Bluetooth transmission device for monitoring gastric residual volume during enteral nutrition in infants and young children

Abstract

This invention relates to the field of gastric residual volume detection technology, specifically a Bluetooth transmission device for ultrasound monitoring of gastric residual volume during enteral nutrition for infants and young children. The device includes a main body structure and a transmission device-mounted control system. The control system includes an ultrasound signal acquisition module, a signal processing module, a Bluetooth transmission module, a residual volume calculation module, and a graded alarm module. This invention achieves this by selecting a target frequency band to match the acoustic impedance characteristics of gastric fluid, dynamically tuning the probe's transmission power based on abdominal wall thickness to reduce gas and tissue interference and improve signal accuracy. It corrects signal mapping deviations based on a three-dimensional gastric cavity model, compensates for postural shifts, generates a gastric fluid distribution model to enhance accuracy, dynamically segments data packets and embeds time-series tags to ensure complete transmission and anti-interference capabilities, combines intake rate and gastric emptying curve correction parameters to quantify volume and compensate for errors, improving calculation reliability, and generating graded alarm commands to link with clinical operations.

Description

Technical Field

[0001] This invention relates to the field of gastric residual volume detection technology, and in particular to a Bluetooth transmission device for ultrasound monitoring of gastric residual volume during enteral nutrition for infants and young children. Background Technology

[0002] The field of medical monitoring equipment technology encompasses the research and application of equipment and methods related to monitoring gastric residual volume in infant enteral nutrition care. The core of this field involves assessing gastric fluid residue through technological means to guide nutritional delivery and prevent complications. Traditional techniques rely on gastric tube aspiration, which is invasive and carries risks. Existing improved techniques utilize ultrasound imaging for non-invasive detection; however, these devices are bulky, have complex operating procedures, and rely on offline data export, failing to meet the needs for real-time monitoring and convenient data transmission, thus limiting their widespread use in clinical and home settings.

[0003] Among them, the ultrasound gastric residual volume monitoring Bluetooth transmission device for infant enteral nutrition refers to a miniaturized monitoring device based on ultrasound 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 collects signals using a small ultrasound probe that fits snugly against the infant's abdomen, and synchronously transmits the data to a mobile terminal using Bluetooth technology. Combined with a mobile application, it enables data visualization and threshold alarm functions, solving the problems of bulky size, 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. Its applicability to infants and young children is limited, clinical operation requires specialized personnel and is difficult to perform frequently, resulting in discrete monitoring data and an inability to continuously track gastric emptying dynamics. Existing ultrasound detection equipment is bulky and complex to operate, relying on offline data export and manual analysis, which is insufficient for home or mobile care needs, limiting its application. Ultrasound imaging technology is not optimized for the gastric cavity morphology and positional changes of infants and young children; reflected signals are easily affected by gastric wall peristalsis artifacts and spatial mapping biases, significantly impacting data accuracy due to dynamic environments. Data transmission relies on wired connections or non-real-time protocols, unable to synchronously process multi-dimensional physiological parameters, leading to delayed alarm responses and hindering rapid clinical decision-making. Traditional algorithms do not integrate dynamic parameters such as enteral nutrition intake rate and gastric emptying curves; residual volume calculation results lack real-time compensation capabilities, failing to adapt to the rapidly changing physiological states of infants and young children, thus reducing the clinical guidance value of monitoring results. Existing alarm mechanisms are mostly based on static thresholds and do not incorporate gastric emptying rate grading triggering recommendations, which increases the risk of false alarms or missed alarms and affects the timeliness and safety of feeding program adjustments. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the existing technology and propose a Bluetooth transmission device for monitoring the gastric residual volume by ultrasound during enteral nutrition of infants and young children.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A Bluetooth transmission device for monitoring gastric residual volume via ultrasound during enteral nutrition in infants and young children, the device comprising a main body structure and a transmission device-mounted control system: the transmission device-mounted control system includes:

[0008] The ultrasound signal acquisition module detects multi-band reflected signals emitted by the ultrasound probe in the abdomen of infants and young children, selects target frequency bands that match the acoustic impedance characteristics of gastric fluid, dynamically adjusts the probe's transmission power based on the abdominal wall thickness, and generates a gastric fluid reflection feature map.

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

[0010] The Bluetooth transmission module calls the three-dimensional distribution data of the gastric fluid, segments the data packets according to the intensity of environmental signal interference, embeds time tags and device identification codes, and generates anti-interference gastric residual volume data packets.

[0011] The residual volume calculation module parses the anti-interference gastric residual volume data packet, calculates the gastric fluid volume integral value, corrects the integral parameters based on the infant enteral nutrition intake rate and gastric emptying curve, and generates a dynamically compensated gastric residual volume value.

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

[0013] Optionally, the gastric fluid reflection feature map includes the target frequency band reflection signal, transmission power adjustment parameters, and abdominal wall thickness matching coefficient; the gastric fluid three-dimensional distribution data includes a spatial mapping correction factor, signal offset compensation amount, and a three-dimensional morphological model of the gastric cavity; the anti-interference gastric residual volume data package includes a time sequence label, a unique device identifier, and a data segmentation structure; the dynamically compensated gastric residual volume value includes a volume integral value, enteral nutrition intake rate, and gastric emptying curve parameters; and the enteral nutrition status grading alarm instructions include enteral nutrition suspension instructions, medical intervention alarms, and safety threshold judgment criteria.

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

[0015] The signal detection submodule detects the signal emitted by the ultrasound probe attached to the infant's abdomen, acquires multi-band reflection signals, extracts the reflection content that does not exceed the detection requirements based on the time delay and received intensity of the frequency band, and generates the abdominal reflection echo intensity value by combining parameters according to the abdominal contact area and signal amplitude.

[0016] The frequency band filtering submodule extracts the acoustic impedance ratio corresponding to the frequency band based on the abdominal reflected echo intensity value, calls the acoustic impedance parameters of the infant's gastric fluid, compares the matching degree of the two types of parameters, filters the set of frequency bands whose acoustic impedance differences meet the threshold condition, and generates a fluid 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, and determines the probe transmission power range corresponding to the frequency band by combining the reflection signal penetration characteristics and the thickness relationship. It selects the power value combination with the response amplitude in the target range for transmission and reception operations, and establishes a gastric fluid reflection feature map.

[0018] Optionally, the signal processing module includes:

[0019] The reflection map acquisition submodule extracts reflection intensity, time delay and detector position data based on the gastric fluid reflection feature 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 morphology matching submodule calls the reflection mapping calibration data, combines the volume node coordinates, gastric wall boundary curvature points and detector mapping rules in the three-dimensional morphological model of the infant's stomach cavity, locates the mapping position of the calibration signal in the three-dimensional coordinate system, judges the offset between the calibration signal and the morphological boundary, and obtains the spatial offset correction vector value.

[0021] The distribution calculation submodule integrates 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.

[0022] Optionally, the Bluetooth transmission module includes:

[0023] The signal sensing submodule acquires the three-dimensional distribution data of the gastric fluid and the radio spectrum signal in the infant ward. It combines the interference intensity, duration and frequency of the different frequency bands to calculate the interference rate value, identify the disturbance changes in the interference peak range, and generate the interference rate value.

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

[0025] The tag recombination submodule embeds time-series tags and device identification information into the data segments determined by the segmented data length range value, recombines the data numbers, and the receiving end completes the sequence verification and offset judgment to generate an anti-interference gastric residual data packet.

[0026] Optionally, the specific formula for calculating the interference rate value is as follows:

[0027]

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

[0029] Optionally, the residual calculation module includes:

[0030] The anti-interference analysis submodule acquires the signal time series, noise interference value and original liquid volume data in the anti-interference gastric residual volume data packet. Based on the relationship between noise interference change and volume offset at the corresponding time point, it calculates the average offset value of continuous liquid volume, determines the range of continuous liquid volume variation over time, and generates continuous liquid volume interval values.

[0031] The integral parameter correction submodule calls the continuous liquid volume interval value, the infant enteral nutrition intake rate and gastric emptying curve data, and combines the difference between the volume change trend over time and the intake and emptying rhythm to correct the original volume change ratio segment and generate the corrected volume trend coefficient.

[0032] The dynamic compensation calculation submodule assesses the flow state of contents over a period of time based on the linkage between the corrected volume trend coefficient and the current intake rate data, and dynamically compensates for the current volume evolution path to construct a gastric volume estimation structure at a complete time point and generate a dynamically compensated gastric residual volume value.

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

[0034]

[0035] Where, ΔV d (t) represents the average offset of the liquid volume at the current time t, V x N represents the raw liquid volume data collected at time x. xy represents the noise interference value at time x, y represents the total number of sampled data points used for calculation, and V0 represents the liquid volume data at the initial time point.

[0036] Optionally, the tiered alarm module includes:

[0037] The residual state assessment submodule extracts the variation characteristics of residual volume during nutrient infusion based on the comparison between the dynamic compensation residual volume value and the infant perfusion volume record and the resting gastric fluid baseline volume. It then combines the gastric fluid emptying rhythm data to classify the phased trends and obtain the residual state data of gastric contents.

[0038] The offset feature extraction submodule extracts the residual change gradient at continuous time nodes based on the change relationship between the residual state data of the gastric contents and the staged gastric capacity benchmark range. Combined with the slope interval distribution of the periodic change rate, it calculates the residual dynamic offset intensity feature value, refines the residual dynamic offset intensity feature, and obtains the offset dynamic prediction analysis result.

[0039] The level signal determination submodule determines the current risk level range 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 grading alarm instruction.

[0040] Optionally, the specific formula for calculating the residual dynamic offset intensity characteristic value is as follows:

[0041]

[0042] Where, θ Δv Represents the residual dynamic migration intensity characteristic value, v i v represents the residual volume of gastric contents recorded at the i-th time point. i+1 ω represents the gastric residual volume recorded at the (i+1)th time point. i and ω i+1 t represents the adjustment coefficients for the stage-specific residual changes corresponding to nodes i and i+1, respectively. i and t i+1 These represent the recorded time points. This represents the baseline stomach capacity set for the current stage of infant development, 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 as follows:

[0044] In this invention, target frequency bands are selected to match the acoustic impedance characteristics of gastric fluid. Combined with the abdominal wall thickness, the probe's transmission power is dynamically tuned to reduce gas and tissue interference and improve signal accuracy. Based on a three-dimensional model of the gastric cavity, signal mapping deviations are corrected, and body position shifts are compensated to generate a gastric fluid distribution model, enhancing accuracy. Data packets are dynamically segmented and embedded with time-series tags to ensure complete transmission and anti-interference. Combined with intake rate and gastric emptying curve, parameters are corrected to quantify volume and compensate for errors, improving computational reliability. Graded alarm commands are generated to link clinical operations, achieving closed-loop management and improving the timeliness of real-time monitoring and decision-making. Attached Figure Description

[0045] Figure 1 This is a system flowchart of the present invention;

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

[0047] To make the objectives, technical solutions, and advantages of this invention clearer, the 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 merely illustrative and not intended to limit the invention.

[0048] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and 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, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0049] Please see Figure 1 A Bluetooth transmission device for monitoring gastric residual volume via ultrasound during enteral nutrition in infants and young children, the device comprising a main body structure and a transmission device-mounted control system: the transmission device-mounted control system includes:

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

[0051] The signal processing module calls the gastric fluid reflection feature map, combines it with the three-dimensional morphological model of the infant's stomach cavity, corrects the spatial mapping deviation of the reflection signal, compensates for the signal offset caused by changes in body position, and generates three-dimensional distribution data of gastric fluid.

[0052] The Bluetooth transmission module is based on the three-dimensional distribution data of gastric fluid. It dynamically segments data packets according to the signal interference intensity of the infant ward environment, embeds time-series tags and unique device identifiers, and generates anti-interference gastric residual volume data packets after verification and reconstruction at the receiving end.

[0053] The residual volume calculation module parses the anti-interference gastric residual volume data package, calculates the integral value of the gastric fluid volume, and dynamically corrects the integral calculation parameters by combining the infant's enteral nutrition intake rate and gastric emptying curve to generate a dynamically compensated gastric residual volume value.

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

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

[0056] Please see Figure 2 The ultrasonic signal acquisition module includes:

[0057] The signal detection submodule detects the signal emitted by the ultrasound probe attached to the infant's abdomen, acquires multi-band reflection signals, extracts the reflection content that does not exceed the detection requirements based on the time delay and received intensity of the frequency band, and generates the abdominal reflection echo intensity value by combining parameters according to the abdominal contact area and signal amplitude.

[0058] During the execution of the ultrasound signal detection module, the first step is to confirm the fit between the probe and the infant's abdomen. A contact pressure sensor is used to determine the fit, judging by the pressure applied per unit area. If this value exceeds 1.5 kPa, the fit is considered good; otherwise, the probe angle and position need to be readjusted. Subsequently, the system activates a multi-band signal transmission mechanism, emitting a set of ultrasound pulse signals every 1 MHz within the frequency range of 2 MHz to 10 MHz. Simultaneously, the return time and intensity of the reflected signals are recorded, with an acquisition period of 5 milliseconds. At least 100 sets of data are continuously acquired for analysis, and the maximum echo intensity and time delay are extracted for each frequency band. Data with delays exceeding 10 microseconds or intensities below 20 dB were filtered out, retaining only the data sets that met the requirements for subsequent processing. Within the retained data, the echo intensity of each set was combined with the contact area to calculate the signal strength per unit area. For example, if the contact area is 12.5 square centimeters and the echo intensity of a certain frequency band is 35 dB, then the combined value for that frequency band is 437.5. If there are five effective frequency bands, the calculated combined values ​​are 437.5, 410.2, 392.7, 465.0, and 450.8 respectively, with an average value of 431.24. This value is used as a representative value for the echo intensity of the entire abdominal region for subsequent analysis.

[0059] The frequency band filtering submodule extracts the acoustic impedance ratio corresponding to the frequency band based on the intensity value of the abdominal reflected echo, calls the acoustic impedance parameters of the gastric fluid in infants and young children, compares the matching degree of the two types of parameters, filters the set of frequency bands whose acoustic impedance differences meet the threshold conditions, and generates a fluid matching frequency band group.

[0060] The frequency band selection module uses abdominal echo intensity values ​​as a basis to perform acoustic impedance comparison analysis for each frequency band. First, it obtains the reference acoustic impedance parameters of the gastric fluid. This parameter is determined by the fluid type; for example, the density of breast milk is approximately 1030 kg / m³, and the speed of sound is approximately 1470 m / s. Multiplying these values ​​yields a reference acoustic impedance value of approximately 1.51 million reels. Then, it estimates the acoustic impedance values ​​for each frequency band's reflected signals. This estimation is performed by comparing the reflected signal intensity to the transmitted signal intensity, combined with the known acoustic impedance constant of the abdominal wall tissue. For example, if the reflected intensity is higher than 30... If the ratio of the acoustic impedance to the emission intensity reaches a certain standard, the acoustic impedance of the corresponding frequency band can approach the liquid reference value. The difference between the acoustic impedance value of all frequency bands and the liquid acoustic impedance is judged. When the difference is lower than the set threshold of 300,000 reels, it is determined to be a matched frequency band. For example, if the acoustic impedance of a certain frequency band is 1,480,000 reels, the difference with breast milk is 31,000 reels, which is far below the threshold, and it is determined to be a valid match. After applying this method to all frequency bands, the set of frequency bands that meet the conditions is finally selected to form a liquid matched frequency band group, which is used for subsequent power adjustment and signal enhancement operations.

[0061] The power control submodule obtains the estimated value of the abdominal wall thickness of infants and young children based on the liquid matching frequency band group, and determines the probe transmission power range corresponding to the frequency band by combining the penetration characteristics of the reflected signal and the thickness relationship. It selects the power value combination with the response amplitude in the target range for transmission and reception operations and establishes the gastric fluid reflection feature map.

[0062] After receiving the frequency band selection results, the power control module needs to adjust the power according to the thickness of the infant's abdominal wall. First, it estimates the abdominal wall thickness based on the reflected signal delay time. With the speed of sound taken as approximately 1580 meters per second, a signal delay of 7 microseconds results in a thickness of approximately 5.53 millimeters. This value serves as the basic parameter for adjusting the transmission power. Within the matched frequency band, the penetration capability of each frequency to the abdominal wall is analyzed. Higher frequencies have shorter wavelengths and shallower penetration depths, requiring higher power to improve the quality of the reflected signal. For example, the wavelength of the 5 MHz band is approximately 0.316 millimeters, with a penetration capability of approximately 0.38 millimeters. Since the gastric fluid is much thinner than the abdominal wall, a relatively high transmission power should be set, and the power range should be controlled within a safe range. For example, the lower limit should be set to 12 milliwatts to ensure that the smallest reflected signal can be identified, and the upper limit should be set to 25 milliwatts to prevent excessive energy from causing local overheating. Each frequency band should be selected to transmit a power value in the range of 28 to 40 dB based on the actual echo intensity variation. After transmission, the signal echo should be collected again to form a reflection intensity matrix corresponding to the frequency band and power. An image should be established to reflect the reflection characteristics of gastric fluid under different frequency bands and power combinations for structural analysis and subsequent identification operations.

[0063] Please see Figure 2 The signal processing module includes:

[0064] The reflectance acquisition submodule extracts reflection intensity, time delay, and detector position data based on the gastric fluid reflectance feature map. It compares the detector array order with the signal mapping order to identify the signal mapping direction and arrangement deviation magnitude, and generates reflectance mapping calibration data.

[0065] The reflection map acquisition submodule decomposes and processes the signals acquired from the multi-channel detector array based on the gastric fluid reflection feature map. The detectors are arranged in a regular 6x6 array, numbered sequentially to determine the spatial order. Each detector records the signal waveform of the sound waves propagating inside the fluid and being reflected back. The extraction of reflection intensity is based on the difference between the peak value of the echo signal and the background noise. A valid reflection signal is typically defined as a peak value exceeding twice the average amplitude of the background noise. For example, if the background noise is 30 mV and the peak noise is 90 mV, then the signal is valid. The time delay is obtained by comparing the absolute time points of signal transmission and reception. The time difference, combined with the sound velocity in the gastric cavity (typically 1500 m / s), is used to estimate the signal propagation distance. For example, if the time delay is 20 microseconds, the propagation path is 30 millimeters. The detector positions are determined based on the array... The column index assigns initial two-dimensional coordinates. The matching between the number corresponding to each signal and the array number needs to be compared by building an index table 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 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 indicates that an arrangement error occurred during the acquisition process. The magnitude of the arrangement deviation can be determined by the average distance difference between continuous 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 millimeters, it is considered that calibration is required. The final dataset includes reflection intensity, time delay, position coordinates, and offset vector, and is uniformly labeled with mapping numbers for subsequent processing.

[0066] The morphology matching submodule calls the reflection mapping calibration data, combines the volume node coordinates, gastric wall boundary curvature points and detector mapping rules in the three-dimensional morphological model of the infant's stomach cavity, locates the mapping position of the calibration signal in the three-dimensional coordinate system, judges the offset between the calibration signal 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. This model is constructed from a high-density volumetric mesh, with each node having three-dimensional coordinate attributes. The projection process maps the two-dimensional detector planar position to the three-dimensional structural surface through a set of affine transformations. This mapping is formed by fitting the actual abdominal wall structure of infants and young children. The gastric wall boundary is extracted using a curvature point sampling method, typically extracting feature points at equidistant intervals of 5 millimeters. During positioning, the curvature point closest to the detector reflection position is selected for comparison. If the spatial distance between the two exceeds a set tolerance threshold, such as 5 millimeters, it is considered to have a significant offset, and its offset vector value in three-dimensional coordinates is calculated. This vector is used for subsequent distribution correction, forming a spatial consistency input between the signal and the model.

[0068] The distribution calculation submodule corrects the vector value based on the spatial offset, integrates the reflection intensity and node attitude angle data, and associates the spatial relationship between the time delay and the 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 3D lattice model, associating 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 reflection intensity correction factor. When the attitude angle is 0 degrees, there is no adjustment; if the angle is 60 degrees, only half the intensity is retained. As the angle increases, the reflection intensity correction value decreases. Combined with the node time delay data, the spatiotemporal propagation path between the node and the detector is estimated, and a point-to-voxel mapping relationship is established. The 3D space is divided into grids, and each stereo pixel unit integrates multiple detection signals, assigning different weights according to the distance from the center point. The closer the point, the greater the weight. For example, a distance of 5 mm results in a weight of 1, and a distance of 15 mm results in a weight of 1 / 3. Through weighted calculation, the average reflection intensity value within each spatial unit is summarized, thereby establishing a 3D distribution image of the gastric fluid, and simultaneously outputting the center position of the high-density fluid region and the boundary points of the distribution range.

[0070] Please see Figure 2 The Bluetooth transmission module includes:

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

[0072] The specific formula for calculating the interference rate is as follows:

[0073]

[0074] Among them, D rate The value represents the interference rate, j represents the total number of radio frequency bands detected, and P represents the interference rate. i T represents the interference intensity corresponding to the i-th frequency band, in decibels and milliwatts. i f represents the duration of interference within the i-th frequency band, in seconds. i This represents the frequency of interference events occurring in the i-th frequency band;

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

[0076] Interference intensity P iThe power is obtained based on real-time power monitoring values ​​from a spectrum analyzer or an embedded RF sensing module, measured in decibels and milliwatts (dBm). A reasonable range is typically -90 dBm to -30 dBm. After conversion to milliwatts, a logarithmic conversion formula is used.

[0077]

[0078] Under the condition of a monitored value of -60dBm, the following calculations were performed:

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

[0080] To ensure the operability of the calculation scale, the interference intensity needs to be uniformly converted into milliwatt units for calculation.

[0081] Interference duration T i The interference duration was determined by counting the number of seconds the signal remained continuously above the interference threshold. The threshold was set to -75 dBm via software. A complete record was generated from the start of system timing until the signal dropped below the threshold when the interference intensity was above the threshold and remained there continuously, measured in seconds. In the 2.4 GHz band within the ward, the interference duration was measured to be 6 seconds.

[0082] Interference frequency f i This indicates the number of interference events detected in this frequency band within a 1-minute time window. Each event is defined as valid interference if its interference intensity is above a threshold and its duration exceeds 0.2 seconds. The wireless radio frequency 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, with the number of frequency bands j = 3, we monitored frequency bands 1, 2, and 3 respectively, and recorded the values ​​as follows:

[0085] Frequency Band 1:

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

[0087] Frequency Band 2:

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

[0089] Frequency 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 roots of each numerator:

[0094] First item:

[0095] With a denominator of 10, the result is 0.0006;

[0096] Second item:

[0097] With a denominator of 6, we get approximately 0.00119.

[0098] Third item: With a denominator of 13, the result is approximately 0.00024.

[0099] Sum the three terms and take the average:

[0100]

[0101] The results indicate that the combined interference rate of the three main frequency bands in the current time period is 0.0006767, representing the average level of interference energy density in both space and time. Comparing this value with the interference alarm threshold in the signal sensing submodule can determine whether the current interference has entered the warning stage. If the system's warning value is set to 0.0005, the current result exceeds the set boundary and should be classified as an active interference zone. This value can be used as an initial input parameter for subsequent modules to further trace the source of the interference signal, isolate interference, and push environmental adjustment strategies.

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

[0103] The data segmentation submodule constructs a node data density model based on the interference rate and node density in the 3D distributed data, extracting the location and unit data volume of each node and calculating the data density per unit volume. For example, if a node has 2 kilobytes of data in 1 cubic centimeter of space, then the density of that node is 2 kilobytes per cubic centimeter. A joint ratio is calculated based on the interference rate and density of each node to determine whether it falls within a set ratio range, thus identifying it as a candidate segmentation region. For example, if the joint ratio threshold is 80 microvolt-hertz per kilobyte, and a node has an interference rate of 160 microvolt-hertz and a density of 2 kilobytes per cubic centimeter, then the joint ratio of that node is 80, meeting the screening criteria. By aggregating nodes that meet the criteria, a minimum spatial boundary is established to determine candidate data segments. For the original data packets in the initially selected regions, if the length exceeds 256 kilobytes, it is proportionally split into two 150-kilobyte segments; if it is less than 64 kilobytes, data packet merging or padding operations are performed to ensure that the final generated data packets are within the transmittable range, thus deriving the segmentation length configuration parameters for each new data packet.

[0104] The tag recombination submodule embeds time-series tags and device identification information into the data segments determined by the segmented data length interval value, reassembles the data by numbering, and the receiving end completes the sequence verification and offset judgment to generate an anti-interference gastric residual data packet.

[0105] The tag reassembly submodule embeds timing information and device identification identifiers into the divided data segments. Each data segment begins with a timestamp and device number, for example, embedding the time as 10:45:30 on a certain day and the device number as 001, forming a tagged data header. Data segment numbers increment sequentially from 1000, identifying the numbering information of each segment. Upon receiving the data, the receiving end checks the data sequence for continuity based on the numbering information. If there are skipped numbers, it's considered an abnormal data offset. Simultaneously, it checks the consistency of time between adjacent segments based on the timestamps. If the time interval exceeds a set maximum error (e.g., 5 seconds), it's identified as out-of-order or data loss. Finally, the data segments are reassembled sequentially into a complete tagged data packet for subsequent processing, ensuring good continuity and accuracy of information even in environments with spectral interference.

[0106] Please see Figure 2 The residual calculation module includes:

[0107] The anti-interference parsing submodule acquires the signal time series, noise interference value and original liquid volume data in the anti-interference gastric residual volume data packet. Based on the relationship between noise interference change and volume offset at the corresponding time point, it calculates the average offset value of continuous liquid volume, determines the range of continuous liquid volume variation over time, and generates continuous liquid volume interval values.

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

[0109]

[0110] Where, ΔV d (t) represents the average offset of the liquid volume at the current time t, V x N represents the raw liquid volume data collected at time x. x y represents the noise interference value at time x, 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 offset of the liquid volume at the current time t, in milliliters.

[0112] y represents the total number of samples, with a value of 5. Based on the signal sampling frequency of once every 15 minutes, 5 valid data points are continuously acquired within 1 hour.

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

[0114] N x The noise interference value extracted at the x-th sampling time is converted into volumetric interference equivalents through signal filtering margin analysis, which are 0.4, 0.3, 0.2, 0.5, and 0.4 ml, respectively.

[0115] V0 represents the initial liquid volume at the time point, obtained from the first sampling, which 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 calculate the average:

[0126] 96.4 ÷ 5 = 19.28;

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

[0128] ΔV d (t) = 19.28 - 20.6 = -1.32;

[0129] The results indicate that the average liquid volume offset at the current time point is -1.32 ml. A negative value indicates that the overall volume is decreasing, and the change is within the safe baseline range. If the intervention threshold is set to issue an alert if the offset exceeds 5 ml, this value is still within the normal fluctuation range and can be used as the basic data for trend analysis input to the subsequent risk assessment module.

[0130] The integral parameter correction submodule calls the continuous liquid volume interval value, the infant enteral nutrition intake rate and gastric emptying curve data, and combines the volume change trend over time and the difference between the intake and emptying rhythm to correct the original volume change ratio segment and generate the corrected volume trend coefficient.

[0131] The integral parameter correction submodule, based on continuous liquid volume intervals, infant nutrient intake rates, and gastric emptying trend curves, divides volume intervals according to time periods, such as 0 to 10 minutes, 10 to 20 minutes, etc., and calculates the median of the volume data for each interval as a representative volume. For example, if the volume range for a certain interval is 40 to 44 ml, the median is taken as 42 ml. If the corresponding intake rate is constant at 5 ml per minute within 10 minutes, then the total intake is 50 ml. Simultaneously, based on gastric emptying characteristics and referencing clinical emptying rate trends, such as 3.5 to 4 ml per minute, the actual trend of gastric contents change is assessed by comparing the volume change within the same time period with the difference between the intake and the emptying volume. If the volume increase rate is lower than the intake rate, it may be due to accelerated emptying; conversely, it may be due to slower emptying. Taking actual data as an example, if the rate of liquid volume change is 0.8 ml / min, the rate of ingestion is 5 ml / min, and the rate of emptying is 3.9 ml / min, then the difference between volume increase and ingestion / emptying is 1.1 ml, and the volume change rate accounts for approximately 73%. Based on this, it is determined that the volume change rate in the current segment is slightly lower than expected, so the coefficient for this segment is adjusted to 0.73 in subsequent calculations. This method is used to correct all time periods sequentially, resulting in the corrected trend parameters, such as 0.73 for the 0-10 minute segment and 0.94 for the 10-20 minute segment, etc.

[0132] The dynamic compensation calculation submodule assesses the flow status of contents over a period of time based on the linkage between the corrected volume trend coefficient and the current intake rate data, and dynamically compensates for the current volume evolution path to construct a gastric volume estimation structure at a complete time point and generate a dynamically compensated gastric residual volume value.

[0133] The dynamic compensation calculation submodule corrects the correlation between the volume trend coefficient and the intake rate, constructing a continuous structure of gastric fluid volume changes over time. Starting with initial volume data, the current intake rate is multiplied by the corresponding trend coefficient at each time interval to obtain the volume increase value for each minute. For example, if the intake rate is 6 ml / min and the corresponding trend coefficient is 0.85, the volume change in that minute is 5.1 ml. Combining this with the volume data from the previous time point, such as 58 ml at minute 14, the estimated volume for minute 15 is 63.1 ml. The volume change value is progressively added minute by minute to construct a volume change sequence. During enteral feeding of infants, if the intake rate decreases to 3 ml / min and the emptying trend strengthens to 4 ml / min, the trend coefficient may decrease to 0.6, and the volume may decrease instead of 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, thus establishing volume estimates at each time point that are closer to the actual flow state, forming a complete and continuous structure for estimating gastric residual volume. At a certain point in time, such as 30 minutes, based on the aforementioned data, the volume can be deduced to be approximately 44.6 ml.

[0134] Please see Figure 2 The tiered alarm module includes:

[0135] The residual state assessment submodule extracts the variation characteristics of residual volume during nutrient infusion based on the comparison between the dynamic compensation residual volume value and the infant perfusion volume record and the resting gastric fluid baseline volume. It then combines the gastric fluid emptying rhythm data to classify the phased trends and obtain the residual state data of gastric contents.

[0136] The residual state assessment submodule relies on the volume data of each nutritional infusion for the infant, and systematically compares it with changes in gastric residual volume and the baseline gastric fluid volume at rest. First, the actual input volume is recorded during infusion, for example, 25 ml for one infusion. Simultaneously, the current residual volume in the stomach is read using ultrasound imaging or a non-invasive vital sign monitoring module; for example, if the residual volume is 10 ml before infusion and 18 ml after infusion, meaning only 17 ml is emptied after 25 ml is infused. This data is then compared with the baseline gastric fluid volume at rest. For example, the baseline gastric fluid volume for a 2.5 kg infant at rest is 5 ml. If the residual volume is measured in milliliters, the current residual volume is significantly higher than the baseline level. Data is continuously recorded at multiple time points, such as 18 ml, 15 ml, and 12 ml at 8:00 AM, 11:00 AM, and 2:00 PM respectively. The trend of residual volume change within each time period is extracted and classified in conjunction with the infant's gastric emptying rhythm. If the residual volume continues to decrease during the day and is close to the baseline value, it is classified as normal emptying type. Conversely, if it remains at a high level for a long time and the change is not obvious, it is judged as retention type. The residual characteristic curve is formed by statistical classification according to the stage and the status classification of each time period is labeled. Finally, a structured dataset for the residual status of gastric contents during nutrient input is generated.

[0137] The offset feature extraction submodule extracts the residual change gradient at continuous time nodes based on the relationship between the residual state data of gastric contents and the phased gastric capacity baseline range. It combines the slope interval distribution of the periodic change rate to calculate the residual dynamic offset intensity feature value, refines the residual dynamic offset intensity feature, and obtains the offset dynamic prediction analysis results.

[0138] The specific formula for calculating the residual dynamic migration intensity eigenvalue is as follows:

[0139]

[0140] Where, θ Δv Represents the residual dynamic migration intensity characteristic value, v i v represents the residual volume of gastric contents recorded at the i-th time point (in milliliters). i+1 ω represents the gastric residual volume recorded at the (i+1)th time point. i and ω i+1 t represents the stage residual change adjustment coefficients (unitless, correction coefficients) corresponding to nodes i and i+1, respectively. i and t i+1 These represent the recorded time points (unit: minutes). This represents the baseline stomach capacity (in milliliters) set for the current infant stage, and n represents the total number of consecutive time intervals used for accumulation (number of dimension items).

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

[0142] Parameter v i+1 The residual volume at the next adjacent sampling time point was obtained in the same way and its value was 14 ml.

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

[0144] Parameter t i With t i+1 These are the corresponding sampling time points, in minutes. Sampling was conducted at 9:00 and 10:00, which translates to 540 minutes and 600 minutes respectively.

[0145] Parameter ω i With ω i+1 The residual volume adjustment coefficients for each time period are quantified using a gastric motility score. The scoring criteria are based on two indicators: gastric contents 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 level 2, with a coefficient of 0.75. In the second time period, the emptying rate increases and the fluctuation intensifies, resulting in a score of level 4, with a coefficient of 1.25.

[0146] Substitute the parameters into the formula:

[0147]

[0148] Calculate each item one by one:

[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] Calculate the complete expression:

[0155]

[0156] The results show that the residual dynamic migration intensity characteristic value for the current time interval is 0.0054. This value characterizes the fluctuation of the residual gastric contents volume over time, combined with the dynamic state; a higher value indicates a higher intensity of gastric residual fluctuation. By statistically analyzing the average migration intensity of each interval within a continuous time window, a migration dynamic trend curve can be constructed. The current results will be incorporated as components of the migration characteristics of individual intervals into the input structure of dynamic predictive analysis.

[0157] The level signal determination submodule determines the current risk level range 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 classification alarm instruction.

[0158] The risk level determination submodule compares the extracted dynamic offset results with the preset enteral nutrition safety threshold for infants and young children. For example, if the current average offset is 16 ml, and the system sets the safety threshold to 10 ml, then the offset exceeds 6 ml. The system sets intervention level standards based on the degree of offset. For example, an offset between 0 and 5 ml is classified as low risk, 6 to 10 ml as medium risk, and more than 10 ml as high risk. The current offset is classified as medium risk. The system continuously tracks the risk level trend. If two consecutive time periods are at the medium risk level, the system automatically enters a warning state and issues a yellow alarm signal. If the risk level continues to rise or reaches the high risk level, the system upgrades to an orange signal. The system can record the frequency and duration of daily risk level changes and generate standardized grading instructions, which are transmitted to the nutrition management module or monitoring system through the status signal interface to achieve graded early warning response to the current enteral nutrition status of infants and young children, ensuring the accuracy of phased monitoring.

[0159] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A Bluetooth transmission device for monitoring the gastric residual volume by ultrasound during enteral nutrition of infants and young children, characterized in that it comprises: The device comprises a body structure and a transmission device carrying control system, wherein the transmission device carrying control system comprises: The ultrasonic signal acquisition module detects the multi-frequency band reflected signals emitted by the abdominal ultrasonic probe of the infant, screens the target frequency band meeting the sound impedance characteristics of the stomach liquid, dynamically adjusts the probe emission power based on the abdominal wall thickness, and generates the stomach liquid reflection characteristic map; The signal processing module calls the stomach liquid reflection characteristic map, combines the three-dimensional shape model of the infant's stomach cavity, corrects the spatial mapping deviation and body position deviation of the reflected signal, and generates the three-dimensional distribution data of the stomach liquid; The Bluetooth transmission module calls the three-dimensional distribution data of the stomach liquid, divides the data packet according to the environmental signal interference intensity, embeds the time sequence label and the device identification code, and generates the anti-interference stomach residual volume data packet; The residual volume calculation module analyzes the anti-interference stomach residual volume data packet, calculates the stomach liquid volume integral value, corrects the integral parameters based on the infant's enteral nutrition intake rate and the stomach emptying curve, and generates the dynamic compensation stomach residual volume value; The hierarchical alarm module judges whether to trigger the enteral nutrition suspension scheme or the medical intervention alarm based on the dynamic compensation stomach residual volume value and the infant's enteral nutrition safety threshold, and generates the enteral nutrition state hierarchical alarm instruction. The stomach liquid reflection characteristic map comprises target frequency band reflected signals, emission power adjustment parameters, and abdominal wall thickness matching coefficients. The three-dimensional distribution data of the stomach liquid comprises spatial mapping correction factors, signal offset compensation amounts, and a three-dimensional shape model of the stomach cavity. The anti-interference stomach residual volume data packet comprises a time sequence label, a device unique identification code, and a data segmentation structure. The dynamic compensation stomach residual volume value comprises a volume integral value, an enteral nutrition intake rate, and a stomach emptying curve parameter.

2. The Bluetooth transmission device for monitoring the ultrasonic gastric residual volume during enteral nutrition of infants and young children according to claim 1, characterized in that: The enteral nutrition state hierarchical alarm instruction comprises an enteral nutrition suspension instruction, a medical intervention alarm, and a safety threshold judgment basis.

3. The Bluetooth transmission device for monitoring ultrasonic stomach residual volume during enteral nutrition of infants and young children according to claim 1, characterized in that: The ultrasonic signal acquisition module comprises: The signal detection sub-module detects the signal emitted by the ultrasonic probe attached to the infant's abdomen, acquires multi-frequency band reflected signals, extracts the reflection content that does not exceed the detection requirements according to the time delay and reception intensity of the frequency band, combines parameters according to the abdominal attachment area and signal amplitude, and generates the abdominal reflection echo intensity value; The frequency band screening sub-module extracts the acoustic impedance ratio corresponding to the frequency band according to the abdominal reflection echo intensity value, calls the acoustic impedance parameters of the infant's stomach liquid, compares the matching degree of the two types of parameters, screens the frequency band set whose acoustic impedance difference meets the threshold condition, and generates the liquid matching frequency band group; The power regulation sub-module obtains the estimated value of the infant's abdominal wall thickness according to the liquid matching frequency band group, determines the probe emission power range corresponding to the frequency band by combining the reflection signal penetration characteristics and the thickness relationship, selects the power value combination with the response amplitude in the target interval for emission and reception operation, and establishes the stomach liquid reflection characteristic map.

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

5. The Bluetooth transmission device for monitoring the ultrasonic gastric residual volume during enteral nutrition of infants and young children according to claim 4, characterized in that: The Bluetooth transmission module includes: The signal sensing sub-module obtains the three-dimensional distribution data of the liquid in the stomach and the radio frequency spectrum signal in the infant ward, combines the interference intensity, the duration and the interference frequency of the different frequency bands, calculates the interference disturbance rate value, identifies the disturbance change in the interference peak value interval, and generates the interference disturbance rate value; The data segmentation sub-module 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 section, adjusts the data packet structure, delimits the segmentation range, and generates a segmentation data length interval value; The label reorganization sub-module reorganizes the data according to the data segment determined by the segmentation data length interval value, embeds the time sequence label and the equipment identification information, and receives the sequence verification and offset judgment of the receiving end to generate an anti-interference stomach residual volume data packet.

6. The Bluetooth transmission device for monitoring the ultrasonic gastric residual volume during enteral nutrition of infants and young children according to claim 5, characterized in that: The specific calculation formula of the calculation of the interference disturbance rate value is: where D rate represents the interference disturbance rate value, j represents the total number of detected radio frequency bands, 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 i-th frequency band, in seconds, f i represents the frequency of occurrence of interference events in the i-th frequency band.

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

8. The Bluetooth transmission device for monitoring the ultrasonic gastric residual volume during enteral nutrition of infants and young children according to claim 7, characterized in that: The specific calculation formula of the calculation of the average offset value of the continuous liquid volume is: wherein ΔV d (t) represents the liquid volume average 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 monitoring the ultrasonic gastric residual volume during enteral nutrition of infants and young children according to claim 7, characterized in that: The hierarchical alarm module includes: The residual state evaluation sub-module extracts the change amplitude characteristics of the residual volume in the nutrition infusion process based on the comparison relationship between the dynamic compensation residual volume value and the infant perfusion volume record and the resting period gastric fluid reference amount, classifies the stage trend according to the gastric fluid emptying rhythm data, and obtains the gastric content residual state data; The offset feature extraction submodule extracts the residual change gradient of the continuous time node based on the change relationship between the gastric content residual state data and the periodic gastric volume reference range, calculates the residual dynamic offset intensity feature value in combination with the slope interval distribution of the periodic change rate, refines the residual dynamic offset intensity feature, and obtains the dynamic prediction analysis result. The grade signal determination submodule determines the interval where the current risk grade is located based on the deviation degree between the dynamic prediction analysis result and the infant enteral nutrition safety threshold in combination with the intervention grade reference range set by the system, and obtains the enteral nutrition state grading alarm instruction.

10. The Bluetooth transmission device for monitoring the ultrasonic gastric residual volume during enteral nutrition of infants and young children according to claim 9, characterized in that: The specific calculation formula of the residual dynamic offset intensity feature value is: wherein θ Δv represents the residual dynamic deviation intensity characteristic value, v i represents the recorded gastric content residual volume value at the i-th time node, v i+1 represents the gastric residual volume value recorded at the i+1-th time node, ω i and ω i+1 respectively represent the phase residual change adjustment coefficients corresponding to the nodes i and i+1, t i and t i+1 respectively represent the recording time nodes, represents the gastric capacity reference value set for the corresponding stage of the current infant, and n represents the total number of continuous time intervals for accumulation.

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