the need for the target user to wear additional monitoring equipment, thereby improving the target user's experience. Furthermore, since blood oxygen measurement is not used, the acquired data is not affected by motion artifacts; and since pressure oscillation is not used, the acquired data is not affected by changes in the elastic inertia of the pipeline.

[0066] As another optional implementation, the target user's respiratory status data may be acquired through contact sensing methods such as chest and abdominal motion sensors, oral and nasal airflow velocity sensors, and esophageal pressure detection catheters.

[0067] S202, determining respiratory characteristic information based on the respiratory state data; the respiratory characteristic information includes a respiratory peak change rate, a respiratory pressure change rate, and a respiratory flow ratio.

[0068] As an optional embodiment, the ventilator pre-stores a first expression corresponding to the respiratory peak change rate, a second expression corresponding to the respiratory pressure change rate, and a third expression corresponding to the respiratory flow ratio. The respiratory state data is substituted into the first expression, the second expression, and the third expression to determine the respiratory peak change rate, the respiratory pressure change rate, and the respiratory flow ratio.

[0069] As another optional embodiment, the ventilator is provided with a pre-trained neural network model for identifying respiratory characteristic information. The respiratory state data is input into the neural network model to obtain the output respiratory peak change rate, respiratory pressure change rate and respiratory flow ratio.

[0070] S203 , determining the hypopnea type of the target user according to the respiratory peak change rate, the respiratory pressure change rate, and the respiratory flow ratio.

[0071] The hypopnea type may include any one of central apnea, obstructive apnea and alveolar hypopnea.

[0072] In an embodiment of the present application, the value range of each respiratory characteristic information corresponding to each hypopnea type can be pre-set, so as to determine the hypopnea type of the target user based on the target user's respiratory peak change rate, respiratory pressure change rate and respiratory flow ratio, as well as the value range of each respiratory characteristic information.

[0073] Optionally, a candidate hypoventilation type can be determined from all hypoventilation types based on the peak respiratory rate of change, and then the target user's hypoventilation type can be determined from the candidate hypoventilation types based on the respiratory pressure change rate and the respiratory flow ratio; or, a candidate hypoventilation type can be determined from all hypoventilation types based on the respiratory pressure change rate, and then the target user's hypoventilation type can be determined from the candidate hypoventilation types based on the peak respiratory rate of change and the respiratory flow ratio; or, a candidate hypoventilation type can be determined from all hypoventilation types based on the respiratory flow ratio, and then the target user's hypoventilation type can be determined from the candidate hypoventilation types based on the peak respiratory rate of change and the respiratory pressure change rate.

[0074] In the above-mentioned method for identifying the type of hypopnea, respiratory status data of the target user is obtained; respiratory characteristic information is determined based on the respiratory status data; the respiratory characteristic information includes the respiratory peak rate of change, the respiratory pressure rate of change, and the respiratory flow ratio; and the hypopnea type of the target user is determined based on the respiratory peak rate of change, the respiratory pressure rate of change, and the respiratory flow ratio. Using the collected respiratory status data, it is not only possible to determine whether a hypopnea event has occurred, but also to determine the specific hypopnea type by combining the characteristics of the hypopnea type. Since only respiratory-related data is collected, the obtained data is not affected by motion artifacts or changes in the elastic inertia of the tubing, thereby improving the accuracy of the data used to determine the hypopnea type and thus improving the accuracy of identifying the hypopnea type.

[0075] In one embodiment, an implementation of the above S203 is provided, such as Figure 3 As shown in the figure, the above “determining the type of hypopnea event based on the respiratory peak change rate, respiratory pressure change rate and respiratory flow ratio” includes:

[0076] S301 : Determine whether a hypopnea event occurs based on a respiratory peak change rate and a first change rate threshold.

[0077] In an embodiment of the present application, if the respiratory peak change rate is greater than or equal to the first change rate threshold, it is determined that a hypopnea event has occurred; if the respiratory peak value is less than the first change rate threshold, it is determined that no hypopnea event has occurred.

[0078] S302: When it is determined that a hypopnea event occurs, the hypopnea type of the target user is determined according to the respiratory pressure change rate and the respiratory flow ratio.

[0079] In the embodiment of the present application, the hypopnea type of the target user can be determined based on the value range of the respiratory pressure change rate and the value range of the respiratory flow ratio corresponding to each hypopnea type.

[0080] Exemplarily, the candidate hypoventilation type can be first determined from all hypoventilation types based on the respiratory pressure change rate, and then the hypoventilation type of the target user can be determined from the candidate hypoventilation types based on the respiratory flow ratio; or, the candidate hypoventilation type can be first determined from all hypoventilation types based on the respiratory flow ratio, and then the hypoventilation type of the target user can be determined from the candidate hypoventilation types based on the respiratory pressure change rate.

[0081] Optionally, in the embodiment of the present application, Figure 4 As shown in the figure, the hypopnea type of the target user is determined based on the respiratory pressure change rate and respiratory flow ratio, including:

[0082] S401 : When the respiratory pressure change rate is less than or equal to a second change rate threshold, and the respiratory flow ratio is less than or equal to a ratio threshold, determine that the hypopnea type is central apnea.

[0083] S402: When the respiratory pressure change rate is less than or equal to the second change rate threshold, and the respiratory flow ratio is greater than the ratio threshold, determine that the hypopnea type is obstructive apnea.

[0084] S403: When the respiratory pressure change rate is greater than the second change rate threshold and the respiratory flow ratio is greater than the ratio threshold, determine that the hypoventilation type is alveolar hypoventilation.

[0085] In the embodiment of the present application, central apnea is caused by problems in the central nervous system, resulting in insufficient spontaneous breathing effort by the user, and thus exhibits lower volatility in the pressure signal and flow signal, i.e., a smaller rate of change in respiratory pressure and a smaller respiratory flow ratio; obstructive apnea is caused by airway obstruction, resulting in a lower and unstable flow rate, i.e., a smaller rate of change in respiratory pressure and a larger respiratory flow ratio; alveolar hypoventilation is caused by alveolar dysfunction, resulting in an increase in the peak inspiratory pressure, i.e., a larger rate of change in respiratory pressure and a larger respiratory flow ratio.

[0086] In the above-mentioned application embodiment, it is first determined whether a hypoventilation event has occurred. When a hypoventilation event has not occurred, there is no need to further determine the type of hypoventilation, thereby avoiding wasting the computing resources of the ventilator. When it is determined that a hypoventilation event has occurred, the hypoventilation type of the target user is determined based on the respiratory pressure change rate and the respiratory flow ratio, thereby improving the accuracy of the determination.

[0087] In one embodiment, an implementation of the above S202 is provided, where the respiratory state data includes the respiratory peak flow rate, inspiratory pressure data, and respiratory flow data of multiple breaths per unit time, such as Figure 5 As shown, the above-mentioned “determining respiratory characteristic information based on respiratory airflow data” includes:

[0088] S501, determining a respiratory peak change rate according to the respiratory peak flow rate.

[0089] Optionally, the maximum respiratory peak flow rate and the minimum respiratory peak flow rate in multiple breaths within a unit time can be determined, and the difference between the maximum respiratory peak flow rate and the minimum respiratory peak flow rate can be determined, as well as the average respiratory peak flow rate of multiple breaths within a unit time, and the ratio of the difference between the maximum respiratory peak flow rate and the minimum respiratory peak flow rate to the average respiratory peak flow rate can be determined as the respiratory peak change rate.

[0090] Optionally, in the embodiment of the present application, Figure 6 As shown, the above S501 "determining the peak respiratory rate of change according to the peak respiratory flow rate" includes:

[0091] S601, determining an average flow rate of peak respiratory flow rates of multiple breaths within a unit time.

[0092] S602: Determine a plurality of differences between the peak flow rate and the average flow rate of a plurality of breaths within a unit time.

[0093] S603: Determine a respiratory peak change rate based on the multiple differences and the number of breaths.

[0094] In the embodiment of the present application, the peak respiratory flow rates of multiple breaths in a unit time are summed to obtain the total peak respiratory flow rate, and then the ratio of the total peak respiratory flow rate to the number of breaths is determined as the average flow rate of the peak respiratory flow rate. ; Further, determine the peak respiratory flow rate of each breath per unit time Multiple differences from the average flow rate ; Further, the sum of the squares of the multiple differences is determined, as shown in Formula 1, and the respiratory peak change rate is determined based on the sum of the squares of the multiple differences and the number n of multiple breaths:

[0095] (Formula 1)

[0096] S502: Determine the respiratory pressure change rate based on the inspiratory pressure data.

[0097] Optionally, the maximum inspiratory pressure and the minimum inspiratory pressure in multiple breaths within a unit time can be determined, and the difference between the maximum inspiratory pressure and the minimum inspiratory pressure can be determined, as well as the average inspiratory pressure of multiple breaths within a unit time, and the ratio of the difference between the maximum inspiratory pressure and the minimum inspiratory pressure to the average inspiratory pressure can be determined as the respiratory pressure change rate.

[0098] Optional, such as Figure 7 As shown, the above S502 "determining the respiratory pressure change rate according to the inspiratory pressure data" includes:

[0099] S701, determining a difference between inspiratory pressure data corresponding to any two breaths in a plurality of breaths.

[0100] S702: Determine the maximum value and the minimum value from the difference.

[0101] S703: Determine the respiratory pressure change rate based on the maximum value and the minimum value.

[0102] In the embodiment of the present application, the difference between the inspiratory pressure data corresponding to any two breaths in multiple breaths is determined. , determine the maximum value from multiple differences and minimum value , further, as shown in Formula 2, the respiratory pressure change rate is determined based on the maximum and minimum values:

[0103] (Equation 2)

[0104] In the embodiment of the present application, the respiratory pressure change rate is used to represent the change in the inspiratory flow rate.

[0105] S503: Determine a respiratory flow ratio according to the ratio of the expiratory flow to the inspiratory flow in the respiratory flow data.

[0106] In the embodiment of the present application, the respiratory flow ratio is shown in Formula 3:

[0107] (Equation 3)

[0108] in, is the inspiratory flow, is the expiratory flow.

[0109] In the above application embodiment, the respiratory characteristic information is determined by a preset formula, thereby ensuring the accuracy of the respiratory characteristic information.

[0110] In one embodiment, an implementation of the above S201 is provided, such as Figure 8 As shown, the above-mentioned "obtaining the target user's respiratory status data" includes:

[0111] S801, obtaining initial respiratory status data through a ventilator sensor.

[0112] In this embodiment, the ventilator's own sensors collect the target user's initial respiratory status data, eliminating the need for the target user to wear additional monitoring equipment, thereby improving the target user's experience. Furthermore, since blood oxygen measurement is not used, the acquired data is not affected by motion artifacts; and since pressure oscillation is not used, the acquired data is not affected by changes in the elastic inertia of the tubing.

[0113] S802, performing denoising processing on the initial respiratory state data to obtain respiratory state data; the denoising processing includes wavelet transform and Butterworth.

[0114] In an embodiment of the present application, the collected respiratory signal is subjected to denoising. For example, initial respiratory state data is processed using wavelet transforms to obtain respiratory state data. Wavelet denoising is a signal processing method based on wavelet transforms that separates signal from noise through multi-scale analysis, with advantages such as time-frequency localization and strong adaptability. Alternatively, the initial respiratory state data is processed using Butterworth denoising to obtain respiratory state data. Butterworth denoising is a signal processing method based on frequency domain filtering that removes noise from the signal using a Butterworth filter.

[0115] In the above-mentioned application embodiment, the initial respiratory status data of the target user is collected through the ventilator's own sensor, without the target user having to wear additional monitoring equipment, thereby improving the target user's experience, and the collected data is denoised to improve the accuracy of the respiratory status data.

[0116] In one embodiment, a complete method for identifying the type of hypopnea is provided, comprising:

[0117] S1, obtains initial respiratory status data through the ventilator sensor.

[0118] S2, performing denoising processing on the initial respiratory state data to obtain respiratory state data; the denoising processing includes wavelet transform and Butterworth.

[0119] S3, determining an average flow rate of the peak respiratory flow rates of multiple breaths within a unit time.

[0120] S4, determining a plurality of differences between the peak flow rate and the average flow rate of a plurality of breaths within a unit time.

[0121] S5, determining a respiratory peak change rate based on the multiple differences and the number of breaths.

[0122] S6, determining the difference between the inspiratory pressure data corresponding to any two breaths in the multiple breaths.

[0123] S7, determining the maximum and minimum values ​​from the difference values.

[0124] S8. Determine the respiratory pressure change rate based on the maximum and minimum values.

[0125] S9, determining a respiratory flow ratio according to the ratio of the expiratory flow to the inspiratory flow in the respiratory flow data.

[0126] S10 , determining whether a hypopnea event occurs based on the respiratory peak change rate and a first change rate threshold.

[0127] S11, when the respiratory pressure change rate is less than or equal to the second change rate threshold, and the respiratory flow ratio is less than or equal to the ratio threshold, the hypoventilation type is determined to be central apnea; when the respiratory pressure change rate is less than or equal to the second change rate threshold, and the respiratory flow ratio is greater than the ratio threshold, the hypoventilation type is determined to be obstructive apnea; when the respiratory pressure change rate is greater than the second change rate threshold, and the respiratory flow ratio is greater than the ratio threshold, the hypoventilation type is determined to be alveolar hypoventilation.

[0128] In the above-mentioned method for identifying the type of hypopnea, respiratory status data of the target user is obtained; respiratory characteristic information is determined based on the respiratory status data; the respiratory characteristic information includes the respiratory peak rate of change, the respiratory pressure rate of change, and the respiratory flow ratio; and the hypopnea type of the target user is determined based on the respiratory peak rate of change, the respiratory pressure rate of change, and the respiratory flow ratio. Using the collected respiratory status data, it is not only possible to determine whether a hypopnea event has occurred, but also to determine the specific hypopnea type by combining the characteristics of the hypopnea type. Since only respiratory-related data is collected, the obtained data is not affected by motion artifacts or changes in the elastic inertia of the tubing, thereby improving the accuracy of the data used to determine the hypopnea type and thus improving the accuracy of identifying the hypopnea type.

[0129] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed 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 portion of steps or stages in other steps.

[0130] Based on the same inventive concept, embodiments of the present application also provide a device for identifying the type of hypoventilation, for implementing the aforementioned method for identifying the type of hypoventilation. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the device for identifying the type of hypoventilation provided below can be found in the aforementioned method for identifying the type of hypoventilation, and will not be further elaborated here.

[0131] In one embodiment, Figure 9 As shown, a device for identifying the type of hypopnea is provided, comprising: an acquisition module 10, a first determination module 11 and a second determination module 12, wherein:

[0132] The acquisition module 10 is used to acquire the respiratory status data of the target user.

[0133] The first determining module 11 is used to determine respiratory characteristic information according to the respiratory state data; the respiratory characteristic information includes respiratory peak change rate, respiratory pressure change rate and respiratory flow ratio.

[0134] The second determining module 12 is configured to determine the hypopnea type of the target user according to the respiratory peak change rate, the respiratory pressure change rate, and the respiratory flow ratio.

[0135] In one embodiment, the second determining module 12 includes: a first determining unit and a second determining unit, wherein:

[0136] The first determining unit is configured to determine whether a hypopnea event occurs according to a respiratory peak change rate and a first change rate threshold.

[0137] The second determining unit is configured to determine the hypopnea type of the target user according to the respiratory pressure change rate and the respiratory flow ratio when determining that a hypopnea event occurs.

[0138] In one embodiment, the second determining unit is specifically configured to determine that the type of hypopnea is central apnea when the respiratory pressure change rate is less than or equal to a second change rate threshold and the respiratory flow ratio is less than or equal to a ratio threshold; determine that the type of hypopnea is obstructive apnea when the respiratory pressure change rate is less than or equal to the second change rate threshold and the respiratory flow ratio is greater than the ratio threshold; and determine that the type of hypopnea is alveolar hypopnea when the respiratory pressure change rate is greater than the second change rate threshold and the respiratory flow ratio is greater than the ratio threshold.

[0139] In one embodiment, the first determining module 11 includes: a third determining unit, a fourth determining unit, and a fifth determining unit, wherein:

[0140] The third determining unit is configured to determine a respiratory peak change rate according to the respiratory peak flow rate.

[0141] The fourth determining unit is configured to determine a respiratory pressure change rate according to the inspiratory pressure data.

[0142] The fifth determining unit is configured to determine the respiratory flow ratio according to the ratio of the expiratory flow to the inspiratory flow in the respiratory flow data.

[0143] In one embodiment, the fourth determining unit is specifically configured to determine a difference between inspiratory pressure data corresponding to any two breaths in a plurality of breaths; determine a maximum value and a minimum value from the difference; and determine a respiratory pressure change rate based on the maximum value and the minimum value.

[0144] In one embodiment, the third determination unit is specifically configured to determine an average flow rate of the peak respiratory flow rates of multiple breaths within a unit time; determine multiple differences between the peak respiratory flow rates and the average flow rate of multiple breaths within a unit time; and determine a peak respiratory flow rate change rate based on the multiple differences and the number of breaths.

[0145] In one embodiment, the acquisition module 10 includes an acquisition unit and a processing unit, wherein:

[0146] The acquisition unit is used to acquire initial respiratory state data through a ventilator sensor.

[0147] The processing unit is used to perform denoising processing on the initial respiratory state data to obtain respiratory state data; the denoising processing includes wavelet transform and Butterworth.

[0148] Each module in the aforementioned device for identifying the type of hypopnea may be implemented in whole or in part through software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0149] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0150] Obtain the target user's breathing status data;

[0151] Determine respiratory characteristic information based on respiratory status data; respiratory characteristic information includes respiratory peak change rate, respiratory pressure change rate and respiratory flow ratio;

[0152] The hypopnea type of the target user is determined based on the peak respiratory rate of change, respiratory pressure rate of change, and respiratory flow ratio.

[0153] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0154] determining whether a hypopnea event occurs according to the peak respiratory rate of change and a first rate of change threshold;

[0155] When a hypopnea event is determined to have occurred, the hypopnea type of the target user is determined based on the respiratory pressure change rate and the respiratory flow ratio.

[0156] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0157] When the respiratory pressure change rate is less than or equal to the second change rate threshold, and the respiratory flow ratio is less than or equal to the ratio threshold, determining that the hypopnea type is central apnea;

[0158] When the respiratory pressure change rate is less than or equal to the second change rate threshold, and the respiratory flow ratio is greater than the ratio threshold, determining that the hypopnea type is obstructive apnea;

[0159] When the respiratory pressure change rate is greater than the second change rate threshold and the respiratory flow ratio is greater than the ratio threshold, the hypoventilation type is determined to be alveolar hypoventilation.

[0160] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0161] Based on the peak respiratory flow rate, determine the peak respiratory rate of change;

[0162] Determine the respiratory pressure change rate based on the inspiratory pressure data;

[0163] The respiratory flow ratio is determined according to the ratio of the expiratory flow to the inspiratory flow in the respiratory flow data.

[0164] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0165] determining a difference between inspiratory pressure data corresponding to any two breaths during the plurality of breaths;

[0166] Determine the maximum and minimum values ​​from the differences;

[0167] Based on the maximum and minimum values, determine the rate of change of respiratory pressure.

[0168] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0169] Determine the average flow rate of the peak respiratory flow rate of multiple breaths per unit time;

[0170] determining a plurality of differences between a peak respiratory flow rate and an average respiratory flow rate for a plurality of breaths per unit time;

[0171] Based on the plurality of differences and the number of breaths, the peak respiratory rate of change is determined.

[0172] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0173] Obtain initial respiratory status data through the ventilator sensor;

[0174] The initial respiratory state data is subjected to denoising processing to obtain respiratory state data; the denoising processing includes wavelet transform and Butterworth.

[0175] 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 following steps are implemented:

[0176] Obtain the target user's breathing status data;

[0177] Determine respiratory characteristic information based on respiratory status data; respiratory characteristic information includes respiratory peak change rate, respiratory pressure change rate and respiratory flow ratio;

[0178] The hypopnea type of the target user is determined based on the peak respiratory rate of change, respiratory pressure rate of change, and respiratory flow ratio.

[0179] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0180] determining whether a hypopnea event occurs according to the peak respiratory rate of change and a first rate of change threshold;

[0181] When a hypopnea event is determined to have occurred, the hypopnea type of the target user is determined based on the respiratory pressure change rate and the respiratory flow ratio.

[0182] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0183] When the respiratory pressure change rate is less than or equal to the second change rate threshold, and the respiratory flow ratio is less than or equal to the ratio threshold, determining that the hypopnea type is central apnea;

[0184] When the respiratory pressure change rate is less than or equal to the second change rate threshold, and the respiratory flow ratio is greater than the ratio threshold, determining that the hypopnea type is obstructive apnea;

[0185] When the respiratory pressure change rate is greater than the second change rate threshold and the respiratory flow ratio is greater than the ratio threshold, the hypoventilation type is determined to be alveolar hypoventilation.

[0186] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0187] Based on the peak respiratory flow rate, determine the peak respiratory rate of change;

[0188] Determine the respiratory pressure change rate based on the inspiratory pressure data;

[0189] The respiratory flow ratio is determined according to the ratio of the expiratory flow to the inspiratory flow in the respiratory flow data.

[0190] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0191] determining a difference between inspiratory pressure data corresponding to any two breaths during the plurality of breaths;

[0192] Determine the maximum and minimum values ​​from the differences;

[0193] Based on the maximum and minimum values, determine the rate of change of respiratory pressure.

[0194] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0195] Determine the average flow rate of the peak respiratory flow rate of multiple breaths per unit time;

[0196] determining a plurality of differences between a peak respiratory flow rate and an average respiratory flow rate for a plurality of breaths per unit time;

[0197] Based on the plurality of differences and the number of breaths, the peak respiratory rate of change is determined.

[0198] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0199] Obtain initial respiratory status data through the ventilator sensor;

[0200] The initial respiratory state data is subjected to denoising processing to obtain respiratory state data; the denoising processing includes wavelet transform and Butterworth.

[0201] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0202] Obtain the target user's breathing status data;

[0203] Determine respiratory characteristic information based on respiratory status data; respiratory characteristic information includes respiratory peak change rate, respiratory pressure change rate and respiratory flow ratio;

[0204] The hypopnea type of the target user is determined based on the peak respiratory rate of change, respiratory pressure rate of change, and respiratory flow ratio.

[0205] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0206] determining whether a hypopnea event occurs according to the peak respiratory rate of change and a first rate of change threshold;

[0207] When a hypopnea event is determined to have occurred, the hypopnea type of the target user is determined based on the respiratory pressure change rate and the respiratory flow ratio.

[0208] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0209] When the respiratory pressure change rate is less than or equal to the second change rate threshold, and the respiratory flow ratio is less than or equal to the ratio threshold, determining that the hypopnea type is central apnea;

[0210] When the respiratory pressure change rate is less than or equal to the second change rate threshold, and the respiratory flow ratio is greater than the ratio threshold, determining that the hypopnea type is obstructive apnea;

[0211] When the respiratory pressure change rate is greater than the second change rate threshold and the respiratory flow ratio is greater than the ratio threshold, the hypoventilation type is determined to be alveolar hypoventilation.

[0212] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0213] Based on the peak respiratory flow rate, determine the peak respiratory rate of change;

[0214] Determine the respiratory pressure change rate based on the inspiratory pressure data;

[0215] The respiratory flow ratio is determined according to the ratio of the expiratory flow to the inspiratory flow in the respiratory flow data.

[0216] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0217] determining a difference between inspiratory pressure data corresponding to any two breaths during the plurality of breaths;

[0218] Determine the maximum and minimum values ​​from the differences;

[0219] Based on the maximum and minimum values, determine the rate of change of respiratory pressure.

[0220] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0221] Determine the average flow rate of the peak respiratory flow rate of multiple breaths per unit time;

[0222] determining a plurality of differences between a peak respiratory flow rate and an average respiratory flow rate for a plurality of breaths per unit time;

[0223] Based on the plurality of differences and the number of breaths, the peak respiratory rate of change is determined.

[0224] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0225] Obtain initial respiratory status data through the ventilator sensor;

[0226] The initial respiratory state data is subjected to denoising processing to obtain respiratory state data; the denoising processing includes wavelet transform and Butterworth.

[0227] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. 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. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory 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), magnetic 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. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0228] The technical features of the above embodiments can be combined arbitrarily. In order 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 application.

[0229] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for identifying the type of hypopnea, characterized in that: The method comprises: Obtain the target user's breathing status data; Determining respiratory characteristic information based on the respiratory state data; the respiratory characteristic information includes a respiratory peak change rate, a respiratory pressure change rate, and a respiratory flow ratio; The hypopnea type of the target user is determined according to the respiratory peak change rate, the respiratory pressure change rate, and the respiratory flow ratio.

2. The method according to claim 1, characterized in that Determining the type of hypopnea event according to the respiratory peak change rate, the respiratory pressure change rate, and the respiratory flow ratio includes: determining whether a hypopnea event occurs according to the peak respiratory rate of change and a first rate of change threshold; When it is determined that the hypopnea event occurs, the hypopnea type of the target user is determined according to the respiratory pressure change rate and the respiratory flow ratio.

3. The method according to claim 2, characterized in that Determining the hypopnea type of the target user according to the respiratory pressure change rate and the respiratory flow ratio includes: When the respiratory pressure change rate is less than or equal to a second change rate threshold, and the respiratory flow ratio is less than or equal to a ratio threshold, determining that the hypopnea type is central apnea; When the respiratory pressure change rate is less than or equal to a second change rate threshold, and the respiratory flow ratio is greater than a ratio threshold, determining that the hypopnea type is obstructive apnea; When the respiratory pressure change rate is greater than a second change rate threshold, and the respiratory flow ratio is greater than a ratio threshold, it is determined that the hypoventilation type is alveolar hypoventilation.

4. The method according to claim 1, wherein The respiratory state data includes peak respiratory flow rate, inspiratory pressure data, and respiratory flow data of multiple breaths per unit time. Based on the respiratory state data, respiratory characteristic information is determined, including: Determining the peak respiratory rate of change according to the peak respiratory flow rate; determining the respiratory pressure change rate according to the inspiratory pressure data; The respiratory flow ratio is determined according to the ratio of the expiratory flow to the inspiratory flow in the respiratory flow data.

5. The method according to claim 4, characterized in that Determining the respiratory pressure change rate according to the inspiratory pressure data includes: Determining a difference between inspiratory pressure data corresponding to any two breaths in the plurality of breaths; determining a maximum value and a minimum value from the differences; The respiratory pressure change rate is determined according to the maximum value and the minimum value.

6. The method according to claim 4, characterized in that Determining the peak respiratory rate of change according to the peak respiratory flow rate includes: Determining an average flow rate of peak respiratory flow rates of a plurality of breaths within the unit time; determining a plurality of differences between the peak respiratory flow rate and the average flow rate for a plurality of breaths within the unit time; The respiratory peak change rate is determined based on the plurality of differences and the number of the plurality of breaths.

7. The method according to any one of claims 1 to 6, characterized in that The step of obtaining the target user's respiratory status data includes: Obtain initial respiratory status data through the ventilator sensor; The initial respiratory state data is subjected to denoising processing to obtain the respiratory state data; the denoising processing includes wavelet transform and Butterworth.

8. A device for identifying the type of hypopnea, characterized in that: The device comprises: An acquisition module is used to obtain the respiratory status data of the target user; A first determining module is configured to determine respiratory characteristic information based on the respiratory state data; the respiratory characteristic information includes a respiratory peak change rate, a respiratory pressure change rate, and a respiratory flow ratio; The second determining module is configured to determine the hypopnea type of the target user according to the respiratory peak change rate, the respiratory pressure change rate, and the respiratory flow ratio.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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