Surgical aspirator capable of intelligently adjusting suction force

Abstract

The invention discloses a surgical aspirator capable of intelligently adjusting suction force, and belongs to the field of medical instruments. A surgical aspirator capable of intelligently adjusting suction force comprises an aspirator main body, one end of the aspirator main body is provided with a connector used for being connected with a negative pressure source, the other end of the aspirator main body is provided with an aspirator head used for extracting body fluid and secretions, the aspirator head is made of non-metal soft materials, two suction ports are formed in the aspirator head, and the aspirator head is connected with the connector. The suction ports comprise a side suction port and a positive suction port; the device further comprises an intelligent sensing system and an intelligent suction adjusting system. The problem that the suction force of an existing aspirator is difficult to adjust according to different tissue types is solved, the tissue types are accurately recognized by monitoring the physical characteristics of the tissues in an operation area in real time, the working states of the side suction opening and the positive suction opening of the aspirator head are automatically switched according to the recognized tissue types, and the operation efficiency is improved. The suction force can be automatically adjusted, so that the risk of tissue damage caused by improper suction force is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical devices, in particular to a surgical suction device with intelligent suction force adjustment. BACKGROUND

[0002] In the surgical process, the suction device is one of the indispensable devices. The traditional surgical suction device usually adopts a fixed suction force or a manually adjusted suction force, which is difficult to accurately adjust the suction force according to different tissue types, so as to meet the switching of different suction force demand scenes. Therefore, it does not meet the existing demand, and for this, we propose a surgical suction device with intelligent suction force adjustment. SUMMARY

[0003] The purpose of the present application is to provide a surgical suction device with intelligent suction force adjustment, which can accurately identify the tissue type by monitoring the physical properties of the tissue in the surgical area in real time during the surgical process, and automatically switch the working state of the side suction port and the front suction port of the suction device head according to the identified tissue type, so as to realize the automatic adjustment of the suction force, thereby reducing the risk of tissue damage caused by improper suction force and solving the problems raised in the above background.

[0004] To achieve the above purpose, the present application provides the following technical scheme: a surgical suction device with intelligent suction force adjustment, comprising a suction device main body, one end of the suction device main body is provided with a connecting head for connecting a negative pressure source, the other end of the suction device main body is provided with a suction device head for extracting body fluids and secretions, the suction device head is made of a soft non-metallic material, two suction ports are provided on the suction device head, which are a side suction port and a front suction port, the side suction port is located on the side of the suction device head and is provided with a plurality of side suction ports for fine tissues requiring smaller suction force, the front suction port is located at the front end of the front surface of the suction device head for situations requiring larger suction force, and a switching valve is provided on the suction device head for switching the working state of the side suction port and the front suction port in real time during the operation. It also includes an intelligent sensing system and an intelligent suction force adjustment system, and the intelligent sensing system is integrated in the suction device head area. The intelligent sensing system is configured to monitor the physical properties of the contacted tissue in the surgical area in real time through various integrated sensors, including mechanical sensors, optical sensors and impedance sensors, and transmit the collected multi-dimensional tissue data to the intelligent suction force adjustment system, wherein the optical sensor analyzes the surface microstructure of the tissue through reflectivity. The intelligent suction force adjustment system is configured to analyze the received multi-dimensional tissue data, analyze the tissue type of the contacted tissue, control the switching valve to switch the working state of the side suction port and the front suction port based on the suction force adjustment strategy and according to the tissue type, and realize the automatic adjustment of the suction force of the suction device head. The working states of the side suction port and the positive suction port of the switching valve are automatically controlled based on a suction adjustment strategy, and the optimal ideal suction parameter is calculated according to the preset suction parameter and the structural design parameter of the target suction port and a suction limiting factor.

[0005] Further, the intelligent sensing system comprises: The data acquisition module is configured to integrate various types of sensors to monitor the physical properties of the contacted tissue in the surgical area in real time, so as to obtain multi-dimensional tissue data of the surgical area, wherein the sensors include mechanical sensors, optical sensors and impedance sensors. The mechanical sensor is used to detect the compression deformation properties of the tissue in real time, including the elastic modulus and the viscous resistance. The optical sensor is used to analyze the microstructure of the tissue surface through reflectivity. The impedance sensor is used to measure the electrical conductivity of the tissue and distinguish between nerve, muscle or fat tissue. The data processing module is configured to preprocess the collected raw data, including filtering and denoising and data correction, remove noise by using a filtering algorithm, and correct the collected multi-dimensional tissue data according to the characteristics of the sensors. The data transmission module is configured to compress the collected multi-dimensional tissue data to reduce the data transmission amount, and to check the integrity of the data in real time during data transmission, and to automatically trigger a retransmission mechanism when a data transmission error is detected.

[0006] Further, the data transmission module comprises: The data compression module is configured to remove redundant information in the multi-dimensional tissue data before compression, and then compress the collected multi-dimensional tissue data according to the data type. The data verification module is configured to use a multi-level verification mechanism to preliminarily verify the multi-dimensional tissue data, and if an error is found, to further verify in detail, and when a data transmission error is detected, to automatically trigger a retransmission mechanism and set a priority queue for the retransmitted data to ensure that critical data is retransmitted first. When the number of consecutive data transmission errors exceeds three, the system switches to a redundant channel or reduces the transmission rate. The transmission quality monitoring module is configured to monitor the quality of data transmission in real time, including transmission speed, packet loss rate and delay, dynamically adjust the transmission parameters according to the real-time monitored transmission quality, and when the transmission quality drops below a preset threshold, automatically send a warning signal and provide optimization suggestions, including adjusting the transmission path or switching the communication protocol.

[0007] Further, the data acquisition module comprises: A collection quality monitoring module is configured to monitor the quality of data collection in real time, including the accuracy, integrity and consistency of data, and automatically adjust sensor parameters or re-collect data when data quality problems are detected. A data collection fault-tolerant module is configured to introduce redundant collection during data collection, and recover the original data through redundant data when part of the data is lost or damaged.

[0008] Further, the intelligent suction adjustment system comprises: A feature extraction module is configured to extract key features from the received multi-dimensional tissue data and automatically label the extracted features. A tissue analysis module is configured to construct a model using a machine learning algorithm, analyze the extracted features through the model, identify the type of contact tissue, and classify the tissue type. A suction adjustment module is configured to develop a suction adjustment strategy in advance according to the tissue type and surgical requirements, determine the corresponding suction adjustment strategy based on the tissue type identified by the tissue analysis module, and automatically control the switching valve to switch the working state of the side suction port and the positive suction port based on the suction adjustment strategy.

[0009] Further, the feature extraction module specifically comprises: Feature extraction: extract key features from multi-dimensional tissue data, including: Extract the hardness, elasticity and pressure distribution characteristics of the tissue from the mechanical sensor data; Extract the color, texture and blood vessel distribution characteristics of the tissue from the optical sensor data; Extract the electrical conductivity and electrical impedance characteristics of the tissue from the impedance sensor data; Feature labeling: analyze the extracted features using a deep learning algorithm, extract color and texture features from optical sensor data through a convolutional neural network, extract time series features from mechanical sensor and impedance sensor data through a recurrent neural network, and generate labeling information for the features according to the analysis results, including feature category, location and intensity. To ensure the accuracy of labeling, the labeling results are verified through comparison of manual labeling and automatic labeling results, or through cross-validation. Feature enhancement: normalize the extracted features, convert feature data of different modalities to the same numerical range, eliminate dimensional differences and numerical range differences between different features, and ensure the comparability of the features. Then, the features of different modalities are fused to generate a comprehensive feature vector. Feature management: establish a feature database to store the extracted feature data and its labeling information. The stored data is used for model training, and provides data indexing and retrieval, as well as data backup and recovery functions.

[0010] Further, the tissue analysis module comprises: a model construction module configured to construct a model using a machine learning algorithm and train the model using the labeled feature data in the feature database; a recognition and classification module configured to analyze the extracted features according to the trained model, identify the type of contact tissue, and classify the contact tissue, verify the classification result to ensure the accuracy and reliability of the classification, and trigger further verification mechanism if the classification result is uncertain; a feedback learning module configured to collect feedback information of the classification result from doctors or operators for further optimization of the model, perform online learning and update of the model according to real-time feedback information, and analyze the cases of classification errors to find out the shortcomings of the model for reference for subsequent model improvement.

[0011] Further, the suction adjustment module comprises: a strategy formulation module configured to formulate suction adjustment strategies for different tissue types and surgical requirements in advance and store the strategies in a strategy library, wherein the suction adjustment strategies include the suction size corresponding to each tissue type and the switching rule of the suction port, and the strategy library is updated regularly according to new surgical data or feedback information to adapt to changes in different surgical scenarios and tissue types; a suction control module configured to automatically control the working state of the switching valve switching between the side suction port and the positive suction port according to the tissue type identified by the tissue analysis module and the suction adjustment strategy provided by the strategy formulation module, so as to automatically adjust the suction size of the suction device main body; a safety monitoring module configured to monitor the suction size of the suction device main body in real time, and monitor the stress of the tissue during the suction adjustment process, and if the adjusted suction size exceeds the range of the corresponding suction adjustment strategy or the stress of the tissue is abnormal, an audible and visual alarm signal is sent and the operator is prompted to take appropriate measures.

[0012] Further, the optical sensor analyzes the microstructure of the tissue surface by reflectance, comprising: collecting an optical illumination image of the tissue surface, and determining the optical absorption coefficient and the optical scattering coefficient of the contact tissue in the surgical area according to the optical illumination image; setting the illumination parameters for the contact tissue in the surgical area according to the optical absorption coefficient and the optical scattering coefficient; collecting a tissue image based on the illumination parameters by a spatial frequency domain imaging system and demodulating the tissue image, and determining the diffuse reflectance according to the demodulated tissue image; determining the physiological parameters of the contact tissue in the surgical area based on the diffuse reflectance, and determining the tissue activity state of the contact tissue in the surgical area based on the physiological parameters; According to the tissue activity state, the structural stability of the tissue contacted by the surgical area is determined, and the structural elasticity of the tissue contacted by the surgical area is determined based on the structural stability; According to the structural elasticity, a detection index is determined, a state change condition of the detection index is obtained, an action attribute is determined according to the state change condition, and the action attribute includes infiltration, heating, and ice compressing; The mechanical properties of the tissue contacted by the surgical area are obtained, and the initial soft and hard attribute of the tissue contacted by the surgical area is determined according to the mechanical properties; According to the action attribute and the initial soft and hard attribute of the tissue contacted by the surgical area, a critical value parameter of the action medium is configured; According to the configuration result, a structural strain environment of the tissue contacted by the surgical area is generated, and a structural change characteristic description of the tissue contacted by the surgical area in the structural strain environment is obtained; According to the structural change characteristic description, a structural dynamic change rule of the tissue contacted by the surgical area is determined, and a physiological parameter dynamic change sequence of the tissue contacted by the surgical area is determined according to the structural dynamic change rule and the diffuse reflectance; According to the physiological parameter dynamic change sequence, the surface microstructure of the tissue contacted by the surgical area is determined.

[0013] Further, based on the suction adjustment strategy, the working state of the side suction port and the positive suction port of the switching valve is automatically controlled, including: According to the suction adjustment strategy, the on-off state of the side suction port and the positive suction port is determined, and the target suction port in the open state is selected based on the on-off state; The preset suction force parameter of the target suction port is obtained, and the maximum suction force parameter of the target suction port is determined according to the preset suction force parameter; Based on the suction adjustment strategy, the current suction force parameter for the identified tissue type is determined, and the limit suction force parameter for the identified tissue type to maintain a stable state is determined; According to the current suction force parameter, the limit suction force parameter, and the maximum suction force parameter of the target suction port, the ideal suction force parameter of the target suction port is calculated:

[0014] Wherein, The ideal suction force parameter of the target suction port is represented as The suction force reduction factor corresponding to the design structure of the target suction port is represented as, and the value is 0.3-0.5, The maximum suction force parameter of the target suction port is represented as The current suction force parameter for the identified tissue type is represented as The limit suction force parameter for the identified tissue type to maintain a stable state is represented as The required porosity for the identified tissue type to be completely absorbed is represented as Expressed as the current design porosity of the target suction port, Expressed as the suction saturation of the target suction port, It is expressed as the intake pressure index of the target suction port, with a value of 0.5-0.7. It is expressed as the time-varying load increment of the target suction port under the maximum suction parameter, It is expressed as the time-varying load increment of the target suction port under the ultimate suction parameter that maintains a steady state for the identified tissue type; Determine the working mode of the target suction port and the control parameters under the working mode according to the ideal suction parameters of the target suction port; The working state parameters of the target suction port are controlled by control parameters.

[0015] Compared with the prior art, the present invention has the following beneficial effects: During the operation, the intelligent sensing system of the present invention can monitor the physical properties of the tissue in the surgical area in real time, including mechanical properties, optical properties and electrical properties, so as to accurately identify the tissue type. The intelligent suction adjustment system automatically switches the working status of the side suction port and the front suction port of the suction head according to the identified tissue type, thereby realizing automatic adjustment of the suction force. This design not only improves the safety and accuracy of the operation, reduces the risk of tissue damage caused by improper suction, but also reduces the operating difficulty of the surgeon and improves the efficiency of the operation. At the same time, the suction head of the suction device is made of non-metallic soft material, which can better fit the surgical area, so that tissue separation can reduce bleeding. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Fig. 1 This is a schematic structural diagram of a surgical suction device with intelligent suction adjustment according to the present invention; Fig. 2 This is a schematic diagram of the appearance of the surgical suction device with intelligent suction adjustment of the present invention.

[0017] In the figure: 1. Suction device body; 2. Connector; 3. Suction device head; 4. Side suction port; 5. Front suction port. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0019] In order to solve the technical problem that the existing surgical aspirator usually adopts fixed suction or manually adjusts the suction, it is difficult to accurately adjust the suction according to different tissue types, and different suction demand scenes cannot be switched, please refer to Figs. 1-2 The embodiment provides the following technical scheme: The surgical aspirator with intelligent suction adjustment comprises an aspirator main body 1, a connecting head 2 for connecting a negative pressure source is arranged at one end of the aspirator main body 1, and an aspirator head 3 for extracting body fluid and secretion is arranged at the other end of the aspirator main body 1; the aspirator head 3 is made of a soft non-metal material; two suction ports are arranged on the aspirator head 3, which are a side suction port 4 and a front suction port 5; the side suction port 4 is arranged on the side of the aspirator head 3 and is provided with a plurality of side suction ports 4, which are used for fine tissues requiring small suction; the front suction port 5 is arranged at the front end of the front surface of the aspirator head 3 and is used for situations requiring large suction; and a switching valve is arranged on the aspirator head 3 and is used for switching the working states of the side suction port 4 and the front suction port 5 in real time during the operation.

[0020] The technical effect of the above technical scheme is that the surgical aspirator with intelligent suction adjustment realizes flexible switching of the working states of the suction ports according to different tissue types and operation requirements during the operation through a unique structural design; the aspirator head 3 is made of a soft non-metal material and can better fit the operation area, so as to reduce bleeding when separating tissues and reduce damage to the tissues; the arrangement of the side suction port 4 and the front suction port 5 enables the aspirator main body 1 to select a working mode with small suction or a working mode with large suction according to requirements; the side suction port 4 is suitable for fine tissues and can avoid tissue damage caused by excessive suction; the front suction port 5 is suitable for situations requiring rapid removal of body fluid or secretion; through the real-time switching function of the switching valve, the doctor can flexibly adjust the working state of the aspirator according to the actual situation during the operation, the flexibility and accuracy of the operation are improved, the operation risk is reduced, and the overall efficiency and safety of the operation are improved.

[0021] The surgical aspirator with intelligent suction adjustment further comprises an intelligent sensing system and an intelligent suction adjustment system; and the intelligent sensing system is integrated in the aspirator head 3 region. The intelligent sensing system is configured to monitor the physical properties of the contacted tissues in the operation region in real time through integrated various sensors including a mechanical sensor, an optical sensor and an impedance sensor, and transmit the collected multi-dimensional tissue data to the intelligent suction adjustment system; the optical sensor analyzes the microstructure of the tissue surface through reflectivity. The intelligent suction adjustment system is configured to analyze the received multi-dimensional tissue data, analyze the tissue type of the contacted tissues, control the switching valve to switch the working states of the side suction port 4 and the front suction port 5 based on a suction adjustment strategy and according to the tissue type, and realize automatic adjustment of the suction size of the aspirator head 3. The working states of the side suction port 4 and the positive suction port 5 are automatically controlled by switching the valve based on a suction adjustment strategy, and the optimal ideal suction parameter is calculated according to the preset suction parameter and the structural design parameter of the target suction port and the suction limiting factor.

[0022] The technical effects of the above technical solution are as follows: The intelligent sensing system can monitor the physical properties of the contacted tissue in the operation area in real time, including mechanical, optical and electrical multi-dimensional data. Through these data, the intelligent suction adjustment system can accurately analyze the type of the contacted tissue (such as nerve, muscle, fat, etc.), and automatically switch the working states of the side suction port and the positive suction port according to the type of the tissue, so as to realize the automatic adjustment of the suction size. Through intelligent adjustment, the error of manual operation is reduced, and the safety and accuracy of the operation are improved. During the operation, different tissues have different tolerances to suction. Through the above design, the aspirator can automatically adjust the suction according to the type of the tissue, so as to avoid tissue damage or low operation efficiency caused by excessive or insufficient suction. For example, for delicate tissues (such as nerves, lymph nodes, heart tissues, etc.), the aspirator main body 1 will automatically switch to the side suction port 4 and use smaller suction, so as to protect the tissue from damage.

[0023] The intelligent sensing system comprises: The data acquisition module is configured to integrate various types of sensors to monitor the physical properties of the contacted tissue in the operation area in real time, so as to obtain multi-dimensional tissue data of the operation area. The sensors include mechanical sensors, optical sensors and impedance sensors. The mechanical sensor: real-time detects the compression deformation characteristics of the tissue, including the elastic modulus and the viscous resistance; The optical sensor: analyzes the microstructure of the tissue surface through reflectivity; The impedance sensor: measures the electrical conductivity of the tissue to distinguish between nerve, muscle or fat tissue; The data processing module is configured to preprocess the collected raw data, including filtering and denoising and data correction. The filtering algorithm (such as Kalman filtering) is used to remove noise, and the multi-dimensional tissue data collected is corrected according to the characteristics of the sensor. The data transmission module is configured to compress the collected multi-dimensional tissue data to reduce the data transmission amount, and to check the integrity of the data in real time during data transmission. When a data transmission error is detected, the retransmission mechanism is automatically triggered.

[0024] The technical effects of the above technical solutions are: the data acquisition module integrates a mechanical sensor, an optical sensor, and an impedance sensor, can monitor multiple physical properties of the tissue in the surgical area in real time, can comprehensively and accurately reflect the state of the tissue in the surgical area through multi-dimensional monitoring, and provide a reliable data basis for subsequent intelligent analysis and suction force adjustment; the data processing module can improve the quality of the data through a series of preprocessing operations such as filtering denoising and data correction; the data transmission module compresses the collected multi-dimensional tissue data, effectively reduces the data transmission amount, improves the data transmission efficiency, reduces the system delay, and verifies the integrity of the data in real time during data transmission; once a data transmission error is detected, the automatic retransmission mechanism is triggered to ensure the integrity and reliability of data transmission; the data transmission mechanism can ensure that the intelligent suction force adjustment system obtains the tissue data of the surgical area in time and accurately, so as to realize rapid and accurate suction force adjustment.

[0025] The data transmission module comprises: The data compression module is configured to remove redundant information in the multi-dimensional tissue data before compression, and then compress the collected multi-dimensional tissue data according to the data type; The data verification module is configured to use a multi-level verification mechanism to preliminarily verify the multi-dimensional tissue data, and if an error is found, further detailed verification is performed; when a data transmission error is detected, the automatic retransmission mechanism is triggered, and a priority queue is set for the retransmitted data to ensure that critical data is retransmitted in priority; Wherein, if the number of times of continuously detecting data transmission errors exceeds three times, the redundant channel is switched to or the transmission rate is reduced; The transmission quality monitoring module is configured to monitor the quality of data transmission in real time, including transmission speed, packet loss rate, and delay; according to the real-time monitored transmission quality, the transmission parameters (such as transmission rate, retransmission frequency, etc.) are dynamically adjusted; and based on the real-time monitored transmission quality, when the transmission quality drops below the preset threshold, an early warning signal is automatically sent, and optimization suggestions are provided, including adjusting the transmission path or switching the communication protocol.

[0026] The technical effects of the above technical solutions are: the data compression module removes redundant information in the multi-dimensional organization data before compression, and then performs targeted compression according to the data type, which can ensure the simplicity and efficiency of the transmitted data. The data verification module adopts a multi-level verification mechanism to perform preliminary verification and detailed verification on the multi-dimensional organization data, which can quickly find errors in data transmission and ensure data integrity through an automatic retransmission mechanism. At the same time, a priority queue is set for retransmitted data to ensure that critical data is retransmitted first, further improving the reliability and priority management capability of data transmission. When the number of consecutive detected data transmission errors exceeds three times, the system automatically switches to a redundant channel or reduces the transmission rate to ensure the continuity of data transmission. The transmission quality monitoring module monitors the quality of data transmission in real time, which can effectively cope with complex and variable network environments and ensure that data transmission is always in the best state.

[0027] The data acquisition module includes: The quality monitoring module is configured to monitor the quality of data acquisition in real time, including the accuracy, integrity and consistency of the data. When a data quality problem is detected, the sensor parameters are automatically adjusted or the data is reacquired. The data acquisition fault-tolerant module is configured to introduce redundant acquisition during data acquisition. When some data is lost or damaged, the original data can be recovered through redundant data.

[0028] The technical effects of the above technical solutions are: the quality monitoring module can monitor the quality of data acquisition in real time, and can quickly find problems in the data acquisition process. Once a data quality problem is detected, the sensor parameters are automatically adjusted to ensure that the collected data meets the quality requirements, effectively improving the stability and reliability of data acquisition. The data acquisition fault-tolerant module introduces a redundant acquisition mechanism to simultaneously acquire multiple data copies during data acquisition. When some data is lost or damaged, the original data can be recovered using redundant data, reducing the need for resampling due to data loss and improving overall efficiency.

[0029] The intelligent suction adjustment system includes: The feature extraction module is configured to extract key features from the received multi-dimensional organization data and automatically label the extracted features. The organization analysis module is configured to construct a model using a machine learning algorithm, analyze the extracted features through the model, identify the type of contact organization, and classify the organization type. The suction adjustment module is configured to develop a suction adjustment strategy in advance according to the organization type and surgical requirements, determine the corresponding suction adjustment strategy based on the organization type identified by the organization analysis module, and automatically control the switching valve to switch the working state of the side suction port 4 and the positive suction port 5 based on the suction adjustment strategy.

[0030] The technical effects of the above technical solutions are: the feature extraction module can extract key features from multi-dimensional organizational data and automatically label these features, providing an accurate basis for subsequent organizational analysis. The organizational analysis module uses advanced machine learning algorithms to build models and analyze the extracted features to accurately identify the type of contact tissue (such as nerves, muscles, and fat) and classify it. The precise identification capability ensures the effectiveness and effectiveness of the suction adjustment, and the suction adjustment module automatically selects the appropriate suction adjustment strategy based on the tissue type identified by the tissue analysis module to automatically adjust the suction size, ensuring the safety and efficiency of the surgical operation.

[0031] The feature extraction module, specifically: Feature extraction: extract key features from multi-dimensional organizational data, including: Extract the hardness, elasticity, and pressure distribution characteristics of the tissue from the mechanical sensor data; Extract the color, texture, and blood vessel distribution characteristics of the tissue from the optical sensor data; Extract the electrical conductivity and electrical impedance characteristics of the tissue from the impedance sensor data; Feature labeling: use deep learning algorithms to analyze the extracted features, extract color and texture features from optical sensor data through convolutional neural networks, extract time series features from mechanical sensor and impedance sensor data through recurrent neural networks, and generate labeling information for the features based on the analysis results, including feature category, location, and intensity. To ensure the accuracy of the labeling, the labeling results are verified through manual labeling and automatic labeling results, or through cross-validation. Feature enhancement: normalize the extracted features, convert different modal feature data to the same numerical range, eliminate the dimensional and numerical range differences between different features, and ensure the comparability of the features. Then, different modal features are fused to generate a comprehensive feature vector. Feature management: establish a feature database to store the extracted feature data and its labeling information. The stored data is used for model training and provides data indexing and retrieval, as well as data backup and recovery functions.

[0032] The technical effects of the above technical solutions are: extracting multiple key features from the data of mechanical sensors, optical sensors and impedance sensors can comprehensively reflect the physical properties of the tissue, providing a rich data foundation for subsequent tissue analysis, using a deep learning algorithm to analyze and label the extracted features, and verifying the labeling results to improve the accuracy and reliability of the labeling, normalizing the extracted features to ensure the comparability of the features, so that features of different modalities can be effectively fused together to generate a comprehensive feature vector, and the fused feature vector can more comprehensively reflect the characteristics of the tissue, providing high-quality data support for subsequent tissue analysis, and establishing a feature database to store the extracted feature data and its labeling information, which not only serves the training of the model, but also provides data indexing and retrieval functions, facilitating users to quickly find and use the required data, and at the same time, has data backup and recovery functions to ensure the security and integrity of the data.

[0033] The tissue analysis module comprises: The model construction module is configured to construct a model using a machine learning algorithm and train the model using the labeled feature data in the feature database; The recognition and classification module is configured to analyze the extracted features according to the trained model, identify the type of the contacted tissue, and classify it, and verify the classification result to ensure the accuracy and reliability of the classification, and if the classification result is uncertain, trigger a further verification mechanism; The feedback learning module is configured to collect feedback information from doctors or operators on the classification result for further optimization of the model, and according to the real-time feedback information, the model is learned and updated online, and the cases of classification errors are analyzed to find out the shortcomings of the model, providing a reference for subsequent model improvement.

[0034] The technical effects of the above technical solutions are: the model construction module uses advanced machine learning algorithms to construct a model and trains the model using the labeled feature data in the feature database, which covers multiple tissue types and surgical scenarios, ensuring the model has wide applicability and high accuracy, the recognition and classification module analyzes the extracted features according to the trained model, which can accurately identify the type of the contacted tissue and classify it, this accurate identification capability provides a reliable basis for the intelligent suction adjustment system, ensuring the pertinence and effectiveness of the suction adjustment, and after completing the tissue classification, the classification result is verified to ensure the accuracy and reliability of the classification, and the real-time feedback mechanism of the feedback learning module is used for further optimization of the model, improving the adaptability and accuracy of the model.

[0035] The suction adjustment module comprises: The strategy making module is configured to make suction adjustment strategies in advance according to different organization types and surgical requirements and store the strategies in a strategy library, the suction adjustment strategies including the suction size corresponding to each organization type and the suction port switching rule, and regularly update the strategy library according to new surgical data or feedback information to adapt to changes in different surgical scenarios and organization types. The suction control module is configured to automatically control the working state of the switching valve switching the side suction port 4 and the positive suction port 5 according to the organization type identified by the organization analysis module and the suction adjustment strategy provided by the strategy making module, to automatically adjust the suction size of the aspirator main body 1, for example, for fine tissues (such as aspirating nerves, lymph nodes, heart tissues, etc. which require a small suction), switching to the side suction port 4; for cases requiring a larger suction (such as aspirating normal tissues which require a larger suction), switching to the positive suction port 5. The safety monitoring module is configured to monitor the suction size of the aspirator main body 1 in real time, and at the same time, monitor the stress of the organization during the suction adjustment process, and if the adjusted suction exceeds the range of the corresponding suction adjustment strategy or the stress of the organization is abnormal, an audible and visual alarm signal is issued and the operator is prompted to take appropriate measures.

[0036] The technical effects of the above technical solutions are: the strategy making module ensures the pertinence and effectiveness of the suction adjustment through accurate strategy making, and can meet the needs of different surgical scenarios and organization types, the suction control module automatically controls the working state of the switching valve switching the side suction port 4 and the positive suction port 5 according to the organization type identified by the organization analysis module and the suction adjustment strategy provided by the strategy making module, to automatically adjust the suction size of the aspirator main body 1, this automatic control reduces the frequency and time of manual adjustment of the suction by the doctor during the operation, so that the doctor can focus more on the operation itself, improving the operation efficiency, and the safety monitoring module monitors the suction size of the aspirator main body 1 in real time, and monitors the stress of the organization during the suction adjustment process, can judge whether the suction adjustment or the stress of the organization is abnormal, and immediately issues an audible and visual alarm signal when an abnormality occurs, through real-time monitoring and early warning mechanism, the risk of tissue damage caused by improper suction can be significantly reduced, and the safety of the operation is improved.

[0037] Working principle: the aspirator head 3 is made of non-metallic soft material, which can better fit the surgical area to reduce bleeding when separating tissues. The side suction port 4 and the positive suction port 5 are arranged to enable the aspirator body 1 to select a smaller suction force or a larger suction force working mode as needed. The side suction port 4 is suitable for fine tissues to avoid tissue damage caused by excessive suction force. The positive suction port 5 is suitable for situations that require rapid removal of body fluids or secretions, improving the flexibility and accuracy of surgical operations. The intelligent sensing system can monitor the physical properties of the tissues in the surgical area in real time, accurately identify the tissue type, and automatically switch the working state of the side suction port and the positive suction port of the aspirator head according to the identified tissue type, realizing automatic adjustment of the suction force. This not only improves the safety and accuracy of the operation and reduces the risk of tissue damage caused by improper suction force, but also reduces the operation difficulty of the surgeon and improves the operation efficiency.

[0038] In one embodiment, the optical sensor analyzes the microstructure of the tissue surface by reflectance, including: Collecting an optical illumination image of the tissue surface, determining the optical absorption coefficient and the optical scattering coefficient of the contacted tissue in the surgical area according to the optical illumination image; Setting the illumination parameters for the contacted tissue in the surgical area according to the optical absorption coefficient and the optical scattering coefficient; Collecting a tissue image based on the illumination parameters by a spatial frequency domain imaging system and demodulating the tissue image, determining the diffuse reflectance according to the demodulated tissue image; Determining the physiological parameters of the contacted tissue in the surgical area based on the diffuse reflectance, and determining the tissue activity state of the contacted tissue in the surgical area based on the physiological parameters; Determining the structural stability of the contacted tissue in the surgical area according to the tissue activity state, and determining the structural elasticity of the contacted tissue in the surgical area based on the structural stability; Determining the detection index according to the structural elasticity, obtaining the state change condition of the detection index, and determining the action attribute according to the state change condition, the action attribute including: infiltration, heating, and ice compress; Obtaining the mechanical properties of the contacted tissue in the surgical area, and determining the initial soft and hard attribute of the contacted tissue in the surgical area according to the mechanical properties; Configuring the critical value parameters of the action medium according to the action attribute and the initial soft and hard attribute of the contacted tissue in the surgical area; Generating a structural strain environment of the contacted tissue in the surgical area according to the configuration result, and obtaining a structural change characteristic description of the contacted tissue in the surgical area in the structural strain environment; Determining the structural dynamic change rule of the contacted tissue in the surgical area according to the structural change characteristic description, and determining the physiological parameter dynamic change sequence of the contacted tissue in the surgical area according to the structural dynamic change rule and the diffuse reflectance; According to the physiological parameter dynamic change sequence, the surface microstructure of the tissue contacted by the surgical area is determined.

[0039] In this embodiment, the detection index is represented as a mapping index for the elasticity of the tissue structure. In this embodiment, the state change condition is represented as a condition factor that causes the state parameter to change due to the external action of the detection index. In this embodiment, the action medium is represented as a specific application medium of the action attribute, such as ice, alcohol, or a hand warmer, etc. In this embodiment, the critical value parameter is represented as a state index critical value of the action medium, such as a temperature critical value, an ice degree critical value, etc. In this embodiment, the structure dynamic change law is represented as a periodic dynamic law of the adaptive structure change of the tissue contacted by the surgical area.

[0040] The beneficial effects of the above technical solution are: by determining the structure dynamic change law of the tissue contacted by the surgical area by determining the structure elasticity of the tissue contacted by the surgical area and then setting the action condition, the natural structure deformation parameter of the tissue contacted by the surgical area under the influence of the external environment can be reasonably determined to determine the final microstructure of the tissue contacted by the surgical area, ensuring data reliability and reference value, laying a reference condition for subsequent tissue type determination, and improving practicality.

[0041] In one embodiment, based on the suction adjustment strategy, the automatic control switches the working state of the side suction port 4 and the positive suction port 5 of the valve, including: According to the suction adjustment strategy, the on-off state of the side suction port 4 and the positive suction port 5 is determined, and the target suction port in the open state is selected based on the on-off state; The preset suction force parameter of the target suction port is obtained, and the maximum suction force parameter of the target suction port is determined according to the preset suction force parameter; Based on the suction adjustment strategy, the current suction force parameter for the identified tissue type is determined, and the limit suction force parameter for the identified tissue type to remain in a stable state is determined; According to the current suction force parameter, the limit suction force parameter, and the maximum suction force parameter of the target suction port, the ideal suction force parameter of the target suction port is calculated: wherein, represents the ideal suction force parameter of the target suction port, represents the suction force reduction factor corresponding to the design structure of the target suction port, and the value is 0.3-0.5, represents the maximum suction force parameter of the target suction port, represents the current suction force parameter for the identified tissue type, a limit suction parameter of the identified tissue type maintaining a stable state, a required porosity of the identified tissue type being completely absorbed, a current design porosity of the target suction port, a suction saturation degree of the target suction port, an air inlet pressure index of the target suction port, taking a value of 0.5-0.7, a time-varying load increment of the target suction port under a maximum suction parameter, a time-varying load increment of the target suction port under a limit suction parameter of the identified tissue type maintaining a stable state, determining a working mode of the target suction port and a control parameter under the working mode according to the ideal suction parameter of the target suction port; controlling a working state parameter of the target suction port through the control parameter.

[0042] In the embodiment, the suction reduction factor is a suction attenuation factor of the target suction port under a structure limit, and is determined according to a void density of the target suction port; In the embodiment, the required porosity is a porosity design value of the suction port under a requirement of completely absorbing the identified tissue type; In the embodiment, the suction saturation degree is a suction intensity of the target suction port; In the embodiment, the air inlet pressure index is a difficulty index of an air inlet pressure of the target suction port, and is determined according to a number of suction holes and a gap; In the embodiment, the time-varying load increment of the target suction port under the maximum suction parameter is a specific increment of a load of the target suction port under the maximum suction parameter increasing with working time; In the embodiment, the time-varying load increment of the target suction port under the limit suction parameter of the identified tissue type maintaining a stable state is a specific increment of a load of the target suction port under the limit suction parameter increasing with working time.

[0043] The above technical solution has the beneficial effects that: by first determining the target suction port and then calculating the optimal ideal suction parameter according to the preset suction parameter and structure design parameter of the target suction port and the suction limit factor, the complete absorption of the contacted tissue of the surgical area can be ensured, and the problem of low suction efficiency caused by design defects or design deficiencies of the target suction port can be overcome, the efficient and complete absorption of the contacted tissue of the surgical area is realized, and the practicality and reliability are improved.

[0044] It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting, since the scope of the present application will be limited to the appended claims. It must be noted that, as used in the specification and the appended claims, the singular form "a," "an" and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a component" can include a plurality of components. Similarly, the words "comprise," "comprises," and "comprising," as well as the words "include," "includes," and "including," when used in this specification and in the following claims, are intended to specify the presence of stated features, regions, integers, steps, operations, elements, or components, but they do not preclude the presence or addition of one or more other features, regions, integers, steps, operations, elements, components, or groups thereof. Furthermore, these terms do not necessarily denote the presence of anything that can be claimed as new. The meaning of "a," "an," and "the" also includes plural references and plural forms, for example, "a" or "an" entity includes one or more entities.

[0045] While the embodiments of the application have been shown and described herein, it is understood that modifications, substitutions, changes, and alterations can be made by those skilled in the art without departing from the spirit and scope of the present application.

Claims

1. A surgical suction device with intelligent suction adjustment, comprising a suction device body (1), characterized in that: One end of the suction device body (1) is provided with a connector (2) for connecting to a negative pressure source, and the other end of the suction device body (1) is provided with a suction head (3) for extracting body fluids and secretions. The suction head (3) is made of a non-metallic soft material. The suction head (3) is provided with two suction ports, namely a side suction port (4) and a positive suction port (5). The side suction port (4) is located on the side of the suction device head (3) and is provided with a plurality of them, and is used for delicate tissues requiring smaller suction force. The positive suction port (5) is located at the front end of the front of the suction device head (3) and is used in situations requiring larger suction force. At the same time, a switching valve is provided on the suction device head (3) for switching the working states of the side suction port (4) and the positive suction port (5) in real time during surgery. It also includes an intelligent sensing system and an intelligent suction adjustment system, wherein the intelligent sensing system is integrated in the area of ​​the suction head (3); The intelligent sensing system is configured to monitor the physical properties of the tissue in contact with the surgical area in real time through the integration of various sensors, including mechanical sensors, optical sensors, and impedance sensors, and transmit the collected multi-dimensional tissue data to the intelligent suction adjustment system, wherein the optical sensor analyzes the microstructure of the tissue surface through reflectivity; The intelligent suction adjustment system is configured to analyze the received multi-dimensional tissue data, analyze the tissue type of the contacted tissue, and control the switching valve to switch the working state of the side suction port (4) and the positive suction port (5) based on the suction adjustment strategy and according to the tissue type, thereby realizing automatic adjustment of the suction force of the suction head (3); The working states of the switching side suction port (4) and the positive suction port (5) are automatically controlled based on the suction adjustment strategy, and are used to calculate the optimal ideal suction parameters according to the preset suction parameters and structural design parameters of the target suction port and the suction limiting factor.

2. The surgical suction device with intelligent suction adjustment according to claim 1, characterized in that: The intelligent sensing system comprises: A data acquisition module is configured to integrate multiple types of sensors to monitor the physical properties of tissues in contact with the surgical area in real time, and is used to obtain multi-dimensional tissue data of the surgical area, wherein the sensors include mechanical sensors, optical sensors, and impedance sensors; Mechanical sensor: Real-time detection of tissue compression deformation characteristics, including elastic modulus and viscous resistance; Optical sensors: Analyze tissue surface microstructure through reflectivity; Impedance sensors: measure tissue conductivity and differentiate between nerve, muscle, or fat tissue; A data processing module is configured to pre-process the collected raw data, including filtering and denoising and data correction, by removing noise through a filtering algorithm and correcting the collected multi-dimensional tissue data according to the characteristics of the sensor; The data transmission module is configured to compress the collected multi-dimensional organizational data to reduce the data transmission volume, and verify the integrity of the data in real time during the data transmission process. When a data transmission error is detected, a retransmission mechanism is automatically triggered.

3. The surgical suction device with intelligent suction adjustment according to claim 2, characterized in that: Optical sensors: Analyze tissue surface microstructures through reflectivity, including: collecting an optical illumination image of the tissue surface, and determining an optical absorption coefficient and an optical scattering coefficient of the tissue contacted by the surgical area based on the optical illumination image; Setting illumination parameters for the tissue contacted by the surgical area according to the optical absorption coefficient and the optical scattering coefficient; A tissue image based on illumination parameters is collected by a spatial frequency domain imaging system, the tissue image is demodulated, and the diffuse reflectance is determined according to the demodulated tissue image; determining physiological parameters of the tissue in contact with the surgical area based on diffuse reflectivity, and determining the tissue activity state of the tissue in contact with the surgical area based on the physiological parameters; Determine the structural stability of the tissue in contact with the surgical area based on the tissue activity state, and determine the structural elasticity of the tissue in contact with the surgical area based on the structural stability; Determine a detection index based on the structural elasticity, obtain a state change condition of the detection index, and determine an action attribute based on the state change condition, wherein the action attribute includes: infiltration, heating, and ice compress; Obtaining the mechanical properties of the tissue in contact with the surgical area, and determining the initial soft and hard properties of the tissue in contact with the surgical area based on the mechanical properties; The critical value parameters of the action medium are configured according to the action properties and the initial hard and soft properties of the tissue in contact with the surgical area; Generate a structural strain environment of the tissue in contact with the surgical area according to the configuration results, and obtain a description of the structural change characteristics of the tissue in contact with the surgical area in the structural strain environment; Determine the dynamic change law of the structure of the tissue in contact with the surgical area based on the structural change characteristics, and determine the dynamic change sequence of the physiological parameters of the tissue in contact with the surgical area based on the structural dynamic change law and diffuse reflectivity; The surface microstructure of the tissue contacted by the surgical area is determined based on the dynamic change sequence of physiological parameters.

4. The surgical suction device with intelligent suction adjustment according to claim 2, characterized in that: The data transmission module includes: a data compression module configured to remove redundant information from the multi-dimensional organizational data before compression, and then compress the collected multi-dimensional organizational data according to the data type; The data verification module is configured to use a multi-level verification mechanism to perform preliminary verification on multi-dimensional organizational data. If errors are found, further detailed verification is performed. When data transmission errors are detected, the retransmission mechanism is automatically triggered and a priority queue is set for the retransmitted data to ensure that critical data is retransmitted first; If data transmission errors are detected more than three times in a row, the system switches to a redundant channel or reduces the transmission rate. The transmission quality monitoring module is configured to monitor the quality of data transmission in real time, including transmission speed, packet loss rate and delay, and dynamically adjust transmission parameters based on the real-time monitored transmission quality. Based on the real-time monitored transmission quality, when the transmission quality drops below a preset threshold, it automatically issues an early warning signal and provides optimization suggestions, including adjusting the transmission path or switching the communication protocol.

5. The surgical suction device with intelligent suction adjustment according to claim 2, characterized in that: The data acquisition module includes: An acquisition quality monitoring module is configured to monitor the quality of data acquisition in real time, including the accuracy, completeness, and consistency of the data, and automatically adjust sensor parameters or re-acquire data when data quality issues are detected; The data acquisition fault-tolerant module is configured to introduce redundant acquisition during the data acquisition process, and to restore the original data through the redundant data when part of the data is lost or damaged.

6. The surgical suction device with intelligent suction adjustment according to claim 1, characterized in that: The intelligent suction adjustment system comprises: a feature extraction module configured to extract key features from the received multi-dimensional organizational data and automatically annotate the extracted features; a tissue analysis module configured to build a model using a machine learning algorithm, analyze the extracted features through the model, identify the type of contacted tissue, and classify the tissue type; The suction regulating module is configured to formulate a suction regulating strategy in advance according to the tissue type and surgical requirements, determine the corresponding suction regulating strategy according to the tissue type identified by the tissue analysis module, and automatically control the switching valve to switch the working states of the side suction port (4) and the positive suction port (5) based on the suction regulating strategy.

7. The surgical suction device with intelligent suction adjustment according to claim 6, characterized in that: Based on the suction adjustment strategy, the switching valve automatically controls the working states of the switching side suction port (4) and the positive suction port (5), including: Determining the switch states of the side suction port (4) and the front suction port (5) according to the suction force adjustment strategy, and selecting a target suction port in an open state based on the switch states; Obtaining preset suction parameters of the target suction port, and determining a maximum suction parameter of the target suction port according to the preset suction parameters; determining a current suction parameter for the identified tissue type based on a suction adjustment strategy, and determining a limit suction parameter for the identified tissue type to maintain a stable state; The ideal suction parameters of the target suction port are calculated based on the current suction parameters, the limit suction parameters and the maximum suction parameters of the target suction port: in, Expressed as the ideal suction parameter of the target suction port, It is expressed as the suction reduction factor corresponding to the design structure of the target suction port, with a value of 0.3-0.

5. Expressed as the maximum suction parameter of the target suction port, Denoted as the current suction parameter for the identified tissue type, shows the limiting suction parameters for maintaining a stable state for the identified tissue types, represents the required porosity for complete resorption of the identified tissue type, Expressed as the current design porosity of the target suction port, Expressed as the suction saturation of the target suction port, It is expressed as the intake pressure index of the target suction port, with a value of 0.5-0.

7. It is expressed as the time-varying load increment of the target suction port under the maximum suction parameter, It is expressed as the time-varying load increment of the target suction port under the ultimate suction parameter that maintains a steady state for the identified tissue type; Determine the working mode of the target suction port and the control parameters under the working mode according to the ideal suction parameters of the target suction port; The working state parameters of the target suction port are controlled by control parameters.

8. The surgical suction device with intelligent suction adjustment according to claim 6, characterized in that: The feature extraction module is specifically: Feature extraction: extracting key features from multi-dimensional organizational data, including: Extracting tissue hardness, elasticity, and pressure distribution characteristics from mechanical sensor data; Extracting color, texture, and vascularity characteristics of tissue from optical sensor data; extracting conductivity and electrical impedance characteristics of tissue from impedance sensor data; Feature annotation: Analyze the extracted features using deep learning algorithms. A convolutional neural network is used to extract color and texture features from optical sensor data. A recurrent neural network is used to extract time series features from mechanical sensor and impedance sensor data. Based on the analysis results, annotation information is generated for the features, including feature category, location, and intensity. To ensure the accuracy of the annotations, the annotations are verified by comparing manual and automatic annotation results or through cross-validation. Feature enhancement: Normalize the extracted features, convert the feature data of different modalities to the same numerical range, eliminate the dimensional differences and numerical range differences between different features, ensure the comparability of the features, and then fuse the features of different modalities to generate a comprehensive feature vector; Feature management: Establish a feature database to store the extracted feature data and its annotation information. The stored data is used for model training and provides data indexing and retrieval as well as data backup and recovery functions.

9. The surgical suction device with intelligent suction adjustment according to claim 6, characterized in that: The tissue analysis module includes: A model building module is configured to build a model using a machine learning algorithm and train it using labeled feature data in a feature database; The recognition and classification module is configured to analyze the extracted features based on the trained model, identify the type of contacted tissue, classify it, and verify the classification results to ensure the accuracy and reliability of the classification. If there is uncertainty in the classification results, further verification mechanisms are triggered; The feedback learning module is configured to collect feedback information on classification results from doctors or operators for further optimization of the model. Based on real-time feedback information, the model is learned and updated online, and cases with classification errors are analyzed to identify the shortcomings of the model and provide a reference for subsequent model improvements.

10. The surgical suction device with intelligent suction adjustment according to claim 6, characterized in that: The suction adjustment module includes: A strategy formulation module is configured to pre-formulate suction adjustment strategies based on different tissue types and surgical requirements and store them in a strategy library. The suction adjustment strategies include suction levels and suction port switching rules corresponding to each tissue type. The strategy library is regularly updated based on new surgical data or feedback information to adapt to changes in different surgical scenarios and tissue types. A suction control module is configured to automatically control the switching valve to switch the working state of the side suction port (4) and the positive suction port (5) based on the tissue type identified by the tissue analysis module and the suction adjustment strategy provided by the strategy formulation module, thereby automatically adjusting the suction force of the suction device body (1); The safety monitoring module is configured to monitor the suction force of the suction device body (1) in real time and, at the same time, monitor the force applied to the tissue during the suction force adjustment process. If the adjusted suction force exceeds the range of the corresponding suction force adjustment strategy or the force applied to the tissue is abnormal, an audible and visual alarm signal is issued to prompt the operator to take corresponding measures.

Images