Intelligent anesthesia induction mask capable of monitoring gastric retention

Abstract

The invention relates to the technical field of breathing masks, in particular to an intelligent anesthesia induction mask capable of monitoring gastric retention, the intelligent anesthesia induction mask comprises a mask body and an ultrasonic detection module, and the mask body is communicated with a breathing tube; a smell detection module used for detecting smell data in the oral cavity is communicated in the breathing tube, and the smell detection module is electrically connected with a controller; the controller is electrically connected with a myoelectricity electrode used for stimulating swallowing related muscles, and the controller is used for sending an ultrasonic verification instruction to the outside based on comparison of smell data and retention comparison data when the myoelectricity electrode is started; the controller is further used for acquiring an ultrasonic image at the current time based on the ultrasonic verification instruction, acquiring a real-time gastric motility parameter based on the ultrasonic image in unit time, and sending a gastric retention risk reminding instruction to the outside when the real-time gastric motility parameter is inconsistent with a set comparison gastric motility parameter; the residual volume of the stomach is dynamically evaluated through the ultrasonic sensor, and decision support is provided for anesthetists.

Description

Technical Field

[0001] This invention relates to the field of respiratory mask technology, and more specifically to an intelligent anesthesia induction mask that can monitor gastric retention. Background Technology

[0002] For normal patients, gastric fluid retention lasts approximately 1-2 hours, while solid food retention lasts approximately 4-6 hours. Food retention is relatively short-lived, but in patients with gastric retention, emptying time can be prolonged to several hours or even days. A large amount of food and fluid may accumulate in the stomach of patients with gastric retention. For patients undergoing routine or urgent anesthesia surgery, the use of anesthetic drugs can suppress normal swallowing and cough reflexes, increasing the risk of reflux and aspiration during anesthesia induction or recovery, which can be life-threatening in severe cases. Therefore, it is necessary to monitor for gastric retention.

[0003] During the wearing of a breathing mask, the pre-oxygenation phase is a crucial step in establishing oxygen reserves through high-concentration pure oxygen inhalation before anesthesia induction, providing a time window for subsequent procedures such as endotracheal intubation. During subsequent anesthesia induction, the patient loses consciousness, and the risk of gastric reflux increases sharply. If the gastric retention status can be assessed in real time during the pre-oxygenation phase, the anesthesia plan can be adjusted in advance, avoiding a passive situation during emergency airway management. Therefore, this invention provides an intelligent anesthesia induction mask that can monitor gastric retention, dynamically assessing the residual gastric volume using an ultrasound sensor, providing decision support for anesthesiologists. Summary of the Invention

[0004] To address the aforementioned issues, this invention provides an intelligent anesthesia induction mask capable of monitoring gastric retention. It dynamically assesses the amount of residual gastric contents using an ultrasound sensor, providing decision support for anesthesiologists.

[0005] To achieve the above objectives, the technical solution of the present invention is as follows: an intelligent anesthesia induction mask for monitoring gastric retention, comprising a mask body for wearing on the patient's face and an ultrasound detection module for ultrasound detection of residual food in the stomach, wherein a breathing tube is connected to the mask body; a branch tube is also connected between the breathing tube and the mask body, and an odor detection module for detecting oral odor data is connected inside the branch tube, and the odor detection module is electrically connected to a controller;

[0006] The controller is electrically connected to electromyographic electrodes for stimulating swallowing-related muscles, which are located below the mask body.

[0007] The controller uses odor data from the electromyographic electrodes at startup to compare the odor data with a set retention comparison data. If the odor data matches the retention comparison data, an early warning command is sent to the outside; if the odor data does not match the retention comparison data, an ultrasound verification command is sent to the outside.

[0008] The controller is also used to input comparative gastric motility parameters corresponding to normal patients. These parameters include the frequency and amplitude of antral contractions. It acquires ultrasound images at the current time based on ultrasound verification commands, and obtains real-time gastric motility parameters based on ultrasound images within a unit of time. It then compares the comparative gastric motility parameters with the real-time gastric motility parameters for consistency. If they match, it sends a normal risk warning command to the outside world; otherwise, it sends a gastric retention risk warning command to the outside world.

[0009] Furthermore, a spring plate is rotatably fitted to the top of the mask body, and a shielding layer is fixedly connected to the spring plate. The electromyography electrode is located at the end of the shielding layer away from the mask body.

[0010] A pressure sensor is also fixedly connected to the spring plate, and the pressure sensor is electrically connected to the controller;

[0011] The pressure sensor is used to detect real-time pressure data when the jaw muscle contacts the spring plate. The controller is also used to calculate the change value of the real-time pressure data before and after the electromyographic electrode is activated, and compare the change value with the set swallowing initiation value. If the change value is greater than the swallowing initiation value, a gastric peristalsis stimulation mark is added to the ultrasound image at the current time; if the change value is less than or equal to the swallowing initiation value, a normal gastric peristalsis mark is added to the ultrasound image at the current time.

[0012] Furthermore, an insulating layer is provided between the pressure sensor and the electromyography electrode.

[0013] Furthermore, the spring sheet includes a first support sheet and a second support sheet. The first support sheet contacts the area below the chin, and the electromyographic electrode and pressure sensor are located on the side of the first support sheet away from the mask body. The first and second support sheets are L-shaped, with the second support sheet contacting the larynx, and the pressure sensor is also located on the side of the second support sheet closer to the larynx.

[0014] Furthermore, the controller is also used to classify and label the real-time pressure data based on the positions of the first support plate and the second support plate, wherein the real-time pressure data corresponding to the first support plate is the first pressure data, and the real-time pressure data corresponding to the second support plate is the second pressure data.

[0015] Before the electromyographic electrodes are activated, the controller acquires the average value of the first pressure data within the current time period and compares the average value with the set fit value. If the average value matches the fit value, a verification pass command is sent to the outside; if the average value does not match the fit value, a spring sheet fit adjustment command is sent to the outside.

[0016] Furthermore, the controller is also used to draw a change graph based on the second pressure data before the electromyographic electrodes are activated, and to obtain the trajectory shape of the real-time pressure data based on the change graph. If the trajectory shape changes regularly, a swallowing verification reminder is sent to the outside world, and an activation command is sent to the electromyographic electrodes; if the trajectory shape changes irregularly, a waiting command is sent to the outside world.

[0017] Furthermore, the controller is also used to acquire the ultrasound image at the current time before the electromyographic electrode is activated, use the real-time gastric motility parameters of the ultrasound image as correction values, and adjust the comparative gastric motility parameters based on the correction values; then, based on the first pressure data and the second pressure data when the patient is in a supine position, a supine position mark is made, and the supine position mark is set as the initial state of the comparison process between odor data and retention comparison data.

[0018] Furthermore, the controller is also used to calculate and compare the changes in gastric motility parameters and real-time gastric motility parameters based on gastric retention risk warning instructions, and classify the gastric retention risk level according to the changes.

[0019] Furthermore, the controller is also used to calculate the difference based on adjacent second pressure data, compare the difference with the set lateral pressure value, and if the difference is greater than the lateral pressure value, output the corresponding position and orientation to the ultrasound image based on the larger second pressure data; if the difference is less than the lateral pressure value, send a normal body position command to the outside world.

[0020] Furthermore, the controller is also used to acquire and record the first and second pressure data of the patient when in a supine position during the recovery period, based on early warning reminders and gastric retention risk reminders;

[0021] Within the current time period, calculate the number of fluctuations in the second pressure data and compare the number of fluctuations with the awakening value. If the number of fluctuations is greater than the awakening value, send an awakening reminder command to the outside world; if the number of fluctuations is less than the awakening value, send a standby command to the outside world.

[0022] The above approach has the following beneficial effects:

[0023] 1. In this protocol, since patients with gastric retention have a large amount of residual food in their stomachs, the food undergoes excessive fermentation in the stomach, producing a large amount of odorous gases containing hydrogen sulfide (putrid smell) and methanethiol (rotten cabbage smell). For patients with pathologically reduced lower esophageal sphincter pressure, the gastric reflux gas is detected to determine the condition of gastric retention.

[0024] 2. In this protocol, for patients without lower esophageal sphincter pressure, gastric retention can be confirmed by stimulating gastric motility and assisting ultrasound detection. Ultrasound can be used to observe the peristalsis around the pyloric antrum. If the peristalsis is weakened or absent, combined with the enlargement of the gastric cavity, gastric retention can be diagnosed.

[0025] 3. In this scheme, after the mask is worn, the elasticity of the spring plate pushes the electromyographic electrodes and pressure sensor to fit against the chin, thereby adjusting the support direction of the spring plate. This facilitates the stimulation of swallowing-related muscles by the electromyographic electrodes on the spring plate. At the same time, based on the changes in swallowing movements caused by the activation of the electromyographic electrodes, the real-time pressure data changes detected by the pressure sensor are used to mark the ultrasound images, so as to facilitate the accuracy of subsequent verification and comparison of gastric motility parameters.

[0026] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the mask body of an embodiment of the intelligent anesthesia induction mask for monitoring gastric retention of the present invention;

[0028] Figure 2 This is a schematic diagram of the controller interaction of an embodiment of the intelligent anesthesia induction mask for monitoring gastric retention of the present invention.

[0029] The reference numerals in the accompanying drawings of the instruction manual include: 1, mask body; 2, breathing tube; 3, first support piece; 31, second support piece. Detailed Implementation

[0030] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0032] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0033] The following detailed description illustrates the specific implementation method:

[0034] Example 1:

[0035] As attached Figures 1 to 2 As shown: A smart anesthesia induction mask for monitoring gastric retention includes a mask body 1 for wearing on the patient's face and an ultrasound detection module for ultrasound detection of food residue in the stomach. A breathing tube 2 is connected to the mask body 1. A branch tube is also connected between the breathing tube 2 and the mask body 1. An odor detection module for detecting odor data in the oral cavity is connected inside the branch tube. The odor detection module is electrically connected to a controller.

[0036] The controller is electrically connected to electromyographic electrodes for stimulating swallowing-related muscles, and the electromyographic electrodes are located below the mask body 1. The controller is used to compare the odor data at the time of activation of the electromyographic electrodes with the set retention comparison data. If the odor data is consistent with the retention comparison data, an early warning reminder command is sent to the outside world. In this embodiment, the outside world includes the display screen of the ventilator, etc. If the odor data is inconsistent with the retention comparison data, an ultrasound verification command is sent to the outside world.

[0037] For example, in normal individuals, the lower esophageal sphincter briefly opens (for about 3-5 seconds) at the junction of the esophagus and stomach during swallowing to allow food to pass through, then immediately closes, forming a high-pressure barrier that slows gastric emptying to prevent the reflux of stomach contents or gas into the esophagus, thus blocking the path of odors towards the mouth. However, in patients with gastric retention, a large amount of residual food remains in the stomach, and excessive fermentation of the food produces large amounts of odorous gases containing hydrogen sulfide (a putrid smell) and methanethiol (a rotten cabbage smell). For patients with pathologically decreased lower esophageal sphincter pressure, the presence of gastric reflux gas can be detected to determine the extent of gastric retention.

[0038] The controller is also used to input comparative gastric motility parameters corresponding to normal patients. These parameters include the frequency and amplitude of antral contractions. It acquires ultrasound images at the current time based on ultrasound verification commands, and obtains real-time gastric motility parameters based on ultrasound images within a unit of time. It then compares the comparative gastric motility parameters with the real-time gastric motility parameters for consistency. If they match, it sends a normal risk warning command to the outside world; otherwise, it sends a gastric retention risk warning command to the outside world.

[0039] For example, in patients without lower esophageal sphincter pressure, stimulating gastric motility can aid in ultrasound detection to confirm gastric retention. After swallowing, the brainstem sends signals to the gastric wall smooth muscle via vagal nerve motor fibers, causing an increase in the frequency and amplitude of antral contractions. This enhanced peristalsis allows for observation of gastric emptying efficiency and changes in gastric cavity morphology, verifying the frequency and amplitude of antral contractions. For instance, a normal postprandial antral contraction frequency should be >50 times / hour, with an average amplitude >30 mmHg / 2 hours. If ultrasound shows a decreased contraction frequency or weakened amplitude, it suggests insufficient gastric motility, potentially leading to gastric retention. Secondly, vagal nerve excitation can also promote fundus relaxation and pyloric opening, reducing intragastric pressure and accelerating the flow of gastric contents into the duodenum. Ultrasound can be used to observe peristalsis around the pyloric antrum; if peristalsis is weakened or absent, combined with gastric cavity enlargement, gastric retention can be diagnosed.

[0040] A spring plate is rotatably fitted to the top of the mask body 1, and a shielding layer is fixedly connected to the spring plate. The electromyographic electrodes are located at the end of the shielding layer away from the mask body 1. A pressure sensor is also fixedly connected to the spring plate, located around the electromyographic electrodes, and electrically connected to the controller. An insulating layer is provided between the pressure sensor and the electromyographic electrodes. The insulating layer reduces current interference to the pressure sensor during the operation of the electromyographic electrodes, thereby improving the stability and accuracy of the pressure sensor during detection.

[0041] The pressure sensor is used to detect real-time pressure data when the jaw muscle contacts the spring plate. The controller is also used to calculate the change value of the real-time pressure data before and after the electromyographic electrode is activated, and compare the change value with the set swallowing initiation value. If the change value is greater than the swallowing initiation value, a gastric peristalsis stimulation mark is added to the ultrasound image at the current time; if the change value is less than or equal to the swallowing initiation value, a normal gastric peristalsis mark is added to the ultrasound image at the current time.

[0042] For example, the pressure sensor is used to detect real-time pressure data when the jaw muscle contacts the spring plate. The controller is also used to calculate the change value of the real-time pressure data before and after the electromyographic electrode is activated, compare the change value with the set swallowing initiation value, and add a gastric peristalsis stimulation mark to the ultrasound image at the current time if the change value is greater than the swallowing initiation value; if the change value is less than or equal to the swallowing initiation value, add a normal gastric peristalsis mark to the ultrasound image at the current time.

[0043] After the mask body 1 is worn, the elasticity of the spring plate pushes the electromyographic electrodes and pressure sensor to fit against the chin, thereby adjusting the support direction of the spring plate. This facilitates the stimulation of swallowing-related muscles by the electromyographic electrodes on the spring plate. At the same time, based on the changes in swallowing movements caused by the activation of the electromyographic electrodes, the real-time pressure data changes detected by the pressure sensor are used to mark the ultrasound image, so as to facilitate the accuracy of subsequent verification and comparison of gastric motility parameters.

[0044] Example 2:

[0045] The difference from Embodiment 1 is that the spring sheet includes a first support sheet 3 and a second support sheet 31. The first support sheet 3 contacts the area below the chin, and the electromyographic electrode and pressure sensor are located on the side of the first support sheet 3 away from the mask body 1. The first support sheet 3 and the second support sheet 31 are L-shaped, and the second support sheet 31 contacts the larynx. The pressure sensor is also located on the side of the second support sheet 31 closer to the larynx.

[0046] The specific implementation process is as follows: the first support plate 3 facilitates the electromyographic electrode and pressure sensor to make support contact with the jaw muscle, and at the same time provides a basic support position for the second support plate 31; then the second support plate 31 makes contact with the larynx, so that the pressure sensor on the second support plate 31 can confirm the movement of the larynx, thereby determining whether the swallowing action has been completed.

[0047] In another embodiment, the controller is further configured to classify and label real-time pressure data based on the positions of the first support plate 3 and the second support plate 31, wherein the real-time pressure data corresponding to the first support plate 3 is the first pressure data, and the real-time pressure data corresponding to the second support plate 31 is the second pressure data; before the electromyographic electrodes are activated, the controller obtains the average value of the first pressure data within the current time period, compares the average value with the set fit value, and if the average value is consistent with the fit value, sends a verification pass command to the outside; if the average value is inconsistent with the fit value, sends a spring plate fit adjustment command to the outside.

[0048] For example, during the wearing of the mask body 1, the first support piece 3 and the second support piece 31 apply pressure to the skin surface through their own elasticity. This may result in the first support piece 3 and the second support piece 31 being in contact with the skin too firmly or too loosely. If the skin contact is too firm, it may easily lead to damage to the first support piece 3 and the second support piece 31 during long-term contact with the skin. If the skin contact is too loose, it may easily lead to inaccurate real-time pressure data measured by the pressure sensor on the first support piece 3 and the second support piece 31 on the chin or throat. Adjustments are made by adjusting the fit of the spring pieces to reduce the accuracy of subsequent labeling.

[0049] Example 3:

[0050] The difference from Embodiment 2 is that the controller is also used to draw a change graph based on the second pressure data before the electromyographic electrodes are activated, and to obtain the trajectory shape of the real-time pressure data based on the change graph. If the trajectory shape changes regularly, a swallowing verification reminder is sent to the outside world, and an activation command is sent to the electromyographic electrodes; if the trajectory shape changes irregularly, a waiting command is sent to the outside world.

[0051] For example, during anesthesia, the patient's stable breathing status can be detected using secondary pressure data. By analyzing the regular changes in the trajectory pattern, it can be determined whether the patient's breathing is stable or in a state of light anesthesia, thereby reducing the impact of unstable breathing on gastric motility and improving the accuracy of subsequent verification of gastric motility parameters.

[0052] Example 4:

[0053] The difference from Example 3 is that the controller is also used to acquire the ultrasound image at the current time before the electromyographic electrode is activated, use the real-time gastric motility parameters of the ultrasound image as correction values, and adjust the comparative gastric motility parameters based on the correction values; then, based on the first pressure data and the second pressure data when the patient is in a supine position, a supine position mark is made, and the supine position mark is set as the initial state of the comparison process of odor data and retention comparison data.

[0054] For example, real-time gastric motility parameters of patients in a normal state can be used to correct the comparative gastric motility parameters to ensure the accuracy of subsequent comparisons. When patients are in a supine position, reflux is more likely to occur. A supine position can be used as the baseline state for odor data verification to improve the accuracy of the odor data verification process.

[0055] The controller is also used to calculate and compare the changes in gastric motility parameters and real-time gastric motility parameters based on gastric retention risk warning instructions, and classify the gastric retention risk level according to the changes.

[0056] For example, classifying patients by risk level of gastric retention allows physicians to more intuitively understand the risk of reflux and take timely measures such as tracheal management or adjusting the anesthesia plan.

[0057] Example 5:

[0058] The difference from Embodiment 4 is that the controller is also used to calculate the difference based on adjacent second pressure data, compare the difference with the set lateral pressure value, and if the difference is greater than the lateral pressure value, output the corresponding position and orientation to the ultrasound image based on the larger second pressure data; if the difference is less than the lateral pressure value, send a normal body position command to the outside world.

[0059] For example, when a patient is in a supine position, the stomach may shift backward or downward due to gravity, increasing the distance between the stomach body and the abdominal wall, affecting the contact and imaging quality of the ultrasound probe. However, when the patient is in a right lateral decubitus position, the stomach shifts forward and to the left of the abdominal wall due to gravity, bringing the stomach body closer to the anterior abdominal wall. In this position, the ultrasound probe can make more direct contact with the stomach wall, reducing interference from intestinal gas or fatty tissue and improving image clarity. Therefore, using the right lateral decubitus position as a reminder helps ensure the accuracy of the ultrasound examination process.

[0060] The difference between adjacent second pressure data is calculated to determine the patient's current lateral decubitus position. Different body positions cause changes in the pressure exerted on the laryngeal muscles due to body weight, thereby generating changes in the pressure of the second pressure data. This allows for corresponding positional marking, which can be used to determine the accuracy of ultrasound data monitoring by location and orientation during subsequent medical record review or verification.

[0061] Example 6:

[0062] The difference from Embodiment 5 is that the controller is also used to acquire and record the first pressure data and the second pressure data when the patient is in a supine position during the recovery period, based on the early warning reminder command and the gastric retention risk reminder; within the current time period, it calculates the number of fluctuations in the second pressure data, compares the number of fluctuations with the recovery value, and if the number of fluctuations is greater than the recovery value, it sends a recovery reminder command to the outside world; if the number of fluctuations is less than the recovery value, it sends a standby command to the outside world.

[0063] For example, by assessing the impact of a patient's respiratory rate on laryngeal vibration during the awakening process, it can be determined whether the patient has awakened and appropriate reminders can be given. This ensures that physicians can promptly address any reflux caused by intubation discomfort after awakening, thereby ensuring patient safety while improving patient comfort.

[0064] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A smart anesthesia induction mask for monitoring gastric retention, comprising a mask body (1) for wearing on the patient's face and an ultrasound detection module for ultrasound detection of residual food in the stomach, wherein a breathing tube (2) is connected to the mask body (1); characterized in that, A branch tube is connected between the breathing tube (2) and the mask body (1), and an odor detection module for detecting oral odor data is connected in the branch tube. The odor detection module is electrically connected to a controller. The controller is electrically connected to electromyographic electrodes for stimulating swallowing-related muscles, and the electromyographic electrodes are located below the mask body (1); The controller uses odor data from the electromyographic electrodes at startup to compare the odor data with a set retention comparison data. If the odor data matches the retention comparison data, an early warning command is sent to the outside; if the odor data does not match the retention comparison data, an ultrasound verification command is sent to the outside. The controller is also used to input comparative gastric motility parameters corresponding to normal patients. These parameters include the frequency and amplitude of antral contractions. It acquires ultrasound images at the current time based on ultrasound verification commands, and obtains real-time gastric motility parameters based on ultrasound images within a unit of time. It then compares the comparative gastric motility parameters with the real-time gastric motility parameters for consistency. If they match, it sends a normal risk warning command to the outside world; otherwise, it sends a gastric retention risk warning command to the outside world.

2. The intelligent anesthesia induction mask for monitoring gastric retention according to claim 1, characterized in that, A spring plate is rotatably fitted on the top of the mask body (1), and a shielding layer is fixedly connected to the spring plate. The electromyography electrode is located at the end of the shielding layer away from the mask body (1). A pressure sensor is also fixedly connected to the spring plate, and the pressure sensor is electrically connected to the controller; The pressure sensor is used to detect real-time pressure data when the jaw muscle contacts the spring plate. The controller is also used to calculate the change value of the real-time pressure data before and after the electromyographic electrode is activated, and compare the change value with the set swallowing initiation value. If the change value is greater than the swallowing initiation value, a gastric peristalsis stimulation mark is added to the ultrasound image at the current time; if the change value is less than or equal to the swallowing initiation value, a normal gastric peristalsis mark is added to the ultrasound image at the current time.

3. The intelligent anesthesia induction mask for monitoring gastric retention according to claim 2, characterized in that, An insulating layer is provided between the pressure sensor and the electromyography electrode.

4. The intelligent anesthesia induction mask for monitoring gastric retention according to claim 3, characterized in that, The spring sheet includes a first support sheet (3) and a second support sheet (31). The first support sheet (3) is in contact with the area below the chin. The electromyographic electrode and the pressure sensor are located on the side of the first support sheet (3) away from the mask body (1). The first support sheet (3) and the second support sheet (31) are L-shaped. The second support sheet (31) is in contact with the larynx. The pressure sensor is also located on the side of the second support sheet (31) close to the larynx.

5. The intelligent anesthesia induction mask for monitoring gastric retention according to claim 4, characterized in that, The controller is also used to classify and label the real-time pressure data based on the positions of the first support plate (3) and the second support plate (31), wherein the real-time pressure data corresponding to the first support plate (3) is the first pressure data, and the real-time pressure data corresponding to the second support plate (31) is the second pressure data; Before the electromyographic electrodes are activated, the controller acquires the average value of the first pressure data within the current time period and compares the average value with the set fit value. If the average value matches the fit value, a verification pass command is sent to the outside; if the average value does not match the fit value, a spring sheet fit adjustment command is sent to the outside.

6. The intelligent anesthesia induction mask for monitoring gastric retention according to claim 5, characterized in that, The controller is also used to draw a change graph based on the second pressure data before the electromyographic electrodes are activated, and to obtain the trajectory shape of the real-time pressure data based on the change graph. If the trajectory shape changes regularly, a swallowing verification reminder is sent to the outside world, and an activation command is sent to the electromyographic electrodes; if the trajectory shape changes irregularly, a waiting command is sent to the outside world.

7. The intelligent anesthesia induction mask for monitoring gastric retention according to claim 6, characterized in that, The controller is also used to acquire the ultrasound image at the current time before the electromyographic electrodes are activated, use the real-time gastric motility parameters of the ultrasound image as correction values, and adjust the comparative gastric motility parameters based on the correction values; then, based on the first pressure data and the second pressure data when the patient is in a supine position, a supine position mark is made, and the supine position mark is set as the initial state of the comparison process of odor data and retention comparison data.

8. The intelligent anesthesia induction mask for monitoring gastric retention according to claim 7, characterized in that, The controller is also used to calculate and compare the changes in gastric motility parameters and real-time gastric motility parameters based on gastric retention risk warning instructions, and classify the gastric retention risk level according to the changes.

9. The intelligent anesthesia induction mask for monitoring gastric retention according to claim 8, characterized in that, The controller is also used to calculate the difference based on adjacent second pressure data, compare the difference with the set lateral pressure value, and if the difference is greater than the lateral pressure value, output the corresponding position and orientation to the ultrasound image based on the larger second pressure data. If the difference is less than the lateral pressure value, a normal body position command is sent to the outside.

10. The intelligent anesthesia induction mask for monitoring gastric retention according to claim 9, characterized in that, The controller is also used to acquire and record the first and second pressure data of the patient in the supine position during the recovery period, based on early warning reminders and gastric retention risk reminders; Within the current time period, calculate the number of fluctuations in the second pressure data and compare the number of fluctuations with the awakening value. If the number of fluctuations is greater than the awakening value, send an awakening reminder command to the outside world; if the number of fluctuations is less than the awakening value, send a standby command to the outside world.

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