Ultrasonic stomach residual volume monitoring Bluetooth transmission equipment for infant enteral nutrition

Abstract

The invention relates to the technical field of stomach residual volume detection, in particular to ultrasonic stomach residual volume monitoring Bluetooth transmission equipment for infant enteral nutrition. The equipment comprises a body structure and a transmission equipment carrying control system, wherein the transmission equipment carrying control system comprises an ultrasonic signal acquisition module, a signal processing module, a Bluetooth transmission module, a residual volume calculation module and a grading alarm module. According to the method, the target frequency band is screened to be matched with the acoustic impedance characteristics of the liquid in the stomach, the transmitting power of the probe is dynamically tuned in combination with the abdominal wall thickness, gas and tissue interference is reduced, signal precision is improved, signal mapping deviation is corrected based on the gastral cavity three-dimensional model, body position deviation is compensated, the liquid distribution model in the stomach is generated, and accuracy is enhanced; data packets are dynamically segmented, time sequence labels are embedded, transmission completeness and interference resistance are ensured, parameters are corrected by combining the intake rate and a gastric emptying curve, the volume is quantified, errors are compensated, the calculation reliability is improved, and graded alarm instructions are generated to be linked with clinical operation.

Description

Technical Field

[0001] The present invention relates to the technical field of gastric residual volume detection, and in particular to a Bluetooth transmission device for ultrasonic gastric residual volume monitoring during enteral nutrition for infants. Background Art

[0002] The field of medical monitoring equipment technology includes the research, development, and application of equipment and methods related to monitoring gastric residual volume in enteral nutrition care for infants and young children. The core content of this field involves the use of technical means to assess the residual liquid in the stomach to guide nutritional supply and prevent complications. Traditional technology relies on gastric tube suction, which requires invasive operations and carries risks. Existing improved technologies use ultrasound imaging principles to achieve non-invasive detection, but their equipment is large in size, the operation process is complicated, and it relies on offline data export methods. It cannot meet the needs of real-time monitoring and convenient transmission, which restricts its widespread use in clinical and home scenarios.

[0003] The Bluetooth transmission device for ultrasonic gastric residual volume monitoring during enteral nutrition in infants and young children is a miniaturized monitoring device based on ultrasonic reflection signal acquisition and wireless transmission technology. This device addresses the need for real-time acquisition and remote interaction of gastric residual volume data. It uses a small ultrasound probe that fits snugly against the infant's abdomen to collect signals and synchronizes the data to a mobile device using Bluetooth technology. This data is then integrated with a mobile application to visualize the data and provide threshold alarms, addressing the issues of bulky, cumbersome operation, and delayed data transmission associated with traditional devices.

[0004] Traditional gastric tube aspiration relies on invasive procedures, posing risks such as aspiration and mucosal damage. It is not suitable for infants and young children, and clinical procedures require specialized personnel and are difficult to perform frequently. This leads to discrete monitoring data and an inability to continuously track gastric emptying dynamics. Existing ultrasound detection equipment is bulky and has complex operating procedures. It relies on offline data export and manual analysis, making it difficult to meet the needs of home or mobile care settings, limiting its scope of application. Ultrasound imaging technology is not optimized for the gastric morphology and body position changes of infants and young children. Reflected signals are susceptible to artifacts from gastric wall peristalsis and spatial mapping errors, and data accuracy is significantly affected by the dynamic environment. Data transmission relies on wired connections or non-real-time protocols, making it impossible to synchronize multi-dimensional physiological parameters, resulting in delayed alarm responses and difficulty supporting rapid clinical decision-making. Traditional algorithms do not integrate dynamic parameters such as enteral nutrition intake rate and gastric emptying curves. The residual volume calculation results lack real-time compensation capabilities and cannot adapt to the rapidly changing physiological state of infants and young children, reducing the clinical value of monitoring results. Existing alarm mechanisms are mostly based on static thresholds and do not combine gastric emptying rate graded triggering operation recommendations, resulting in an increased risk of false alarms or missed alarms, affecting the timeliness and safety of feeding plan adjustments. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an ultrasonic gastric residual volume monitoring Bluetooth transmission device during enteral nutrition for infants.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A Bluetooth transmission device for ultrasonic gastric residual volume monitoring during enteral nutrition for infants and young children, comprising a main body structure and a transmission device-mounted control system. The transmission device-mounted control system comprises:

[0008] The ultrasound signal acquisition module detects the multi-band reflection signals emitted by the ultrasound probe on the infant's abdomen, selects the target frequency band that matches the acoustic impedance characteristics of the gastric fluid, dynamically adjusts the probe transmission power based on the abdominal wall thickness, and generates a gastric fluid reflection characteristic map;

[0009] The signal processing module calls the gastric liquid reflection characteristic map, combines it with the three-dimensional morphological model of the infant's stomach cavity, corrects the reflection signal spatial mapping deviation and body position change offset, and generates three-dimensional distribution data of the gastric liquid;

[0010] The Bluetooth transmission module calls the three-dimensional distribution data of the gastric fluid, divides the data packet according to the interference intensity of the environmental signal, embeds the timing tag and the device identification code, and generates an anti-interference gastric residual volume data packet;

[0011] The residual volume calculation module parses the anti-interference gastric residual volume data packet, calculates the gastric liquid volume integral value, modifies the integral parameter based on the infant enteral nutrition intake rate and the gastric emptying curve, and generates a dynamic compensated gastric residual volume value;

[0012] The graded alarm module determines whether to trigger an enteral nutrition suspension plan or a medical intervention alarm based on the dynamically compensated gastric residual volume value and the infant enteral nutrition safety threshold, and generates an enteral nutrition status graded alarm instruction.

[0013] Optionally, the gastric liquid reflection characteristic map includes the target frequency band reflection signal, the transmission power adjustment parameter, and the abdominal wall thickness matching coefficient; the gastric liquid three-dimensional distribution data includes the spatial mapping correction factor, the signal offset compensation amount, and the gastric cavity three-dimensional morphological model; the anti-interference gastric residual volume data packet includes a timing label, a device unique identification code, and a data segmentation structure; the dynamically compensated gastric residual volume value includes a volume integral value, an enteral nutrition intake rate, and a gastric emptying curve parameter; the enteral nutrition status graded alarm instruction includes an enteral nutrition pause instruction, a medical intervention alarm, and a safety threshold judgment basis.

[0014] Optionally, the ultrasonic signal acquisition module includes:

[0015] The signal detection submodule detects the ultrasound probe's transmitted signal when the infant's abdomen is attached, obtains multi-band reflected signals, extracts the reflected content that does not exceed the detection requirements based on the time delay and reception intensity of the frequency bands, and combines parameters based on the abdominal attachment area and signal amplitude to generate the abdominal reflection echo intensity value;

[0016] The frequency band screening submodule extracts the acoustic impedance ratio corresponding to the frequency band based on the abdominal reflection echo intensity value, calls the acoustic impedance parameters of the infant's gastric fluid, compares the matching degree of the two types of parameters, and screens the frequency band set whose acoustic impedance difference meets the threshold condition to generate a liquid matching frequency band group;

[0017] The power control submodule obtains the estimated value of the infant's abdominal wall thickness based on the liquid matching frequency band group, determines the probe transmission power range corresponding to the frequency band based on the relationship between the reflection signal penetration characteristics and thickness, selects the power value combination with the response amplitude in the target range for transmission and reception operations, and establishes the intragastric liquid reflection characteristic map.

[0018] Optionally, the signal processing module includes:

[0019] The reflection map acquisition submodule extracts the reflection intensity, time delay and detector position data based on the gastric fluid reflection characteristic map, compares the detector array order with the signal mapping order, identifies the signal mapping direction and arrangement deviation amplitude, and generates reflection mapping calibration data;

[0020] The morphological matching submodule calls the reflection mapping calibration data, combines the volume node coordinates, the gastric wall boundary curvature points and the detector mapping rules in the infant stomach cavity three-dimensional morphological model, locates the mapping position of the calibration signal in the three-dimensional coordinate system, determines the offset between the calibration signal and the morphological boundary, and obtains the spatial offset correction vector value;

[0021] The distribution calculation submodule integrates the reflection intensity and the node attitude angle data according to the spatial offset correction vector value, and associates the spatial relationship between the time delay and the node coordinates to generate the three-dimensional distribution data of the gastric fluid.

[0022] Optionally, the Bluetooth transmission module includes:

[0023] The signal sensing submodule obtains the three-dimensional distribution data of the gastric fluid and the radio spectrum signal in the infant ward, calculates the interference disturbance rate value by combining the interference intensity, duration and frequency of the different frequency bands, identifies the disturbance change within the interference peak interval, and generates the interference disturbance rate value;

[0024] The data segmentation submodule establishes a joint ratio relationship according to the interference disturbance rate value and the data density of the nodes in the three-dimensional distribution data, selects the corresponding segment and adjusts the data packet structure, defines the segmentation range, and generates the segmentation data length interval value;

[0025] The label reassembly submodule embeds timing labels and device identification information according to the data segments determined by the data length interval values, reassembles the data numbers, and the receiving end completes sequence verification and offset judgment to generate an anti-interference gastric residual volume data packet.

[0026] Optionally, the specific calculation formula for calculating the interference disturbance rate value is:

[0027]

[0028] Among them, D rate represents the interference disturbance rate value, j represents the total number of radio frequency bands detected, P i Represents the interference intensity corresponding to the i-th frequency band, in decibel milliwatts, T i Represents the duration of interference in the ith frequency band, in seconds, f i Represents the frequency of interference events in the i-th frequency band.

[0029] Optionally, the residual amount calculation module includes:

[0030] The anti-interference analysis submodule obtains the signal time series, noise interference value and original liquid volume data in the anti-interference gastric residual volume data packet, calculates the average offset value of the continuous liquid volume based on the relationship between the noise interference change and the volume offset corresponding to the time point, determines the range of change of the continuous liquid volume over time, and generates the continuous liquid volume interval value;

[0031] The integral parameter correction submodule calls the continuous liquid volume interval value, the infant enteral nutrition intake rate and the gastric emptying curve data, combines the volume change trend of the time period with the difference between the intake and emptying rhythm, corrects the original volume change ratio segment, and generates a corrected volume trend coefficient;

[0032] The dynamic compensation calculation submodule evaluates the flow state of the contents in the time period based on the linkage relationship between the modified volume trend coefficient and the current intake rate data, and dynamically compensates the current volume evolution path, constructs the gastric volume estimation structure at the complete time point, and generates a dynamically compensated gastric residual volume value.

[0033] Optionally, the specific calculation formula for calculating the continuous average liquid volume offset value is:

[0034]

[0035] Where, ΔV d (t) represents the average liquid volume offset value at the current time point t, V x Represents the original liquid volume data collected at the xth moment, N xrepresents the noise interference value corresponding to the xth moment, y represents the total number of sampling data points used for calculation, and V0 represents the liquid volume data at the initial time point.

[0036] Optionally, the hierarchical alarm module includes:

[0037] The residual state assessment submodule extracts the variation amplitude characteristics of the residual volume during the nutritional infusion process based on the comparative relationship between the dynamic compensation residual volume value and the infant infusion volume record and the resting gastric fluid baseline volume, and classifies the stage trend in combination with the gastric fluid emptying rhythm data to obtain the gastric content residual state data;

[0038] The excursion feature extraction submodule extracts the residual change gradient at continuous time nodes based on the change relationship between the gastric content residual state data and the staged gastric capacity reference range, calculates the residual dynamic excursion intensity characteristic value based on the slope interval distribution of the periodic change rate, refines the residual dynamic excursion intensity feature, and obtains the excursion dynamic prediction analysis result;

[0039] The level signal determination submodule determines the current risk level interval based on the degree of deviation between the offset dynamic prediction analysis result and the infant enteral nutrition safety threshold, combined with the intervention level benchmark range set by the system, and obtains the enteral nutrition status graded alarm instruction.

[0040] Optionally, the specific calculation formula for calculating the residual dynamic offset strength characteristic value is:

[0041]

[0042] Among them, θ Δv represents the residual dynamic offset strength characteristic value, v i represents the residual volume of gastric contents recorded at the i-th time node, v i+1 represents the gastric residual volume value recorded at the i+1th time node, ω i and ω i+1 Represent the stage-by-stage residual change adjustment coefficients corresponding to nodes i and i+1, respectively, i and t i+1 Respectively represent the recording time nodes, It represents the gastric capacity baseline value set for the current infant or young child at the corresponding stage, and n represents the total number of consecutive time intervals used for accumulation.

[0043] Compared with the prior art, the advantages and positive effects of the present invention are:

[0044] In the present invention, by screening the target frequency band to match the acoustic impedance characteristics of the gastric fluid, combining the abdominal wall thickness to dynamically tune the probe transmission power, reducing gas and tissue interference, improving signal accuracy, correcting the signal mapping deviation based on the three-dimensional model of the gastric cavity, compensating for body position deviation, generating a gastric fluid distribution model, enhancing accuracy, dynamically segmenting data packets and embedding timing tags to ensure complete transmission and anti-interference, combining the intake rate and gastric emptying curve to correct parameters, quantifying the volume and compensating for errors, improving calculation reliability, generating graded alarm instructions to link clinical operations, realizing closed-loop management, and improving real-time monitoring and decision-making timeliness. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a system flow chart of the present invention;

[0046] Figure 2 This is a system block diagram of the present invention. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0048] In the description of the present invention, it should be understood that the terms "length," "width," "up," "down," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inside," "outside," and the like, indicating positions or relationships, are based on the positions or relationships shown in the accompanying drawings and are intended only to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, in the description of the present invention, "plurality" means two or more, unless otherwise expressly and specifically defined.

[0049] See also Figure 1 , a Bluetooth transmission device for monitoring gastric residual volume during enteral nutrition for infants and young children, the device comprising a main body structure and a transmission device equipped with a control system: the transmission device equipped with a control system comprises:

[0050] The ultrasound signal acquisition module detects the multi-band reflection signals emitted by the ultrasound probe attached to the infant's abdomen, selects the target frequency band that matches the acoustic impedance characteristics of the infant's gastric fluid, dynamically adjusts the probe's transmission power based on the infant's abdominal wall thickness, and generates a gastric fluid reflection feature map.

[0051] The signal processing module uses the gastric fluid reflection feature map and combines it with the three-dimensional morphological model of the infant's stomach cavity to correct the spatial mapping deviation of the reflection signal, compensate for the signal offset caused by body position changes, and generate three-dimensional distribution data of the gastric fluid;

[0052] The Bluetooth transmission module dynamically segments data packets based on the three-dimensional distribution data of gastric fluid and the intensity of environmental signal interference in the infant ward. The data packets are then embedded with timing tags and unique device identification codes. The receiving end then verifies and reassembles the data packets to generate interference-resistant gastric residual volume data packets.

[0053] The residual volume calculation module parses the anti-interference gastric residual volume data packet, calculates the integral value of the gastric liquid volume, combines the infant's enteral nutrition intake rate with the gastric emptying curve to dynamically correct the integral calculation parameters, and generates a dynamic compensation gastric residual volume value;

[0054] The graded alarm module determines whether to trigger the enteral nutrition suspension plan or medical intervention alarm based on the dynamic compensation gastric residual volume value and the infant enteral nutrition safety threshold, and generates a graded alarm instruction for the enteral nutrition status.

[0055] The gastric liquid reflection characteristic map includes the target frequency band reflection signal, transmission power adjustment parameters, and abdominal wall thickness matching coefficient. The three-dimensional distribution data of the gastric liquid includes the spatial mapping correction factor, the signal offset compensation amount, and the three-dimensional morphological model of the gastric cavity. The anti-interference gastric residual volume data packet includes the timing label, the device unique identification code, and the data segmentation structure. The dynamic compensation gastric residual volume value includes the volume integral value, the enteral nutrition intake rate, and the gastric emptying curve parameters. The enteral nutrition status graded alarm instructions include the enteral nutrition suspension instruction, the medical intervention alarm, and the safety threshold judgment basis.

[0056] See also Figure 2 , the ultrasonic signal acquisition module includes:

[0057] The signal detection submodule detects the ultrasound probe's transmitted signal when the infant's abdomen is attached, obtains multi-band reflected signals, extracts the reflected content that does not exceed the detection requirements based on the time delay and reception intensity of the frequency bands, and combines parameters based on the abdominal attachment area and signal amplitude to generate the abdominal reflection echo intensity value;

[0058] During the execution of the ultrasonic signal detection module, it is first necessary to confirm the fit quality between the probe and the infant's abdomen, and use a contact pressure sensor to judge the fit. The pressure value applied per unit area is used for judgment. If the value exceeds 1.5 kPa, it can be considered to be in good fit. Otherwise, the angle and position of the probe need to be readjusted. The system then starts the multi-band signal transmission mechanism, and sends a group of ultrasonic pulse signals every 1 MHz in the frequency range of 2 MHz to 10 MHz. At the same time, the return time and intensity of the reflected signal are recorded. The acquisition cycle is 5 milliseconds, and at least 100 groups of data are continuously collected for analysis. The maximum echo intensity and time delay are extracted for each frequency band. , screen out data with a delay of more than 10 microseconds or an intensity lower than 20 decibels, and retain only the data groups that meet the requirements for subsequent processing. In the retained data, each group of echo intensity and the fitting area are combined and calculated to reflect the signal strength per unit area. For example, the fitting area is 12.5 square centimeters. If the echo intensity of a certain frequency band is 35 decibels, the combination value of this frequency band is 437.5. If there are 5 valid frequency bands, the calculated combination values ​​are 437.5, 410.2, 392.7, 465.0 and 450.8 respectively, and the average value is 431.24, which is used as the representative value of the echo intensity of the entire abdominal area for subsequent analysis.

[0059] The frequency band screening submodule extracts the acoustic impedance ratio corresponding to the frequency band based on the abdominal reflection echo intensity value, calls the acoustic impedance parameters of the infant's gastric fluid, compares the matching degree of the two types of parameters, and screens the frequency band set whose acoustic impedance difference meets the threshold condition to generate the liquid matching frequency band group;

[0060] The frequency band screening module performs acoustic impedance comparison analysis on each frequency band based on the abdominal echo intensity value. First, the reference acoustic impedance parameters of the gastric fluid are obtained. This parameter is determined by the type of liquid. For example, the density of breast milk is about 1030 kilograms per cubic meter and the speed of sound is about 1470 meters per second. After multiplication, the reference value of liquid acoustic impedance is about 1.51 million Rayles. Then, the acoustic impedance value of the reflected signal in each frequency band is estimated. This estimation is calculated by the ratio of the reflected signal intensity to the transmitted signal intensity and combined with the known acoustic impedance constant of the abdominal wall tissue. For example, if the reflection intensity is higher than 30 points, the acoustic impedance value of the gastric fluid is higher than 30 points. If the ratio of the acoustic impedance to the emission intensity reaches a certain standard, the acoustic impedance of the corresponding frequency band can be close to the liquid reference value. The difference between the acoustic impedance values ​​of all frequency bands and the liquid acoustic impedance is judged. When the difference is lower than the set threshold of 300,000 Rael, it is judged as a matching frequency band. For example, if the acoustic impedance of a certain frequency band is 1.48 million Rael, the difference with breast milk is 31,000 Rael, which is far below the threshold and is judged as an effective match. After this method is applied to all frequency bands, a set of frequency bands that meet the conditions are finally screened out to form a liquid matching frequency band group for subsequent power adjustment and signal enhancement operations.

[0061] The power control submodule obtains an estimated value of the infant's abdominal wall thickness based on the liquid matching frequency band group. Combining the relationship between the reflection signal penetration characteristics and thickness, it determines the probe transmission power range corresponding to the frequency band. It selects a power value combination with a response amplitude within the target range for transmission and reception operations, and establishes a characteristic map of the intragastric liquid reflection.

[0062] After receiving the frequency band screening results, the power control module needs to adjust the power according to the thickness of the infant's abdominal wall. First, the thickness of the abdominal wall is estimated based on the delay time of the reflected signal. The speed of sound is about 1580 meters per second. If the signal delay time is 7 microseconds, the thickness can be obtained to be about 5.53 mm. This value is used as the basic parameter for transmitting power adjustment. In the matching frequency band, the ability of each frequency to penetrate the abdominal wall is analyzed one by one. The higher the frequency, the shorter the wavelength and the smaller the penetration depth. A higher power is required to improve the quality of the reflected signal. For example, the wavelength of the 5 MHz frequency band is about 0.316 mm, and the penetration ability is about 0.38 mm. It is much lower than the thickness of the abdominal wall, so a relatively high transmission power should be set, and the power range needs to be controlled within the range that meets the safety standards. For example, the lower limit is set to 12 milliwatts to ensure that the minimum reflected signal can be identified, and the upper limit is set to 25 milliwatts to prevent excessive energy from causing local overheating. Each frequency band selects a power value within the range of 28 to 40 decibels for transmission according to the actual echo intensity change. After transmission, the signal echo is collected again to form a reflection intensity matrix corresponding to the frequency band and power, and an image is established to reflect the reflection characteristics of the gastric fluid under different frequency band and power combinations for structural analysis and subsequent identification operations.

[0063] See also Figure 2 , the signal processing module includes:

[0064] The reflection map acquisition submodule extracts reflection intensity, time delay, and detector position data based on the gastric fluid reflection characteristic map. It compares the detector array sequence with the signal mapping sequence, identifies the signal mapping direction and arrangement deviation amplitude, and generates reflection mapping calibration data.

[0065] The reflection map acquisition submodule decomposes and processes the signals collected from the multi-channel detector array according to the reflection characteristic map of the liquid in the stomach. The detectors are arranged in a regular six-by-six array and numbered in sequence to calibrate the spatial order. Each detector will record the signal waveform of the sound wave propagating inside the liquid and reflected back. The extraction of reflection intensity is based on the difference between the peak value of the echo signal and the background noise. Usually, the peak value exceeds 2 times the average amplitude of the background as the judgment standard for an effective reflection signal. For example, if the background is 30 millivolts and the peak value is 90 millivolts, then the point is valid. The acquisition of time delay requires comparing the absolute time points of signal transmission and reception. The time difference is combined with the sound speed of the medium in the gastric cavity, usually 1500 meters per second, to estimate the signal propagation distance. For example, if the time delay is 20 microseconds, the propagation path is 30 mm. The position of the detector is based on the array The column index is assigned to the initial two-dimensional coordinates. The matching between the number corresponding to each signal and the array number requires the construction of an index table for comparison during data decoding. The signal mapping direction is determined by analyzing the direction of the displacement vector constructed between adjacent reflection points. If the average value of the angle between adjacent vectors is greater than 15 degrees, it is considered that the signal arrangement has shifted. In actual scenarios, if the waveform distribution received by multiple groups of detectors deviates from the preset arrangement order, it means that an arrangement error has occurred during the acquisition process. The amplitude of the arrangement deviation can be determined by the mean of the distance difference between consecutive vectors. The ideal arrangement is a uniform straight line interval. If the position of a detector deviates from its theoretical value by more than 5 mm, it is considered that calibration is required. The final data set contains reflection intensity, time delay, position coordinates, and offset vector, and is uniformly labeled with mapping numbers for subsequent processing.

[0066] The morphological matching submodule calls the reflection mapping calibration data, combines the volume node coordinates in the infant stomach cavity 3D morphological model, the gastric wall boundary curvature points and the detector mapping rules, locates the mapping position of the calibration signal in the 3D coordinate system, determines the offset between it and the morphological boundary, and obtains the spatial offset correction vector value;

[0067] The morphological matching submodule maps the detector signal to a three-dimensional gastric cavity model based on the previously generated reflection mapping calibration data. The model is constructed from a high-density volume grid, and each node has three-dimensional coordinate attributes. The projection process maps the two-dimensional detector plane position to the three-dimensional structure surface through a set of affine transformations. This mapping is formed by fitting the actual infant abdominal wall structure. The gastric wall boundary is extracted using curvature point sampling, and feature points are often extracted at equal intervals of every 5 mm. During positioning, the curvature point closest to the detector reflection position is selected for comparison. If the spatial distance between the two exceeds the set tolerance threshold, such as 5 mm, it is considered that there is a significant offset, and the offset vector value in the three-dimensional coordinates is calculated. This vector is used for subsequent distribution correction to form a spatial consistency input between the signal and the model.

[0068] The distribution calculation submodule integrates the reflection intensity and node attitude angle data based on the spatial offset correction vector value, and associates the spatial relationship between time delay and node coordinates to generate three-dimensional distribution data of gastric fluid;

[0069] The distribution calculation submodule applies the aforementioned correction vector to each volume node in the three-dimensional lattice model and associates the corrected position with the original reflection intensity data. In addition, considering that the liquid surface may be tilted, the attitude angle of each node is also included in the correction factor of the reflection intensity. When the attitude angle is 0 degrees, there is no adjustment. If the angle is 60 degrees, only half of the intensity is retained. As the angle increases, the reflection intensity correction value decreases. Combined with the node time delay data, it estimates the spatiotemporal propagation path between it and the detector and establishes a point-to-voxel mapping relationship. The three-dimensional space is divided into a grid, and each stereo pixel unit integrates multiple detection signals. Different weights are assigned according to the distance from the center point. The closer the distance, the greater the weight. For example, if the distance is 5 mm, the weight is 1, and if the distance is 15 mm, the weight is reduced to 1 / 3. Through weighted calculation, the average reflection intensity value in each spatial unit is summarized, thereby establishing a three-dimensional distribution image of the gastric fluid, and outputting the center position of the high-density liquid area and the boundary point of the distribution range.

[0070] See also Figure 2 , the Bluetooth transmission module includes:

[0071] The signal sensing submodule obtains the three-dimensional distribution data of gastric fluid and the radio spectrum signal in the infant ward. It combines the interference intensity, duration and frequency of different frequency bands to calculate the interference disturbance rate value, identify the disturbance changes within the interference peak interval, and generate the interference disturbance rate value.

[0072] The specific calculation formula for calculating the interference disturbance rate value is:

[0073]

[0074] Among them, D rate represents the interference disturbance rate value, j represents the total number of radio frequency bands detected, P i Represents the interference intensity corresponding to the i-th frequency band, in decibel milliwatts, T i Represents the duration of interference in the ith frequency band, in seconds, f i Represents the frequency of interference events in the i-th frequency band;

[0075] The interference disturbance rate value represents the average disturbance performance of multi-band interference characteristics in the radio interference environment of the ward under multiple dimensions such as intensity, duration, and frequency.

[0076] Interference intensity P iThe acquisition is based on the real-time power monitoring value of the spectrum analyzer or embedded RF sensing module. The unit is decibel milliwatt. The reasonable value range is usually -90dBm to -30dBm. After converting to milliwatt power, use the logarithmic conversion formula:

[0077]

[0078] When the monitoring value is -60dBm, the calculation results are:

[0079] P1=10 -6 =0.000001mW;

[0080] To ensure that the calculation scale is operational, the interference intensity needs to be uniformly converted into milliwatt units for calculation;

[0081] Interference duration T i The data is obtained by counting the number of seconds the signal continuously exceeds the interference threshold. The threshold is set to -75dBm by the software. When the interference intensity exceeds the threshold and persists continuously, the system starts counting until the signal drops below the threshold, forming a complete record in seconds. In the 2.4GHz frequency band within the ward, the interference duration was measured to be 6 seconds.

[0082] Interference frequency f i Indicates the number of interference events detected in the frequency band within a 1-minute time window. Each event must meet the interference intensity higher than the threshold and last for more than 0.2 seconds to be defined as a valid interference. The wireless RF monitoring module detected a total of 9 valid interference events in the 2.4GHz frequency band during the 1-minute sampling period, resulting in:

[0083] f1=9;

[0084] Substituting the above data into the formula, the number of frequency bands j = 3, and monitoring frequency bands 1, 2, and 3 respectively, the recorded values ​​are as follows:

[0085] Band 1:

[0086] Interference intensity 60dBm, corresponding power 0.000001mW, interference duration 6 seconds, interference frequency 9

[0087] Band 2:

[0088] Interference intensity 5dBm, corresponding to power 0.0000032mW, interference duration 4 seconds, interference frequency 5

[0089] Band 3:

[0090] Interference intensity 70dBm, corresponding power 0.0000001mW, interference duration 10 seconds, interference frequency 12

[0091] Substitute into the formula:

[0092]

[0093] Calculate the square root of each numerator:

[0094] Item 1:

[0095] The denominator is 10, which gives 0.0006;

[0096] Item 2:

[0097] The denominator is 6, which gives approximately 0.00119;

[0098] Item 3: The denominator is 13, which gives approximately 0.00024

[0099] Add the three terms and find the average:

[0100]

[0101] The results show that the combined interference perturbation rate of the three main frequency bands during the current period is 0.0006767, representing the average level of interference energy density in space and time. This value is compared with the interference alarm threshold in the signal perception submodule to determine whether the current interference perturbation has entered the early warning stage. If the system sets the warning value to 0.0005, the current result has exceeded the set boundary and should be determined to be in the active interference perturbation range. This value can be used as the initial input parameter for subsequent modules to further trace the disturbance signal, isolate the interference, and promote environmental adjustment strategies.

[0102] The data segmentation submodule establishes a joint ratio relationship based on the interference disturbance rate value and the data density of the nodes in the three-dimensional distribution data, selects the corresponding segment and adjusts the data packet structure, defines the segmentation range, and generates the segmentation data length interval value;

[0103] The data segmentation submodule constructs a node data density model based on the interference perturbation rate and the node density in the three-dimensional distribution data. It extracts the location and unit data volume of each node and calculates the data density per unit volume. For example, if a node holds 2 kilobytes of data within a 1 cubic centimeter space, the density of that node is 2 kilobytes per cubic centimeter. A joint ratio is calculated based on each node's interference perturbation rate and density to determine whether it falls within a set ratio range, identifying the candidate segmentation region. For example, if the joint ratio threshold is 80 microvolt hertz centimeters per kilobyte, if a node has an interference perturbation rate of 160 microvolt hertz and a density of 2 kilobytes per cubic centimeter, the node's joint ratio is 80, meeting the screening criteria. By aggregating the nodes that meet the criteria, a minimum spatial boundary is established to identify candidate data segments. For the original data packets in the preselected region, if the length exceeds 256 kilobytes, they are split into two 150-kilobyte segments in equal proportion. If the length is less than 64 kilobytes, the packets are merged or padded to ensure that the resulting data packets are within the transmittable range. This results in the segmentation length configuration parameters for each new data packet.

[0104] The label reassembly submodule embeds the timing label and device identification information according to the data segments determined by the data length interval value, reorganizes the data numbers, and the receiving end completes the sequence check and offset judgment to generate an anti-interference gastric residual quantity data packet;

[0105] The label reassembly submodule embeds timing information and device identification into the divided data segments. Each data segment is embedded with a time tag and device number at the beginning. For example, if the embedded time is 10:45:30 on a certain day, the device number is 001, forming a labeled data header. The data segment numbers are incremented starting from 1000, and the number information of each segment is identified segment by segment. After receiving the data, the receiving end uses the number information to determine whether the data sequence is continuous. If there is a skip between numbers, it is considered a data offset anomaly. At the same time, the time between adjacent segments is determined based on the time tag. If the time interval exceeds the set maximum error, such as 5 seconds, it is identified as a missequence or data loss. Finally, the data segments are reassembled in sequence into complete labeled data packets and used for subsequent processing to ensure that the information has good continuity and accuracy in a spectrum interference environment.

[0106] See also Figure 2 , the residual calculation module includes:

[0107] The anti-interference analysis submodule obtains the signal time series, noise interference value and original liquid volume data in the anti-interference gastric residual volume data packet, calculates the average offset value of the continuous liquid volume based on the relationship between the noise interference change and volume offset corresponding to the time point, determines the range of change of the continuous liquid volume over time, and generates the continuous liquid volume interval value;

[0108] The specific calculation formula for calculating the average offset value of continuous liquid volume is:

[0109]

[0110] Where, ΔV d (t) represents the average liquid volume offset value at the current time point t, V x Represents the original liquid volume data collected at the xth moment, N x represents the noise interference value corresponding to the xth moment, y represents the total number of sampling data points used for calculation, and V0 represents the liquid volume data at the initial time point;

[0111] ΔV d (t) represents the average liquid volume offset value at the current time point t, in milliliters,

[0112] y represents the total number of sampling times, which is 5. Based on the signal sampling frequency of 1 time every 15 minutes, 5 valid data are continuously obtained within 1 hour.

[0113] V x The liquid volume data obtained by the x-th sampling, measured by the ultrasonic sensor, are 20.6, 19.7, 18.9, 18.0, and 17.4 ml, respectively.

[0114] N x The noise interference value extracted at the xth sampling time is converted into volume interference equivalent through signal filtering residual analysis, which are 0.4, 0.3, 0.2, 0.5, and 0.4 ml respectively.

[0115] V0 represents the liquid volume value at the initial time point, which is obtained from the first sampling and is 20.6 ml.

[0116] The calculation process is as follows:

[0117] The first step is to add the original volume of each sampling point to the corresponding interference value:

[0118] Group 1: 20.6 + 0.4 = 21.0;

[0119] Group 2: 19.7 + 0.3 = 20.0;

[0120] Group 3: 18.9 + 0.2 = 19.1;

[0121] Group 4: 18.0 + 0.5 = 18.5;

[0122] Group 5: 17.4 + 0.4 = 17.8;

[0123] The second step is to sum the above five items:

[0124] 21.0+20.0+19.1+18.5+17.8=96.4;

[0125] The third step is to find the average value:

[0126] 96.4÷5=19.28;

[0127] Step 4: Substitute the formula to calculate the average offset value:

[0128] ΔV d (t) = 19.28-20.6 = -1.32;

[0129] The result shows that the average liquid volume offset at the current time point is -1.32 ml. A negative value indicates that the overall volume is on a downward trend, and the change is within the safety benchmark range. If the intervention threshold is set to an offset of more than 5 ml, an early warning will be issued. This is still within the normal fluctuation range and can be used as basic data for trend analysis and input into the subsequent risk assessment module.

[0130] The integral parameter correction submodule calls the continuous liquid volume interval value, infant enteral nutrition intake rate and gastric emptying curve data, combines the volume change trend of the time period with the difference between the intake and emptying rhythm, corrects the original volume change ratio segment, and generates a corrected volume trend coefficient;

[0131] The integral parameter correction submodule is based on the continuous liquid volume interval value, infant nutrition intake rate and gastric emptying trend curve, and divides the volume interval according to the time period, such as 0 to 10 minutes, 10 to 20 minutes, etc., and calculates the median of the volume data of each interval as the representative volume. For example, the volume range of a certain interval is 40 to 44 ml, and the median is 42 ml. If the corresponding intake rate is constant at 5 ml per minute within 10 minutes, the total intake is 50 ml. At the same time, according to the gastric emptying characteristics, refer to the clinical emptying rate change trend, such as 3.5 to 4 ml per minute, and compare the volume change in the same time period with the difference between the intake and the emptying volume to evaluate the actual change trend of gastric contents. If the volume growth rate is lower than the intake rate, it may be caused by accelerated emptying, otherwise it may be due to slower emptying. For example, consider real-world data. For a specific period, the liquid volume change rate is 0.8 ml / minute, the intake rate is 5 ml / minute, and the emptying trend is 3.9 ml / minute. The difference between volume growth and intake and emptying is 1.1 ml, and the volume change trend accounts for approximately 73%. Based on this, the volume change ratio for the current period is slightly lower than expected, so the coefficient for that period is adjusted to 0.73 in subsequent calculations. This method is applied sequentially to all time periods to form the corrected trend parameters, such as 0.73 for the 0-10 minute period and 0.94 for the 10-20 minute period.

[0132] The dynamic compensation calculation submodule evaluates the flow state of the contents during the time period based on the linkage relationship between the corrected volume trend coefficient and the current intake rate data, and dynamically compensates the current volume evolution path, constructing a gastric volume estimation structure at a complete time point and generating a dynamically compensated gastric residual volume value;

[0133] The dynamic compensation calculation submodule associates a modified volume trend coefficient with the intake rate to construct a continuous temporal structure for the change in gastric fluid volume. Starting with the initial volume data, the current intake rate is multiplied by the corresponding trend coefficient at each time point, and the cumulative volume growth value is calculated. For example, if the intake rate at a certain moment is 6 ml / min and the corresponding trend coefficient is 0.85, the volume change in that minute is 5.1 ml. Combined with the volume data from the previous time point, for example, if the volume at the 14th minute is 58 ml, the estimated volume at the 15th minute is 63.1 ml. Volume changes are gradually added minute by minute to construct a volume change sequence. During enteral feeding in infants and young children, if the intake rate drops to 3 ml / min and the emptying trend strengthens to 4 ml / min, the trend coefficient may drop to 0.6, and the volume may decrease rather than increase in the next minute. Based on this trend, the volume growth path needs to be corrected. For example, the original estimated volume should be 66 ml, but under the new conditions it is only 63.8 ml. This creates a volume estimate that better reflects the actual flow conditions at each time point, forming a complete and continuous structure for estimating gastric residual volume. At a certain point in time, such as 30 minutes, the volume can be deduced from the above data to be approximately 44.6 ml.

[0134] See also Figure 2 , the hierarchical alarm module includes:

[0135] The residual state assessment submodule extracts the amplitude characteristics of the residual volume during nutrition infusion based on the comparative relationship between the dynamic compensation residual volume value and the infant perfusion volume record and the resting gastric fluid baseline volume. It then classifies the stage trend based on the gastric fluid emptying rhythm data to obtain the gastric content residual state data.

[0136] During the execution of the residual state assessment submodule, it is necessary to rely on the volume data of each nutritional infusion of infants and young children, and conduct a systematic comparison in combination with the changes in the residual volume in the stomach and the baseline volume of gastric fluid in the resting period. First, the actual input volume is recorded during the infusion, for example, one infusion is recorded as 25 ml, and the current residual volume in the stomach is read through the ultrasound imaging device or the non-invasive vital sign monitoring module. For example, the residual volume before infusion is 10 ml, and the residual volume after infusion is 18 ml, that is, after inputting 25 ml, only 17 ml is emptied; compare this data with the baseline volume of gastric fluid in the resting period. If the reference volume of gastric fluid in the resting state of a 2.5 kg infant is 5 milliliters, the current residual volume is significantly higher than the baseline level; continuously record data at multiple time nodes, such as 18 ml, 15 ml, and 12 ml at 8 a.m., 11 a.m., and 2 p.m., respectively, and extract the changing trend of the residual volume in each time period. Combined with the gastric emptying rhythm of infants and young children, it is classified. If the daytime residual volume continues to decrease and is close to the baseline value, it is classified as a normal emptying type. On the contrary, if it remains at a high level for a long time and the change is not obvious, it is determined to be a retention type. The residual characteristic curve is formed by stage statistics and the state classification of each time period is marked, and finally a structured data set for the residual state of gastric contents during nutrition input is generated.

[0137] The excursion feature extraction submodule extracts the residual change gradient at continuous time nodes based on the changing relationship between the gastric content residual state data and the staged gastric capacity benchmark range. Combined with the slope interval distribution of the periodic change rate, it calculates the residual dynamic excursion intensity characteristic value, refines the residual dynamic excursion intensity feature, and obtains the excursion dynamic prediction analysis results.

[0138] The specific calculation formula for calculating the residual dynamic offset intensity characteristic value is:

[0139]

[0140] Among them, θ Δv represents the residual dynamic offset strength characteristic value, v i represents the residual volume of gastric contents recorded at the i-th time node (unit: ml), v i+1 represents the gastric residual volume value recorded at the i+1th time node, ω i and ω i+1 Respectively represent the stage-by-stage residual change adjustment coefficients (unitless, correction coefficients) corresponding to nodes i and i+1, t i and t i+1 Respectively represent the recording time node (unit: minute), Indicates the gastric capacity benchmark value set for the current infant or young child at the corresponding stage (unit: ml), and n indicates the total number of consecutive time intervals used for accumulation (the number of dimension items);

[0141] Parameter v iThis value represents the residual gastric volume of the infant at the i-th sampling time. This value is obtained through continuous gastric ultrasound imaging monitoring. Each sampling is performed using a non-invasive scan in a standard posture. For example, the first sampling point at 9:00 AM measured a residual volume of 17 mL; the second sampling point at 10:00 AM measured a residual volume of 14 mL.

[0142] Parameter v i+1 is the residual volume at the next adjacent sampling time node, obtained in the same way, and the value is 14 ml.

[0143] parameter This is a reference value for gastric capacity at certain stages, set based on infant weight. According to the recommendations of the Gastroenterology Group of the Chinese Medical Association's Pediatrics Branch, the average gastric capacity for newborns weighing 2.5 to 3 kg is 15 ml, so it is set here as 15.

[0144] Parameter t i With t i+1 The corresponding sampling time points are in minutes. The sampling times are 9:00 and 10:00, which are converted to 540 minutes and 600 minutes.

[0145] Parameter ω i With ω i+1 The residual volume adjustment coefficients for each time period are quantified using the gastric motility score. The scoring criteria are based on two indicators: gastric emptying rate and fluctuation frequency. Gastric motility is divided into five levels, with corresponding values ​​of 0.6, 0.75, 1.0, 1.25, and 1.5. In the first time period, the emptying rate is slow and the fluctuation frequency is low, resulting in a gastric motility score of 2 and a corresponding coefficient of 0.75. In the second time period, the emptying rate is increased and the fluctuation frequency is intensified, resulting in a gastric motility score of 4 and a corresponding coefficient of 1.25.

[0146] Substitute each parameter into the formula:

[0147]

[0148] Let’s calculate item by item first:

[0149] 14·1.25=17.5;

[0150] |17-15|=2, the square root is

[0151] 17·0.75=12.75;

[0152] The numerator is 17.5 + 1.41 - 12.75 = 6.16;

[0153] The denominator is 600+540=1140;

[0154] Evaluate the full expression:

[0155]

[0156] The results indicate that the residual dynamic shift intensity characteristic value for the current time interval is 0.0054. This value characterizes the degree of fluctuation in gastric residual volume over time, coupled with dynamic conditions. Larger values ​​indicate greater gastric residual fluctuation intensity. By averaging the shift intensity across intervals within a continuous time window, a shift dynamic trend curve can be constructed. This result will be incorporated into the dynamic prediction analysis input structure as a component of the individual interval shift characteristics.

[0157] The level signal determination submodule determines the current risk level based on the deviation between the offset dynamic prediction analysis results and the infant enteral nutrition safety threshold, combined with the intervention level benchmark range set by the system, and obtains the enteral nutrition status graded alarm instructions;

[0158] The level signal judgment submodule needs to compare the extracted dynamic results of the deviation with the preset infant enteral nutrition safety threshold. For example, if the current deviation average is 16 ml, and the system sets the safety threshold at 10 ml, the deviation exceeds 6 ml. The system sets the intervention level standard according to the degree of deviation. For example, deviations between 0 and 5 ml are classified as low risk, 6 to 10 ml are classified as medium risk, and more than 10 ml are classified as high risk. The current deviation is at a medium risk level. Continuous tracking is carried out in combination with the risk level trend. If the risk level is at a medium risk level for two consecutive time periods, it is automatically determined to enter an alert state and a yellow alarm signal is issued. If it continues to rise or reaches a high risk, it is upgraded to an orange signal. The system can record the frequency and duration of daily risk level changes, and form standardized grading instructions, which are transmitted to the nutrition management module or monitoring system through the status signal interface to achieve a graded early warning response to the current infant enteral nutrition status and ensure the accuracy of phased monitoring.

[0159] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. Ultrasonic gastric residual volume monitoring Bluetooth transmission device for infant enteral nutrition, characterized by: The device includes a main body structure and a transmission device equipped with a control system: the transmission device equipped with a control system includes: The ultrasound signal acquisition module detects the multi-band reflection signals emitted by the ultrasound probe on the infant's abdomen, selects the target frequency band that matches the acoustic impedance characteristics of the gastric fluid, dynamically adjusts the probe transmission power based on the abdominal wall thickness, and generates a gastric fluid reflection characteristic map; The signal processing module calls the gastric liquid reflection characteristic map, combines it with the three-dimensional morphological model of the infant's stomach cavity, corrects the reflection signal spatial mapping deviation and body position change offset, and generates three-dimensional distribution data of the gastric liquid; The Bluetooth transmission module calls the three-dimensional distribution data of the gastric fluid, divides the data packet according to the interference intensity of the environmental signal, embeds the timing tag and the device identification code, and generates an anti-interference gastric residual volume data packet; The residual volume calculation module parses the anti-interference gastric residual volume data packet, calculates the gastric liquid volume integral value, modifies the integral parameter based on the infant enteral nutrition intake rate and the gastric emptying curve, and generates a dynamic compensated gastric residual volume value; The graded alarm module determines whether to trigger an enteral nutrition suspension plan or a medical intervention alarm based on the dynamically compensated gastric residual volume value and the infant enteral nutrition safety threshold, and generates an enteral nutrition status graded alarm instruction.

2. The Bluetooth transmission device for ultrasonic gastric residual volume monitoring during enteral nutrition for infants according to claim 1, characterized in that: The gastric liquid reflection characteristic map includes the target frequency band reflection signal, the transmission power adjustment parameter, and the abdominal wall thickness matching coefficient; the gastric liquid three-dimensional distribution data includes the spatial mapping correction factor, the signal offset compensation amount, and the gastric cavity three-dimensional morphological model; the anti-interference gastric residual volume data packet includes a timing label, a device unique identification code, and a data segmentation structure; the dynamically compensated gastric residual volume value includes a volume integral value, an enteral nutrition intake rate, and a gastric emptying curve parameter; the enteral nutrition status graded alarm instruction includes an enteral nutrition suspension instruction, a medical intervention alarm, and a safety threshold judgment basis.

3. The Bluetooth transmission device for ultrasonic gastric residual volume monitoring during enteral nutrition for infants according to claim 1, characterized in that: The ultrasonic signal acquisition module includes: The signal detection submodule detects the ultrasound probe's transmitted signal when the infant's abdomen is attached, obtains multi-band reflected signals, extracts the reflected content that does not exceed the detection requirements based on the time delay and reception intensity of the frequency bands, and combines parameters based on the abdominal attachment area and signal amplitude to generate the abdominal reflection echo intensity value; The frequency band screening submodule extracts the acoustic impedance ratio corresponding to the frequency band based on the abdominal reflection echo intensity value, calls the acoustic impedance parameters of the infant's gastric fluid, compares the matching degree of the two types of parameters, and screens the frequency band set whose acoustic impedance difference meets the threshold condition to generate a liquid matching frequency band group; The power control submodule obtains the estimated value of the infant's abdominal wall thickness based on the liquid matching frequency band group, determines the probe transmission power range corresponding to the frequency band based on the relationship between the reflection signal penetration characteristics and thickness, selects the power value combination with the response amplitude in the target range for transmission and reception operations, and establishes the intragastric liquid reflection characteristic map.

4. The Bluetooth transmission device for ultrasonic gastric residual volume monitoring during enteral nutrition for infants according to claim 3, characterized in that: The signal processing module includes: The reflection map acquisition submodule extracts the reflection intensity, time delay and detector position data based on the gastric fluid reflection characteristic map, compares the detector array order with the signal mapping order, identifies the signal mapping direction and arrangement deviation amplitude, and generates reflection mapping calibration data; The morphological matching submodule calls the reflection mapping calibration data, combines the volume node coordinates, the gastric wall boundary curvature points and the detector mapping rules in the infant stomach cavity three-dimensional morphological model, locates the mapping position of the calibration signal in the three-dimensional coordinate system, determines the offset between the calibration signal and the morphological boundary, and obtains the spatial offset correction vector value; The distribution calculation submodule integrates the reflection intensity and the node attitude angle data according to the spatial offset correction vector value, and associates the spatial relationship between the time delay and the node coordinates to generate the three-dimensional distribution data of the gastric fluid.

5. The Bluetooth transmission device for ultrasonic gastric residual volume monitoring during enteral nutrition for infants according to claim 4, characterized in that: The Bluetooth transmission module includes: The signal sensing submodule obtains the three-dimensional distribution data of the gastric fluid and the radio spectrum signal in the infant ward, calculates the interference disturbance rate value by combining the interference intensity, duration and frequency of the different frequency bands, identifies the disturbance change within the interference peak interval, and generates the interference disturbance rate value; The data segmentation submodule establishes a joint ratio relationship according to the interference disturbance rate value and the data density of the nodes in the three-dimensional distribution data, selects the corresponding segment and adjusts the data packet structure, defines the segmentation range, and generates the segmentation data length interval value; The label reassembly submodule embeds timing labels and device identification information according to the data segments determined by the data length interval values, reassembles the data numbers, and the receiving end completes sequence verification and offset judgment to generate an anti-interference gastric residual volume data packet.

6. The Bluetooth transmission device for ultrasonic gastric residual volume monitoring during enteral nutrition for infants according to claim 5, characterized in that: The specific calculation formula for calculating the interference disturbance rate value is: Among them, D rate represents the interference disturbance rate value, j represents the total number of radio frequency bands detected, P i Represents the interference intensity corresponding to the i-th frequency band, in decibel milliwatts, T i represents the duration of interference in the ith frequency band, in seconds, f i Represents the frequency of interference events in the i-th frequency band.

7. The Bluetooth transmission device for ultrasonic gastric residual volume monitoring during enteral nutrition for infants according to claim 5, characterized in that: The residual amount calculation module includes: The anti-interference analysis submodule obtains the signal time series, noise interference value and original liquid volume data in the anti-interference gastric residual volume data packet, calculates the average offset value of the continuous liquid volume based on the relationship between the noise interference change and the volume offset corresponding to the time point, determines the range of change of the continuous liquid volume over time, and generates the continuous liquid volume interval value; The integral parameter correction submodule calls the continuous liquid volume interval value, the infant enteral nutrition intake rate and the gastric emptying curve data, combines the volume change trend of the time period with the difference between the intake and emptying rhythm, corrects the original volume change ratio segment, and generates a corrected volume trend coefficient; The dynamic compensation calculation submodule evaluates the flow state of the contents in the time period based on the linkage relationship between the modified volume trend coefficient and the current intake rate data, and dynamically compensates the current volume evolution path, constructs the gastric volume estimation structure at the complete time point, and generates a dynamically compensated gastric residual volume value.

8. The Bluetooth transmission device for ultrasonic gastric residual volume monitoring during enteral nutrition for infants according to claim 7, characterized in that: The specific calculation formula for calculating the average offset value of the continuous liquid volume is: Where, ΔV d (t) represents the average liquid volume offset value at the current time point t, V x Represents the original liquid volume data collected at the xth moment, N x represents the noise interference value corresponding to the xth moment, y represents the total number of sampling data points used for calculation, and V0 represents the liquid volume data at the initial time point.

9. The Bluetooth transmission device for ultrasonic gastric residual volume monitoring during enteral nutrition for infants according to claim 7, characterized in that: The hierarchical alarm module includes: The residual state assessment submodule extracts the variation amplitude characteristics of the residual volume during the nutritional infusion process based on the comparative relationship between the dynamic compensation residual volume value and the infant infusion volume record and the resting gastric fluid baseline volume, and classifies the stage trend in combination with the gastric fluid emptying rhythm data to obtain the gastric content residual state data; The excursion feature extraction submodule extracts the residual change gradient at continuous time nodes based on the change relationship between the gastric content residual state data and the staged gastric capacity reference range, calculates the residual dynamic excursion intensity characteristic value based on the slope interval distribution of the periodic change rate, refines the residual dynamic excursion intensity feature, and obtains the excursion dynamic prediction analysis result; The level signal determination submodule determines the current risk level interval based on the degree of deviation between the offset dynamic prediction analysis result and the infant enteral nutrition safety threshold, combined with the intervention level benchmark range set by the system, and obtains the enteral nutrition status graded alarm instruction.

10. The Bluetooth transmission device for ultrasonic gastric residual volume monitoring during enteral nutrition for infants according to claim 9, characterized in that: The specific calculation formula for calculating the residual dynamic offset strength characteristic value is: Among them, θ Δv represents the residual dynamic offset strength characteristic value, v i represents the residual volume of gastric contents recorded at the i-th time node, v i+1 represents the gastric residual volume value recorded at the i+1th time node, ω i and ω i+1 Represent the stage-by-stage residual change adjustment coefficients corresponding to nodes i and i+1, respectively, i and t i+1 Respectively represent the recording time nodes, It represents the gastric capacity baseline value set for the current infant or young child at the corresponding stage, and n represents the total number of consecutive time intervals used for accumulation.

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