Artificial intelligence-driven handheld ultrasonic system integrating intelligent cooperation and environment perception

Abstract

The invention discloses an artificial intelligence-driven intelligent cooperation and environment perception integrated handheld ultrasonic system, which comprises handheld ultrasonic equipment and a mobile terminal, and is characterized in that the handheld ultrasonic equipment is communicated with the mobile terminal through a remote cooperation platform, and the remote cooperation platform comprises a guide module, an intelligent voice module, an environment adaptation module and an electric quantity control module; the guidance module comprises a display end, an information collection and storage module and an information search module, the intelligent voice module comprises a voice collector and a voice processor, the environment adaptation module comprises a sensor and a receiving processor, and the electric quantity control module comprises an electric quantity monitor and an electric quantity adjuster. Through a remote cooperation system, automatic language detection and multi-language switching are achieved, an energy consumption strategy of the handheld ultrasonic equipment is optimized through an electric quantity control module, setting of the handheld ultrasonic equipment is automatically optimized by collecting and analyzing environment data in real time, and the display brightness, contrast ratio and noise filtering parameters of the equipment are automatically adjusted to adapt to the current environment.

Description

Technical Field

[0001] The present invention relates to the technical field of medical ultrasonic imaging diagnosis, and in particular to an artificial intelligence-driven handheld ultrasonic system integrating intelligent collaboration and environmental perception. Background Art

[0002] Ultrasound examination is widely used in the field of obstetrics. Through regular ultrasound examination, doctors can monitor the growth and development of the fetus, promptly diagnose special conditions such as fetal growth restriction and polyhydramnios, and effectively prevent adverse health outcomes for pregnant women, fetuses, and newborns. Handheld ultrasound equipment is a type of portable medical imaging equipment that has gradually matured in recent years. Compared with traditional large ultrasound equipment, handheld ultrasound equipment has the characteristics of small size and light weight, which significantly increases the accessibility and convenience of ultrasound examinations.

[0003] Existing technologies such as the Chinese patent with publication number CN106326661A disclose a handheld ultrasound diagnostic system that can realize remote diagnosis and remote control. The system includes: a handheld B-ultrasound, a doctor-side APP, a telemedicine server and an expert-side APP. Through this system, medical experts can monitor and guide the operation process of grassroots doctors. Experts judge the condition based on the patient data uploaded by grassroots doctors and provide accurate analysis results and diagnostic information. In addition, grassroots doctors can obtain standardized ultrasound diagnosis processes and parameter adjustment guidance for ultrasound images through remote collaboration, which improves the efficiency of medical services. However, due to the interoperability of the Internet platform and with the development of technology, related technologies have gradually become outdated.

[0004] As more and more ultrasound equipment is exported overseas, multilingual ultrasound equipment has become inevitable. In the prior art, the multilingual interface of ultrasound diagnostic equipment usually requires users to manually switch languages, and lacks the ability to automatically adapt to user language preferences. In the process of remote collaboration, different languages ​​used by both users will cause trouble in the communication process, so it is necessary to change the language in time to facilitate communication. Summary of the invention

[0005] To solve the above problems, the present invention proposes an artificial intelligence-driven handheld ultrasound system that integrates intelligent collaboration and environmental perception, including a handheld ultrasound device and a mobile terminal. The handheld ultrasound device is connected to the mobile terminal through a remote collaboration platform. The remote collaboration platform includes a guidance module, an intelligent voice module, an environmental adaptation module and a power control module. The guidance module includes a display terminal, an information collection and storage module and an information search module. The intelligent voice module includes a voice collector and a voice processor. The environmental adaptation module includes a sensor and a receiving processor. The power control module includes a power monitor and a power regulator. The information collection and storage module is used to collect and store knowledge content. The voice processor is used to recognize and translate the received voice.

[0006] Furthermore, the information search module and the display end are connected to the handheld ultrasonic device, and the information search module is connected to the mobile end through the information collection and storage module.

[0007] Furthermore, the display terminal is connected to the mobile terminal, and both include a real-time image sharing tool and an annotation tool.

[0008] Furthermore, the voice collector is arranged on the handheld ultrasonic device to receive the language used by the user.

[0009] Furthermore, the voice processor is connected to the display terminal, and the voice processor controls and changes the language of the display terminal.

[0010] Furthermore, the sensor includes an ambient light sensor, an electromagnetic interference detector or a noise sensor.

[0011] Furthermore, the sensor is arranged on the handheld ultrasound device, the sensor is connected to a receiving processor, the receiving processor is connected to the handheld ultrasound device and a display terminal, and the receiving processor includes a grayscale mapper or a noise reduction processor.

[0012] Furthermore, the power monitor is arranged on the handheld ultrasonic device to monitor the power of the handheld ultrasonic device, the power regulator is used to control the power supply of the handheld ultrasonic device, and the power monitor is connected to the power regulator.

[0013] Furthermore, the handheld ultrasound device is connected to the remote collaboration platform via wired or wireless connection.

[0014] Furthermore, the remote collaboration platform is connected to the mobile terminal via wired or wireless connection.

[0015] The beneficial effects of the present invention are as follows:

[0016] The artificial intelligence-driven handheld ultrasound system with integrated intelligent collaboration and environmental perception of the present invention realizes automatic language detection and multi-language switching through a remote collaboration system, thereby optimizing the doctor's operating experience; the power control module optimizes the energy consumption strategy of the handheld ultrasound device, displays the power status in real time, and provides energy-saving suggestions; by real-time collection and analysis of environmental data, the settings of the handheld ultrasound device are automatically optimized, and the display brightness, contrast, and noise filtering parameters of the device are automatically adjusted to adapt to the current environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a structural schematic diagram of the present invention.

[0018] Figure 2 It is a connection relationship diagram of the remote collaboration platform.

[0019] Figure numerals: 1. Handheld ultrasonic device, 2. Remote collaboration platform, 3. Mobile terminal, 4. Guidance module, 401. Display terminal, 402. Information collection and storage module, 403. Information search module, 5. Intelligent voice module, 501. Voice collector, 502. Voice processor, 6. Environmental adaptation module, 601. Sensor, 602. Receiving processor, 7. Power control module, 701. Power monitor, 702. Power regulator. DETAILED DESCRIPTION

[0020] Embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and intended to be used to explain the present invention, but should not be understood as limiting the present invention.

[0021] The present invention proposes an artificial intelligence-driven handheld ultrasound system that integrates intelligent collaboration and environmental perception, including a handheld ultrasound device 1 and a mobile terminal 3. The handheld ultrasound device 1 is connected to the mobile terminal 3 through a remote collaboration platform 2. The remote collaboration platform 2 includes a guidance module 4, an intelligent voice module 5, an environmental adaptation module 6 and a power control module 7. The guidance module 4 includes a display terminal 401, an information collection and storage module 402 and an information search module 403. The intelligent voice module 5 includes a voice collector 501 and a voice processor 502. The environmental adaptation module 6 includes a sensor 601 and a receiving processor 602. The power control module 7 includes a power monitor 701 and a power regulator 702. The information collection and storage module 402 is used to collect and store knowledge content. The voice processor 502 is used to recognize and translate received voices.

[0022] The information search module 403 and the display terminal 401 are connected to the handheld ultrasound device 1, and the information search module 403 is connected to the mobile terminal 3 through the information collection and storage module 402. The display terminal 401 is connected to the mobile terminal 3, and both include real-time image sharing tools and annotation tools.

[0023] The operator accesses the patient data and medical condition through the information search module 403, and uses the AI ​​algorithm to provide diagnostic suggestions and operational guidance through the information in the information collection and storage module 402, thereby assisting doctors in making more accurate medical judgments.

[0024] The display terminal 401 and the mobile terminal 3 provide annotation and marking tools, allowing doctors to mark and annotate on the image to more clearly convey diagnostic opinions and discuss cases. Doctors can communicate with other medical professionals in real time through the remote collaboration platform 2 to share and discuss ultrasound images.

[0025] The voice collector 501 is provided on the handheld ultrasonic device 1 and is used to receive the language used by the user. The voice processor 502 is connected to the display terminal 401, and the voice processor 502 controls and changes the language of the display terminal 401. Automatic language detection is performed to identify the user language and dynamically switch, so as to achieve seamless switching of the multi-language interface, so that the user can select and use the device according to his or her language preference.

[0026] The sensor 601 includes an ambient light sensor, an electromagnetic interference detector or a noise sensor. The sensor 601 is arranged on the handheld ultrasound device 1, and the sensor 601 is connected to a receiving processor 602, and the receiving processor is connected to the handheld ultrasound device 1 and the display terminal 401, and the receiving processor includes a grayscale mapper or a noise reduction processor, which is used to detect ambient noise and filter noise.

[0027] After the handheld ultrasound device 1 is turned on, the ambient light sensor, noise sensor and electromagnetic interference detector collect ambient light, noise and electromagnetic interference data in real time. Machine learning is used to analyze environmental data, identify environmental changes and trigger adaptive adjustments. The image data is processed through a convolutional neural network to automatically adjust the display brightness, contrast and noise filtering parameters of the device to adapt to the current environment. The machine learning model is used to learn the impact of light, noise and electromagnetic waves on image quality to optimize its ability to generate operation guidance and environmental adjustment suggestions.

[0028] The power monitor 701 is arranged on the handheld ultrasonic device 1 for monitoring the power of the handheld ultrasonic device 1 . The power regulator 702 is used to control the power supply of the handheld ultrasonic device 1 . The power monitor 701 is connected to the power regulator 702 .

[0029] After the handheld ultrasound device 1 is turned on, the power monitor 701 integrated in the device monitors the energy consumption status of the device in real time. The power consumption sensor 601 collects data such as power, battery status, and usage mode in real time. The machine learning model analyzes the battery power data in real time to identify usage modes and environmental conditions. According to information conditions such as the current power and usage scenario, the device intelligently optimizes or the doctor manually adjusts the power consumption mode.

[0030] Through the data fusion and deep learning model of the power monitor 701, the energy distribution is optimized according to the actual usage scenario and the energy consumption strategy is automatically switched. Using the reinforcement learning model, the power consumption mode is continuously adjusted according to the real-time monitoring of power and inspection needs, including three modes:

[0031] 1. High-performance mode: In high-load usage scenarios, prioritize device performance and appropriately increase energy consumption;

[0032] 2. Balanced mode: In normal use scenarios, balance device performance and energy consumption to achieve longer battery life;

[0033] 3. Energy-saving mode: In low-load usage scenarios, priority is given to reducing energy consumption and maximizing equipment usage time.

[0034] Power status prompt: Use edge computing to process data on local devices and prompt users in real time through applications, displaying real-time power status and energy-saving suggestions, and providing mode switching functions.

[0035] 1. Real-time display: The power status and remaining battery time are displayed in real time on the device interface and mobile 3 applications.

[0036] 2. Low battery reminder: When the battery level is lower than the set threshold, the system will automatically remind the doctor and provide energy-saving suggestions.

[0037] 3. Energy-saving suggestions: Based on real-time energy consumption data, provide specific energy-saving suggestions, such as reducing screen brightness, turning off unnecessary functions, etc.

[0038] The handheld ultrasound device 1 is connected to the remote collaboration platform 2 via wired or wireless connection. The remote collaboration platform 2 is connected to the mobile terminal 3 via wired or wireless connection.

[0039] Although the above embodiments have been shown and described, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. Changes, modifications, substitutions and variations of the above embodiments by those of ordinary skill in the art are all within the scope of protection of the present invention.

Claims

1. An artificial intelligence-driven handheld ultrasound system integrating intelligent collaboration and environmental perception, characterized in that: include: A handheld ultrasound device and a mobile terminal, the handheld ultrasound device is connected to the mobile terminal through a remote collaboration platform, the remote collaboration platform includes a guidance module, an intelligent voice module, an environmental adaptation module and a power control module, the guidance module includes a display terminal, an information collection and storage module and an information search module, the intelligent voice module includes a voice collector and a voice processor, the environmental adaptation module includes a sensor and a receiving processor, the power control module includes a power monitor and a power regulator, the information collection and storage module is used to collect and store knowledge content, and the voice processor is used to recognize and translate the received voice.

2. The artificial intelligence-driven handheld ultrasound system integrating intelligent collaboration and environmental perception according to claim 1, characterized in that: The information search module and the display end are connected to the handheld ultrasonic device, and the information search module is connected to the mobile end through the information collection and storage module.

3. The artificial intelligence-driven handheld ultrasound system integrating intelligent collaboration and environmental perception according to claim 1, characterized in that: The display terminal is connected to the mobile terminal, and both include a real-time image sharing tool and an annotation tool.

4. The artificial intelligence-driven integrated intelligent collaboration and environmental perception handheld ultrasound system according to claim 1, characterized in that: The voice collector is arranged on the handheld ultrasonic device and is used for receiving the language used by the user.

5. The artificial intelligence-driven integrated intelligent collaboration and environmental perception handheld ultrasound system according to claim 1, characterized in that: The voice processor is connected to the display terminal, and the voice processor controls and changes the language of the display terminal.

6. The artificial intelligence-driven integrated intelligent collaboration and environmental perception handheld ultrasound system according to claim 1, characterized in that: The sensor includes an ambient light sensor, an electromagnetic interference detector or a noise sensor.

7. The artificial intelligence-driven integrated intelligent collaboration and environmental perception handheld ultrasound system according to claim 1, characterized in that: The sensor is arranged on the handheld ultrasound device, the sensor is connected to the receiving processor, the receiving processor is connected to the handheld ultrasound device and the display end, and the receiving processor includes a grayscale mapper or a noise reduction processor.

8. The artificial intelligence-driven integrated intelligent collaboration and environmental perception handheld ultrasound system according to claim 1, characterized in that: The power monitor is arranged on the handheld ultrasonic device and is used to monitor the power of the handheld ultrasonic device. The power regulator is used to control the power supply of the handheld ultrasonic device. The power monitor is connected to the power regulator.

9. The artificial intelligence-driven integrated intelligent collaboration and environmental perception handheld ultrasound system according to claim 1, characterized in that: The handheld ultrasound device is connected to the remote collaboration platform via wired or wireless connection.

10. The artificial intelligence-driven integrated intelligent collaboration and environmental perception handheld ultrasound system according to claim 1, characterized in that: The remote collaboration platform is connected to the mobile terminal via wired or wireless connection.

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