Vehicle oxygen supply method and vehicle

Abstract

The application provides a vehicle oxygen supply method and a vehicle, and relates to the technical field of oxygen supply. The method comprises the following steps: obtaining target data and original pressure data, wherein the target data comprises vehicle speed data of a vehicle in which a target user is located and / or motion intensity data of the target user, and the original pressure data represents pressure data of a safety belt used by the target user when the target user breathes; correcting the original pressure data based on the target data to obtain target pressure data; determining a breathing frequency of the target user based on the target pressure data; and controlling an oxygen supply device in the vehicle to supply oxygen to the target user based on the breathing frequency. Based on the above scheme, the accuracy of the operating parameter can be improved, and when the oxygen supply device operates with more accurate operating parameters, the demand of the user for oxygen can be met to the greatest extent.

Description

Technical Field

[0001] This application relates to the field of oxygen supply technology, and more particularly to a vehicle oxygen supply method and vehicle in the field of oxygen supply technology. Background Technology

[0002] To prevent oxygen deficiency in vehicles, in-vehicle oxygen generators can be installed to provide oxygen to the in-vehicle environment. When using an in-vehicle oxygen generator, the oxygen supply volume and mode need to be adjusted based on the user's breathing rate.

[0003] If there is a significant deviation in breathing rate, the operating data of the in-vehicle oxygen concentrator (e.g., oxygen supply volume, oxygen supply mode) adjusted according to breathing rate will also be inaccurate. When the in-vehicle oxygen concentrator supplies oxygen to the user based on inaccurate operating data, it may fail to meet the user's oxygen needs, threatening the user's life safety.

[0004] Therefore, improving the accuracy of operational data from vehicle-mounted oxygen concentrators is a pressing issue that needs to be addressed. Summary of the Invention

[0005] This application provides a vehicle oxygen supply method and a vehicle. The method can improve the accuracy of operating parameters, thereby enabling the oxygen supply device to operate with more accurate operating parameters, which can maximize the satisfaction of users' oxygen needs.

[0006] In a first aspect, this application provides a method for supplying oxygen to a vehicle, the method comprising:

[0007] Acquire target data and raw pressure data. The target data includes the vehicle speed data of the vehicle in which the target user is located and / or the exercise intensity data of the target user. The raw pressure data represents the pressure data of the seat belt used by the target user when the target user breathes.

[0008] The original pressure data is corrected based on the target data to obtain the target pressure data;

[0009] Based on the target pressure data, determine the respiratory rate of the target user;

[0010] Based on breathing rate, the oxygen supply device in the vehicle is controlled to supply oxygen to the target user.

[0011] In this embodiment, when collecting the pressure data of the user's seatbelt during breathing (i.e., raw pressure data), the raw pressure data can be corrected first using the vehicle speed data and / or the user's exercise intensity data. Then, the corrected raw pressure data (i.e., target pressure data) is used to determine the user's breathing rate. This determined breathing rate is then used to control the oxygen supply device in the vehicle to provide oxygen to the user. Compared to the prior art, where directly using the collected raw pressure data to determine the user's breathing rate leads to inaccuracies, this embodiment does not directly use the collected raw pressure data. Instead, it first corrects the raw pressure data using vehicle speed data and / or the user's exercise intensity data, making the corrected pressure data more accurate. Using more accurate pressure data allows for a more accurate determination of the user's breathing rate. This more accurate breathing rate improves the accuracy of the operating parameters of the oxygen supply device (i.e., the onboard oxygen generator), enabling the oxygen supply device to operate with more precise parameters and maximizing the fulfillment of the user's oxygen needs.

[0012] In conjunction with the first aspect, in some implementations of the first aspect, the determination of the target user's respiratory rate based on target pressure data includes:

[0013] Determine the peak pressure data corresponding to each adjacent inspiration phase in the target pressure data;

[0014] The time interval between peak pressure data collection points is defined as the initial time difference;

[0015] The initial duration difference can be determined as the initial respiratory cycle, or the initial respiratory cycle can be determined based on the initial duration difference and the individual characteristics of the target user.

[0016] The respiratory rate is determined based on the initial respiratory cycle.

[0017] In this application embodiment, when determining the initial duration difference, two methods for determining the initial respiratory cycle are provided: "determining the initial duration difference as the initial respiratory cycle, or determining the initial respiratory cycle based on the initial duration difference and the individual characteristics of the target user". This avoids the limitation of determining the initial respiratory cycle by a single method, and provides multiple ways to determine the initial respiratory cycle, thereby improving the flexibility of the initial respiratory cycle determination method.

[0018] In conjunction with the first aspect and the above implementation methods, in some implementation methods of the first aspect, the determination of respiratory rate based on the initial respiratory cycle includes:

[0019] Based on the average respiratory cycle corresponding to the sliding window segment where each of the multiple initial respiratory cycles is located and each initial respiratory cycle, determine the first weight of each initial respiratory cycle;

[0020] Each initial respiratory cycle is corrected based on the first weight to obtain the first respiratory cycle corresponding to each initial respiratory cycle;

[0021] The respiratory rate is determined based on the first respiratory cycle.

[0022] In this embodiment, the weights of each initial respiratory cycle within each sliding window segment are dynamically assigned in units of sliding window segments. Compared to uniformly assigning weights to all initial respiratory cycles, this reduces the complexity of weight assignment and improves its efficiency. Furthermore, when some abnormal respiratory cycle data exists, it only adversely affects the weight assignment of the initial respiratory cycles within the sliding window containing the abnormal respiratory cycle data, without affecting the weight assignment of the initial respiratory cycles within the sliding windows containing other normal respiratory cycle data. This allows for precise isolation of abnormal respiratory cycle data and reduces its adverse impact on the overall data, thereby improving the accuracy of data processing and ultimately enhancing the accuracy of the determined user respiratory rate.

[0023] In conjunction with the first aspect and the above implementation methods, in some implementation methods of the first aspect, the determination of respiratory rate based on the first respiratory cycle includes:

[0024] The first respiratory cycle corresponding to the initial respiratory cycle in each sliding window segment where the inspiratory intensity is greater than the inspiratory intensity threshold corresponding to each sliding window segment is determined as the respiratory cycle to be corrected.

[0025] The corrected respiratory cycle is obtained by adjusting the second weight corresponding to the respiratory cycle to be corrected.

[0026] The corrected respiratory cycle to be corrected and the uncorrected respiratory cycle are determined as the second respiratory cycle. The uncorrected respiratory cycle refers to the first respiratory cycle corresponding to the initial respiratory cycle in each sliding window segment where the inspiratory intensity is less than or equal to the inspiratory intensity threshold corresponding to each sliding window segment.

[0027] The respiratory rate is determined based on the second respiratory cycle.

[0028] In this embodiment of the application, in order to avoid deviations in data processing results caused by sudden deep breathing of the user, the initial respiratory cycle with a larger inspiratory intensity in the sliding window segment can be determined by the inspiratory intensity threshold corresponding to the sliding window segment, and the first respiratory cycle corresponding to the initial respiratory cycle with a larger inspiratory intensity is corrected again, so as to reduce the deviations in data processing results caused by sudden deep breathing of the user, thereby improving the accuracy of the determined user respiratory rate.

[0029] In conjunction with the first aspect and the above implementation methods, in some implementation methods of the first aspect, the determination of respiratory rate based on the second respiratory cycle includes:

[0030] Based on the initial duration difference and the individual characteristics of the target user, the initial respiratory cycle is determined, and the second respiratory cycle is determined as the target respiratory cycle.

[0031] With the initial duration difference determined as the initial respiratory cycle, the target respiratory cycle is determined based on the second respiratory cycle.

[0032] Determine the respiratory rate based on the target respiratory cycle.

[0033] In this application embodiment, when determining the target respiratory cycle, two methods for determining the target respiratory cycle are provided, namely, "determining the second respiratory cycle as the target respiratory cycle, or determining the target respiratory cycle based on the second respiratory cycle", which avoids the limitation of determining the target respiratory cycle by a single method, and provides multiple ways to determine the target respiratory cycle, thereby improving the flexibility of the target respiratory cycle determination method.

[0034] In combination with the first aspect and the above implementation methods, in some implementation methods of the first aspect, the determination of the target respiratory cycle based on the second respiratory cycle includes:

[0035] The second respiratory cycle is corrected based on the correction amount corresponding to the individual characteristics of the target user to obtain the third respiratory cycle;

[0036] The target respiratory cycle is determined based on the third respiratory cycle.

[0037] In this embodiment, the respiratory cycle is corrected by adjusting the amount corresponding to the user's individual characteristics, making the corrected respiratory cycle more consistent with the user's individual characteristics and more accurate. Consequently, the user's respiratory rate determined using a more accurate respiratory cycle will also be more accurate.

[0038] Combining the first aspect and the above implementation methods, in some implementation methods of the first aspect, the determination of the target respiratory cycle based on the third respiratory cycle includes:

[0039] The third respiratory cycle is corrected based on the error correction amount corresponding to the target device to obtain the fourth respiratory cycle. Here, the target device refers to the device used to collect raw pressure data.

[0040] The fourth respiratory cycle was determined as the target respiratory cycle.

[0041] In this embodiment, the respiratory cycle is corrected by adjusting the amount corresponding to the device that collects pressure data, making the corrected respiratory cycle more realistic and accurate. Consequently, the user's respiratory rate determined using a more accurate respiratory cycle will also be more accurate.

[0042] Combining the first aspect and the above implementation methods, in some implementation methods of the first aspect, the determination of the initial respiratory cycle based on the initial duration difference and the individual characteristics of the target user includes:

[0043] The initial duration difference is corrected based on the correction amount corresponding to the individual characteristics of the target user to obtain the first duration difference;

[0044] The initial respiratory cycle is determined based on the first time difference.

[0045] In this embodiment, the duration difference is corrected by adjusting the amount corresponding to the user's individual characteristics, making the corrected duration difference more consistent with the user's individual characteristics and more accurate. Consequently, the respiratory cycle determined using a more accurate duration difference will also be more accurate, leading to a more accurate respiratory rate based on a more accurate respiratory cycle.

[0046] Combining the first aspect and the above implementation methods, in some implementation methods of the first aspect, the determination of the initial respiratory cycle based on the first duration difference includes:

[0047] The first time difference is corrected based on the error correction amount corresponding to the target device to obtain the second time difference;

[0048] The second time difference was determined as the initial respiratory cycle.

[0049] In this embodiment, the duration difference is corrected by adjusting the correction amount corresponding to the device that collects pressure data, making the corrected duration difference more realistic and accurate. Consequently, the respiratory cycle determined using a more accurate duration difference will also be more accurate, leading to a more accurate respiratory rate based on a more accurate respiratory cycle.

[0050] Combining the first aspect and the above implementation methods, in some implementation methods of the first aspect, the above-mentioned correction of the original pressure data based on the target data to obtain the target pressure data includes:

[0051] Based on the target data and the interference coefficient corresponding to the target data, the interference pressure data corresponding to the target data is determined in the original pressure data;

[0052] Remove interfering pressure data from the original pressure data to obtain the target pressure data.

[0053] In this embodiment of the application, interfering pressure data corresponding to the target data is removed from the original pressure data, so that the remaining pressure data only contains pressure data caused by the breathing of the target user. This results in cleaner pressure data related to the breathing of the target user, avoiding interference from interfering pressure data on data processing, improving the accuracy of data processing, and thus improving the accuracy of the determined user breathing frequency.

[0054] In combination with the first aspect and the above implementation methods, in some implementation methods of the first aspect, the determination of respiratory rate based on the target respiratory cycle includes:

[0055] Based on the unit duration and the target respiratory cycle, determine the initial respiratory rate corresponding to the target respiratory cycle;

[0056] If the initial respiratory rate is 1, then the initial respiratory rate is defined as the respiratory rate.

[0057] When there are multiple initial respiratory rates, determine the window average value of at least one initial respiratory rate corresponding to each sliding window segment;

[0058] The average value of the window averages is determined as the respiratory rate.

[0059] In this embodiment of the application, when there are multiple respiratory rates, a step-by-step averaging calculation is implemented by using a sliding window segment. That is, the average value of a small range is calculated first, and then a final average value is calculated by using the average values ​​of multiple small ranges. The step-by-step averaging calculation method can reduce the complexity of respiratory rate calculation, enhance the stability of respiratory rate calculation results, and also reduce the amount of data processed in a single respiratory rate calculation, realize block calculation, and improve the calculation efficiency of respiratory rate.

[0060] In conjunction with the first aspect and the above-described implementations, in some implementations of the first aspect, controlling the oxygen supply device in the vehicle to supply oxygen to the target user based on the breathing rate includes:

[0061] Based on the target user's breathing rate, the target oxygen supply mode is determined among multiple oxygen supply modes. Among these multiple oxygen supply modes, the activation time of the oxygen supply device in the vehicle is different for each oxygen supply mode.

[0062] Based on the target oxygen supply mode, control the oxygen supply device to supply oxygen to the target user.

[0063] In this embodiment, when the breathing rate of any user (i.e., the target user) in the vehicle is determined, an oxygen supply mode matching the user's breathing rate (i.e., the target oxygen supply mode) can be selected from multiple oxygen supply modes based on that breathing rate. This oxygen supply mode is then used to control the oxygen supply device to supply oxygen to the user. Compared to the previous method where the user had to manually turn on the oxygen supply device, resulting in low intelligence, this application automatically selects the oxygen supply mode based on the user's breathing rate. It automatically selects the oxygen supply mode that matches the user's breathing rate from multiple oxygen supply modes, using the selected mode to automatically provide the user with maximum oxygen supply. This improves the intelligence of in-vehicle oxygen supply, maximizes the user's oxygen needs, and enhances the timeliness and effectiveness of oxygen inhalation.

[0064] In conjunction with the first aspect, in certain implementations of the first aspect, the above-mentioned determination of the target oxygen supply mode among multiple oxygen supply modes based on the target user's respiratory rate includes:

[0065] If the target user's breathing rate is less than the preset rate, the first oxygen supply mode among multiple oxygen supply modes is determined as the target oxygen supply mode. The first oxygen supply mode means that the oxygen supply device is turned on at the moment when the target user's inhalation is detected.

[0066] If the target user's breathing rate is greater than or equal to the preset rate, the second oxygen supply mode among multiple oxygen supply modes is determined as the target oxygen supply mode. The second oxygen supply mode refers to the oxygen supply mode in which the oxygen supply device is turned on before the target user inhales.

[0067] In this embodiment, the oxygen supply mode that matches the user's breathing rate is automatically selected based on the difference between the user's breathing rate and a preset rate, so as to ensure that the selected oxygen supply mode can meet the user's oxygen demand to the greatest extent, thereby improving the intelligence of in-vehicle oxygen supply and maximizing the satisfaction of the user's oxygen demand.

[0068] Combining the first aspect and the above-described implementation methods, in some implementation methods of the first aspect, the determination of the target oxygen supply mode among multiple oxygen supply modes based on the target user's respiratory rate includes:

[0069] Based on the target user's respiratory rate and current respiratory intensity, the target oxygen supply mode is determined among multiple oxygen supply modes.

[0070] In this embodiment, in addition to the user's breathing rate, the user's current breathing intensity is also considered. By combining the user's breathing rate and current breathing intensity, the target oxygen supply mode is determined from multiple oxygen supply modes. This allows for the automatic selection of an oxygen supply mode that matches both the user's breathing rate and current breathing intensity, making the selected oxygen supply mode more accurate and better meeting the user's oxygen needs. This further improves the intelligence of in-vehicle oxygen supply and maximizes the satisfaction of the user's oxygen requirements.

[0071] Combining the first aspect and the above implementation methods, in some implementation methods of the first aspect, the determination of the target oxygen supply mode among multiple oxygen supply modes based on the target user's respiratory rate and current respiratory intensity includes:

[0072] If the target user's breathing rate is less than the preset rate and the target user's current breathing intensity is less than the preset intensity, the first oxygen supply mode among multiple oxygen supply modes is determined as the target oxygen supply mode. The first oxygen supply mode means that the oxygen supply device is turned on at the moment when the target user's inhalation is detected.

[0073] If the target user's breathing rate is greater than or equal to the preset frequency and the target user's current breathing intensity is greater than or equal to the preset intensity, the second oxygen supply mode among multiple oxygen supply modes is determined as the target oxygen supply mode. The second oxygen supply mode refers to the oxygen supply mode in which the oxygen supply device is turned on before the target user inhales.

[0074] In this embodiment, the oxygen supply mode is automatically selected by combining the difference between the user's breathing rate and the preset frequency, as well as the difference between the user's current breathing intensity and the preset intensity, to ensure that the selected oxygen supply mode can meet the user's oxygen needs to the greatest extent. This further improves the intelligence of in-vehicle oxygen supply and maximizes the satisfaction of the user's oxygen needs.

[0075] In conjunction with the first aspect and the above implementation methods, in some implementations of the first aspect, the method further includes:

[0076] Based on the target user's respiratory rate in the previous moment and the target user's historical respiratory rate, predict when the second oxygen supply mode will be activated in the current moment.

[0077] Among them, historical breathing frequency refers to at least one breathing frequency of the target user before the previous moment of the current moment.

[0078] In this embodiment, since there is the strongest temporal correlation between the user's respiratory rate at the previous moment and the user's respiratory rate at the current moment, and the user's historical respiratory rate can capture the trend of respiratory rate changes over a longer period of time, the user's respiratory rate at the previous moment can be used as the prediction anchor point, and the user's historical respiratory rate can be used as the data basis for mining the pattern of respiratory rate changes to predict the start time of the second oxygen supply mode at the current moment, so that the predicted start time of the second oxygen supply mode at the current moment can be more accurate.

[0079] Combining the first aspect and the above-described implementation methods, in some implementation methods of the first aspect, the determination of the target oxygen supply mode among multiple oxygen supply modes based on the target user's respiratory rate includes:

[0080] The target oxygen supply mode is determined among multiple oxygen supply modes based on the target user's respiratory rate and / or the target user's current respiratory intensity.

[0081] In conjunction with the first aspect and the above-described implementations, in some implementations of the first aspect, the target oxygen supply mode further includes a switching frequency, which is the same as the respiratory rate of the target user. Based on the target oxygen supply mode, controlling the oxygen supply device to supply oxygen to the target user includes:

[0082] When the oxygen supply device is turned on, the switching frequency is used to control the oxygen supply device to supply oxygen to the target user in the target oxygen supply mode.

[0083] In this embodiment, when the oxygen supply device is turned on, the device is controlled to supply oxygen to the user in the selected oxygen supply mode by a switching frequency that is the same as the user's breathing frequency. This ensures that the oxygen supply time of the device can accurately match the user's oxygen demand, avoiding the oxygen demand gap caused by delayed oxygen supply, the problem of insufficient oxygen supply due to too low oxygen supply frequency, and the problem of over-supply due to too high oxygen supply frequency. This further improves the intelligence of in-vehicle oxygen supply and maximizes the satisfaction of the user's oxygen demand.

[0084] In conjunction with the first aspect and the above implementation methods, in some implementations of the first aspect, the method further includes:

[0085] Based on the respiratory rate of the target user, the target oxygen supply capacity of the oxygen supply device is determined, wherein the respiratory rate of the target user is positively correlated with the target oxygen supply capacity;

[0086] The aforementioned oxygen supply control device supplies oxygen to the target user in the target oxygen supply mode, including:

[0087] The oxygen supply device is controlled to supply oxygen to the target user at the target oxygen supply amount in the target oxygen supply mode.

[0088] In this embodiment, in addition to controlling the oxygen supply device to supply oxygen to the user in the selected oxygen supply mode, the oxygen supply amount that matches the user's breathing rate can also be determined. This allows the oxygen supply device to supply oxygen to the user in the selected oxygen supply mode with the determined oxygen supply amount, thus avoiding the problems of insufficient or excessive oxygen supply. This further improves the intelligence of in-vehicle oxygen supply and maximizes the satisfaction of the user's oxygen needs.

[0089] In conjunction with the first aspect and the above implementation methods, in some implementations of the first aspect, the method further includes:

[0090] Obtain the target user's current sitting posture;

[0091] Based on the target user's current sitting posture, the target oxygen supply direction of the oxygen supply device is obtained, where the target oxygen supply direction represents the direction of the target user's face.

[0092] The aforementioned controlled oxygen supply device supplies oxygen to the target user at a target oxygen supply volume in the target oxygen supply mode, including:

[0093] The oxygen supply device is controlled to supply oxygen to the target user in the target oxygen supply mode with the target oxygen supply amount and the target oxygen supply direction.

[0094] In this embodiment, in addition to controlling the oxygen supply device to supply oxygen to the user at the determined oxygen supply amount under the selected oxygen supply mode, the oxygen supply direction that matches the user's current sitting posture can also be determined. This allows the oxygen supply device to supply oxygen to the user at the determined oxygen supply amount and direction under the selected oxygen supply mode, thus avoiding the problem of insufficient oxygen supply caused by the oxygen supply direction not being in the direction of the user's face. This further improves the intelligence of in-vehicle oxygen supply and maximizes the satisfaction of the user's oxygen needs.

[0095] In conjunction with the first aspect and the above implementation methods, in some implementations of the first aspect, the method further includes:

[0096] Based on the respiratory rate of the target user, the target oxygen supply capacity of the oxygen supply device is determined, wherein the respiratory rate of the target user is positively correlated with the target oxygen supply capacity;

[0097] Obtain the target user's current sitting posture;

[0098] Based on the target user's current sitting posture, the target oxygen supply direction of the oxygen supply device is obtained, where the target oxygen supply direction represents the direction of the target user's face.

[0099] The aforementioned oxygen supply control device supplies oxygen to the target user in the target oxygen supply mode, including:

[0100] The oxygen supply device is controlled to supply oxygen to the target user in the target oxygen supply mode with the target oxygen supply amount and / or the target oxygen supply direction.

[0101] Secondly, this application provides a vehicle oxygen supply device, the device comprising:

[0102] The acquisition module is used to acquire target data and raw pressure data. The target data includes the vehicle speed data of the vehicle where the target user is located and / or the exercise intensity data of the target user. The raw pressure data represents the pressure data of the seat belt used by the target user when the target user breathes.

[0103] The processing module is used to correct the original pressure data based on the target data to obtain the target pressure data; based on the target pressure data, determine the respiratory rate of the target user; and based on the respiratory rate, control the oxygen supply device in the vehicle to supply oxygen to the target user.

[0104] Thirdly, this application provides a vehicle including a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, causing the vehicle to perform the methods described in the first aspect or any possible implementation thereof.

[0105] Fourthly, this application provides a computer program product comprising: computer program code, which, when run on a computer, causes the computer to perform the method described in the first aspect or any possible implementation thereof.

[0106] Fifthly, this application provides a computer-readable storage medium storing computer program code that, when executed on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof. Attached Figure Description

[0107] Figure 1 This is a schematic diagram of a vehicle oxygen supply method provided in an embodiment of this application.

[0108] Figure 2 This is a schematic diagram of a seat belt provided in an embodiment of this application.

[0109] Figure 3 This is a schematic diagram of the architecture of a vehicle oxygen supply system provided in an embodiment of this application.

[0110] Figure 4 This is a schematic flowchart of a vehicle oxygen supply method provided in an embodiment of this application.

[0111] Figure 5This is another schematic diagram of a vehicle oxygen supply method provided in the embodiments of this application.

[0112] Figure 6 This is a schematic diagram of the vehicle oxygen supply device provided in the embodiments of this application.

[0113] Figure 7 This is a schematic diagram of the vehicle structure provided in the embodiments of this application. Detailed Implementation

[0114] The technical solutions in this application will be clearly and thoroughly described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in the text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more than two.

[0115] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0116] Figure 1 This is a schematic diagram of a vehicle oxygen supply method provided in an embodiment of this application.

[0117] For example, such as Figure 1 As shown, Figure 1 The system includes a vehicle 101, a seat belt 102, and an onboard oxygen generator 103. Both the seat belt 102 and the onboard oxygen generator 103 are located within the vehicle 101.

[0118] When driving vehicle 101, users can ensure their safety by fastening their seat belts 102. When users need oxygen supply from the onboard oxygen concentrator 103, they can manually turn on the onboard oxygen concentrator 103 to supply oxygen.

[0119] Currently, when providing oxygen to the vehicle via the onboard oxygen concentrator 103, the oxygen supply volume and mode of the onboard oxygen concentrator 103 need to be adjusted based on the user's breathing rate. If... Figure 2When the sensor assembly 104, as shown, collects the force signal from the seatbelt 102 caused by the user's breathing, directly using this force signal to calculate the user's breathing rate may result in significant deviations in the calculated breathing rate due to interference from vehicle speed, user characteristics, and sensor errors. Adjusting the oxygen supply volume and mode of the on-board oxygen concentrator 103 based on this significantly deviated breathing rate will also lead to deviations in the adjusted oxygen supply volume and mode. When the on-board oxygen concentrator 103 supplies oxygen to the user with these deviated oxygen supply volumes and modes, it may fail to meet the user's oxygen needs, threatening the user's life safety.

[0120] In view of this, this application proposes a vehicle oxygen supply method and a vehicle. Through the embodiments of this application, when collecting pressure data of the user's seat belt during breathing, the user's breathing rate is not determined directly from the collected pressure data. Instead, the collected pressure data is first corrected using vehicle speed data and / or user's exercise intensity data to make the corrected pressure data more accurate. Using more accurate pressure data, a more accurate user breathing rate can be determined. By controlling the operating parameters of the oxygen supply device in the vehicle with a more accurate user breathing rate, the accuracy of the operating parameters can be improved. Consequently, when the oxygen supply device operates with more accurate parameters, it can maximize the satisfaction of the user's oxygen needs, thereby improving the timeliness and effectiveness of oxygen inhalation.

[0121] The following is combined Figures 2 to 5 The vehicle oxygen supply method provided in the embodiments of this application will be described in detail.

[0122] Figure 2 This is a schematic diagram of a seat belt provided in an embodiment of this application.

[0123] For example, such as Figure 2 As shown, Figure 2 It includes a seat belt 102 and a sensor assembly 104. The sensor assembly 104 is mounted on the seat belt 102.

[0124] Sensor assembly 104 is used to collect force signals from the seat belt 102 caused by the user's breathing, and convert the collected force signals into corresponding electrical signals. The electrical signal is then subjected to at least one preprocessing step, such as amplification and filtering, by the signal preprocessing unit corresponding to sensor assembly 104 to remove noise signals, resulting in a noise-removed electrical signal. This noise-removed, high-quality electrical signal is then sent to the central control module in the vehicle, whereby the central control module analyzes the breathing frequency corresponding to the force signal.

[0125] The sensor component 104 may represent a sensor component capable of acquiring force signals, such as at least one of a pressure sensor, a strain gauge sensor, or a capacitive sensor.

[0126] For example, the sensor assembly 104 can be installed at any location in the seat belt 102, such as at least one of the shoulder strap portion, lap belt portion, etc., corresponding to the seat belt 102, to detect the force signal of the seat belt 102 caused by the rise and fall of the chest and abdomen when the user breathes.

[0127] By installing a sensor assembly on the seatbelt that collects force signals corresponding to the user's breathing rate, it eliminates the need for users to wear external detection devices to monitor their breathing rate. This reduces interference from external devices, making the sensor assembly more acceptable and less resistant to user feedback, thus improving the user's riding experience. For example, reducing interference from external detection devices on the driver's operations also enhances the driver's driving experience.

[0128] Figure 3 This is a schematic diagram of the architecture of a vehicle oxygen supply system provided in an embodiment of this application.

[0129] For example, such as Figure 3 The vehicle oxygen supply system shown may include a data acquisition module 111, a central control module 112, and an oxygen supply device execution module 113.

[0130] The data acquisition module 111 includes the aforementioned sensor component 104 and a corresponding signal preprocessing unit for the sensor component 104.

[0131] The central control module 112 is the core control part of the vehicle oxygen supply system. It can receive the noise-removed electrical signal sent by the data acquisition module 111 and analyze the user's breathing rate through the noise-removed electrical signal. Then, it sends control commands to the oxygen supply device execution module 113 through the analyzed breathing rate, so as to control the oxygen supply device (i.e., the above-mentioned vehicle oxygen generator 103) to turn on or off, and to control the oxygen supply device's oxygen supply mode to be synchronous oxygen supply mode or predictive oxygen supply mode and the oxygen supply amount of the oxygen supply device through the oxygen supply device execution module 113.

[0132] When the oxygen supply device execution module 113 receives the control command sent by the central control module 112, it can control the oxygen supply device to perform the oxygen supply operation corresponding to the control command, such as turning on the oxygen supply, turning off the oxygen supply, adjusting the oxygen supply amount, switching the oxygen supply mode, or turning off the oxygen supply mode, to ensure the normal operation of the oxygen supply device.

[0133] In the synchronous oxygen supply mode, the switching frequency of the oxygen supply device matches the user's breathing rate. The device activates when the user inhales and deactivates when the user exhales, ensuring real-time synchronization between the device's activation and deactivation to prevent oxygen waste. In the predictive oxygen supply mode, the device activates a certain time before the user inhales to provide pre-inhalation oxygen and deactivates a certain time before exhalation, ensuring timely oxygen delivery and preventing delayed oxygen intake.

[0134] pass Figure 3 The vehicle oxygen supply system shown integrates user breathing rate acquisition and oxygen supply device control within the vehicle, enabling intelligent collaborative work between the data acquisition module 111 and the oxygen supply device execution module 113. This reduces interference within the vehicle oxygen supply system, improving its stability and reliability. Furthermore, it reduces connection and coordination issues between the data acquisition module 111 and the oxygen supply device execution module 113, enhancing the overall integrity of the vehicle oxygen supply system. Moreover, it eliminates the need for additional devices to detect user breathing rate, reducing detection, installation, and maintenance costs. Figure 3 The vehicle oxygen supply system shown can be adapted to different types of cars and oxygen supply devices, has a wide range of applications, and is easier to promote.

[0135] Figure 4 This is a schematic flowchart of a vehicle oxygen supply method provided in an embodiment of this application. The method can be... Figure 1 The vehicle 101 in the vehicle is executed, or the vehicle oxygen supply system in vehicle 101 is executed.

[0136] For example, such as Figure 4 As shown, the method 400 includes the following implementation process:

[0137] S410, acquire target data and raw pressure data.

[0138] The target data includes vehicle speed data of the target user's vehicle and / or the target user's exercise intensity data. The raw pressure data represents the pressure data of the seat belt used by the target user when the target user breathes. The target user refers to any user in the vehicle, such as the driver, front passenger, or rear passenger.

[0139] For example, when a target user is detected in the vehicle, if the target user is found to be wearing a seat belt, the sensor assembly 104 installed on the seat belt can collect multiple force signals (i.e., pressure data) caused by the user's breathing in real time. The force signals directly collected by the sensor assembly 104 without any data processing are called "raw pressure data".

[0140] The vehicle speed data may include at least one of the following: vehicle speed data, vehicle acceleration data, etc. Motion intensity data represents the intensity of different physical activities of the target user. The more intense the physical activity, the greater the motion intensity data. For example, the motion intensity data corresponding to turning the head is greater than that corresponding to raising an arm. Motion intensity data can be determined by the force signal fluctuation collected by the sensor component 104 within a preset time (e.g., 1 second), and the force signal fluctuation is positively correlated with the motion intensity data. Furthermore, vehicle speed data is included in the target data because the vehicle's braking, bumping, acceleration, deceleration, and turning maneuvers can be transmitted to the seatbelt through the vehicle body, causing additional inertial pressure between the seatbelt and the user. This pressure is not due to the user's own actions and will significantly interfere with the seatbelt pressure data, affecting its accuracy. For example, when the vehicle brakes suddenly, the vehicle speed drops sharply, and the user is thrown forward due to inertia, causing the seatbelt to bear additional pressure instantaneously; when the vehicle is traveling at a low and stable speed, there is essentially no additional pressure due to the sudden drop in vehicle speed. The inclusion of motion intensity data in the target data is because users' active physical activities inside the vehicle, such as adjusting their seating posture, raising their arms, turning their heads, and bending over, directly alter the contact state between their body and the seatbelt, causing fluctuations in seatbelt pressure data. This is not due to the additional inertial pressure mentioned above, but rather because these activities significantly interfere with the accuracy of the seatbelt pressure data. Furthermore, higher motion intensity (e.g., vigorous twisting) leads to greater instantaneous fluctuations in seatbelt pressure data; conversely, lower motion intensity (e.g., the user remaining stationary) results in smaller instantaneous fluctuations in seatbelt pressure data.

[0141] S420, based on the target data, corrects the original pressure data to obtain the target pressure data.

[0142] For example, when obtaining target data and raw pressure data, the raw pressure data can be corrected using the target data to obtain corrected raw pressure data (which can be called "target pressure data"). This is because the raw pressure data collected by the sensor component 104 may be affected to varying degrees by vehicle operation states such as braking, bumping, acceleration, deceleration, and turning, and / or user movement states such as raising a hand or swaying the body. Therefore, it is necessary to correct the raw pressure data using the target data to obtain target pressure data after removing interference. This ensures that the target pressure data only contains pressure data caused by the target user's breathing and does not contain pressure data caused by vehicle speed, target user movement, etc., thus improving the accuracy of the target pressure data. As a result, the target pressure data can more accurately reflect the target user's breathing changes.

[0143] When correcting the original pressure data using the target data, the interference coefficient corresponding to the target data can be determined first. Then, the interference pressure data corresponding to the target data can be determined in the original pressure data using the target data and the interference coefficient corresponding to the target data. This interference pressure data can then be removed from the original pressure data, and the remaining original pressure data can be determined as the target pressure data.

[0144] For example, if the original pressure data is 10N and the interference pressure data corresponding to the target data is 0.5N, the 0.5N is removed from the 10N, and the remaining 9.5N is determined as the target pressure data.

[0145] Optionally, when there is only one target data point, the product of the single target data point and its corresponding interference coefficient can be used to determine the interference pressure data. Alternatively, when there are multiple target data points, the product of each target data point and its corresponding interference coefficient can be determined first, and the sum of these multiple products can be used to determine the interference pressure data.

[0146] Optionally, when the target data is vehicle speed data, the corresponding interference coefficient is a speed interference coefficient; for example, when the vehicle speed data is vehicle acceleration data, the corresponding interference coefficient is an acceleration interference coefficient. And / or, when the target data is motion intensity data, the corresponding interference coefficient is a body activity interference coefficient. That is, there is a correspondence between the target data and the interference coefficient corresponding to the target data.

[0147] In this embodiment of the application, interfering pressure data corresponding to the target data is removed from the original pressure data, so that the remaining pressure data only contains pressure data caused by the breathing of the target user. This results in cleaner pressure data related to the breathing of the target user, avoiding interference from interfering pressure data on data processing, improving the accuracy of data processing, and thus improving the accuracy of the determined user breathing frequency.

[0148] S430 determines the respiratory rate of the target user based on target pressure data.

[0149] For example, when the target pressure data is obtained, the respiratory rate of the target user can be determined using the target pressure data.

[0150] The S440 controls the oxygen supply system in the vehicle to supply oxygen to the target user based on breathing rate.

[0151] For example, when the respiratory rate of the target user is obtained, the respiratory rate of the target user can be used to control the operating parameters of the oxygen supply device in the vehicle (e.g., the on-board oxygen generator 103 mentioned above) to supply oxygen to the target user.

[0152] In such Figure 4 In method 400, when collecting pressure data (i.e., raw pressure data) of the user's seatbelt during breathing, the raw pressure data can be corrected using vehicle speed data and / or the user's exercise intensity data. Then, the corrected raw pressure data (i.e., target pressure data) is used to determine the user's breathing rate. The determined breathing rate is then used to control the oxygen supply device in the vehicle to provide oxygen to the user. Compared to existing technologies where directly using the collected raw pressure data to determine the user's breathing rate leads to inaccuracies, this embodiment does not directly use the collected raw pressure data. Instead, it first corrects the raw pressure data using vehicle speed data and / or the user's exercise intensity data, making the corrected pressure data more accurate. Using more accurate pressure data allows for a more accurate determination of the user's breathing rate. This more accurate breathing rate improves the accuracy of the operating parameters of the oxygen supply device, enabling the device to operate with more precise parameters and maximize the user's oxygen needs.

[0153] It should be noted that S410 to S440 above are a simplified description of the vehicle oxygen supply method provided in the embodiments of this application. The following will further elaborate on... Figure 4 The specific implementation methods shown in the embodiments are described in detail below:

[0154] When executing S430, when determining the respiratory rate of the target user through the target pressure data, multiple raw inspiratory pressure data are collected for each inspiratory phase of the target user. After the multiple raw inspiratory pressure data are corrected by the target data, the corrected raw inspiratory pressure data will become part of the target pressure data. Therefore, multiple pressure data (i.e., the corrected raw inspiratory pressure data) corresponding to each inspiratory phase of the target user can be determined from the target pressure data.

[0155] Adjacent inhalation phases are selected from multiple inhalation phases, and multiple pressure data points corresponding to each adjacent inhalation phase are determined from the target pressure data. For example, the first inhalation phase corresponds to 3 pressure data points, and the second inhalation phase corresponds to 5 pressure data points. Then, the maximum pressure data point (which can be called the "peak pressure data point") is determined from the multiple pressure data points corresponding to each adjacent inhalation phase. For example, the peak pressure data point E is the peak pressure data point E of the 3 pressure data points corresponding to the first inhalation phase, and F is the peak pressure data point F of the 5 pressure data points corresponding to the second inhalation phase. It should be understood that if a certain inhalation phase has only one pressure data point, then that single pressure data point is determined as the peak pressure data point corresponding to that inhalation phase.

[0156] When determining the peak pressure data corresponding to each adjacent inspiratory phase, the acquisition time of each of the two peak pressure data points corresponding to the adjacent inspiratory phases can be obtained, and the time interval between the acquisition times of the two peak pressure data points can be determined as the initial duration difference. Specifically, the time difference between the acquisition time of one peak pressure data point and the acquisition time of the other peak pressure data point is calculated, and this time difference is determined as the initial duration difference. For example, the difference between the acquisition time of pressure data F and the acquisition time of pressure data E can be determined as the initial duration difference.

[0157] When the initial duration difference is obtained, it can be directly determined as the target user's initial respiratory cycle; alternatively, instead of directly determining the initial duration difference as the target user's initial respiratory cycle, the individual characteristics of the target user are first obtained, and then the initial respiratory cycle is determined by comparing the initial duration difference with the target user's individual characteristics. This allows for the initial duration difference to be corrected using the target user's individual characteristics, resulting in a more accurate corrected initial duration difference, which is then used as the target user's initial respiratory cycle. The individual characteristics include at least one of the target user's body type, breathing habits, age, and emotional characteristics.

[0158] When obtaining the initial respiratory cycle of a target user by "determining the initial duration difference as the initial respiratory cycle, or by determining the initial respiratory cycle based on the initial duration difference and the individual characteristics of the target user", the respiratory rate of the target user can be determined through the initial respiratory cycle.

[0159] In this application embodiment, when determining the initial duration difference, two methods for determining the initial respiratory cycle are provided: "determining the initial duration difference as the initial respiratory cycle, or determining the initial respiratory cycle based on the initial duration difference and the individual characteristics of the target user". This avoids the limitation of determining the initial respiratory cycle by a single method, and provides multiple ways to determine the initial respiratory cycle, thereby improving the flexibility of the initial respiratory cycle determination method.

[0160] When determining the respiratory rate of a target user through the initial respiratory cycle, at least one sliding window segment can be obtained by sliding the sliding window data through multiple initial respiratory cycles, and each sliding window segment includes at least one initial respiratory cycle, that is, each initial respiratory cycle is within the sliding window segment.

[0161] In this process, multiple initial respiratory cycles are arranged in chronological order from early to late to avoid sorting disorder, so that the resulting sliding window segment has the following timestamps: the timestamps of the initial respiratory cycles included in the previous sliding window segment are all earlier than the timestamps of the initial respiratory cycles included in the next sliding window segment, and the timestamps of the previous initial respiratory cycles included in the same sliding window segment are earlier than the timestamps of the next initial respiratory cycles.

[0162] The sliding window data includes the sliding window size and the sliding step size, with the window size being the same as the sliding step size. This is because, to avoid errors caused by multiple optimization corrections of the same initial respiratory cycle, the preset sliding step size can be set to the same step size as the sliding window size. For example, if the sliding window size is 5, the corresponding preset sliding step size is also 5, ensuring that the same initial respiratory cycle appears only in one sliding window segment, rather than in multiple sliding window segments, thus achieving optimization correction only once for the same initial respiratory cycle. Furthermore, the sliding window size can be determined by the total number of multiple initial respiratory cycles, and the window size that can evenly divide multiple initial respiratory cycles is determined as the final sliding window size. If no window size can evenly divide multiple initial respiratory cycles, the window size with the smallest remainder can be determined as the final sliding window size, and the remainder is allocated to the last sliding window segment. For ease of explanation, this application embodiment uses an example that can be evenly divided into multiple initial respiratory cycles.

[0163] For example, the initial respiratory cycles are a, b, c, d, e, f, the sliding window size is 3, and the sliding step size is 3. By sliding the sliding window of size 3 through a, b, c, d, e, f with a sliding step size of 3, the first sliding window segment and the second sliding window segment are obtained. The first sliding window segment includes the initial respiratory cycles a, b, c, and the second sliding window segment includes the initial respiratory cycles d, e, f.

[0164] Furthermore, when dividing the sliding window segments, the sliding window segments containing each of the multiple initial respiratory cycles can be determined, and the average value of all initial respiratory cycles included in each sliding window segment (which can be called the "average respiratory cycle") can be determined. By comparing the average respiratory cycle of each sliding window segment with the individual initial respiratory cycles included in each sliding window segment, the first weight corresponding to each initial respiratory cycle in each sliding window segment can be determined. The first weight corresponding to each initial respiratory cycle is used to correct for each initial respiratory cycle. It should be understood that the first weight corresponding to each initial respiratory cycle is calculated using the sliding window segment as the unit of calculation.

[0165] For example, if the first sliding window segment includes all initial respiratory cycles a, b, and c, calculate the average of a, b, and c included in the first sliding window segment. Then, determine the first weight corresponding to a, the first weight corresponding to b, and the first weight corresponding to c using the average of a, b, and c and their corresponding values. If the second sliding window segment includes all initial respiratory cycles d, e, and f, calculate the average of d, e, and f included in the second sliding window segment. Then, determine the first weight corresponding to d, the first weight corresponding to e, and the first weight corresponding to f using the average of d, e, and f and their corresponding values.

[0166] Upon obtaining the first weight corresponding to each initial respiratory cycle, the initial respiratory cycles can be corrected using these first weights to obtain corrected initial respiratory cycles (which can be referred to as "first respiratory cycles"). Then, the target user's respiratory rate is determined using the first respiratory cycles corresponding to each initial respiratory cycle. Specifically, the first respiratory cycle corresponding to each initial respiratory cycle is determined by multiplying the first weight corresponding to each initial respiratory cycle by the initial respiratory cycle itself.

[0167] In this embodiment, the weights of each initial respiratory cycle within each sliding window segment are dynamically assigned in units of sliding window segments. Compared to uniformly assigning weights to all initial respiratory cycles, this reduces the complexity of weight assignment and improves its efficiency. Furthermore, when some abnormal respiratory cycle data exists, it only adversely affects the weight assignment of the initial respiratory cycles within the sliding window containing the abnormal respiratory cycle data, without affecting the weight assignment of the initial respiratory cycles within the sliding windows containing other normal respiratory cycle data. This allows for precise isolation of abnormal respiratory cycle data and reduces its adverse impact on the overall data, thereby improving the accuracy of data processing and ultimately enhancing the accuracy of the determined user respiratory rate.

[0168] When determining the respiratory rate of a target user through the first respiratory cycle, all pressure data corresponding to two consecutive inhalations of the target user can be identified in the target pressure data, and the average value of all pressure data corresponding to two consecutive inhalations can be calculated (which can be called "average pressure data"). This average pressure data is then determined as the inspiratory intensity of the initial respiratory cycle corresponding to the consecutive inhalations.

[0169] When the inspiratory intensity corresponding to each initial respiratory cycle within each sliding window segment is obtained, the inspiratory intensity threshold for each sliding window segment can be determined using the inspiratory intensity corresponding to each initial respiratory cycle within that segment. The relationship between the inspiratory intensity threshold and the inspiratory intensity corresponding to each initial respiratory cycle within that segment is then determined. Based on this relationship, the first respiratory cycle requiring correction (referred to as the "respiratory cycle to be corrected") and the first respiratory cycle not requiring correction (referred to as the "respiratory cycle not to be corrected") are identified.

[0170] The initial respiratory cycles included in each sliding window segment are identified as having an inspiratory intensity greater than the inspiratory intensity threshold corresponding to each sliding window segment. Additionally, the initial respiratory cycles included in each sliding window segment are identified as having an inspiratory intensity less than or equal to the inspiratory intensity threshold corresponding to each sliding window segment.

[0171] Within each sliding window segment, the first respiratory cycle corresponding to the initial respiratory cycle with an inspiratory intensity greater than the inspiratory intensity threshold corresponding to that sliding window segment is identified as the respiratory cycle to be corrected. Conversely, the first respiratory cycle corresponding to the initial respiratory cycle with an inspiratory intensity less than or equal to the inspiratory intensity threshold corresponding to that sliding window segment is identified as the respiratory cycle not to be corrected. In other words, a respiratory cycle not to be corrected represents the first respiratory cycle corresponding to the initial respiratory cycle with an inspiratory intensity less than or equal to the inspiratory intensity threshold corresponding to that sliding window segment, while a respiratory cycle to be corrected represents the first respiratory cycle corresponding to the initial respiratory cycle with an inspiratory intensity greater than the inspiratory intensity threshold corresponding to that sliding window segment.

[0172] Once the respiratory cycles to be corrected are determined, a second weight corresponding to each cycle can be determined. This second weight is used to correct each respiratory cycle. It should be understood that the second weight is calculated using a sliding window segment as the unit of calculation.

[0173] Upon obtaining the second weight corresponding to each respiratory cycle to be corrected, the respiratory cycles to be corrected can be adjusted using these second weights to obtain corrected respiratory cycles. Both the corrected and uncorrected respiratory cycles are then designated as second respiratory cycles. The target user's respiratory rate is then determined using the second respiratory cycles corresponding to each initial respiratory cycle. Specifically, the product of the second weight corresponding to each respiratory cycle to be corrected and the original respiratory cycle is used to determine the corrected respiratory cycles to be corrected.

[0174] In this embodiment of the application, in order to avoid deviations in data processing results caused by sudden deep breathing of the user, the initial respiratory cycle with a larger inspiratory intensity in the sliding window segment can be determined by the inspiratory intensity threshold corresponding to the sliding window segment, and the first respiratory cycle corresponding to the initial respiratory cycle with a larger inspiratory intensity is corrected again, so as to reduce the deviations in data processing results caused by sudden deep breathing of the user, thereby improving the accuracy of the determined user respiratory rate.

[0175] In the above-mentioned "determining the initial respiratory cycle based on the initial duration difference and the individual characteristics of the target user", the second respiratory cycle can be directly determined as the target respiratory cycle. However, in the above-mentioned "determining the initial duration difference as the initial respiratory cycle", the second respiratory cycle is not directly determined as the target respiratory cycle. Instead, the individual characteristics of the target user are first obtained to correct the second respiratory cycle based on the individual characteristics of the target user, resulting in a more accurate corrected second respiratory cycle. The corrected second respiratory cycle is then determined as the target respiratory cycle.

[0176] When the target respiratory cycle is obtained by "determining the second respiratory cycle as the target respiratory cycle, or determining the target respiratory cycle based on the second respiratory cycle", the respiratory rate of the target user can be determined through the target respiratory cycle.

[0177] In this application embodiment, when determining the target respiratory cycle, two methods for determining the target respiratory cycle are provided, namely, "determining the second respiratory cycle as the target respiratory cycle, or determining the target respiratory cycle based on the second respiratory cycle", which avoids the limitation of determining the target respiratory cycle by a single method, and provides multiple ways to determine the target respiratory cycle, thereby improving the flexibility of the target respiratory cycle determination method.

[0178] When determining the target respiratory cycle using the second respiratory cycle, the individual characteristics of the target user can be obtained first. Based on the second respiratory cycle and combined with the individual characteristics of the target user, each second respiratory cycle is modified to obtain the modified second respiratory cycle (which can be called the "third respiratory cycle"). The target respiratory cycle is then determined using the third respiratory cycle.

[0179] Specifically, the correction amount corresponding to the individual characteristics of the target user is first determined, and then the second respiratory cycle is corrected using the correction amount corresponding to the individual characteristics to obtain the third respiratory cycle. The product of the correction amount corresponding to the individual characteristics and the second respiratory cycle is determined as the third respiratory cycle.

[0180] In this embodiment, the respiratory cycle is corrected by adjusting the amount corresponding to the user's individual characteristics, making the corrected respiratory cycle more consistent with the user's individual characteristics and more accurate. Consequently, the user's respiratory rate determined using a more accurate respiratory cycle will also be more accurate.

[0181] When determining the target respiratory cycle using the third respiratory cycle, the error correction amount corresponding to the device used to collect the raw pressure data (which can be called the "target device") can be determined first. Based on the third respiratory cycle and combined with the error correction amount, each third respiratory cycle is corrected using the error correction amount to obtain the corrected third respiratory cycle (which can be called the "fourth respiratory cycle"). The fourth respiratory cycle is then determined as the target respiratory cycle. Specifically, the difference between the third respiratory cycle and the error correction amount is determined as the target respiratory cycle.

[0182] Optionally, when obtaining the correction amount and error correction amount corresponding to the individual characteristics, the second respiratory cycle after correction by the correction amount or error correction amount corresponding to the individual characteristics can be determined as the target respiratory cycle.

[0183] In this embodiment, the respiratory cycle is corrected by adjusting the amount corresponding to the device that collects pressure data, making the corrected respiratory cycle more realistic and accurate. Consequently, the user's respiratory rate determined using a more accurate respiratory cycle will also be more accurate.

[0184] In the above process of "determining the initial respiratory cycle based on the initial duration difference and the individual characteristics of the target user", the individual characteristics of the target user can be obtained first. Based on the initial duration difference, the individual characteristics of the target user can be combined to correct each initial duration difference, resulting in a corrected initial duration difference (which can be called the "first duration difference"). The initial respiratory cycle is then determined using the first duration difference.

[0185] Specifically, the correction amount corresponding to the individual characteristics of the target user is first determined, and then the initial duration difference is corrected using the correction amount corresponding to the individual characteristics to obtain the first duration difference. The product of the correction amount corresponding to the individual characteristics and the initial duration difference is determined as the first duration difference.

[0186] In this embodiment, the duration difference is corrected by adjusting the amount corresponding to the user's individual characteristics, making the corrected duration difference more consistent with the user's individual characteristics and more accurate. Consequently, the respiratory cycle determined using a more accurate duration difference will also be more accurate, leading to a more accurate respiratory rate based on a more accurate respiratory cycle.

[0187] When determining the initial respiratory cycle using the first time difference, the error correction amount corresponding to the device used to collect the raw pressure data (which can be called the "target device") can be determined first. Based on the first time difference and combined with the error correction amount, each first time difference is corrected using the error correction amount to obtain the corrected first time difference (which can be called the "second time difference"). The second time difference is then determined as the initial respiratory cycle. Specifically, the difference between the second time difference and the error correction amount is determined as the initial respiratory cycle.

[0188] Optionally, when obtaining the correction amount and error correction amount corresponding to the individual characteristics, the initial duration difference after correction by the correction amount or error correction amount corresponding to the individual characteristics can also be determined as the initial respiratory cycle.

[0189] In this embodiment, the duration difference is corrected by adjusting the correction amount corresponding to the device that collects pressure data, making the corrected duration difference more realistic and accurate. Consequently, the respiratory cycle determined using a more accurate duration difference will also be more accurate, leading to a more accurate respiratory rate based on a more accurate respiratory cycle.

[0190] When determining the respiratory rate of a target user through the target respiratory cycle, the initial respiratory rate corresponding to each target respiratory cycle can be determined first by using the unit duration and each target respiratory cycle. Among them, one initial respiratory rate corresponds to one target respiratory cycle, and the unit duration can be 1 second, 1 minute (min), 1 hour (h), etc., which are not limited in this application embodiment.

[0191] When the initial respiratory rate is obtained, it can be determined whether there are multiple initial respiratory rates. If there is only one initial respiratory rate, this single initial respiratory rate can be directly determined as the target user's respiratory rate. If there are multiple initial respiratory rates, the average value of at least one initial respiratory rate corresponding to each sliding window segment (which can be called the "window average value") can be determined. Then, a second average calculation is performed on this window average value to obtain the average of the window average values, and this average of the window average values ​​is then determined as the target user's respiratory rate. It should be understood that the window average value is calculated using the sliding window segment as the unit of calculation.

[0192] In this embodiment of the application, when there are multiple respiratory rates, a step-by-step averaging calculation is implemented by using a sliding window segment. That is, the average value of a small range is calculated first, and then a final average value is calculated by using the average values ​​of multiple small ranges. The step-by-step averaging calculation method can reduce the complexity of respiratory rate calculation, enhance the stability of respiratory rate calculation results, and also reduce the amount of data processed in a single respiratory rate calculation, realize block calculation, and improve the calculation efficiency of respiratory rate.

[0193] It should be noted that, Figure 4 All steps are in Figure 5 The corresponding embodiments are described in detail, and will not be repeated here.

[0194] Figure 5 This is another schematic diagram of a vehicle oxygen supply method provided in the embodiments of this application.

[0195] For example, such as Figure 5 As shown, the method 500 includes the following implementation process:

[0196] S1 collects the raw pressure data of the user's seat belt in real time when it detects that the user is wearing a seat belt.

[0197] For example, when a user (i.e., the target user mentioned above) is detected in the vehicle, in order to detect the user's breathing rate, it is possible to detect in real time whether the user is properly fastened with a seat belt.

[0198] When the user is detected to have fastened the seat belt, the sensor assembly 104 installed on the seat belt can collect multiple raw pressure data of the seat belt caused by the user's breathing in real time.

[0199] Optionally, the seatbelt is equipped with a buckle switch detection device, which uses a microswitch inside the buckle to determine whether the bolt is inserted. When the bolt is fully inserted, the switch closes, indicating that the user has properly fastened the seatbelt; when the bolt is not fully inserted, the switch does not close, indicating that the user has not properly fastened the seatbelt.

[0200] Optionally, the vehicle is equipped with a camera that can capture the user's current image in real time and analyze the captured image to determine whether the user has fastened their seatbelt.

[0201] S2, determine the original actual force value corresponding to the original pressure data.

[0202] For example, when acquiring multiple raw pressure data points from the seatbelt, each raw pressure data point can first be converted into a corresponding digital quantity. Then, a pressure-force conversion model can be used to convert each digital quantity into a corresponding raw actual force value, completing the processing flow from signal acquisition to digital processing and then to physical quantity restoration. This is because the raw pressure data is output by the sensor component 104, relies on hardware circuitry, and is an analog electrical signal that cannot be directly calculated and is difficult to understand. By converting the raw pressure data into digital quantities, the raw pressure data is processed into a recognizable data format that can be directly calculated and understood, and the data's anti-interference capability is improved. Converting the digital quantity into an actual force value yields a physical quantity that humans can understand and use to judge the user's breathing pressure (i.e., breathing depth), thus obtaining a physically meaningful physical quantity. For example, if the raw pressure data is A Pascals, A Pascals can be converted into a digital quantity A1, and then digital quantity A1 can be converted into a force value signal A2 Newtons (N).

[0203]

[0204] In formula (1), D( t) This represents the digital quantity corresponding to the raw pressure data, where t represents the acquisition time of the raw pressure data, and p... t p represents the raw pressure data. min p represents the minimum pressure threshold (i.e., the lower limit of pressure data) that sensor assembly 104 can detect. max This indicates the maximum pressure threshold signal (i.e., the upper limit of pressure data) that the sensor assembly 104 can detect; N represents the quantization bits, a positive integer, which is the number of digital bits converted by the sensor assembly 104 and determines the accuracy of signal quantization; 2 N This represents the total number of levels of the quantized digital signal. Where p... min With p max These are factory parameters belonging to sensor assembly 104, for example, the p of sensor assembly 104. min =0 kPa, p of sensor assembly 104 max It can be set according to the stress scenario of the seat belt, for example, p max=50kPa, which can cover pressure data fluctuations caused by user breathing, for example, 0.5kPa-10kPa; N is a hardware parameter of sensor component 104, for example, N=12, the corresponding quantization range is 0-4095, or N=16, the corresponding quantization range is 0-65535.

[0205] F(t) = K × D( t) +b (2)

[0206] In formula (2), F(t) represents the original actual force value corresponding to the digital quantity of the original pressure data, K represents the force value scaling factor, and D(t) represents the force value scaling factor. t) The linear proportional relationship between D and F(t); b represents the force offset used to eliminate the zero drift error of sensor assembly 104, and when D( t) When K is 0, b is F(t). K and b can be obtained through sample test calibration. K can be obtained by linear fitting of pressure applied to sensor assembly 104 by standard brick weights (e.g., 1 kg - 5 kg), and b can be obtained by calibration when sensor assembly 104 is not under force. This application embodiment does not limit this.

[0207] S3 filters the original actual force value to obtain the filtered actual force value.

[0208] For example, when obtaining the original actual force value, the original actual force value can be filtered to obtain the filtered actual force value (which can be denoted as "S"). f (t)”).

[0209] Optionally, when filtering the original actual force value, at least one of the following can be used: Butterworth filter, Chebyshev filter, elliptic filter, Bessel filter, Wiener filter, and Kalman filter. For ease of understanding, this application uses the Butterworth filter as an example to illustrate the filtering of the original actual force value. The Butterworth filter is a commonly used linear filter with a flat frequency response within its passband. It can be used to filter high-frequency and low-frequency interference signals in the original actual force value, making the filtered actual force value more accurate.

[0210]

[0211] In formula (3), H(s) represents the transfer function of the Butterworth filter in the complex frequency domain, and V represents the ratio of the output signal to the input signal in the complex frequency domain, used to describe the filter's processing characteristics for signals of different frequencies; s represents the complex frequency variable, used to transform the "time-domain signal" into the "frequency-domain signal", solving the limitations of time-domain signal analysis, so as to more efficiently analyze the frequency components in the actual force value; c The cutoff angular frequency (VC) defines the passband and stopband ranges of the filter. When the actual force value frequency V is less than VC, it can pass through the filter relatively smoothly (passband). When the actual force value frequency V is greater than VC, it will be gradually attenuated by the filter (stopband). n represents the order of the Butterworth filter, a positive integer, and n is positively correlated with the filtering performance of the Butterworth filter. It should be understood that a filter generally corresponds to only one SC at any given time. f (t); or, when there are m filters, there will be their respective corresponding S at the same time. f1 (t), S f2 (t)……S fm (t), and S f1 (t), S f2 (t)……S fm The mean of (t) is determined as the final S. f (t).

[0212] Furthermore, since the filtered actual force value may be affected by vehicle operating conditions such as braking, bumps, acceleration, deceleration, and turning, as well as user movement such as raising hands and swaying the body, in order to improve the accuracy of the final result, it is necessary to remove the interference caused by vehicle operating conditions and user movement from the filtered actual force value. This ensures that the filtered actual force value after removing interference only contains pressure data caused by user breathing, and does not contain pressure data caused by vehicle speed, target user movement, etc., so that the filtered actual force value after removing interference can more accurately reflect the user's breathing changes.

[0213] Specifically, when removing interference from vehicle operating state and user motion state in the filtered actual force value, the interference force value corresponding to vehicle operating state and user motion state can be calculated first. The sum of the interference force value corresponding to vehicle operating state and user motion state is determined as the total interference amount to be removed from the filtered actual force value. The difference between the filtered actual force value and the total interference amount is determined as the filtered actual force value after removing interference (which can be called the "processed filtered actual force value").

[0214] For example, when determining the disturbance force value corresponding to the vehicle's operating state, the vehicle's current acceleration and the corresponding acceleration disturbance coefficient can be obtained, and the disturbance force value corresponding to the vehicle's operating state can be determined using the current acceleration and the corresponding acceleration disturbance coefficient. Specifically, the product of the current acceleration and the corresponding acceleration disturbance coefficient can be determined as the disturbance force value corresponding to the vehicle's operating state.

[0215] For example, when determining the interference force value corresponding to a user's movement state, the user's current physical activity intensity and the corresponding physical activity interference coefficient can be obtained, and the interference force value corresponding to the user's movement state can be determined by the current physical activity intensity and the corresponding physical activity interference coefficient. Specifically, the product of the current physical activity intensity and the corresponding physical activity interference coefficient can be determined as the interference force value corresponding to the user's movement state.

[0216] D(V(t))=θ×a(t)+μ×g(t) (4)

[0217] In formula (4), D(V(t)) represents the total interference that needs to be removed from the filtered actual force value, and θ represents the acceleration interference coefficient. θ can be used to quantify the degree of interference between the vehicle's current acceleration and the seat belt force. When multiple accelerations of the vehicle are collected through the vehicle's CAN (Controller Area Network) bus, the relationship between acceleration and seat belt force can be fitted by multiple accelerations within a preset acceleration range to obtain the value of θ. For example, θ = 0.2 N·s 2 / m, where the preset acceleration range can be 0m / s². 2 -10m / s 2 -5m / s 2 -0m / s 2 At least one of the following. μ represents the body activity interference coefficient, which can be used to quantify the degree of interference between body activity intensity and seat belt force. The relationship between body activity intensity and seat belt force can be fitted using different body activity intensities (e.g., adjusting sitting posture, raising an arm, turning the head, etc.) to obtain the value of μ. For example, μ = 0.3 N. μ corresponds to g(t), and the body activity corresponding to g(t) can be obtained through real-time analysis of user images captured by cameras in the vehicle. a(t) represents the vehicle's current acceleration at time t, which can be obtained through the Electronic Stability Program (ESP) or an onboard acceleration sensor, with units of m / s². 2(m / s²). g(t) represents the user's current physical activity intensity at time t. g(t) is positively correlated with physical activity intensity and can be determined by the change in the force signal collected by sensor component 104. For example, if the force signal collected by sensor component 104 fluctuates significantly within 1 second, greater than 5N, then the corresponding physical activity intensity is high, for example, g(t) = 2; or, if the force signal collected by sensor component 104 fluctuates moderately within 1 second, between 2N and 5N, then the corresponding physical activity intensity is low, for example, g(t) = 1; or, if the force signal collected by sensor component 104 fluctuates slightly within 1 second (s), less than 2N, then the corresponding physical activity intensity is low, for example, g(t) = 0.

[0218] S c (t)=S f (t)-D(V(t)) (5)

[0219] In formula (5), S c (t) represents S f (t) corresponds to the processed and filtered actual force value (i.e., the target pressure data mentioned above).

[0220] For example, at time t, θ = 0.2 and a(t) = 1 m / s 2 μ = 0.3, g(t) = 2, S f (t) = 5.

[0221] First calculate D(V(t)):

[0222] D(V(t)) = 0.2 × 1 + 0.3 × 2 = 0.8, which represents the total disturbance corresponding to the vehicle's operating state and the user's motion state at time t.

[0223] Calculate S again c (t):

[0224] S c (t) = 5 - 0.8 = 4.2, which represents the actual force value after filtering at time t.

[0225] S4 identifies the filtered actual force value after processing to obtain the initial respiratory cycle.

[0226] For example, because the user uses a relatively large force when inhaling, the force signal will have a spike. Therefore, when obtaining the processed and filtered actual force value, peak detection can be performed on the processed and filtered actual force value to obtain the signal peak value corresponding to the user's inhalation (i.e., the peak data mentioned above). When obtaining the signal peak values ​​corresponding to the user's adjacent inhalations (i.e., the peak pressure data mentioned above), the time difference between the acquisition times of these two adjacent signal peaks (i.e., the initial duration difference mentioned above) can be calculated, and this duration difference can be determined as the user's adjacent breathing interval (i.e., the initial respiratory cycle mentioned above).

[0227] For example, if the signal peak corresponding to the user's first inhalation is collected at 10:00:00 and the signal peak corresponding to the user's second inhalation is collected at 10:00:02, then the adjacent breathing interval between the user's first and second inhalations is 00:00:02.

[0228] It should be understood that the respiratory cycle is a prerequisite for calculating a user's respiratory rate; the respiratory cycle must be obtained before the respiratory rate can be calculated. The respiratory cycle represents the duration of each breath a user takes, while the respiratory rate represents the number of breaths a user takes per unit of time (e.g., per minute). There is an inverse relationship between the respiratory cycle and the respiratory rate. For example, if the unit duration is 60 seconds and the respiratory cycle is 2 seconds, then the corresponding respiratory rate is... Breathing rate / minute. To improve the accuracy of the calculated respiratory rate, the initial respiratory cycle is optimized in the following manner in the embodiments of this application.

[0229] S5, using the weighted average method to correct the initial respiratory cycle, yields the first respiratory cycle.

[0230] For example, when the initial respiratory cycle is obtained, it can be optimized and corrected by the sliding window dynamic weighted averaging method to obtain the corrected initial respiratory cycle (which can be called the "first respiratory cycle").

[0231] When optimizing and correcting the initial respiratory cycle using the sliding window dynamic weighted averaging method, the size of the sliding window can be determined first, and then the sliding window can be slid across multiple initial respiratory cycles with a preset sliding step size to obtain at least one sliding window segment, each of which includes at least one initial respiratory cycle.

[0232] When at least one sliding window segment is obtained, the average value of all initial respiratory cycles included in each sliding window segment can be determined.

[0233]

[0234] In formula (6), Let represent the average of all initial respiratory cycles included in the j-th sliding window segment (i.e., the average respiratory cycle mentioned above), where j represents the nth sliding window segment, k represents the sliding window size, (j-1)×k+1 represents the first initial respiratory cycle included in the j-th sliding window segment, for example, the first initial respiratory cycle included in the second sliding window segment is d; j×k represents the last initial respiratory cycle included in the j-th sliding window segment, for example, the last initial respiratory cycle included in the second sliding window segment is f; T0(j) represents any initial respiratory cycle included in the j-th sliding window segment.

[0235] When obtaining the average value of all initial respiratory cycles included in each sliding window segment, the absolute deviation between each initial respiratory cycle in each sliding window segment and the average value can be determined by the average value. For example, if the average value of d, e, and f included in the second sliding window segment is A, then the absolute deviation of each of d, e, and f included in the second sliding window segment from A can be calculated.

[0236]

[0237] In formula (7), ΔT j This represents the absolute deviation between each initial respiratory cycle and the average value in the j-th sliding window segment.

[0238] When the absolute deviation between each initial respiratory cycle and the average value in each sliding window segment is obtained, the weight corresponding to each initial respiratory cycle in each sliding window segment can be obtained through this absolute deviation.

[0239]

[0240] In formula (8), w j Let w represent the weights corresponding to each initial respiratory cycle in the j-th sliding window segment (i.e., the first weights mentioned above), and α represent the weight sensitivity coefficient. j With ΔT j Negative correlation, ΔT j The smaller the value, the smaller the difference between the initial respiratory cycle and the average value, indicating greater stability; the corresponding w j The closer to 1; ΔT j The larger the value, the greater the difference between the initial respiratory cycle and the average value, indicating poorer stability; the corresponding w... jThe closer to 0, the better. α is used to control the influence of initial respiratory cycle fluctuations on the weights within the sliding window segment. The larger α is, the faster the weights of the fluctuating data decay. It can be calibrated through sample experiments. For example, collect multiple sets of different initial respiratory cycles, test the effect of α on the smoothing effect within the test range (e.g., 0.5-2.0), and select the α with the smallest smoothed cycle error (e.g., 1.0).

[0241] Optionally, the α and w values ​​vary depending on the user's breathing state. j Different. When the user's breathing is relatively stable, the fluctuation of the initial respiratory cycle is generally small; for example, α is less than or equal to 0.2s, corresponding to w j The initial respiratory cycle fluctuates significantly when the user's breathing is unstable; for example, α is 0.3s-0.5s, corresponding to w. j The initial respiratory cycle fluctuation is 0.6-0.8; when the user's breathing is abnormal (e.g., physical activity disturbance), the initial respiratory cycle fluctuates more significantly, for example, α is greater than or equal to 0.5s, corresponding to w j It is 0-0.6.

[0242] When calculating the weights corresponding to each initial respiratory cycle in each sliding window segment, the weights corresponding to each initial respiratory cycle in each sliding window segment can be used to assign weights to the corresponding initial respiratory cycles to calculate the first respiratory cycle. That is, each initial respiratory cycle has a corresponding first respiratory cycle. Specifically, the product of the first weight corresponding to each initial respiratory cycle and the first initial respiratory cycle is determined as the first respiratory cycle corresponding to each initial respiratory cycle.

[0243] T1(j)=w j ×T0(j) (9)

[0244] In formula (9), T1(j) represents the first respiratory cycle corresponding to each initial respiratory cycle in the j-th sliding window segment.

[0245] For example, with a sliding window size of k = 5 and α = 1.0, the initial respiratory cycles included in the j-th sliding window segment are: 2.0s, 2.1s, 1.9s, 2.5s, and 2.0s.

[0246] First calculate

[0247] This indicates that the average value of all initial respiratory cycles in the j-th sliding window segment is 2.1s.

[0248] Calculate ΔT again j :

[0249] ΔT j1=|2.0-2.1|=0.1s, indicating that the absolute deviation corresponding to the first initial respiratory cycle in the j-th sliding window segment is 0.1s;

[0250] ΔT j2 =|2.1-2.1|=0.0s, indicating that the absolute deviation corresponding to the second initial respiratory cycle in the j-th sliding window segment is 0.0s;

[0251] ΔT j3 =|1.9-2.1|=0.2s, indicating that the absolute deviation corresponding to the third initial respiratory cycle in the j-th sliding window segment is 0.2s;

[0252] ΔT j4 =|2.5-2.1|=0.4s, which means that the absolute deviation corresponding to the 4th initial respiratory cycle in the j-th sliding window segment is 0.4s;

[0253] ΔT j5 =|2.0-2.1|=0.1s, which means that the absolute deviation corresponding to the last initial breathing cycle in the j-th sliding window segment is 0.1s.

[0254] Calculate w again j :

[0255] w j1 =e -1.0×0.1 ≈0.905, indicating that the weight corresponding to the first initial respiratory cycle in the j-th sliding window segment is 0.905;

[0256] w i2 =e -1.0×0.0 =1, indicating that the weight corresponding to the second initial respiratory cycle in the j-th sliding window segment is 1, meaning that the weight of the second initial respiratory cycle is related to... The one with the smallest absolute deviation has the largest corresponding weight;

[0257] w j3 =e -1.0×0.2 ≈0.819, indicating that the weight corresponding to the 3rd initial respiratory cycle in the j-th sliding window segment is 0.819;

[0258] w j4 =e -1.0×0.4 ≈0.670, indicating that the weight corresponding to the 4th initial respiratory cycle in the j-th sliding window segment is 0.670, meaning that the 4th initial respiratory cycle is related to... The absolute deviation is the largest, and the corresponding weight is the smallest.

[0259] w j5 =e -1.0×0.1≈0.905, indicating that the weight corresponding to the last initial breathing cycle in the j-th sliding window segment is 0.905.

[0260] Then calculate T1(j):

[0261] T1(j1)=w j1 ×T0(j1)=0.905×2.0=1.81s, which means that the first respiratory cycle corresponding to the first initial respiratory cycle in the j-th sliding window segment is 1.81s;

[0262] T1(j2)=w j2 ×T0(j2)=1×2.1=2.1s, indicating that the first respiratory cycle corresponding to the second initial respiratory cycle in the j-th sliding window segment is 2.1s;

[0263] T1(j3)=w j3 ×T0(j3)=0.819×1.9=1.5561s, which means that the first respiratory cycle corresponding to the third initial respiratory cycle in the j-th sliding window segment is 1.5561s;

[0264] T1(j4)=w j4 ×T0(j4)=0.670×2.5=1.675s, which means that the first respiratory cycle corresponding to the fourth initial respiratory cycle in the j-th sliding window segment is 1.675s;

[0265] T1(j5)=w j5 ×T0(j5)=0.905×2.0=1.81s, which means that the first respiratory cycle corresponding to the last initial respiratory cycle in the j-th sliding window segment is 1.81s.

[0266] S6, the first respiratory cycle is corrected by the inspiratory intensity and inspiratory intensity slope to obtain the second respiratory cycle.

[0267] For example, when obtaining the first respiratory cycle corresponding to each initial respiratory cycle in each sliding window segment, the inspiratory intensity corresponding to each initial respiratory cycle in each sliding window segment can be determined by the two processed and filtered actual force values ​​corresponding to each initial respiratory cycle in each sliding window segment (i.e., all pressure data corresponding to two adjacent inspiratory breaths mentioned above). Specifically, the average value of the two processed and filtered actual force values ​​corresponding to each initial respiratory cycle (i.e., the average pressure data mentioned above) is determined as the inspiratory intensity corresponding to each initial respiratory cycle, that is, each initial respiratory cycle has its own corresponding inspiratory intensity (also referred to as "inspiratory depth").

[0268] For example, if the filtered actual force value after processing is 6N during the user's first inhalation and the filtered actual force value after processing is 10N during the user's second inhalation in the first sliding window segment, then the inspiratory intensity corresponding to the initial respiratory cycle for the user's first and second inhalations is:

[0269] However, since sudden deep breathing can cause deviations in the final results, it is necessary to correct the first respiratory cycle corresponding to larger inspiratory intensities, while keeping the first respiratory cycle corresponding to smaller inspiratory intensities unchanged. This reduces the interference of extreme large values ​​on the final results and more realistically reflects the user's inspiratory state (also known as the "rising edge of the respiratory signal") using most conventional data, thereby improving the accuracy of the final results. Specifically, an inspiratory intensity threshold for judging the magnitude of inspiratory intensity can be determined by the inspiratory intensity and inspiratory intensity slope corresponding to each initial respiratory cycle in each sliding window segment. This inspiratory intensity threshold is then used to determine the inspiratory intensity corresponding to the first respiratory cycle that needs correction within each initial respiratory cycle in each sliding window segment. A corresponding correction weight is then determined, and the first respiratory cycle requiring correction is corrected using this weight to obtain the corrected first respiratory cycle. Calculating the inspiratory intensity threshold by fusing the inspiratory intensity and inspiratory intensity slope dual features can improve the accuracy of the inspiratory intensity threshold and avoid misjudgments due to a single parameter.

[0270] A th (j)=β×A max (j)+(1-β)×k slope (j) (10)

[0271] In formula (10), A th (j) represents the inspiratory intensity threshold corresponding to the j-th sliding window segment (i.e., the inspiratory intensity threshold corresponding to each of the above sliding window segments), A max (j) represents the maximum inspiratory intensity among the inspiratory intensities corresponding to each initial respiratory cycle in the j-th sliding window segment, k slope (j) represents the average slope of the inspiratory intensity change slope (which can be called "inspiratory intensity slope") corresponding to each initial respiratory cycle in the j-th sliding window segment; β represents the threshold weighting coefficient, β∈[0,1], used to balance the inspiratory intensity (which can be called "inspiratory signal amplitude") and the inspiratory intensity slope (which can also be called "inspiratory signal slope") in the dynamic threshold A. th The proportion of (j) in A, β relative to A thThe stronger the influence of (j), the more likely β can be obtained through sample experiment calibration. The distribution of inhalation intensity and inhalation intensity slope corresponding to different inhalation signals (e.g., deep inhalation signal, shallow inhalation signal) is statistically analyzed, and β is adjusted to minimize the misjudgment rate of inhalation intensity. For example, when β is 0.6, the corresponding inhalation intensity amplitude accounts for 60%, and the inhalation intensity slope accounts for 40%, resulting in the lowest misjudgment rate of inhalation intensity.

[0272] In calculating A th When (j), first calculate the average slope of the inspiratory intensity corresponding to each initial respiratory cycle in each sliding window segment.

[0273]

[0274] In formula (11), k slope(i) (j) represents the inspiratory intensity slope corresponding to the i-th initial respiratory cycle in the j-th sliding window segment, ΔA i (j) represents the change in inspiratory intensity corresponding to the i-th initial respiratory cycle in the j-th sliding window segment, Δt i (j) represents the inspiratory duration corresponding to the i-th initial respiratory cycle in the j-th sliding window segment.

[0275]

[0276] The k obtained from formula (12) slope (j) Substituting into formula (10) yields the inhalation intensity threshold corresponding to each sliding window segment.

[0277] Furthermore, the relationship between the inspiratory intensity corresponding to each initial respiratory cycle within each sliding window segment and the inspiratory intensity threshold corresponding to each sliding window segment is determined. Based on this relationship, the inspiratory intensity corresponding to the first expiratory cycle that requires correction is determined. Specifically, the first respiratory cycle corresponding to the inspiratory intensity greater than the inspiratory intensity threshold of each initial respiratory cycle within each sliding window segment is identified as the first expiratory cycle requiring correction, while the first respiratory cycle corresponding to the inspiratory intensity less than or equal to the inspiratory intensity threshold of each initial respiratory cycle within each sliding window segment is identified as the first expiratory cycle that does not require correction. The "first expiratory cycle requiring correction" can be referred to as the "respiratory cycle to be corrected."

[0278] Once the respiratory cycle to be corrected is determined, the correction weight for each initial respiratory cycle needs to be determined using the inspiratory intensity and inspiratory intensity slope. This correction weight is then used to correct the respiratory cycle, resulting in the corrected first respiratory cycle. Calculating the correction weight using a dual-feature fusion method of inspiratory intensity and inspiratory intensity slope improves the accuracy of the correction weight and avoids biases caused by a single parameter. Furthermore, the correction weight for respiratory cycles not to be corrected is directly set to 1, ensuring it remains unchanged.

[0279]

[0280] In formula (13), w(A) i (j)) represents the correction weight (i.e., the second weight mentioned above) corresponding to the respiratory cycle to be corrected in the j-th sliding window segment, A i (j) represents the i-th initial respiratory cycle in the j-th sliding window segment, k slope(max) (j) represents the maximum slope of the change in inspiratory intensity for each initial respiratory cycle in the j-th sliding window segment.

[0281] When the correction weight corresponding to the respiratory cycle to be corrected is obtained, the respiratory cycle to be corrected can be processed using the correction weight to obtain the corrected first respiratory cycle. The corrected first respiratory cycle and the first respiratory cycle that does not need to be corrected (i.e., the non-corrected respiratory cycle) are determined as the second respiratory cycle. Specifically, the product of the correction weight and the respiratory cycle to be corrected is determined as the corresponding second respiratory cycle.

[0282] T2(j)=w(A i (j))×T1(j) (14)

[0283] In formula (14), T2(j) represents the second respiratory cycle corresponding to each initial respiratory cycle in the j-th sliding window segment.

[0284] For example, with β = 0.6, the inspiratory intensities corresponding to each initial respiratory cycle in the j-th sliding window segment are: 7N, 9N, 8N, 10N, 8N, and the inspiratory intensity slopes are 3.5N / s, 4.8N / s, 4.0N / s, 5.2N / s, and 4.1N / s.

[0285] First calculate A max (j), k slope (j):

[0286] A max (j) = max(7,9,8,10,8) = 10N, indicating that the maximum inspiratory intensity in each initial respiratory cycle in the j-th sliding window segment is 10N.

[0287] The average slope of the inspiratory intensity slope corresponding to each initial respiratory cycle in the j-th sliding window segment is 4.32 N / s;

[0288] Calculate A again th (j):

[0289] A th (j)=0.6×10+(1-0.6)×4.32=7.7N, which means that the inhalation intensity threshold corresponding to the j-th sliding window segment is 7.7N.

[0290] Next, determine the magnitudes of 7N, 9N, 8N, 10N, and 8N relative to 7.7N to identify the respiratory cycle to be corrected.

[0291] When 7N is less than 7.7N, it means that the first respiratory cycle corresponding to 7N is normal data and does not need to be processed. Therefore, the first respiratory cycle corresponding to 7N can be determined as a non-corrected respiratory cycle.

[0292] When 9N, 8N, 10N, and 8N are all greater than 7.7N, it indicates that 9N, 8N, 10N, and 8N are too large and belong to abnormal data. The first respiratory cycle corresponding to each of 9N, 8N, 10N, and 8N needs to be processed. Therefore, the first respiratory cycle corresponding to each of 9N, 8N, 10N, and 8N can be identified as the respiratory cycle to be corrected.

[0293] Calculate k again slope(max) (j):

[0294] k slope(max) (j) = max(3.5,4.8,4.0,5.2,4.1) = 5.2N / s, which means that the maximum slope of the change in the initial respiratory cycle in the j-th sliding window segment is 5.2N / s.

[0295] Then calculate w(A) i (j)):

[0296] This indicates that the correction weight corresponding to the second initial respiratory cycle in the j-th sliding window segment is 0.75;

[0297] This indicates that the corrected weight corresponding to the 3rd initial respiratory cycle in the j-th sliding window segment is 0.66;

[0298] This indicates that the corrected weight corresponding to the 4th initial respiratory cycle in the j-th sliding window segment is 0.83;

[0299] This indicates that the corrected weight corresponding to the 5th initial respiratory cycle in the j-th sliding window segment is 0.66.

[0300] Then calculate T2(j):

[0301] T2(j1)=w(A1(j))×T1(j1)=1×1.81=1.81s, which means that the second respiratory cycle corresponding to the first initial respiratory cycle in the j-th sliding window segment is 1.81s;

[0302] T2(j2)=w(A2(j))×T1(j2)=0.75×2.1=1.575s, which means that the second respiratory cycle corresponding to the second initial respiratory cycle in the j-th sliding window segment is 1.575s;

[0303] T2(j3)=w(A3(j))×T1(j3)=0.66×1.5561≈1.027s, which means that the second respiratory cycle corresponding to the third initial respiratory cycle in the j-th sliding window segment is 1.027s;

[0304] T2(j4)=w(A4(j))×T1(j4)=0.83×1.675≈1.39s, which means that the second respiratory cycle corresponding to the fourth initial respiratory cycle in the j-th sliding window segment is 1.39s;

[0305] T2(j5)=w(A5(j))×T1(j5)=0.66×1.81≈1.195s, which means that the second respiratory cycle corresponding to the last initial respiratory cycle in the j-th sliding window segment is 1.195s.

[0306] S7 modifies the second respiratory cycle based on individual characteristics to obtain the third respiratory cycle.

[0307] For example, the respiratory cycle is also affected by individual differences; different individual characteristics have different effects on the respiratory cycle. Therefore, in order to make the final result more consistent with the user's individual characteristics, the second respiratory cycle can be modified based on individual characteristics to obtain a modified second respiratory cycle (which can be called the "third respiratory cycle"). Individual characteristics may include at least one of the following: body shape characteristics, breathing habits, age, resting heart rate, and emotional characteristics. For ease of understanding, this application embodiment uses body shape characteristics and breathing habits as examples.

[0308] Upon obtaining the user's body shape and breathing habits, these features can be input into a trained feature model. The trained model then outputs correction parameters corresponding to the user's individual characteristics (i.e., the correction amounts for the aforementioned individual characteristics). These correction parameters are then used to correct the second breathing cycle, resulting in the third breathing cycle. Specifically, the product of the correction parameters and the second breathing cycle is used to determine the third breathing cycle. The trained feature model is used to obtain the correction parameters corresponding to the user's individual characteristics.

[0309] k ind =1+γ×(B-B0)+δ×(H-H0) (15)

[0310] In formula (15), k indThe parameters represent correction parameters corresponding to individual user characteristics. γ represents the correction parameter corresponding to body shape characteristics, used to quantify the influence of body shape characteristics on the respiratory cycle. The value of γ can be obtained by fitting the relationship between body shape characteristics and respiratory cycle using different collected body shape characteristics (e.g., height 150cm-190cm, weight 40kg-100kg), for example, γ = 0.02. δ represents the correction parameter corresponding to breathing habit characteristics, used to quantify the influence of breathing habits on the respiratory cycle. The value of δ can be obtained by fitting the relationship between breathing habits and respiratory cycle using different collected breathing habits (e.g., chest breathing, abdominal breathing, chest breathing and abdominal breathing), for example, δ = 0.015. B0 represents the standard body shape parameter corresponding to body shape characteristics, used to compare individual body shape deviations. For example, the average body shape ratio according to ergonomic standards is B0 = 2.3. H0 represents the standard breathing habit parameter corresponding to breathing habit characteristics. Generally, most people's breathing habit is a mixed breathing method combining chest and abdominal breathing, therefore H0 = 3 is set. B represents the individual body shape parameter corresponding to the body shape characteristics, which is related to the user's height and weight. The ratio of height to weight is determined as B. For example, the B value for a height of 175cm and a weight of 70kg is 175 / 70 = 2.5. H represents the individual breathing habit parameter corresponding to the breathing habit characteristics. After the user fastens the seat belt and breathes naturally for a period of time (e.g., 30 seconds), the signal fluctuations collected by the sensor component 104 at the shoulder strap and the sensor component 104 at the lap belt can be used to determine the user's breathing mode. When the signal fluctuations collected by the sensor component 104 at the shoulder strap are large, it can be determined that the user's breathing mode is thoracic breathing, for example, H=1 for thoracic breathing; when the signal fluctuations collected by the sensor component 104 at the lap belt are large, it can be determined that the user's breathing mode is abdominal breathing, for example, H=2 for abdominal breathing; when the signal fluctuations collected by the sensor component 104 at both the shoulder strap and the lap belt are large, it can be determined that the user's breathing mode is a mixed breathing mode combining thoracic and abdominal breathing, for example, H=3 for mixed breathing.

[0311] T3(j)=k ind ×T2(j) (16)

[0312] In formula (16), T3(j) represents the third respiratory cycle corresponding to each initial respiratory cycle in the j-th sliding window segment.

[0313] S8 corrects the third respiratory cycle based on equipment error to obtain the fourth respiratory cycle.

[0314] For example, the respiratory cycle can also be affected by device errors, with different sensor components 104 (i.e., the target device) having different effects on the respiratory cycle. Therefore, to make the final result more accurate, the third respiratory cycle can be corrected by the device error to obtain the corrected third respiratory cycle (i.e., the aforementioned fourth respiratory cycle). The device error can include at least one of the following: errors caused by the cumulative duration of device use, environmental errors, and acquisition errors. For ease of understanding, this application embodiment uses the error caused by the cumulative duration of device use as an example.

[0315] When the cumulative usage time of the device is obtained, it can be input into a trained error model to output a correction parameter (i.e., the aforementioned error correction amount) corresponding to the cumulative usage time. This correction parameter is then used to correct the third respiratory cycle, resulting in the fourth respiratory cycle. Specifically, the difference between the third respiratory cycle and the correction parameter corresponding to the cumulative usage time is determined as the fourth respiratory cycle. The trained error model is used to obtain the correction parameter corresponding to the cumulative usage time of the device.

[0316] E( T) =E0×e -λT +ε(T) (17)

[0317] In formula (17), E( T) The parameters represent the correction parameters corresponding to the cumulative usage time of the equipment, where T represents the cumulative usage time and E0 represents the initial error of the equipment. λ represents the error decay coefficient of the equipment, which is the rate at which the equipment error decays with usage time. λ is positively correlated with the equipment error decay and can be obtained through aging tests. For example, by continuously testing the equipment for 1000 hours and recording the error values ​​corresponding to different usage times, an exponential decay curve can be fitted to obtain the value of λ. For example, λ = 0.001 / h. ε(T) represents the random error corresponding to the random fluctuations of the equipment caused by temperature and electromagnetic interference. It can follow a normal distribution and can be obtained by collecting the signal fluctuations of the equipment when the seat belt is not under stress. For example, ε(T) = 3σ, where σ represents the standard random error of the equipment.

[0318] T4(j)=T3(j)-E( T) (18)

[0319] In formula (18), T4(j) represents the fourth respiratory cycle corresponding to each initial respiratory cycle in the j-th sliding window segment.

[0320] S9 determines the user's breathing rate through the fourth breathing cycle.

[0321] For example, when the fourth respiratory cycle is obtained, the user's respiratory rate can be determined by the number of fourth respiratory cycles (i.e., the target respiratory cycle mentioned above). It is then determined whether the number of fourth respiratory cycles is one.

[0322] When there is one fourth respiratory cycle, the respiratory rate corresponding to that fourth respiratory cycle can be determined as the user's respiratory rate. That is...

[0323] When there are multiple fourth respiratory cycles, the average value of these multiple fourth respiratory cycles can be calculated first, and the respiratory rate corresponding to this average value can be determined as the user's respiratory rate. That is...

[0324] Alternatively, when there are multiple fourth respiratory cycles, first calculate the average of the fourth respiratory cycles corresponding to each sliding window segment. Then, perform a second average calculation on the average of the fourth respiratory cycles corresponding to each sliding window segment to obtain the second average respiratory cycle, which is the average of the average of the fourth respiratory cycles corresponding to each sliding window segment again. The respiratory rate corresponding to the second average respiratory cycle is then determined as the user's respiratory rate. By first calculating the average value of the fourth respiratory cycle corresponding to each sliding window segment, and then averaging the average values ​​of the fourth respiratory cycle corresponding to each sliding window segment again, the essence is to calculate a small-range average value, and then calculate a final average value by averaging multiple small-range average values. This step-by-step averaging method can reduce the complexity of respiratory rate calculation, enhance the stability of respiratory rate calculation results, and reduce the amount of data processed in a single respiratory rate calculation, thereby achieving block calculation and improving the efficiency of respiratory rate calculation.

[0325] Alternatively, when there are multiple fourth respiratory cycles, first calculate the respiratory rate corresponding to each fourth respiratory cycle, then calculate the average of the multiple respiratory rates, and determine the average of the multiple respiratory rates as the user's respiratory rate.

[0326] Alternatively, when there are multiple fourth respiratory cycles, first calculate the respiratory frequency corresponding to the fourth respiratory cycle in each sliding window segment (i.e., the initial respiratory frequency mentioned above), then calculate the average respiratory frequency corresponding to the fourth respiratory cycle in each sliding window segment (i.e., the window average mentioned above), and then perform a second average calculation on the average respiratory frequency corresponding to the fourth respiratory cycle in each sliding window segment to obtain the second average respiratory frequency, which is the respiratory frequency obtained by averaging the average respiratory frequency corresponding to the fourth respiratory cycle in each sliding window segment again (i.e., the average of the window averages mentioned above). The second average respiratory frequency is then determined as the user's respiratory frequency.

[0327] Optionally, when obtaining the initial duration difference, it is not directly determined as the initial respiratory cycle. Instead, considering the influence of individual differences on the duration difference, it is first determined through individual characteristics (e.g., k). ind The initial time difference is then corrected to obtain the corrected initial time difference (i.e., the first time difference mentioned above). Specifically, k... ind The product of the product with the initial duration difference is determined as the first duration difference.

[0328] Furthermore, considering the impact of equipment error on the time difference, this can be addressed through equipment error (e.g., E( T) The first time difference is corrected to obtain the corrected first time difference (i.e., the second time difference mentioned above). Specifically, the first time difference is compared with E( T) The difference is determined as the second duration difference.

[0329] Furthermore, upon obtaining the second time difference, this second time difference is determined as the user's initial respiratory cycle. Then, steps S5 through S9 are executed.

[0330] S10 controls the oxygen supply device in the vehicle to supply oxygen to the user based on the user's breathing rate.

[0331] In one implementation, when the oxygen supply device in the vehicle is controlled to supply oxygen to the user based on the target user's breathing frequency, the oxygen supply mode corresponding to the target user's breathing frequency (which can be called the "target oxygen supply mode") can be determined from the multiple oxygen supply modes that the oxygen supply device in the vehicle can operate based on the target user's breathing frequency, so as to realize flexible switching of oxygen supply mode and improve the timeliness and accuracy of oxygen supply.

[0332] For example, when determining the target oxygen supply mode among multiple oxygen supply modes, the target oxygen supply mode can be determined by the target user's respiratory rate and / or the target user's current respiratory intensity among multiple oxygen supply modes.

[0333] Optionally, when determining the target oxygen supply mode among multiple oxygen supply modes, it can be first determined whether the target user's breathing rate is less than the preset rate.

[0334] When the target user's breathing rate is lower than the preset rate, it means that the target user's breathing rate is not too fast, the breathing is relatively slow, and the demand for oxygen is not urgent. Normal oxygen supply to the target user is sufficient. Therefore, the first oxygen supply mode among multiple oxygen supply modes can be determined as the target oxygen supply mode.

[0335] When the target user's breathing rate is greater than or equal to a preset rate, the second oxygen supply mode among multiple oxygen supply modes can be selected as the target oxygen supply mode. This is because, since the target user generally does not engage in strenuous activity in the vehicle, an excessively rapid breathing rate is likely due to physical discomfort, i.e., a pathological rapid breathing rate. A rapid breathing rate is a manifestation of oxygen deficiency, requiring timely oxygen replenishment through various oxygen supply modes. Therefore, when the target user's breathing rate is greater than or equal to the preset rate, the second oxygen supply mode can be selected as the target oxygen supply mode. By automatically selecting the oxygen supply mode that matches the user's breathing rate based on the relationship between the user's breathing rate and the preset rate, the system ensures that the selected oxygen supply mode maximally meets the user's oxygen needs, improving the intelligence of in-vehicle oxygen supply and maximizing the satisfaction of the user's oxygen requirements.

[0336] Among them, the first oxygen supply mode (i.e. the above-mentioned synchronous oxygen supply mode) means that the oxygen supply device is turned on at the moment when the target user inhales; the second oxygen supply mode (i.e. the above-mentioned predictive oxygen supply mode) means that the oxygen supply device is turned on before the moment when the target user inhales.

[0337] The preset frequency can be represented as the highest safe breathing frequency of the target user when the target user is receiving normal oxygen supply. It can be obtained through calibration, and this application embodiment does not limit it.

[0338] Optionally, when determining the target oxygen supply mode among multiple oxygen supply modes, the current breathing intensity of the target user can also be obtained.

[0339] When the current breathing intensity of the target user is obtained, the target oxygen supply mode can be determined from multiple oxygen supply modes by combining the user's breathing rate and current breathing intensity. This automatic selection of the oxygen supply mode that matches both the user's breathing rate and current breathing intensity results in a more accurate selection that better meets the user's oxygen needs, further enhancing the intelligence of in-vehicle oxygen supply and maximizing the satisfaction of the user's oxygen requirements.

[0340] Furthermore, when determining the target oxygen supply mode among multiple oxygen supply modes by using the target user's breathing rate and current breathing intensity, it is possible to first determine whether the target user's breathing rate is less than a preset frequency, and whether the target user's current breathing intensity is less than a preset intensity.

[0341] When the target user's respiratory rate is lower than a preset rate and their current respiratory intensity is lower than a preset intensity, the first oxygen supply mode among multiple oxygen supply modes can be designated as the target oxygen supply mode. This is because a respiratory rate lower than the preset rate indicates that the target user's breathing is not too rapid and is relatively gentle; and a respiratory intensity lower than the preset intensity indicates that the target user's oxygen demand has not increased but is at a normal level, and the need for oxygen is not urgent. Therefore, when both the target user's respiratory rate and respiratory intensity are lower than the preset rate, the first oxygen supply mode can be designated as the target oxygen supply mode.

[0342] When the target user's breathing rate is greater than or equal to the preset rate, and their current breathing intensity is greater than or equal to the preset intensity, it indicates rapid breathing. Therefore, the second oxygen supply mode among multiple oxygen supply modes can be designated as the target oxygen supply mode. This is because, since the target user generally does not engage in strenuous activity in the vehicle, an excessively rapid breathing rate is likely due to physical discomfort, i.e., pathological rapid breathing, which is a manifestation of oxygen deficiency and requires timely oxygen replenishment through the oxygen supply mode. Furthermore, when the target user's current breathing intensity is greater than or equal to the preset intensity, it indicates an increased oxygen demand and faster oxygen consumption. If oxygen supply is not timely, the target user's oxygen reserves will be rapidly depleted, threatening their life. Therefore, when the target user's current breathing intensity is greater than or equal to the preset intensity, their oxygen demand is urgent, requiring more timely oxygen replenishment through the oxygen supply mode; thus, the second oxygen supply mode can be designated as the target oxygen supply mode. By combining the differences between the user's breathing rate and the preset rate, as well as the differences between the user's current breathing intensity and the preset intensity, the system automatically selects an oxygen supply mode that matches both the user's breathing rate and current breathing intensity. This ensures that the selected oxygen supply mode can meet the user's oxygen needs to the greatest extent, further improving the intelligence of in-vehicle oxygen supply and maximizing the satisfaction of the user's oxygen requirements.

[0343] The preset intensity can be represented as the highest safe intensity of the target user's breathing when the target user is receiving normal oxygen supply. It can be obtained through calibration, and this application embodiment does not limit this.

[0344] Optionally, when the target user's current breathing intensity is greater than or equal to the preset intensity, the second oxygen supply mode can also be determined as the target oxygen supply mode.

[0345] For example, upon obtaining a target oxygen supply mode, the oxygen supply device can be controlled to supply oxygen to the target user through this target oxygen supply mode (e.g., the first oxygen supply mode or the second oxygen supply mode). Compared to the previous method where the user had to manually turn on the oxygen supply device to supply oxygen to themselves, which resulted in low intelligence in oxygen supply, this application can automatically select the oxygen supply mode based on the user's breathing rate. It can automatically determine the oxygen supply mode that matches the user's breathing rate from multiple oxygen supply modes, and use the selected oxygen supply mode to automatically provide the user with the maximum amount of oxygen, thereby improving the intelligence of in-vehicle oxygen supply, maximizing the satisfaction of the user's oxygen needs, and improving the timeliness and effectiveness of oxygen inhalation.

[0346] When controlling the oxygen supply device to supply oxygen to a target user through a target oxygen supply mode, the switching frequencies included in the target oxygen supply mode can be determined first. The switching frequencies included in the target oxygen supply mode are the same as the target user's breathing frequency.

[0347] When the switching frequencies included in the target oxygen supply mode are obtained, the oxygen supply device can be controlled to supply oxygen to the target user in the target oxygen supply mode at the activation time of the oxygen supply device corresponding to the target oxygen supply mode. By controlling the oxygen supply device to supply oxygen to the user in the selected oxygen supply mode at the activation time of the oxygen supply device, using a switching frequency that matches the user's breathing frequency, it ensures that the oxygen supply time of the oxygen supply device can accurately match the user's oxygen demand time. This avoids problems such as oxygen demand gaps due to delayed oxygen supply, insufficient oxygen supply due to excessively low oxygen supply frequency, and over-oxygen supply due to excessively high oxygen supply frequency. This further improves the intelligence of in-vehicle oxygen supply and maximizes the satisfaction of the user's oxygen needs.

[0348] Specifically, when the target oxygen supply mode is the first oxygen supply mode, the corresponding oxygen supply device will activate at the moment the user inhales; when the target oxygen supply mode is the second oxygen supply mode, the corresponding oxygen supply device will activate at a certain time (e.g., 5 seconds) before the user inhales. For example, if the moment a user inhales is 10:00:00, the oxygen supply device will activate at 10:00:00 when the target oxygen supply mode is the first oxygen supply mode; or, if the target oxygen supply mode is the second oxygen supply mode, the oxygen supply device will activate at 09:59:55.

[0349] For example, if the target oxygen supply mode is the first oxygen supply mode, the switching frequency is 30 times / minute, and the oxygen supply device is turned on at 10:00:00, then at 10:00:00, the oxygen supply device can be controlled to supply oxygen to the target user in the first oxygen supply mode at the switching frequency of 30 times / minute corresponding to the first oxygen supply mode.

[0350] For example, if the target oxygen supply mode is the second oxygen supply mode, the switching frequency is 30 times / minute, and the oxygen supply device is turned on at 09:59:55, then at 09:59:55, the oxygen supply device can be controlled to supply oxygen to the target user in the second oxygen supply mode at the switching frequency of 30 times / minute corresponding to the second oxygen supply mode.

[0351] When determining the activation time of the second oxygen supply mode at the current moment, the respiratory rate of the target user at the previous moment and the target user's historical respiratory rate can be obtained. The activation time of the second oxygen supply mode at the current moment (i.e., the moment corresponding to a certain time before the user inhales) can be predicted by using the target user's respiratory rate at the previous moment and the target user's historical respiratory rate.

[0352] Here, historical respiratory rate refers to at least one respiratory rate of the target user before the previous moment. Since there is the strongest temporal correlation between the user's respiratory rate before the current moment and the user's respiratory rate at the current moment, the user's historical respiratory rate can capture the trend of respiratory rate changes over a longer period of time. Therefore, the user's respiratory rate before the current moment can be used as a prediction anchor point, and the user's historical respiratory rate can be used as the data basis for mining the pattern of respiratory rate changes to predict the activation time of the second oxygen supply mode at the current moment, so that the predicted activation time of the second oxygen supply mode at the current moment can be more accurate.

[0353] For example, when controlling the oxygen supply device to supply oxygen to the target user in the target oxygen supply mode, the oxygen supply device can be controlled to supply oxygen to the target user in the target oxygen supply mode with the target oxygen supply amount and / or the target oxygen supply direction.

[0354] Furthermore, when controlling the oxygen supply device to supply oxygen to the target user in the target oxygen supply mode, the required oxygen supply amount (which can be called the "target oxygen supply amount") can be determined first by the target user's breathing rate. This ensures that the determined target oxygen supply amount matches the user's breathing rate, avoiding the problem of oxygen waste caused by the oxygen supply device's inability to match the breathing rate when the user's breathing rate is low and the oxygen demand is low, or the problem of insufficient oxygen caused by the oxygen supply device's inability to match the breathing rate when the user's breathing rate is high and the oxygen demand is high.

[0355] When the target oxygen supply volume of the oxygen supply device is determined, it can be controlled to supply oxygen to the target user at the target oxygen supply volume in the target oxygen supply mode. This allows the oxygen supply device to dynamically adjust according to the target user's real-time breathing rate (also known as "real-time breathing status"), thus avoiding insufficient or excessive oxygen supply. The target user's breathing rate is positively correlated with the target oxygen supply volume. In addition to controlling the oxygen supply device to supply oxygen to the user in the selected oxygen supply mode, an oxygen supply volume matching the user's breathing rate can also be determined. This allows the oxygen supply device to supply oxygen to the user at the determined oxygen supply volume in the selected oxygen supply mode, avoiding insufficient or excessive oxygen supply, further improving the intelligence of in-vehicle oxygen supply, and maximizing the satisfaction of the user's oxygen needs.

[0356] For example, if the target oxygen supply mode is the first oxygen supply mode and the target oxygen supply rate is 245 mL / min, then the oxygen supply device can be controlled to supply oxygen to the target user at an oxygen supply rate of 245 mL / min in the first oxygen supply mode.

[0357] For example, if the target oxygen supply mode is the second oxygen supply mode and the target oxygen supply rate is 260 mL / min, then the oxygen supply device can be controlled to supply oxygen to the target user at an oxygen supply rate of 260 mL / min in the second oxygen supply mode.

[0358] Furthermore, when controlling the oxygen supply device to supply oxygen to the target user at the target oxygen supply volume in the target oxygen supply mode, the current sitting posture of the target user can be obtained first, and the target oxygen supply direction of the oxygen supply device can be obtained through the current sitting posture of the target user. Here, the target oxygen supply direction refers to the direction in which the target user's face is located.

[0359] When the target oxygen supply direction is determined, the oxygen supply device can be controlled to supply oxygen to the target user with the target oxygen supply volume and direction in the target oxygen supply mode. In addition to controlling the oxygen supply device to supply oxygen to the user with the determined oxygen supply volume in the selected oxygen supply mode, it can also determine the oxygen supply direction that matches the user's current sitting posture. This allows the oxygen supply device to supply oxygen to the user with the determined oxygen supply volume and direction in the selected oxygen supply mode, avoiding insufficient oxygen supply caused by the oxygen supply direction not being in the direction of the user's face. This further improves the intelligence of in-vehicle oxygen supply and maximizes the satisfaction of the user's oxygen needs.

[0360] For example, if the target oxygen supply mode is the first oxygen supply mode, the target oxygen supply volume is 245 mL / min, and the target oxygen supply direction is the upper right side, then the oxygen supply device can be controlled to supply oxygen to the target user in the first oxygen supply mode with an oxygen supply volume of 245 mL / min and an oxygen supply direction of the upper right side.

[0361] For example, if the target oxygen supply mode is the second oxygen supply mode, the target oxygen supply volume is 260 mL / min, and the target oxygen supply direction is the upper left side, then the oxygen supply device can be controlled to supply oxygen to the target user in the second oxygen supply mode with an oxygen supply volume of 260 mL / min and an oxygen supply direction of the upper left side.

[0362] Optionally, when controlling the oxygen supply device to supply oxygen to the target user in the target oxygen supply mode, if the target oxygen supply direction corresponding to the current sitting posture of the target user is determined, the oxygen supply device can be controlled to supply oxygen to the target user in the target oxygen supply mode in the target oxygen supply direction.

[0363] In summary, when collecting the pressure data of the user's seatbelt during breathing (i.e., raw pressure data), the raw pressure data can be first corrected using the vehicle speed data and / or the user's exercise intensity data. Then, the corrected raw pressure data (i.e., target pressure data) is used to determine the user's breathing rate. This determined breathing rate is then used to control the vehicle's oxygen supply system to provide oxygen to the user. Correcting the collected raw pressure data using vehicle speed data and / or the user's exercise intensity data makes the corrected pressure data more accurate. Using more accurate pressure data allows for a more accurate determination of the user's breathing rate. This more accurate breathing rate, in turn, improves the accuracy of the operating parameters of the vehicle's oxygen supply system, enabling it to operate with more precise parameters and maximize the user's oxygen needs. Furthermore, dividing the data into blocks based on sliding window segments and dynamically assigning weights to each initial breathing cycle within each sliding window segment reduces the complexity and efficiency of weight allocation, and minimizes the adverse effects of abnormal breathing cycle data on the overall data, thereby improving the accuracy of data processing. Furthermore, the first respiratory cycle corresponding to the initial respiratory cycle with a large inspiratory intensity is further corrected to reduce the bias in data processing results caused by sudden deep breathing by the user. Additionally, the respiratory cycle and duration difference are corrected using correction amounts corresponding to the user's individual characteristics, making the corrected respiratory cycle and duration difference more consistent with the user's individual characteristics and more accurate. Furthermore, the respiratory cycle and duration difference are corrected using correction amounts corresponding to the device collecting pressure data, making the corrected respiratory cycle and duration difference more realistic and accurate. Finally, when there are multiple respiratory rates, a sliding window segment is used to implement step-by-step averaging calculation, reducing the complexity of respiratory rate calculation, enhancing the stability of respiratory rate calculation results, and also reducing the amount of data processed in a single respiratory rate calculation, enabling block calculation and improving the efficiency of respiratory rate calculation.

[0364] Furthermore, by determining the user's breathing rate, automatic selection of the oxygen supply mode can be achieved. It can automatically identify the mode that matches the user's breathing rate from multiple options, maximizing oxygen supply to the user and improving the intelligence of in-vehicle oxygen supply, thus meeting the user's oxygen needs to the greatest extent and enhancing the timeliness and effectiveness of oxygen inhalation. Additionally, by using the user's breathing rate from the previous moment as a prediction anchor point and the user's historical breathing rates as a data basis for analyzing breathing rate variation patterns, the activation time of the second oxygen supply mode at the current moment can be predicted, making the predicted activation time of the second oxygen supply mode at the current moment more accurate. Moreover, at the activation time of the oxygen supply device, by controlling the switching frequency to match the user's breathing rate, the oxygen supply device delivers oxygen to the user in the selected oxygen supply mode with the selected oxygen supply volume and / or direction, avoiding insufficient or excessive oxygen supply, further improving the intelligence of in-vehicle oxygen supply and maximizing the meeting of the user's oxygen needs.

[0365] It should be understood that the above examples are provided to help those skilled in the art understand the embodiments of this application, and are not intended to limit the embodiments of this application to the specific values ​​or scenarios exemplified. Those skilled in the art can obviously make various equivalent modifications or variations based on the above examples, and such modifications or variations also fall within the scope of the embodiments of this application.

[0366] The above text combined Figures 1 to 5 The vehicle oxygen supply method provided in the embodiments of this application is described in detail below; the following will be combined with Figure 6 and Figure 7 The apparatus embodiments of this application are described in detail below. It should be understood that the apparatus in the embodiments of this application can perform the various methods described in the foregoing embodiments of this application, that is, the specific working processes of the various products described below can be referred to the corresponding processes in the foregoing method embodiments.

[0367] Figure 6 This is a schematic diagram of the vehicle oxygen supply device provided in the embodiments of this application.

[0368] For example, such as Figure 6 As shown, the device 600 includes:

[0369] The acquisition module 610 is used to acquire target data and raw pressure data. The target data includes the vehicle speed data of the vehicle where the target user is located and / or the exercise intensity data of the target user. The raw pressure data represents the pressure data of the seat belt used by the target user when the target user breathes.

[0370] The processing module 620 is used to correct the original pressure data based on the target data to obtain the target pressure data; based on the target pressure data, determine the respiratory rate of the target user; and based on the respiratory rate, control the oxygen supply device in the vehicle to supply oxygen to the target user.

[0371] In one possible implementation, the processing module 620 is specifically used for:

[0372] Determine the peak pressure data corresponding to each adjacent inspiration phase in the target pressure data;

[0373] The time interval between peak pressure data collection points is defined as the initial time difference;

[0374] The initial duration difference can be determined as the initial respiratory cycle, or the initial respiratory cycle can be determined based on the initial duration difference and the individual characteristics of the target user.

[0375] The respiratory rate is determined based on the initial respiratory cycle.

[0376] In one possible implementation, the processing module 620 is specifically used for:

[0377] Based on the average respiratory cycle corresponding to the sliding window segment where each of the multiple initial respiratory cycles is located and each initial respiratory cycle, determine the first weight of each initial respiratory cycle;

[0378] Each initial respiratory cycle is corrected based on the first weight to obtain the first respiratory cycle corresponding to each initial respiratory cycle;

[0379] Determine the respiratory rate based on the first respiratory cycle.

[0380] In one possible implementation, the processing module 620 is specifically used for:

[0381] The first respiratory cycle corresponding to the initial respiratory cycle in each sliding window segment where the inspiratory intensity is greater than the inspiratory intensity threshold corresponding to each sliding window segment is determined as the respiratory cycle to be corrected.

[0382] The corrected respiratory cycle is obtained by adjusting the second weight corresponding to the respiratory cycle to be corrected.

[0383] The corrected respiratory cycle to be corrected and the uncorrected respiratory cycle are determined as the second respiratory cycle. The uncorrected respiratory cycle refers to the first respiratory cycle corresponding to the initial respiratory cycle in each sliding window segment where the inspiratory intensity is less than or equal to the inspiratory intensity threshold corresponding to each sliding window segment.

[0384] The respiratory rate is determined based on the second respiratory cycle.

[0385] In one possible implementation, the processing module 620 is specifically used for:

[0386] Based on the initial duration difference and the individual characteristics of the target user, the initial respiratory cycle is determined, and the second respiratory cycle is determined as the target respiratory cycle.

[0387] With the initial duration difference determined as the initial respiratory cycle, the target respiratory cycle is determined based on the second respiratory cycle.

[0388] Determine the respiratory rate based on the target respiratory cycle.

[0389] In one possible implementation, the processing module 620 is specifically used for:

[0390] The second respiratory cycle is corrected based on the correction amount corresponding to the individual characteristics of the target user to obtain the third respiratory cycle;

[0391] The target respiratory cycle is determined based on the third respiratory cycle.

[0392] In one possible implementation, the processing module 620 is specifically used for:

[0393] The third respiratory cycle is corrected based on the error correction amount corresponding to the target device to obtain the fourth respiratory cycle. Here, the target device refers to the device used to collect raw pressure data.

[0394] The fourth respiratory cycle was determined as the target respiratory cycle.

[0395] In one possible implementation, the processing module 620 is specifically used for:

[0396] The initial duration difference is corrected based on the correction amount corresponding to the individual characteristics of the target user to obtain the first duration difference;

[0397] The initial respiratory cycle is determined based on the first time difference.

[0398] In one possible implementation, the processing module 620 is specifically used for:

[0399] The first time difference is corrected based on the error correction amount corresponding to the target device to obtain the second time difference;

[0400] The second time difference was determined as the initial respiratory cycle.

[0401] In one possible implementation, the processing module 620 is specifically used for:

[0402] Based on the target data and the interference coefficient corresponding to the target data, the interference pressure data corresponding to the target data is determined in the original pressure data;

[0403] Remove interfering pressure data from the original pressure data to obtain the target pressure data.

[0404] In one possible implementation, the processing module 620 is specifically used for:

[0405] Based on the unit duration and the target respiratory cycle, determine the initial respiratory rate corresponding to the target respiratory cycle;

[0406] If the initial respiratory rate is 1, then the initial respiratory rate is defined as the respiratory rate.

[0407] When there are multiple initial respiratory rates, determine the window average value of at least one initial respiratory rate corresponding to each sliding window segment;

[0408] The average value of the window averages is determined as the respiratory rate.

[0409] In one possible implementation, the processing module 620 is specifically used for:

[0410] Based on the target user's breathing rate, the target oxygen supply mode is determined among multiple oxygen supply modes. Among these multiple oxygen supply modes, the activation time of the oxygen supply device in the vehicle is different for each oxygen supply mode.

[0411] Based on the target oxygen supply mode, control the oxygen supply device to supply oxygen to the target user.

[0412] In one possible implementation, the processing module 620 is specifically used for:

[0413] If the target user's breathing rate is less than the preset rate, the first oxygen supply mode among multiple oxygen supply modes is determined as the target oxygen supply mode. The first oxygen supply mode means that the oxygen supply device is turned on at the moment when the target user's inhalation is detected.

[0414] If the target user's breathing rate is greater than or equal to the preset rate, the second oxygen supply mode among multiple oxygen supply modes is determined as the target oxygen supply mode. The second oxygen supply mode refers to the oxygen supply mode in which the oxygen supply device is turned on before the target user inhales.

[0415] In one possible implementation, the processing module 620 is specifically used for:

[0416] Based on the target user's respiratory rate and current respiratory intensity, the target oxygen supply mode is determined among multiple oxygen supply modes.

[0417] In one possible implementation, the processing module 620 is specifically used for:

[0418] If the target user's breathing rate is less than the preset rate and the target user's current breathing intensity is less than the preset intensity, the first oxygen supply mode among multiple oxygen supply modes is determined as the target oxygen supply mode. The first oxygen supply mode means that the oxygen supply device is turned on at the moment when the target user's inhalation is detected.

[0419] If the target user's breathing rate is greater than or equal to the preset frequency and the target user's current breathing intensity is greater than or equal to the preset intensity, the second oxygen supply mode among multiple oxygen supply modes is determined as the target oxygen supply mode. The second oxygen supply mode refers to the oxygen supply mode in which the oxygen supply device is turned on before the target user inhales.

[0420] In one possible implementation, the processing module 620 is specifically used for:

[0421] Based on the target user's respiratory rate in the previous moment and the target user's historical respiratory rate, predict when the second oxygen supply mode will be activated in the current moment.

[0422] Among them, historical breathing frequency refers to at least one breathing frequency of the target user before the previous moment of the current moment.

[0423] In one possible implementation, the processing module 620 is specifically used for:

[0424] The target oxygen supply mode is determined among multiple oxygen supply modes based on the target user's respiratory rate and / or the target user's current respiratory intensity.

[0425] In one possible implementation, the processing module 620 is specifically used for:

[0426] When the oxygen supply device is turned on, the switching frequency is used to control the oxygen supply device to supply oxygen to the target user in the target oxygen supply mode.

[0427] In one possible implementation, the processing module 620 is specifically used for:

[0428] Based on the respiratory rate of the target user, the target oxygen supply capacity of the oxygen supply device is determined, wherein the respiratory rate of the target user is positively correlated with the target oxygen supply capacity;

[0429] The oxygen supply device is controlled to supply oxygen to the target user at the target oxygen supply amount in the target oxygen supply mode.

[0430] In one possible implementation, the processing module 620 is specifically used for:

[0431] Obtain the target user's current sitting posture;

[0432] Based on the target user's current sitting posture, the target oxygen supply direction of the oxygen supply device is obtained, where the target oxygen supply direction represents the direction of the target user's face.

[0433] The oxygen supply device is controlled to supply oxygen to the target user in the target oxygen supply mode with the target oxygen supply amount and the target oxygen supply direction.

[0434] In one possible implementation, the processing module 620 is specifically used for:

[0435] Based on the respiratory rate of the target user, the target oxygen supply capacity of the oxygen supply device is determined, wherein the respiratory rate of the target user is positively correlated with the target oxygen supply capacity;

[0436] Obtain the target user's current sitting posture;

[0437] Based on the target user's current sitting posture, the target oxygen supply direction of the oxygen supply device is obtained, where the target oxygen supply direction represents the direction of the target user's face.

[0438] The oxygen supply device is controlled to supply oxygen to the target user in the target oxygen supply mode with the target oxygen supply amount and / or the target oxygen supply direction.

[0439] It should be noted that the aforementioned device 600 is embodied in the form of a functional module. The term "module" here can be implemented in software and / or hardware, without specific limitations.

[0440] For example, a "module" can be a software program, hardware circuit, or a combination of both that implements the above functions. Hardware circuits may include application-specific integrated circuits (ASICs), electronic circuits, processors (e.g., shared processors, proprietary processors, or combined processors) and memory for executing one or more software or firmware programs, combined logic circuits, and / or other suitable components that support the described functions.

[0441] Therefore, the modules of the various examples described in the embodiments of this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0442] Figure 7 This is a schematic diagram of the vehicle structure provided in the embodiments of this application.

[0443] For example, such as Figure 7As shown, the vehicle 700 includes a memory 710 and a processor 720. The memory 710 stores executable program code 7101, and the processor 720 is used to call and execute the executable program code 7101 to perform a vehicle oxygen supply method.

[0444] This application can divide the vehicle into functional modules based on the above method example. For example, each module can correspond to a separate function module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0445] When each functional module is divided according to its corresponding function, the vehicle may include: an acquisition module and a processing module, etc. It should be noted that all relevant content of each step involved in the above method embodiments can be referenced from the functional description of the corresponding functional module, and will not be repeated here.

[0446] The vehicle provided in this application is used to perform the above-mentioned vehicle oxygen supply method, and thus can achieve the same effect as the above-mentioned implementation method.

[0447] When using integrated units, the vehicle may include a processing module and a storage module. The processing module is used to control and manage the vehicle's movements. The storage module is used to support the vehicle in executing relevant program code and data.

[0448] The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits shown in conjunction with the disclosure of this application. The processor may also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and microprocessors, etc., and the storage module may be a memory.

[0449] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described in the foregoing embodiments. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs (Digital Video Discs), CD-ROMs (Compact Disc Read-Only Memory), microdrives, magneto-optical disks, ROMs (Read-Only Memory), RAMs (Random Access Memory), EPROMs (Erasable Programmable Read-Only Memory), EEPROMs (Electrically Erasable Programmable Read Only Memory), DRAMs (Dynamic Random Access Memory), VRAMs (Video Random Access Memory), flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0450] This application also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned steps to implement a vehicle oxygen supply method as described in the above embodiments.

[0451] In addition, the vehicle provided in the embodiments of this application may specifically be a chip, component or module. The vehicle may include a connected processor and a memory. The memory is used to store instructions. When the vehicle is running, the processor may call and execute the instructions to make the chip execute a vehicle oxygen supply method in the above embodiments.

[0452] The vehicle, computer-readable storage medium, computer program product or chip provided in this application are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can be referred to the beneficial effects of the corresponding methods provided above, and will not be repeated here.

[0453] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0454] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0455] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for supplying oxygen to a vehicle, characterized in that, The method includes: Acquire target data and raw pressure data, wherein the target data includes vehicle speed data of the vehicle in which the target user is located and / or the exercise intensity data of the target user, and the raw pressure data represents the pressure data of the seat belt used by the target user when the target user breathes. The original pressure data is corrected based on the target data to obtain the target pressure data; Based on the target pressure data, determine the initial respiratory cycle; Determining the respiratory rate based on the initial respiratory cycle includes: determining a first weight for each initial respiratory cycle based on the average respiratory cycle corresponding to the sliding window segment in which each of the multiple initial respiratory cycles is located and each initial respiratory cycle; correcting each initial respiratory cycle based on the first weight to obtain a first respiratory cycle corresponding to each initial respiratory cycle; and determining the respiratory rate based on the first respiratory cycle. Based on the breathing rate, the oxygen supply device in the vehicle is controlled to supply oxygen to the target user.

2. The method according to claim 1, characterized in that, Determining the initial respiratory cycle based on the target pressure data includes: Determine the peak pressure data corresponding to each adjacent inhalation phase in the target pressure data; The time interval between the peak pressure data acquisition times is determined as the initial time difference; The initial duration difference is determined as the initial respiratory cycle, or the initial respiratory cycle is determined based on the initial duration difference and the individual characteristics of the target user.

3. The method according to claim 2, characterized in that, Determining the respiratory rate based on the first respiratory cycle includes: The first respiratory cycle corresponding to the initial respiratory cycle in each sliding window segment where the inspiratory intensity is greater than the inspiratory intensity threshold corresponding to each sliding window segment is determined as the respiratory cycle to be corrected. The respiratory cycle to be corrected is corrected based on the second weight corresponding to the respiratory cycle to be corrected, so as to obtain the corrected respiratory cycle to be corrected. The corrected respiratory cycle to be corrected and the uncorrected respiratory cycle are determined as the second respiratory cycle, wherein the uncorrected respiratory cycle represents the first respiratory cycle corresponding to the initial respiratory cycle in each sliding window segment where the inspiratory intensity is less than or equal to the inspiratory intensity threshold corresponding to each sliding window segment. The respiratory rate is determined based on the second respiratory cycle.

4. The method according to claim 3, characterized in that, Determining the respiratory rate based on the second respiratory cycle includes: In the case where the initial respiratory cycle is determined based on the initial duration difference and the individual characteristics of the target user, the second respiratory cycle is determined as the target respiratory cycle; In the case where the initial duration difference is determined as the initial respiratory cycle, the target respiratory cycle is determined based on the second respiratory cycle; The respiratory rate is determined based on the target respiratory cycle.

5. The method according to claim 4, characterized in that, Determining the target respiratory cycle based on the second respiratory cycle includes: The second respiratory cycle is corrected based on the correction amount corresponding to the individual characteristics of the target user to obtain the third respiratory cycle; The target respiratory cycle is determined based on the third respiratory cycle.

6. The method according to claim 5, characterized in that, Determining the target respiratory cycle based on the third respiratory cycle includes: The third respiratory cycle is corrected based on the error correction amount corresponding to the target device to obtain the fourth respiratory cycle, wherein the target device refers to the device used to collect the raw pressure data; The fourth respiratory cycle is determined as the target respiratory cycle.

7. The method according to claim 4, characterized in that, The step of determining the initial respiratory cycle based on the initial duration difference and the individual characteristics of the target user includes: The initial duration difference is corrected based on the correction amount corresponding to the individual characteristics of the target user to obtain the first duration difference; The initial respiratory cycle is determined based on the first time difference.

8. The method according to claim 7, characterized in that, Determining the initial respiratory cycle based on the first duration difference includes: The first time difference is corrected based on the error correction amount corresponding to the target device to obtain the second time difference; The second time difference is determined as the initial respiratory cycle.

9. The method according to any one of claims 1 to 8, characterized in that, The step of correcting the original pressure data based on the target data to obtain the target pressure data includes: Based on the target data and the interference coefficient corresponding to the target data, the interference pressure data corresponding to the target data is determined in the original pressure data; The interfering pressure data is removed from the original pressure data to obtain the target pressure data.

10. The method according to any one of claims 4 to 8, characterized in that, Determining the respiratory rate based on the target respiratory cycle includes: Based on the unit duration and the target respiratory cycle, determine the initial respiratory rate corresponding to the target respiratory cycle; When the initial respiratory rate is 1, the initial respiratory rate is determined as the respiratory rate. When there are multiple initial respiratory rates, determine the window average value of at least one initial respiratory rate corresponding to each sliding window segment; The average value of the window values ​​is determined as the respiratory rate.

11. A vehicle, characterized in that, The vehicles include: Memory, used to store executable program code; A processor for calling and running the executable program code from the memory, causing the vehicle to perform the method as described in any one of claims 1 to 10.

Images