A control system and medium for handheld intelligent ultrasonic diagnostic equipment

Abstract

The present invention discloses a control system and medium for a handheld intelligent ultrasonic diagnostic device, and relates to the technical field of medical imaging diagnosis. The system solves the problem that the current manual adjustment method is difficult to ensure that each diagnosis can obtain the best image quality and appropriate detection strength. The system includes: an ultrasonic device; at least one processor; at least one memory storing a computer program, and at least one processor is configured to implement a control method for the handheld intelligent ultrasonic diagnostic device when executing the computer program: the current initial probe parameter setting of the ultrasonic probe, the current position coordinates of the ultrasonic probe relative to the patient's body, and the specific physiological characteristics of the patient are input into a trained clinical ultrasonic probe intelligent control model, and a probe parameter combination matching the best image quality is output; that is, the present invention combines multiple factors to determine the best probe parameters and intelligent control pressure values, thereby achieving accurate diagnosis and improving the accuracy and reliability of ultrasonic diagnosis.

Description

Technical Field

[0001] The present invention relates to the technical field of medical imaging diagnosis, and in particular to a control system and medium of a handheld intelligent ultrasonic diagnostic device. Background Art

[0002] With the development of medical imaging technology, ultrasonic diagnosis is widely used in clinical practice due to its non-invasive, real-time and low-cost characteristics, especially handheld ultrasonic diagnostic equipment, which is more flexible and convenient. However, in actual use, doctors need to manually adjust the probe parameters to adapt to different patient conditions, which is not only time-consuming but also has high requirements on the doctor's experience and skills.

[0003] At present, the parameter adjustment of traditional ultrasonic diagnostic equipment relies on manual adjustment by doctors and lacks intelligent auxiliary systems, which makes the quality of each diagnosis greatly affected by the doctor's personal skills.

[0004] The manual adjustment method in the existing technology is difficult to ensure that the best image quality and appropriate detection strength can be obtained for each diagnosis, especially in emergency situations or when facing patients with different physiological characteristics. This uncertainty may affect the accuracy and safety of the diagnosis. Summary of the invention

[0005] In order to determine the optimal probe parameters based on multiple factors, intelligently control the pressure value, achieve accurate diagnosis, and improve the accuracy and reliability of ultrasonic diagnosis, the present application provides a control system and medium for a handheld intelligent ultrasonic diagnostic device.

[0006] In a first aspect, the present application provides a control system for a handheld intelligent ultrasonic diagnostic device, which adopts the following technical solution:

[0007] A control system for a handheld intelligent ultrasonic diagnostic device, comprising:

[0008] Ultrasound equipment;

[0009] at least one processor;

[0010] At least one memory storing a computer program, and at least one processor configured to implement a method for controlling a handheld intelligent ultrasonic diagnostic device when executing the computer program, the specific steps are as follows:

[0011] Obtaining the current initial probe parameter settings of the ultrasound probe, the current position coordinates of the ultrasound probe relative to the patient's body, and the patient's specific physiological characteristics, wherein the specific physiological characteristics include obesity level and gender, and the probe parameter settings include scanning angle range and frequency;

[0012] Inputting the current initial probe parameter settings of the ultrasound probe, the current position coordinates of the ultrasound probe relative to the patient's body, and the patient's specific physiological characteristics into the trained clinical ultrasound probe intelligent control model, and outputting a probe parameter combination that matches the best image quality;

[0013] Adjusting the ultrasonic probe parameters according to the output probe parameter combination, and simultaneously detecting and obtaining the pressure value applied by the ultrasonic probe to the skin;

[0014] Analyze whether the pressure value falls within the preset reasonable pressure value range;

[0015] If not, then according to the current position coordinates of the ultrasound probe relative to the patient's body, the current detection part of the ultrasound probe is confirmed from the preset three-dimensional coordinate model of the human body, and according to the matching result of the current detection part of the ultrasound probe with the preset key detection part, the interval range in which the pressure value obtained by the detection falls, and the reminder method of the voice broadcast device preset in the ultrasound equipment, the voice broadcast device reminder method that matches the pressure value is analyzed and determined;

[0016] The result information that the pressure value falls within the preset reasonable pressure value range is notified through the reminder method determined by the analysis;

[0017] If yes, no reminder will be given.

[0018] By adopting the above technical solutions, the probe parameters are optimized through the intelligent control model to improve the image quality. The probe pressure value is detected and voice reminders are given according to the situation to ensure the accuracy and safety of the examination. At the same time, personalized adjustments are made according to the physiological characteristics and detection sites of different patients to improve the efficiency and reliability of diagnosis. It is applicable to a variety of scenarios and provides strong support for medical diagnosis.

[0019] Optionally, detecting and obtaining the pressure value applied by the ultrasound probe to the skin includes:

[0020] Starting a pressure sensor array arranged on the ultrasound probe to measure and obtain a pressure value between the ultrasound probe and the skin;

[0021] The pressure value measured by each pressure sensor included in the pressure sensor array is taken as a pixel point to construct and acquire a pressure distribution image;

[0022] The average pressure value of all pixels in the pressure distribution image is calculated as the effective pressure value applied by the ultrasonic probe to the skin.

[0023] By adopting the above technical solution, the pressure sensor array can be used to accurately measure the pressure, and the pressure distribution image can be constructed to help intuitively understand the pressure situation. By calculating the average value to obtain the effective pressure value, the measurement accuracy is improved, providing a reliable basis for ensuring the safety and effectiveness of ultrasound examinations, and also providing accurate data for subsequent pressure judgment and adjustment, improving the performance and practicality of handheld intelligent ultrasound diagnostic equipment.

[0024] Optionally, obtaining a preset reasonable pressure value range includes:

[0025] Extracting pressure features from the pressure distribution image, the pressure features include mean, standard deviation, gradient information of pressure distribution, local peak and valley values;

[0026] According to the current position coordinates of the ultrasound probe relative to the patient's body, the current detection position of the ultrasound probe is confirmed by matching the preset three-dimensional coordinate model of the human body;

[0027] According to the key pressure features associated with the preset detection parts and the reasonable pressure value range analysis scheme based on the key pressure features, the reasonable pressure value range of the corresponding detection parts is analyzed and obtained.

[0028] By adopting the above technical solution, the pressure characteristics are extracted and combined with the detection site analysis to improve the accuracy of pressure judgment. The reasonable interval is determined for different detection sites, making the pressure applied by the ultrasound probe more scientific, which not only ensures the image quality but also avoids discomfort to the patient, improves the safety and reliability of handheld intelligent ultrasound diagnostic equipment, and provides a strong guarantee for accurate diagnosis.

[0029] Optionally, obtaining a reasonable pressure value range analysis solution based on key pressure characteristics includes:

[0030] Obtaining specific requirement information of the detection part, the specific requirement information includes anatomical structure parameters and physiological function parameters;

[0031] The specific requirement information of the detection part and the key pressure feature information associated with the detection part are used as input variables and input into the trained pressure interval range analysis model to output the pressure interval range.

[0032] By adopting the above technical solutions, extracting multiple pressure characteristics can fully reflect the pressure situation, and combining the three-dimensional coordinates of the human body to confirm the detection site more accurately. Analyzing the reasonable pressure range for different parts can ensure the best ultrasound examination effect, while avoiding harm to patients due to improper pressure. It improves the intelligence and adaptability of the equipment, provides reliable guarantee for accurate diagnosis, and makes handheld ultrasound diagnostic equipment more efficient and safer in clinical applications.

[0033] Optionally, obtaining a reasonable pressure value range analysis solution based on key pressure characteristics includes:

[0034] Obtain the weight corresponding to the key pressure feature associated with the preset detection part, and calculate the weighted average pressure value through a weighted average algorithm according to the specific value of the key pressure feature and the weight corresponding to the key pressure feature;

[0035] According to the standard deviation multiples associated with the preset detection parts, the standard deviation of the associated standard deviation multiples is added or subtracted from the weighted average pressure value to form a reasonable pressure value range based on the key pressure characteristics.

[0036] By adopting the above technical solution, the pressure value calculation is made more scientific by combining the weighted average algorithm with the weight of key pressure features. The reasonable interval range is determined based on the standard deviation multiple, which improves the accuracy and reliability of pressure judgment. It can ensure that the ultrasound probe applies appropriate pressure at different detection sites, improve image quality while protecting patient safety, enhance the practicality and professionalism of handheld intelligent ultrasound diagnostic equipment, and provide strong support for clinical diagnosis.

[0037] Optional, if yes, no reminder, including:

[0038] Extracting pressure features from the pressure distribution image, and analyzing whether pressure feature values ​​of different categories fall within a preset pressure feature value threshold range of the corresponding category;

[0039] If yes, no reminder will be given;

[0040] If not, the reminder information is analyzed and determined according to the correspondence between the result information of different categories of pressure characteristic values ​​falling into the preset corresponding category pressure characteristic value threshold range and the reminder information, and the reminder information is broadcasted through the voice broadcast device.

[0041] By adopting the above technical solution, the operation can be carried out without interruption when the pressure is normal, thus improving the inspection efficiency. At the same time, the abnormal pressure characteristic value is reminded to ensure the accuracy and safety of the inspection. By analyzing the pressure characteristic values ​​of different categories, the pressure situation can be judged more comprehensively and the probe operation can be adjusted in time. The intelligence level of handheld intelligent ultrasonic diagnostic equipment is improved, providing reliable guarantee for medical diagnosis and reducing the risk of misdiagnosis due to improper pressure.

[0042] Optionally, the method further includes the following steps after the reminder information is broadcasted through a voice broadcasting device:

[0043] After the preset time interval of the reminder message broadcast, the pressure characteristic value is monitored and obtained;

[0044] Analyzing whether the proportion of the pressure value on one side of the ultrasonic probe to the overall pressure exceeds a preset proportion according to the mean value included in the pressure characteristic value;

[0045] If not, analyzing and determining the adjustment measures of the ultrasonic probe according to the correspondence between the interval range in which the mean value included in the pressure characteristic value falls and the parameter adjustment measures of the ultrasonic probe, and executing the adjustment measures of the ultrasonic probe;

[0046] If yes, then according to the correspondence between the result information that one side of the ultrasonic probe exceeds the preset proportion and the parameter adjustment measures of the ultrasonic probe, the adjustment measures of the ultrasonic probe are analyzed and determined, and the adjustment measures of the ultrasonic probe are executed.

[0047] By adopting the above technical solution, the pressure characteristic value can be continuously monitored after the reminder, and the ultrasound probe parameters can be adjusted according to the situation. Ensure that the pressure value remains within a reasonable range to improve the accuracy of diagnosis. Targeted adjustments can be made to the situation where the pressure ratio on one side exceeds the preset value to improve the adaptability of the equipment. The intelligence level of handheld intelligent ultrasound diagnostic equipment is enhanced, providing medical workers with a more convenient operating experience, which helps to improve the efficiency and quality of diagnosis.

[0048] Optionally, the current initial probe parameter settings of the ultrasound probe, the current position coordinates of the ultrasound probe relative to the patient's body, and the specific physiological characteristics of the patient are input into the trained clinical ultrasound probe intelligent control model, and the output probe parameter combination matching the best image quality includes:

[0049] Obtain the remaining power value of the handheld intelligent ultrasonic diagnostic device;

[0050] Analyze whether the remaining power value of the handheld intelligent ultrasonic diagnostic device exceeds a preset power threshold;

[0051] If yes, maintain the original settings;

[0052] If not, then obtain the specific requirements of this examination, and analyze and determine the priority ranking of different functional categories based on the corresponding relationship between the examination requirements and the priority ranking order of different functional categories of the ultrasound diagnostic equipment. The examination requirements include emergency examination requirements, physical examination requirements, and specialist examination requirements. The functional categories of ultrasound diagnostic equipment include core functions, advanced functions, and auxiliary functions.

[0053] According to the corresponding results of the priority ranking of the function categories and the priority values, the priority values ​​of different function categories are analyzed and determined, and according to the interval ranges into which the priority values ​​of different function categories and the remaining power values ​​of the handheld intelligent ultrasonic diagnostic device fall, the power values ​​allocated to different function categories are analyzed and determined;

[0054] According to the corresponding relationship between the power interval range into which the power value allocated to different functional categories falls and the probe parameter combination, the probe parameter combination of different functional categories is analyzed and determined.

[0055] By adopting the above technical solution, the probe parameter combination can be intelligently adjusted according to the remaining power of the equipment and the inspection requirements. When the power is sufficient, the original settings are maintained. When it is insufficient, the function priority and power allocation are adjusted as needed to ensure the rational use of resources in different scenarios. For example, in emergency, the core functions are given priority, and when the power is low, the non-critical function parameters are appropriately reduced, which not only ensures key diagnosis but also prolongs the use time of the equipment, improves the adaptability and reliability of handheld intelligent ultrasound diagnostic equipment, and provides more accurate and effective support for clinical diagnosis.

[0056] In a second aspect, the present application provides a computer storage medium, which adopts the following technical solution:

[0057] A computer storage medium includes a memory, a processor, and a program stored in the memory and executable on the processor, wherein the program, when loaded and executed by the processor, can implement a method for controlling a handheld intelligent ultrasonic diagnostic device in a control system of a handheld intelligent ultrasonic diagnostic device as described in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic diagram of the overall process of a method for controlling a handheld intelligent ultrasonic diagnostic device in a handheld intelligent ultrasonic diagnostic device control system in an embodiment of the present application.

[0059] Figure 2 It is a flowchart of another embodiment of the present application for detecting and obtaining the pressure value applied by the ultrasound probe to the skin.

[0060] Figure 3 It is a schematic diagram of the process of obtaining a reasonable pressure value range preset in another embodiment of the present application.

[0061] Figure 4 It is a schematic diagram of the process of obtaining a reasonable pressure value range analysis solution based on key pressure characteristics according to another embodiment of the present application. DETAILED DESCRIPTION

[0062] The present application is further described in detail below in conjunction with the accompanying drawings.

[0063] Reference Figure 1 , a control system for a handheld intelligent ultrasonic diagnostic device disclosed in the present application, comprising: an ultrasonic device; at least one processor; at least one memory storing a computer program, wherein the at least one processor is configured to implement a control method for the handheld intelligent ultrasonic diagnostic device when executing the computer program, and the specific steps are as follows:

[0064] Step S100, obtaining the current initial probe parameter settings of the ultrasound probe, the current position coordinates of the ultrasound probe relative to the patient's body, and the patient's specific physiological characteristics.

[0065] Among them, specific physiological characteristics include obesity level and gender, and probe parameter settings include scanning angle range and frequency.

[0066] Specifically, the degree of obesity: It can usually be measured by indicators such as body mass index (BMI), which reflects the patient's body fat content. The degree of obesity can be determined by testing the patient's body composition, such as using a device called bioelectrical impedance analysis to measure fat content.

[0067] Gender: The biological sex of the patient, divided into male and female. Gender can be obtained directly from the patient's medical records.

[0068] Scanning angle range: The range of angles that the ultrasound probe can adjust when scanning, for example, from 30 degrees to 90 degrees. Frequency: The frequency at which the ultrasound probe emits ultrasound waves. Different frequencies are suitable for different inspection sites and depths. The initial probe parameter settings can generally be read from the default settings of the ultrasound device.

[0069] The current position coordinates of the ultrasound probe relative to the patient's body: can be obtained through electromagnetic positioning technology. An electromagnetic sensor is installed on the ultrasound probe, and an electromagnetic field generator is set around the inspection area. The electromagnetic field generator generates a stable magnetic field, and the electromagnetic sensor can detect the changes in the magnetic field and transmit the position information of the probe to the control system of the ultrasound equipment. The control system calculates the position coordinates of the probe relative to the patient's body through an algorithm. For example, when performing a cardiac ultrasound examination, the electromagnetic positioning technology can accurately determine the position of the probe on the patient's chest to better observe the heart structure.

[0070] In step S200, the current initial probe parameter settings of the ultrasound probe, the current position coordinates of the ultrasound probe relative to the patient's body, and the patient's specific physiological characteristics are input into the trained clinical ultrasound probe intelligent control model, and a probe parameter combination that matches the optimal image quality is output.

[0071] In the context of handheld intelligent ultrasound diagnostic equipment, the best image quality refers to the state of ultrasound images that can most clearly and accurately present relevant information such as tissue structure, organ morphology, and lesion characteristics in the patient's body. This state is achieved by comprehensively considering factors such as ultrasound probe parameters (such as scanning angle range and frequency), patient physiological characteristics (such as obesity, gender), and the position coordinates of the ultrasound probe relative to the patient's body.

[0072] Clinical ultrasound probe intelligent control model: This is a model trained with a large amount of data. It can output the probe parameter combination that matches the best image quality based on the input ultrasound probe initial parameter settings, probe position coordinates, and patient physiological characteristics. Probe parameter combination: including but not limited to the combination of scanning angle range, frequency and other parameters. The adjustment of these parameters can achieve the best ultrasound image quality.

[0073] Deep learning technology, such as convolutional neural network (CNN), can be used to build a clinical ultrasound probe intelligent control model. First, a large amount of ultrasound image data with different patient physiological characteristics, probe position coordinates, and corresponding optimal probe parameter combinations are collected as training sets. The data is preprocessed, including normalization, image enhancement, and other operations. Then a suitable CNN architecture is designed to extract and learn features from the input data through multiple layers of convolution, pooling, and fully connected layers. By continuously adjusting the weights and biases of the network and minimizing the loss function using the back propagation algorithm, the model can accurately predict the optimal probe parameter combination. For example, during the training process, for a specific patient, the patient's obesity level, gender, probe position coordinates, and the actual optimal probe parameter combination are known. This information is input into the model, and the model continuously optimizes its own parameters through learning to gradually improve the accuracy of the prediction.

[0074] When it is necessary to output a probe parameter combination that matches the best image quality, the current ultrasound probe initial parameter settings, the current position coordinates of the probe relative to the patient's body, and the patient's specific physiological characteristics are input into the trained intelligent control model. The model performs forward propagation calculations and outputs the predicted probe parameter combination. For example, when performing a liver ultrasound examination, the patient's obesity level is moderately obese, the gender is male, and the current position coordinates of the probe are in the right upper abdominal area. The model calculates and outputs a parameter combination such as the scanning angle range and frequency that is suitable for the patient and the examination site.

[0075] Step S300, adjusting the ultrasonic probe parameters according to the output probe parameter combination, and simultaneously detecting and acquiring the pressure value applied by the ultrasonic probe to the skin.

[0076] Step S400, analyzing whether the pressure value falls within a preset reasonable pressure value range. If not, executing step S500; if yes, executing step S700.

[0077] First, it is necessary to determine the preset reasonable pressure value range. This can be determined through a large number of clinical experiments and data analysis. For example, the pressure value data of different patients during ultrasound examinations, as well as the corresponding image quality and patient feedback information, can be collected. By statistically analyzing these data, a pressure value range that can ensure image quality and high patient comfort can be determined.

[0078] Then, the detected pressure value applied by the ultrasound probe to the skin is compared with this preset interval. This comparison process can be achieved through a software algorithm. A specific program runs in the control system of the ultrasound device to compare the real-time detected pressure value with the upper and lower limits of the preset interval. If the pressure value is within the interval, it is judged as "yes"; if it is not within the interval, it is judged as "no". For example, when performing an abdominal ultrasound examination, the preset reasonable pressure value interval is [X, Y] Newtons. When the detected pressure value is Z Newtons, if X≤Z≤Y, the pressure value is judged to fall within the reasonable interval; otherwise, it is judged to not fall within the reasonable interval.

[0079] Step S500, based on the current position coordinates of the ultrasound probe relative to the patient's body, confirm the current detection part of the ultrasound probe from the preset three-dimensional coordinate model of the human body, and analyze and determine the voice broadcast device reminder method that matches the pressure value based on the matching result between the current detection part of the ultrasound probe and the preset key detection part, the interval range within which the pressure value detected falls, and the voice broadcast device reminder method preset in the ultrasound equipment.

[0080] The three-dimensional coordinate model of the human body is to model the positions of various parts of the human body in space in order to accurately identify the detection position of the probe.

[0081] To confirm the current detection site of the ultrasound probe, a three-dimensional coordinate model of the human body is first established. The three-dimensional image data of the human body can be obtained through medical imaging technology (such as CT scan, MRI, etc.), and then these data are processed and annotated to determine the coordinate range of each body part in three-dimensional space. When the ultrasound probe moves on the patient's body, the position coordinates of the probe are obtained through positioning technology (such as electromagnetic positioning, optical positioning, etc.), and then this coordinate is matched with the three-dimensional coordinate model of the human body. For example, using an electromagnetic positioning system, an electromagnetic sensor is installed on the ultrasound probe, and the position of the probe is determined by detecting changes in the magnetic field. This position coordinate is input into the software system, and the software system calculates and matches according to the three-dimensional coordinate model of the human body to determine the part that the probe is examining, such as the liver, kidneys, etc.

[0082] In order to determine the reminder mode of the voice broadcast device, the reminder modes corresponding to different detection parts and pressure value ranges are pre-set. For example, for the liver examination part, if the pressure value is too low, the voice broadcast is set to "Please increase the probe pressure to obtain a clearer image"; if the pressure value is too high, the voice broadcast is set to "The probe pressure is too high, please reduce it appropriately." After the detection part of the ultrasound probe and the range of the pressure value are determined, the appropriate voice broadcast reminder mode is determined by querying the preset correspondence table. The software system triggers the voice broadcast device to remind according to this determined reminder mode.

[0083] Step S600, the result information that the pressure value falls within the preset reasonable pressure value range is notified through the reminder method determined by analysis.

[0084] If it is determined in step S400 that the pressure value falls within the preset reasonable pressure value range, then a notification is made according to a preset reminder method, which may be in various forms, such as voice broadcast, screen display of prompt information, and the like.

[0085] If voice broadcast is used, different prompt voices can be recorded in advance, and when the conditions are met, the corresponding voices can be played through the audio playback device. For example, record the voice of "pressure value is normal, continue to check", and when the pressure value is in a reasonable range, trigger the audio playback device to play this voice.

[0086] If the prompt information is displayed on the screen, a window may pop up or specific icons and text may be displayed on the display screen of the ultrasound device. For example, the words "pressure is normal" and a green check mark icon may be displayed on the screen, so that the operator can intuitively see the result information that the pressure value is within a reasonable range.

[0087] Step S700: no reminder.

[0088] Reference Figure 2 , the detection and acquisition of the pressure value applied by the ultrasound probe to the skin includes:

[0089] Step S310: start the pressure sensor array arranged on the ultrasound probe to measure and obtain the pressure value between the ultrasound probe and the skin.

[0090] The pressure sensor array here is a collection of multiple pressure sensors arranged at specific positions of the ultrasound probe to accurately measure the pressure generated when the ultrasound probe contacts the patient's skin.

[0091] The pressure sensor array can be a pressure sensor manufactured using micro-electromechanical system (MEMS) technology. These sensors have the advantages of small size, high precision, and fast response speed. During the design stage of the ultrasound probe, the pressure sensor array is reasonably distributed on the surface of the probe or the position inside the probe that contacts the skin. When the ultrasound probe contacts the patient's skin, each sensor in the pressure sensor array starts working, sensing the change in pressure and converting it into an electrical signal. For example, a piezoresistive pressure sensor can be used. When pressure acts on the sensor, the resistance value inside the sensor changes, and the pressure can be determined by measuring the change in resistance value. The sensor transmits the measured pressure value to the control system of the ultrasound equipment in the form of an electrical signal, and the control system processes and analyzes these signals to obtain the pressure value between the ultrasound probe and the skin.

[0092] Step S320: Taking the pressure value measured by each pressure sensor included in the pressure sensor array as a pixel point, a pressure distribution image is constructed and acquired.

[0093] Among them, pixel point: In the constructed pressure distribution image, the pressure value measured by each pressure sensor is regarded as a pixel point, representing a tiny unit in the image, and its grayscale value or color value reflects the corresponding pressure size.

[0094] Pressure distribution image: An image constructed by converting the pressure value measured by each sensor in the pressure sensor array into pixel points. This image intuitively shows the distribution of pressure between the ultrasound probe and the skin, including the size and uniformity of the pressure and the area of ​​local pressure concentration.

[0095] When constructing a pressure distribution image, first transmit the pressure value measured by each sensor in the pressure sensor array to the control system of the ultrasound device. The control system assigns a corresponding image coordinate to each pressure value according to the position of the sensor in the array. Then, map the pressure value to the grayscale value or color value of the pixel. For example, different pressure ranges can be set to correspond to different grayscale levels, with pressure values ​​of 0-10N corresponding to grayscale values ​​of 0-127, and 10-20N corresponding to grayscale values ​​of 128-255. Or use color coding, such as blue for low pressure, yellow for medium pressure, and red for high pressure. Finally, use image generation software to combine these pixels into a complete pressure distribution image and display it on the display screen of the ultrasound device, so that the operator can intuitively observe the pressure distribution.

[0096] Step S330, calculating the average value of the pressure values ​​of all the pixels in the pressure distribution image as the effective pressure value applied by the ultrasonic probe to the skin.

[0097] First, determine the number of pixels in the pressure distribution image. This can be calculated by the resolution of the image, for example, an image with a resolution of 100×100 has a total of 10,000 pixels. Next, read the pressure value corresponding to each pixel. These pressure values ​​are measured by each sensor in the pressure sensor array and are assigned to the corresponding pixel when constructing the pressure distribution image. The pressure value of each pixel can be accessed through the image data storage structure or a specific algorithm. Then, the pressure values ​​of all pixels are accumulated. Use an accumulation variable, starting from the first pixel, and accumulate the pressure value of each pixel to this variable in turn. Finally, calculate the effective pressure value. Divide the accumulated total pressure value by the total number of pixels to get the effective pressure value.

[0098] For example, suppose there is a pressure distribution image with a resolution of 5×5, and the corresponding pixel pressure values ​​are P1=5N, P2=6N, P3=4N, P4=7N, P5=5N, P6=4N, P7=6N, P8=5N, P9=7N, P10=6N, P11=5N, P12=4N, P13=6N, P14=7N, P15=5N, P16=4N, P17=6N, P18=5N, P19=7N, P20=6N, P21=5N, P22=4N, P23=6N, P24=7N, and P25=5N.

[0099] The total pressure value is calculated as follows:

[0100] ∑P=P1+P2+P3+……+P25=

[0101] 5+6+4+7+5+4+6+5+7+6+5+4+6+7+5+4+6+5+7+6+5+4+6+7+5=125N. Then the total number of pixels is calculated to be 25. Finally, the effective pressure value is =∑P / 25=125 / 25=5N.

[0102] Reference Figure 3 , the acquisition of the preset reasonable pressure value range includes:

[0103] Step S410, extracting pressure features from the pressure distribution image, the pressure features including mean, standard deviation, gradient information of pressure distribution, local peaks and valleys.

[0104] Mean: The arithmetic mean of the pressure values ​​of all pixels in the pressure distribution image, reflecting the average level of the overall pressure. Obtaining the mean: The pressure values ​​of all pixels in the pressure distribution image are accumulated, and then divided by the total number of pixels to obtain the mean. For example, there are 100 pixels in the pressure distribution image, and the pressure values ​​are P1, P2, P3...P100 respectively, then the mean = (P1+P2+P3+...+P100) / 100.

[0105] Standard deviation: measures the degree of dispersion of pressure values ​​in the pressure distribution image. The larger the standard deviation, the greater the fluctuation of the pressure value. Obtaining the standard deviation: first calculate the difference between the pressure value of each pixel and the mean, then square and sum these differences, divide them by the total number of pixels, and finally take the square root to get the standard deviation. For example, the mean is M, the pixel pressure value is Pi, and the standard deviation = sqrt(((P1-M)^2+(P2-M)^2+……+(P100-M)^2) / 100).

[0106] Gradient information of pressure distribution: represents the rate of change of pressure in the image space, reflecting the severity and direction of pressure change. Gradient information of pressure distribution: can be obtained by calculating the pressure difference between adjacent pixels. For example, for a two-dimensional pressure distribution image, the pressure difference between adjacent pixels is calculated in the horizontal and vertical directions to obtain the horizontal gradient and vertical gradient.

[0107] Local peak: A local area with relatively high pressure values ​​in the pressure distribution image, which may represent the location where pressure is concentrated. Valley: A local area with relatively low pressure values ​​in the pressure distribution image. Local peak and valley: The local peak and valley can be determined by traversing the pressure distribution image and comparing the pressure values ​​of each pixel with those of its surrounding pixels. If the pressure value of a pixel is greater than the pressure values ​​of all pixels within a certain range around it, then the pixel is a local peak; conversely, if the pressure value of a pixel is less than the pressure values ​​of all pixels within a certain range around it, then the pixel is a valley.

[0108] Step S420: According to the current position coordinates of the ultrasound probe relative to the patient's body, the current detection position of the ultrasound probe is confirmed by matching with a preset three-dimensional human body coordinate model.

[0109] A variety of positioning technologies can be used to determine the current position coordinates of the ultrasound probe relative to the patient's body. For example, an optical positioning system is used to install specific optical markers on the ultrasound probe, and the positions of these markers are tracked by multiple cameras to determine the three-dimensional coordinates of the probe. Alternatively, electromagnetic positioning technology is used to set electromagnetic field generators and sensors around the probe and the inspection area, and the position coordinates of the probe are determined by detecting changes in the magnetic field.

[0110] After the position coordinates of the probe are obtained, they are matched with the preset three-dimensional coordinate model of the human body. The three-dimensional coordinate model of the human body can be constructed through medical imaging data (such as CT scans, MRI, etc.), and the various parts of the human body are marked and the coordinates are determined. The software system compares the position coordinates of the probe with the coordinate ranges of each part in the model to determine the current detection part of the ultrasound probe. For example, if the coordinates of the probe are within the coordinate range of the liver part in the human body model, then it can be determined that the current detection part is the liver.

[0111] Step S430, analyzing and obtaining a reasonable pressure value interval range of the corresponding detection part according to the key pressure feature associated with the preset detection part and a reasonable pressure value interval range analysis scheme based on the key pressure feature.

[0112] Key pressure characteristics associated with the test site: Different test sites have different requirements for the pressure applied by the ultrasound probe. These key pressure characteristics are important indicators that can reflect the rationality of the pressure at a specific test site, such as the mean, standard deviation, etc.

[0113] First, determine the key pressure features associated with different detection sites. This is usually obtained through a large number of clinical experiments and data analysis. For example, for the liver detection site, it may be found that the pressure features with a moderate mean and a small standard deviation are more conducive to obtaining clear ultrasound images. These key pressure features can be pre-stored in the system and correspond to different detection sites.

[0114] There are many ways to analyze the reasonable pressure value range based on key pressure characteristics. A common method is to determine an initial reasonable pressure range based on the pressure characteristic value range of different detection sites under good image quality and patient comfort in historical data. Then, this range is adjusted and optimized through continuous clinical practice and feedback. For example, statistical analysis methods can be used to analyze the relationship between pressure characteristic values ​​and image quality and patient feedback in a large number of liver ultrasound examination cases to determine the reasonable pressure value range of the liver detection site.

[0115] After the detection site and its key pressure characteristics are determined, the reasonable pressure value range of the detection site is calculated according to the analysis scheme. For example, if the current detection site is the kidney, the system calculates the pressure value range suitable for kidney examination, such as [X, Y] Newton, based on the key pressure characteristics associated with the kidney (such as a specific mean and standard deviation range) and the analysis scheme. This range can provide a reference for pressure adjustment during ultrasound examination to ensure the accuracy of the examination and the comfort of the patient.

[0116] Reference Figure 4 , the acquisition of reasonable pressure value range analysis scheme based on key pressure characteristics includes:

[0117] Step S431, obtaining specific requirement information of the detection part, the specific requirement information includes anatomical structure parameters and physiological function parameters.

[0118] Specific requirements for the test site: For different ultrasound test sites, there are specific anatomical structure and physiological function parameter requirements. These parameters are crucial to determine the reasonable pressure value range for the site.

[0119] Anatomical parameters: Parameters that describe the specific anatomical morphological characteristics of the test site in the human body, such as the size, shape, and position of the organ. Anatomical parameters can be obtained through medical imaging technology. For example, patients are examined using imaging equipment such as CT scans and MRIs to obtain detailed anatomical images of the test site, from which parameters such as the size, shape, and position of the organ are measured. Alternatively, medical literature and anatomical databases can be referenced to obtain the typical anatomical parameter range of a specific test site.

[0120] Physiological function parameters: Parameters that reflect the functional characteristics of the test site in the physiological activities of the human body, such as the blood flow velocity and metabolic rate of the organ. Physiological function parameters can be obtained through specific physiological testing equipment or laboratory tests. For example, for the heart test site, electrocardiogram, echocardiogram and other equipment can be used to measure physiological parameters such as the contraction and relaxation function of the heart and blood flow velocity. For the liver test site, blood tests can be used to measure liver function indicators, which indirectly reflect the physiological function status of the liver.

[0121] For example, when performing a liver ultrasound examination, by consulting medical literature and anatomical databases, we determine that the average size of the liver is approximately 25-30 cm long, 15-20 cm wide, and 10-15 cm thick, among other anatomical structural parameters. At the same time, blood tests are performed to obtain liver function indicators, such as alanine aminotransferase and aspartate aminotransferase, which reflect physiological function parameters such as the liver's metabolic function.

[0122] Step S432, taking the specific requirement information of the detection part and the key pressure feature information associated with the detection part as input variables, inputting them into the trained pressure interval range analysis model, and outputting the pressure interval range.

[0123] Pressure range analysis model: This is a trained model that can output the reasonable pressure range of the test site based on the specific requirements of the test site and key pressure feature information. The model establishes a mapping relationship between input information and pressure range by learning a large amount of historical data and expert experience.

[0124] Input variables: including specific requirements of the test site (anatomical structure parameters and physiological function parameters) and key pressure characteristic information associated with the test site. This information is used as the input of the model to predict the reasonable pressure range.

[0125] Output pressure range: that is, the reasonable range of pressure applied by the ultrasound probe suitable for a specific detection site predicted by the model. This range can provide guidance for pressure adjustment during ultrasound examination.

[0126] Machine learning algorithms, such as neural networks and support vector machines, can be used to build pressure range analysis models. First, collect a large amount of historical data from different test sites, including anatomical structure parameters, physiological function parameters, key pressure characteristics, and the corresponding actual reasonable pressure range. Preprocess these data, including data cleaning, feature extraction, and other operations. Then select a suitable machine learning algorithm, divide the data into training sets and test sets, use the training set to train the model, and continuously adjust the model's parameters to improve prediction accuracy. Finally, use the test set to evaluate the trained model to ensure that the model's performance meets the requirements.

[0127] When it is necessary to determine the reasonable pressure range of a certain detection part, the specific requirements information and key pressure feature information of the detection part are organized into the input format required by the model and input into the trained pressure range analysis model. After calculation, the model outputs the predicted pressure range.

[0128] For example, for cardiac ultrasound examinations, a large amount of historical data on cardiac anatomical parameters (such as heart size, ventricular wall thickness, etc.), physiological function parameters (such as heart rate, cardiac output, etc.), key pressure features (such as pressure mean, standard deviation, etc.) and corresponding reasonable pressure ranges of different patients are collected. These data are used to train the neural network model. When it is necessary to determine the reasonable pressure range for a new patient's cardiac examination, the patient's heart-specific requirements and key pressure features are input into the model. The model outputs the predicted pressure range, such as [X, Y] Newton, to provide a reference for pressure adjustment during the ultrasound examination.

[0129] The acquisition of reasonable pressure value range analysis scheme based on key pressure characteristics includes:

[0130] Step S43a, obtaining the weight corresponding to the key pressure feature associated with the preset detection part, and calculating the weighted average pressure value through a weighted average algorithm according to the specific value of the key pressure feature and the weight corresponding to the key pressure feature.

[0131] Weights corresponding to key pressure features: Different key pressure features have different importance in determining the reasonable pressure value range. Each key pressure feature is assigned a weight value to reflect its relative importance.

[0132] Weighted average algorithm: A calculation method that performs weighted summation of data according to the weight of each data, and then divides it by the total weight to obtain the weighted average.

[0133] Weighted average pressure value: A value obtained by weighted averaging the key pressure features associated with the detection area, which is used to further determine the range of reasonable pressure values.

[0134] The weights corresponding to the key pressure features can be determined through expert experience, data analysis, and other methods. For example, experts in the field of ultrasound can be invited to give the weight value of each feature based on the degree of impact of different key pressure features on image quality and patient comfort. Alternatively, by analyzing a large amount of historical ultrasound examination data, the correlation between different key pressure features and the range of reasonable pressure values ​​can be calculated, and the weight can be determined based on the size of the correlation.

[0135] For the calculation of the weighted average algorithm, first obtain the specific value of each key pressure feature, and then multiply it by its corresponding weight. Add the weighted values ​​of all key pressure features and divide them by the total weight to get the weighted average pressure value.

[0136] For example, assuming that the detection part has key pressure features A, B, and C, their corresponding weights are wA, wB, and wC, and their specific values ​​are VA, VB, and VC, respectively. Then the weighted average pressure value P = (wA×VA+wB×VB+wC×VC) / (wA+wB+wC).

[0137] Step S43b, according to the preset standard deviation multiples associated with the detection parts, the standard deviation of the associated standard deviation multiples is added or subtracted from the weighted average pressure value to form a reasonable pressure value interval range based on the key pressure feature.

[0138] Standard Deviation Multiple: A coefficient used to determine the range of reasonable pressure values. It is used in conjunction with the standard deviation to determine the fluctuation range of reasonable pressure values.

[0139] Specifically, first determine the standard deviation multiple associated with the preset detection site. This multiple can be determined by empirical value or obtained through data analysis. For example, after a lot of clinical practice and data analysis, it is found that for a specific detection site, adding or subtracting 2 times the standard deviation of the weighted average pressure value can obtain a more reasonable pressure value range, so the standard deviation multiple here is determined to be 2.

[0140] Then, according to the weighted average pressure value obtained in step S43a, and the standard deviation corresponding to the detection part (the standard deviation can be obtained by statistically analyzing the pressure values ​​of the detection part in the historical data), the reasonable pressure value interval is calculated. The specific calculation method is: interval lower limit = weighted average pressure value - standard deviation multiple × standard deviation; interval upper limit = weighted average pressure value + standard deviation multiple × standard deviation.

[0141] For example, assuming that the weighted average pressure value of a certain detection part is P, the standard deviation of the part is σ, and the standard deviation multiple is determined to be 3. Then the reasonable pressure value range is [P-3σ, P+3σ]. P=10N, σ=2N, then the reasonable pressure value range is [10-3×2,10+3×2]=[4N,16N].

[0142] If yes, no reminder will be given including:

[0143] Step S710, extracting pressure features from the pressure distribution image, and analyzing whether the pressure feature values ​​of different categories fall within the preset pressure feature value threshold range of the corresponding category. If yes, execute step S720; if no, execute step S730.

[0144] Specifically, various mathematical and image processing methods can be used to extract pressure features. For example, for the mean, the pressure values ​​of all pixels in the pressure distribution image can be accumulated and then divided by the total number of pixels to obtain the mean. For the standard deviation, the difference between the pressure value of each pixel and the mean can be calculated, and these differences can be squared and summed, and then divided by the total number of pixels, and finally the square root can be taken to obtain the standard deviation. The gradient information of the pressure distribution can be obtained by calculating the pressure difference between adjacent pixels.

[0145] The threshold ranges of pressure feature values ​​for different categories can be determined in the following ways: First, collect a large number of pressure distribution image data from normal ultrasound examination cases and analyze the value ranges of different pressure features in these data. Then, based on clinical experience and expert opinions, determine a reasonable threshold range so that the pressure feature values ​​within this range are considered normal. For example, for liver ultrasound examination, after data analysis, it is found that the mean value within the range of [X1, Y1] and the standard deviation within the range of [X2, Y2] are considered normal, so these ranges are set as the corresponding pressure feature value threshold ranges.

[0146] Analyzing whether the pressure characteristic values ​​of different categories fall within the preset threshold range of the corresponding category pressure characteristic values ​​can be achieved by comparing the pressure characteristic value with the upper and lower limits of the threshold range. If the pressure characteristic value is within the threshold range, it is judged as "yes"; if it is not within the threshold range, it is judged as "no". For example, for a certain pressure characteristic value P, if X≤P≤Y (where [X,Y] is the threshold range of the pressure characteristic), it is considered that the pressure characteristic value falls within the preset threshold range.

[0147] Pressure characteristic value threshold range: a numerical range pre-set for different types of pressure characteristics, used to determine whether the pressure characteristic value is within a reasonable range.

[0148] Step S720: no reminder;

[0149] Step S730: Analyze and determine the reminder information based on the correspondence between the result information of different categories of pressure characteristic values falling within the preset corresponding category pressure characteristic value threshold ranges and the reminder information, and broadcast the reminder information through a voice broadcast device.

[0150] Reminder information: The content of the information used to remind the operator determined according to the comparison result of the pressure characteristic value and the threshold range, which may include specific prompts such as too high pressure or too low pressure.

[0151] Voice broadcast device: A device capable of playing the reminder information in voice form so that the operator can timely understand the pressure status and make adjustments.

[0152] Specifically, first, determine the result information of different categories of pressure characteristic values falling within the preset corresponding category pressure characteristic value threshold ranges. This step is the result obtained after judging whether different categories of pressure characteristic values are within the threshold range in step S710, and there may be various situations, such as some characteristic values being within the range while some are not, or all not being within the range, etc.

[0153] Then, analyze and determine the reminder information according to the preset correspondence. This correspondence is preset. For example, if the mean pressure characteristic value is lower than the lower limit of the threshold range, the corresponding reminder information can be "The pressure is too low, please appropriately increase the pressure"; if the standard deviation pressure characteristic value is higher than the upper limit of the threshold range, the corresponding reminder information can be "The pressure fluctuates greatly, please adjust the probe position or pressure", etc.

[0154] Finally, broadcast the determined reminder information through a voice broadcast device. The voice broadcast device can be a speaker on the ultrasonic device or an external audio device. After the reminder information is determined, the system sends this information to the voice broadcast device, which plays it in voice form so that the operator can hear it in time and take corresponding measures.

[0155] For example, during an ultrasonic examination, the mean pressure characteristic value extracted from the pressure distribution image is P_mean, and the standard deviation pressure characteristic value is P_std. The preset mean threshold range is [Mean_min, Mean_max], and the standard deviation threshold range is [Std_min, Std_max]. If P_mean < Mean_min and P_std > Std_max, according to the preset correspondence, the determined reminder information is "The pressure is too low and fluctuates greatly, please appropriately increase the pressure and adjust the probe position". Then, the voice broadcast device plays this reminder information to remind the operator to make adjustments.

[0156] Further, according to the correspondence between the result information of the pressure characteristic values ​​of different categories falling into the preset corresponding category pressure characteristic value threshold range and the reminder information, analyzing and determining the reminder information, and broadcasting the reminder information through the voice broadcast device includes:

[0157] Step S731, analyzing whether the motion data of the ultrasound probe is obtained, the motion data including moving speed, direction change and acceleration.

[0158] Movement speed: refers to how fast the ultrasound probe moves relative to the patient's skin during the examination, usually measured in distance per unit time, such as cm / s. For example, when a doctor performs an ultrasound examination, moving the probe quickly and moving the probe slowly will produce different pressure distributions and image effects. Direction change: refers to the change in direction of the ultrasound probe during the examination, which can be expressed in angles. For example, from horizontal to vertical, or from one specific angle to another. The change in direction affects the contact area and angle between the probe and the skin, thereby affecting the pressure distribution. Acceleration: refers to how fast the speed of the ultrasound probe changes during movement, usually measured in the amount of change in speed per unit time, such as cm / s². When the probe suddenly accelerates or decelerates, it will have an instantaneous effect on the pressure distribution, which may cause image quality to deteriorate.

[0159] The specific acquisition method is as follows: Install a miniature accelerometer on the ultrasound probe. The accelerometer is a sensor that can measure the acceleration of an object. It determines the movement speed and acceleration of the probe by detecting the acceleration changes of the probe on the three coordinate axes. For example, when the doctor moves the probe quickly, the accelerometer will detect a larger acceleration value. Install a gyroscope, which can measure the angular velocity of the probe to determine the direction change of the probe. For example, when the doctor turns the probe, the gyroscope will detect the corresponding angular velocity changes, and the angle of the probe's direction change can be obtained by integration. A magnetometer can also be installed. The magnetometer can detect the direction of the earth's magnetic field. Combining the data of the accelerometer and gyroscope, the orientation and direction changes of the probe can be determined more accurately.

[0160] Step S732: If no, execute according to the original settings.

[0161] Step S733, if yes, then according to the correspondence between the result information of different categories of pressure characteristic values ​​falling into the preset corresponding category pressure characteristic value threshold range and the reminder information, the first reminder information is analyzed and determined, and at the same time, according to the correspondence between the result information of different categories of motion data of the ultrasound probe falling into the corresponding preset category motion data threshold and the second reminder information, the second reminder information is analyzed and determined.

[0162] The acquisition of exercise data and the second reminder information is as follows:

[0163] The motion data of the ultrasound probe can be obtained through sensors installed on the probe, such as accelerometers to measure acceleration, gyroscopes to measure changes in direction, and magnetometers to assist in determining orientation. These sensors collect the motion data of the probe in real time and transmit the data to the control system of the device.

[0164] The motion data threshold can be determined through experiments and clinical experience. For example, for different examination parts and examination purposes, the appropriate movement speed range, direction change angle range and acceleration range can be determined through multiple experiments and observations.

[0165] The second reminder information is determined based on the comparison result of the motion data with the corresponding threshold. If the motion data is within the threshold range, usually no reminder is needed or a reminder of "normal motion" can be given; if the motion data exceeds the threshold range, the reminder content is determined according to the specific circumstances of the exceeding, such as "moving speed too fast", "direction change too large" or "acceleration too large".

[0166] Step S734, combining the second reminder information and the first reminder information into a new reminder information, and announcing the new reminder information through a voice announcement device.

[0167] Second reminder information: The reminder content is determined based on the result information that different categories of motion data of the ultrasound probe fall into the corresponding preset category motion data threshold, which is mainly related to the motion status of the probe, such as "moving too fast, please slow down" and "direction changes significantly, please adjust the direction".

[0168] The first reminder information: the reminder information is determined based on the result information that the pressure characteristic values ​​of different categories fall into the preset threshold range of the corresponding category pressure characteristic values, which is mainly related to the pressure distribution, such as "the pressure is too high, please adjust the probe pressure" and "the pressure is too low, please check carefully".

[0169] New reminder information: The comprehensive reminder content obtained by merging the second reminder information and the first reminder information is intended to provide the doctor with information on pressure distribution and probe movement status at the same time, so that the doctor can better adjust the examination operation.

[0170] Assume that in an abdominal ultrasound examination, the pressure characteristic value analyzed from the pressure distribution image is high, and the first reminder message is "pressure is too high, please adjust the probe pressure". At the same time, the sensor detects that the movement speed of the probe exceeds the preset threshold range, and the second reminder message is "moving too fast, please slow down".

[0171] The two reminder messages are combined into a new reminder message: "The pressure is too high, please adjust the probe pressure; at the same time, the movement speed is too fast, please slow down." Then, this new reminder message is broadcast to the doctor through the voice broadcast device. The doctor can adjust the pressure and movement speed of the probe in time according to the reminder to obtain more accurate examination results.

[0172] In addition, regarding the specific reminder information being broadcasted through the voice broadcast device, a decision tree algorithm may also be considered, as follows:

[0173] Step Sa00 collects characteristic data of the doctor and the patient, motion data of the probe (moving speed, direction change, acceleration, etc.), and relevant data of the first reminder information and the second reminder information. The characteristic data of the doctor includes the doctor's experience level (which can be divided into categories such as novice, intermediate, and advanced), and the characteristic data of the patient includes the characteristics of the patient's condition (such as disease type, severity, etc.).

[0174] Acquisition of doctor characteristic data: Doctors can enter their experience level through the system interface before using the device, such as selecting novice, intermediate or advanced options when logging into the system. The system can also automatically determine the doctor's experience level based on the doctor's historical operation data. For example, the experience level can be determined by analyzing factors such as the doctor's proficiency in operating the device over the past period of time and the frequency of adjusting probe parameters.

[0175] Acquisition of patient characteristic data: The patient's condition characteristics can be obtained from the electronic medical record system. Before the ultrasound examination, the device can be connected to the hospital's information system to read the patient's disease type and severity. Doctors can also manually enter the patient's condition characteristics before the examination begins so that the system can better generate reminder information.

[0176] Step Sb00, pre-processing the data, for example, encoding the doctor's experience level and the patient's condition characteristics, discretizing the continuous motion data, etc., to facilitate the use of the decision tree algorithm.

[0177] Coding of doctor experience level and patient condition characteristics: For the doctor's experience level, novice can be coded as 1, intermediate as 2, and advanced as 3. In this way, different experience levels can be represented by numerical values, which is convenient for the algorithm to process.

[0178] For the characteristics of the patient's condition, the disease type can be coded according to a pre-set coding table. For example, heart disease is coded as 1, liver disease is coded as 2, etc. The severity can be divided into three levels: mild, moderate, and severe, coded as 1, 2, and 3 respectively.

[0179] Discretization of probe motion data: The moving speed can be divided into several intervals according to the actual situation. For example, the interval with a moving speed less than 5 cm / s is coded as 1, the interval with a moving speed between 5 cm / s and 10 cm / s is coded as 2, and the interval with a moving speed greater than 10 cm / s is coded as 3.

[0180] Direction changes can be discretized based on the angle range. For example, the interval of direction change less than 30 degrees is encoded as 1, the interval between 30 degrees and 60 degrees is encoded as 2, and the interval greater than 60 degrees is encoded as 3. Acceleration can also be divided into different intervals for encoding.

[0181] Data standardization: If the data has different dimensions, you can standardize it so that the different data have the same scale. For example, normalize all data to the range of 0 to 1, or perform Z-score standardization.

[0182] Assume that the following data is collected: the doctor's experience level is intermediate, the patient has heart disease with moderate severity, the probe movement speed is 8 cm / s, the direction change is 45 degrees, the acceleration is 3 cm / s², the first reminder message is "moderate pressure", and the second reminder message is "slightly faster speed".

[0183] After coding and discretization, the data becomes: doctor experience level is coded as 2, heart disease is coded as 1, severity is coded as 2, movement speed is coded as 2, direction change is coded as 2, and acceleration is coded as appropriate intervals. The processed data can be better used by the decision tree algorithm for subsequent analysis and judgment.

[0184] Step Sc00, input the characteristics of the doctor and the patient, as well as the motion data of the probe, into the constructed decision tree model. The decision tree judges and splits step by step from the root node downward according to the input feature variables until it reaches the leaf node. The category corresponding to the leaf node is the category of the new reminder information. If it is a detailed reminder category, the first reminder information and the second reminder information are merged in detail, for example, "The pressure is too high, please adjust the probe pressure. At the same time, the moving speed is too fast, please slow down, and be careful not to change the direction too much." If it is a concise reminder category, a concise merger is performed, such as "Pressure and speed need to be adjusted."

[0185] The specific process is as follows:

[0186] Input data: The pre-processed doctor and patient characteristics and probe motion data are input into the constructed decision tree model. These data are used as input variables of the decision tree to make decisions starting from the root node.

[0187] Start judging from the root node: The decision tree starts from the root node and judges the input data according to the characteristic attribute test condition of the node. For example, if the test condition of the root node is whether the doctor's experience level is novice, then the judgment is made according to the doctor's experience level code in the input data.

[0188] Step by step, judge and split downward: If the input data meets the test condition of the root node, move down along the corresponding branch to the next node. At each node, further judge the input data according to the characteristic attribute test condition of the node. If the input data does not meet the test condition of the current node, continue to move down along another branch. This process is repeated until a leaf node is reached.

[0189] Determine the category of the leaf node: When reaching a leaf node, determine the category of the new reminder information according to the category represented by the leaf node. If the leaf node represents a detailed reminder category, then the first reminder information and the second reminder information are merged in detail; if the leaf node represents a concise reminder category, then a concise merger is performed.

[0190] Assume that the constructed decision tree model is as follows:

[0191] Root node: whether the doctor's experience level is novice (if yes, branch left, otherwise branch right).

[0192] Left branch node: whether the patient's condition is severe (if yes, branch to the left, otherwise branch to the right). Left branch node (leaf node) of the left branch: detailed reminder category. Right branch node (leaf node) of the left branch: concise reminder category. Right branch node: whether the probe moves too fast (if yes, branch to the left, otherwise branch to the right). Left branch node (leaf node) of the right branch: detailed reminder category. Right branch node (leaf node) of the right branch: concise reminder category.

[0193] Now there is a set of input data: the doctor's experience level is intermediate (coded as 2), the severity of the patient's condition is moderate (coded as 2), and the probe movement speed is 8 cm / s (coded as 2).

[0194] First, we start from the root node. Since the doctor is not a novice, we continue to move down along the right branch. Then, we determine whether the probe is moving too fast. Assuming that according to the pre-set standard, a speed of 8 cm / s is not too fast, we continue to move along the right branch of the right branch and reach the leaf node, which represents the concise reminder category.

[0195] Therefore, for this set of input data, the new reminder information will be a concise reminder category, which is concisely merged according to the first reminder information and the second reminder information.

[0196] Step Sd00, broadcasting the generated new reminder information through a voice broadcasting device.

[0197] A control system for a handheld intelligent ultrasonic diagnostic device further includes steps after the reminder information is broadcasted through a voice broadcast device, which are as follows:

[0198] Step SA00, monitoring and obtaining the pressure characteristic value after the preset time interval of the reminder message broadcast.

[0199] Preset time interval for reminder message broadcast: After the voice broadcast of the reminder message, a specific length of time will pass, which is used to wait for the operator to adjust the pressure or observe the pressure changes.

[0200] Specifically, first determine the length of the preset time interval for the reminder message broadcast. This time interval can be set according to actual conditions, for example, it can be set to a few seconds to a few minutes. Considering the operator's reaction time and the actual needs of the ultrasound examination, a moderate time interval can usually be selected so that the operator has enough time to make adjustments while not making the inspection process too lengthy.

[0201] After a preset time interval, the pressure sensor array is started again to measure the pressure value between the ultrasound probe and the skin, and the pressure characteristic value is extracted from the new pressure distribution image. This process is the same as the method of extracting the pressure characteristic value in the previous step, for example, the average value of the pressure values ​​of all pixels in the pressure distribution image can be calculated as the mean pressure characteristic value, and the standard deviation of the pressure value can be calculated as the standard deviation pressure characteristic value.

[0202] For example, suppose the preset time interval for the reminder message is 10 seconds. After the reminder message is broadcast, the system starts timing and waits for 10 seconds. During these 10 seconds, the operator can adjust the pressure of the ultrasound probe according to the reminder message or observe the pressure changes. After 10 seconds, the system starts the pressure sensor array again to measure the new pressure value and extract the pressure feature values, such as the mean, standard deviation, etc., from the new pressure distribution image to further analyze the pressure condition of the ultrasound probe.

[0203] Step SB00, analyzing whether the proportion of the pressure value on one side of the ultrasonic probe to the overall pressure exceeds a preset proportion based on the mean value included in the pressure characteristic value. If not, execute step SC00; if yes, execute step SD00.

[0204] The mean value contained in the pressure feature value is the arithmetic mean of the pressure values ​​of all pixels in the pressure distribution image, which reflects the average level of the overall pressure.

[0205] The proportion of the pressure value on one side of the ultrasound probe to the overall pressure: the ratio of the sum of the pressure values ​​on one side of the ultrasound probe in contact with the skin to the sum of the pressure values ​​applied by the entire probe.

[0206] Preset ratio: A preset ratio value used to determine whether the pressure concentration on one side of the ultrasound probe is too high.

[0207] Specifically, first, the mean value contained in the pressure characteristic value is determined. This mean value can be obtained by the method of extracting the pressure characteristic value in the previous step, that is, calculating the average value of the pressure values ​​of all pixels in the pressure distribution image.

[0208] Then, the proportion of the pressure value on one side of the ultrasound probe to the overall pressure is calculated. The area where the ultrasound probe contacts the skin can be divided into different parts, such as the left and right sides, the upper and lower sides, etc. For a specific side, the sum of the pressure values ​​of all pixels on that side is counted, and then compared with the sum of the pressure values ​​applied by the entire probe to obtain the proportion of the pressure value on that side to the overall pressure.

[0209] Finally, the calculated proportion is compared with the preset proportion. If the proportion exceeds the preset proportion, it is judged as "yes"; if the proportion does not exceed the preset proportion, it is judged as "no".

[0210] For example, assume that the area where the ultrasound probe contacts the skin is divided into left and right sides, and the mean value contained in the pressure feature value is P_mean. The sum of the pressure values ​​of all pixels on the left is P_left_sum, and the sum of the pressure values ​​applied by the entire probe is P_total_sum. The proportion of the left pressure value to the overall pressure is P_left_sum / P_total_sum. If the preset proportion is 60%, when the calculated proportion is greater than 60%, it is judged as "yes"; when the proportion is less than or equal to 60%, it is judged as "no".

[0211] Step SC00 , analyzing and determining the adjustment measures of the ultrasonic probe according to the correspondence between the interval range in which the mean value included in the pressure characteristic value falls and the parameter adjustment measures of the ultrasonic probe, and executing the adjustment measures of the ultrasonic probe.

[0212] The correspondence between the interval range and the parameter adjustment measures of the ultrasonic probe: Different mean pressure value intervals correspond to specific ultrasonic probe parameter adjustment measures, the purpose of which is to optimize the inspection effect and pressure distribution by adjusting the probe parameters.

[0213] Specifically, first, the mean value contained in the pressure characteristic value is determined. This is consistent with the method of extracting the pressure characteristic value in the previous step, that is, the mean pressure characteristic value is obtained by calculating the average value of the pressure values ​​of all pixels in the pressure distribution image.

[0214] Then, the judgment is made according to the preset mean pressure value interval range. The mean pressure value can be divided into multiple intervals, each interval corresponding to different ultrasonic probe parameter adjustment measures. For example, a low pressure interval, a moderate pressure interval, and a high pressure interval can be set.

[0215] Finally, the adjustment measures of the ultrasound probe are determined according to the range in which the mean falls. If the mean falls into the low pressure range, possible adjustment measures include increasing the pressure applied by the probe, adjusting the probe frequency to improve penetration, etc. If the mean falls into the moderate pressure range, there may be no need for adjustment or fine-tuning, such as optimizing image display parameters, etc. If the mean falls into the high pressure range, possible adjustment measures include reducing the pressure applied by the probe, adjusting the probe angle to reduce pressure concentration, etc.

[0216] For example, assume that three mean pressure intervals are preset: [0, P1] is a low pressure interval, [P1, P2] is a moderate pressure interval, and [P2, ∞) is a high pressure interval. When the determined mean pressure value is P, if P is in the interval [0, P1], the analysis determines that the ultrasonic probe adjustment measures are to increase the probe pressure and adjust the probe frequency; if P is in the interval [P1, P2], there may be no need for adjustment or fine-tuning; if P is in the interval [P2, ∞), the adjustment measures are to reduce the probe pressure and adjust the probe angle. Then perform the corresponding adjustment measures to improve the effect of ultrasonic inspection and pressure distribution.

[0217] Step SD00, based on the correspondence between the result information that one side of the ultrasonic probe exceeds the preset proportion and the parameter adjustment measures of the ultrasonic probe, analyze and determine the adjustment measures of the ultrasonic probe, and execute the adjustment measures of the ultrasonic probe.

[0218] The result information of one side of the ultrasound probe exceeding the preset ratio: refers to the ratio of the sum of the pressure values ​​on one side of the ultrasound probe in contact with the skin to the sum of the pressure values ​​applied by the entire probe exceeding the preset ratio. This indicates that the pressure concentration of the ultrasound probe on this side is too high, which may affect the examination effect and patient comfort.

[0219] Ultrasonic probe parameter adjustment measures: In response to the situation where the pressure concentration on one side of the ultrasonic probe is too high, a series of adjustment operations are taken to optimize the pressure distribution and improve the inspection quality.

[0220] Specifically, first, determine the result information that one side of the ultrasonic probe exceeds the preset proportion. In the previous step, the proportion of the pressure value on one side of the ultrasonic probe to the overall pressure has been calculated and compared with the preset proportion. If the judgment is "yes", it means that one side of the ultrasonic probe exceeds the preset proportion.

[0221] Then, the adjustment measures of the ultrasound probe are determined based on the preset corresponding relationship analysis. This corresponding relationship is pre-set, and the corresponding adjustment measures are determined according to different pressure concentration situations. For example, if the pressure concentration on the left side is too high, you can consider adjusting the probe angle to make the pressure more evenly distributed in the inspection area; or adjust the position of the probe to avoid continuous pressure on the side with pressure concentration.

[0222] Finally, the determined ultrasound probe adjustment measures are performed. This can be done by automatically adjusting the probe parameters through the control system, or by prompting the operator to make manual adjustments.

[0223] For example, assuming the preset ratio is 60%, after calculation, it is found that the pressure value on the left side of the ultrasound probe accounts for 70% of the overall pressure, which exceeds the preset ratio. According to the preset corresponding relationship, the adjustment measure is to move the probe slightly to the right by a certain angle and appropriately reduce the probe pressure. Then, the control system automatically adjusts the position and pressure of the probe, or issues corresponding prompts to the operator, who makes adjustments to improve the pressure distribution and improve the quality of ultrasound examination.

[0224] The current initial probe parameter settings of the ultrasound probe, the current position coordinates of the ultrasound probe relative to the patient's body, and the specific physiological characteristics of the patient are input into the trained clinical ultrasound probe intelligent control model, and the output probe parameter combination matching the best image quality includes:

[0225] Step S210, obtaining the remaining power value of the handheld intelligent ultrasonic diagnostic device.

[0226] Remaining power value: refers to the current remaining power of the handheld intelligent ultrasonic diagnostic device, usually expressed in units such as percentage, milliampere-hour, etc. This value reflects the time and ability of the device to continue working.

[0227] The remaining power value is obtained as follows: Handheld intelligent ultrasonic diagnostic equipment is usually equipped with power detection sensors, which can monitor the battery power of the equipment in real time. These sensors calculate the remaining power value by measuring battery voltage, current and other parameters. For example, by measuring the open circuit voltage of the battery, the percentage of remaining power can be roughly estimated.

[0228] Step S220, analyzing whether the remaining power value of the handheld intelligent ultrasonic diagnostic device exceeds a preset power threshold. If yes, executing step S230; if no, executing step S240.

[0229] Preset power threshold: A preset power value used to determine whether the remaining power of the handheld intelligent ultrasonic diagnostic device is sufficient. This threshold is usually determined according to different working modes, functional requirements and usage scenarios of the device.

[0230] Step S230, maintaining the original settings.

[0231] Step S240, obtaining the specific requirements of this inspection, and analyzing and determining the order of priority of different functional categories according to the corresponding relationship between the inspection requirements and the order of priority of different functional categories of the ultrasonic diagnostic equipment.

[0232] Among them, examination needs include emergency examination needs, physical examination needs, and specialist examination needs; the functional categories of ultrasound diagnostic equipment include core functions, advanced functions, and auxiliary functions.

[0233] Examination requirements: refers to the specific purpose and requirements of ultrasound examinations. Different examination requirements determine the focus and priority of the equipment functions. For example, emergency examination requirements usually emphasize rapid diagnosis and key information acquisition, physical examination requirements focus on comprehensive screening and efficiency, and specialist examination requirements focus on in-depth examinations of specific diseases or organs.

[0234] Function category priority order: According to different inspection requirements, the functions of ultrasound diagnostic equipment are divided into core functions, advanced functions and auxiliary functions, and their priorities in different situations are determined. Core functions are basic functions that the equipment must have, such as basic ultrasound image acquisition and display; advanced functions include some more complex analysis and processing functions, such as three-dimensional imaging, hemodynamic analysis, etc.; auxiliary functions are some auxiliary functions, such as data storage, printing, etc.

[0235] Specifically, the specific requirements for this examination can be obtained as follows: when the device is started, a selection interface is displayed to allow the doctor to select the type of examination, such as emergency examination, physical examination or specialist examination. The examination requirements can also be automatically determined based on the scene and purpose of the examination. For example, if the device is connected to the network system of the emergency room, or detects that the patient is in an emergency state, it can be automatically determined as an emergency examination requirement.

[0236] The specific correspondence between the inspection requirements and the priority order of functional categories is determined as follows: Based on clinical experience and professional knowledge, the corresponding rules between different inspection requirements and functional category priorities are pre-set. For example, for emergency inspection requirements, the core function has the highest priority to ensure rapid acquisition of key diagnostic information; for physical examination requirements, efficiency and comprehensiveness are more important, and the priority of core functions and auxiliary functions may be appropriately balanced; for specialist inspection requirements, the priority of certain advanced functions may be increased according to specific specialist requirements.

[0237] Analyze and determine the priority ranking of different functional categories: According to the obtained inspection requirement information, the priority ranking of core functions, advanced functions and auxiliary functions in this inspection is determined according to the pre-set correspondence. For example, if it is an emergency inspection requirement, the core function may be ranked first, and the priority of advanced functions and auxiliary functions is relatively low; if it is a specialist inspection requirement, the priority ranking of advanced functions may be adjusted according to the characteristics of the specialist.

[0238] Step S250, analyze and determine the priority values ​​of different function categories based on the corresponding results of the function category priority sorting positions and the priority values, and analyze and determine the power values ​​allocated to different function categories based on the priority values ​​of different function categories and the interval ranges into which the remaining power values ​​of the handheld intelligent ultrasonic diagnostic device fall.

[0239] According to the correspondence between the priority ranking of the functional categories and the priority values, the priority values ​​of different functional categories are analyzed and determined: a correspondence table between the priority ranking of the functional categories and the priority values ​​is preset. For example, the first functional category corresponds to a priority value of 80, the second corresponds to 60, and the third corresponds to 40. According to the priority ranking of the functional categories determined in step S240, the correspondence table is searched to determine the priority value of each functional category.

[0240] According to the priority values ​​of different functional categories and the interval ranges into which the remaining power value of the handheld intelligent ultrasonic diagnostic device falls, the power values ​​allocated to different functional categories are analyzed and determined: First, the interval range into which the remaining power value of the device falls is analyzed. For example, if the remaining power is 55%, it is judged to be a medium power interval. Different power allocation strategies are formulated for different power intervals. For example, in the high power interval, a relatively balanced power allocation can be made according to the proportion of the priority value; in the medium power interval, the power allocation ratio of advanced functions and auxiliary functions is appropriately reduced to ensure the stable operation of the core functions; in the low power interval, the core functions are prioritized and the power allocation of advanced functions and auxiliary functions is greatly reduced. According to the power allocation strategy and the priority value of the functional category, the power value allocated to each functional category is calculated. For example, if in the medium power interval, the core function priority value is 80, the advanced function is 60, the auxiliary function is 40, and the total power is 1000 mAh, then it can be allocated according to the proportion of 500 mAh for the core function, 300 mAh for the advanced function, and 200 mAh for the auxiliary function.

[0241] Suppose that in an inspection, after step S240, it is determined that this inspection is a specialist inspection requirement, and the priority ranking of the function categories is the second for core functions, the first for advanced functions, and the third for auxiliary functions. At the same time, the device detects that the remaining power is 40%, which falls into the low power interval. According to the pre-set correspondence, the priority values ​​of the core function are 80, the advanced function is 60, and the auxiliary function is 40. The power allocation strategy in the low power interval is to give priority to the core function and greatly reduce the power allocation of advanced functions and auxiliary functions. Assuming that the total power is 800 mAh, according to the strategy, 400 mAh may be allocated to the core function, 200 mAh to the advanced function, and 200 mAh to the auxiliary function. This ensures that in the case of low power, the equipment can give priority to meeting the operating requirements of the more important core functions in specialist inspections, while appropriately guaranteeing the basic use of advanced functions and auxiliary functions.

[0242] Step S260 , analyzing and determining probe parameter combinations of different functional categories according to the corresponding relationship between the power interval ranges into which the power values ​​allocated to different functional categories fall and the probe parameter combinations.

[0243] The power ranges that the power values ​​assigned to different functional categories fall into: According to different power distribution situations, the power values ​​are divided into different ranges to determine the corresponding probe parameter combinations. For example, they can be divided into high power range, medium power range and low power range.

[0244] Probe parameter combination: A set of parameter combinations set for ultrasound probes based on different functional requirements and power consumption, including scanning frequency, gain, depth and other parameters. Different probe parameter combinations will affect the quality of ultrasound images and the power consumption of the device.

[0245] According to the corresponding relationship between the power ranges assigned to the power values ​​of different functional categories and the probe parameter combinations, the probe parameter combinations of different functional categories are analyzed and determined:

[0246] A correspondence table between the power interval range and the probe parameter combination is established in advance. For example, in the high power interval, a probe parameter combination such as high resolution, high gain, and deeper scanning depth can be used to obtain high-quality ultrasound images; in the medium power interval, the resolution and gain can be appropriately reduced, the scanning depth can be adjusted, and the image quality and power consumption can be balanced; in the low power interval, a low-power probe parameter combination is used, such as reducing the resolution, reducing the gain, reducing the scanning depth, etc., to extend the use time of the device. According to the determined power interval range, the correspondence table is searched to determine the probe parameter combinations of different functional categories.

[0247] Assume that in one check, the power values ​​allocated to different functional categories are determined in step S250. If the power value allocated to the core function is 400 mAh, the advanced function is 300 mAh, and the auxiliary function is 200 mAh, the total power is 1000 mAh.

[0248] First, determine the power range that the power value of each functional category falls into. Assume that according to a pre-set standard, the power value of the core function falls into the medium power range, and the advanced function and auxiliary function also fall into the medium power range.

[0249] Then, according to the corresponding relationship between the medium power interval and the probe parameter combination, the probe parameter combination of the core function is determined to be medium resolution, medium gain, and moderate scanning depth; the probe parameter combination of the advanced function is slightly lower resolution, lower gain, and appropriately reduced scanning depth; the probe parameter combination of the auxiliary function is low resolution, low gain, and a smaller scanning depth. In this way, the device resources can be reasonably allocated under the condition of medium power to meet the needs of different functional categories and at the same time, the use time of the device can be extended as much as possible.

[0250] The definitions of the resolution, gain, and scanning depth mentioned above are as follows: Resolution: can be expressed in pixels, for example, low resolution can be set to 640×480 pixels, medium resolution to 1024×768 pixels, and high resolution to 1920×1080 pixels. Gain: quantified in a specific numerical range, for example, low gain can be set to 0-30dB, medium gain to 30-60dB, and high gain to 60-90dB. Scanning depth: quantified in centimeters, for example, a smaller scanning depth can be set to 5-10 cm, a moderate scanning depth to 10-15 cm, and a deeper scanning depth to 15-20 cm.

[0251] Based on the same inventive concept, an embodiment of the present invention provides a computer storage medium, including a computer program product that can be loaded and executed by a processor to implement the following Figures 1 to 4 Procedures for each step involved in the process.

[0252] The embodiments of this specific implementation method are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Therefore, all equivalent changes made based on the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A control system for a handheld intelligent ultrasonic diagnostic device, characterized in that: include: Ultrasound equipment; at least one processor; At least one memory storing a computer program, and at least one processor configured to implement a method for controlling a handheld intelligent ultrasonic diagnostic device when executing the computer program, the specific steps are as follows: Obtaining the current initial probe parameter settings of the ultrasound probe, the current position coordinates of the ultrasound probe relative to the patient's body, and the patient's specific physiological characteristics, wherein the specific physiological characteristics include obesity level and gender, and the probe parameter settings include scanning angle range and frequency; Inputting the current initial probe parameter settings of the ultrasound probe, the current position coordinates of the ultrasound probe relative to the patient's body, and the patient's specific physiological characteristics into the trained clinical ultrasound probe intelligent control model, and outputting a probe parameter combination that matches the best image quality; Adjusting the ultrasonic probe parameters according to the output probe parameter combination, and simultaneously detecting and obtaining the pressure value applied by the ultrasonic probe to the skin; Analyze whether the pressure value falls within the preset reasonable pressure value range; If not, then according to the current position coordinates of the ultrasound probe relative to the patient's body, the current detection part of the ultrasound probe is confirmed from the preset three-dimensional coordinate model of the human body, and according to the matching result of the current detection part of the ultrasound probe with the preset key detection part, the interval range in which the pressure value obtained by the detection falls, and the reminder method of the voice broadcast device preset in the ultrasound equipment, the voice broadcast device reminder method that matches the pressure value is analyzed and determined; The result information that the pressure value falls within the preset reasonable pressure value range is notified through the reminder method determined by the analysis; If yes, no reminder will be given; The detection and acquisition of the pressure value applied by the ultrasound probe to the skin includes: Starting a pressure sensor array arranged on the ultrasound probe to measure and obtain a pressure value between the ultrasound probe and the skin; The pressure value measured by each pressure sensor included in the pressure sensor array is taken as a pixel point to construct and acquire a pressure distribution image; Calculate the average value of the pressure values ​​of all pixels in the pressure distribution image as the effective pressure value applied by the ultrasonic probe to the skin; The acquisition of the preset reasonable pressure value range includes: Extracting pressure features from the pressure distribution image, the pressure features include mean, standard deviation, gradient information of pressure distribution, local peak and valley values; According to the current position coordinates of the ultrasound probe relative to the patient's body, the current detection position of the ultrasound probe is confirmed by matching the preset three-dimensional human body coordinate model; According to the key pressure features associated with the preset detection parts and the reasonable pressure value range analysis scheme based on the key pressure features, the reasonable pressure value range of the corresponding detection parts is analyzed and obtained; If yes, no reminder will be given including: Extracting pressure features from the pressure distribution image, and analyzing whether pressure feature values ​​of different categories fall within a preset pressure feature value threshold range of the corresponding category; If yes, no reminder will be given; If not, the reminder information is analyzed and determined according to the correspondence between the result information of the pressure characteristic values ​​of different categories falling into the preset threshold range of the pressure characteristic values ​​of the corresponding categories and the reminder information, and the reminder information is broadcasted through the voice broadcasting device; According to the correspondence between the result information of different categories of pressure characteristic values ​​falling into the preset corresponding category pressure characteristic value threshold range and the reminder information, analyzing and determining the reminder information, and broadcasting the reminder information through the voice broadcast device includes: Analyze whether to obtain the motion data of the ultrasound probe, which includes moving speed, direction change, and acceleration; If not, execute according to the original settings; If yes, the first reminder information is determined by analyzing the correspondence between the result information that the pressure characteristic values ​​of different categories fall into the preset pressure characteristic value threshold range of the corresponding category and the reminder information, and the second reminder information is determined by analyzing the correspondence between the result information that the motion data of different categories of the ultrasound probe fall into the corresponding preset motion data threshold of the corresponding category and the second reminder information; Combining the second reminder information and the first reminder information into a new reminder information, and announcing the new reminder information through a voice announcing device; A control system for a handheld intelligent ultrasonic diagnostic device further includes steps after the reminder information is broadcasted through a voice broadcast device, which are as follows: After the preset time interval of the reminder message broadcast, the pressure characteristic value is monitored and obtained; Analyzing whether the proportion of the pressure value on one side of the ultrasonic probe to the overall pressure exceeds a preset proportion according to the mean value included in the pressure characteristic value; If not, analyzing and determining the adjustment measures of the ultrasonic probe according to the correspondence between the interval range in which the mean value included in the pressure characteristic value falls and the parameter adjustment measures of the ultrasonic probe, and executing the adjustment measures of the ultrasonic probe; If yes, then analyzing and determining the adjustment measures of the ultrasound probe according to the correspondence between the result information that one side of the ultrasound probe exceeds the preset proportion and the parameter adjustment measures of the ultrasound probe, and executing the adjustment measures of the ultrasound probe; The acquisition of reasonable pressure value range analysis scheme based on key pressure characteristics includes: Obtaining specific requirement information of the detection part, the specific requirement information includes anatomical structure parameters and physiological function parameters; The specific requirement information of the detection part and the key pressure characteristic information associated with the detection part are input as input variables to the trained pressure interval range analysis model, and the pressure interval range is output; Alternatively, obtaining a reasonable pressure value range analysis solution based on key pressure characteristics includes: Obtain the weight corresponding to the key pressure feature associated with the preset detection part, and calculate the weighted average pressure value through a weighted average algorithm according to the specific value of the key pressure feature and the weight corresponding to the key pressure feature; According to the preset standard deviation multiples associated with the detection parts, the standard deviation of the associated standard deviation multiples is added or subtracted from the weighted average pressure value to form a reasonable pressure value range based on the key pressure characteristics; The current initial probe parameter settings of the ultrasound probe, the current position coordinates of the ultrasound probe relative to the patient's body, and the specific physiological characteristics of the patient are input into the trained clinical ultrasound probe intelligent control model, and the output probe parameter combination matching the best image quality includes: Obtain the remaining power value of the handheld intelligent ultrasonic diagnostic device; Analyze whether the remaining power value of the handheld intelligent ultrasonic diagnostic device exceeds a preset power threshold; If yes, maintain the original settings; If not, then obtain the specific requirements of this examination, and analyze and determine the priority ranking of different functional categories based on the corresponding relationship between the examination requirements and the priority ranking order of different functional categories of the ultrasound diagnostic equipment. The examination requirements include emergency examination requirements, physical examination requirements, and specialist examination requirements. The functional categories of ultrasound diagnostic equipment include core functions, advanced functions, and auxiliary functions. According to the corresponding results of the priority ranking of the function categories and the priority values, the priority values ​​of different function categories are analyzed and determined, and according to the interval ranges into which the priority values ​​of different function categories and the remaining power values ​​of the handheld intelligent ultrasonic diagnostic device fall, the power values ​​allocated to different function categories are analyzed and determined; According to the corresponding relationship between the power interval ranges into which the power values ​​allocated to different functional categories fall and the probe parameter combinations, the probe parameter combinations of different functional categories are analyzed and determined; The specific steps for announcing the reminder information through the voice broadcast device are as follows: Collecting characteristic data of the doctor and the patient, motion data of the probe, and data related to the first reminder information and the second reminder information, wherein the characteristic data of the doctor includes the doctor's experience level, and the characteristic data of the patient includes the characteristics of the patient's condition; Preprocess the data; The characteristics of the doctor and the patient and the motion data of the probe are input into the constructed decision tree model. The decision tree makes judgments and splits gradually from the root node downwards according to the input feature variables until it reaches the leaf node. The category corresponding to the leaf node is the category of the new reminder information. The generated new reminder information is broadcasted through a voice broadcasting device.

2. A computer storage medium, characterized in that: It includes a memory, a processor, and a program stored in the memory and executable on the processor, wherein the program can be loaded and executed by the processor to implement a method for controlling a handheld intelligent ultrasonic diagnostic device in a control system for a handheld intelligent ultrasonic diagnostic device as described in claim 1.

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