A liposuction apparatus

Abstract

The present application provides a kind of liposuction instrument, which includes: pumping handle module, cannula liposuction needle module, negative pressure module and monitoring control module.Cannula liposuction needle module is detachably connected with pumping handle module, negative pressure module is connected with cannula liposuction needle module through pumping handle module, monitoring control module is connected with pumping handle module, cannula liposuction needle module and negative pressure module.Pumping handle module can be used to drive cannula liposuction needle module to perform linear reciprocating motion at a target pumping frequency, so that cannula liposuction needle module performs liposuction operation.Negative pressure module can be used to provide negative pressure to cannula liposuction needle module according to a target negative pressure value.Monitoring control module can be used to collect monitoring data and determine the target pumping frequency and the target negative pressure value based on the monitoring data.The liposuction instrument monitoring control module can determine the target pumping frequency and the target negative pressure value to achieve precise control of liposuction operation.In this way, the liposuction efficiency and safety can be effectively improved.

Description

Technical Field

[0001] This invention relates to the field of medical aesthetic devices, specifically to a liposuction device. Background Technology

[0002] In the field of medical aesthetics and plastic surgery, liposuction, as a core technique for improving body contours and removing excess fat in specific areas, is widely used in fat reshaping treatments for various regions such as the abdomen, legs, and face. With the increasing demand for improved appearance, the frequency of liposuction procedures continues to grow, placing higher demands on the safety, efficiency, and ease of operation of liposuction equipment. As a core instrument, the performance of the liposuction device directly affects the liposuction time, fat removal precision, and postoperative recovery results. Especially in large-scale clinical applications, the stability and reliability of the equipment are crucial factors in ensuring surgical safety and reducing the risk of complications.

[0003] Currently, liposuction is typically performed manually by medical staff, who use a reciprocating suction handle to draw fat particles into a collection device through a liposuction needle under negative pressure. While this type of liposuction device has developed a relatively mature operating procedure over time, its technical design remains at the level of basic functionality, failing to fully consider the needs for efficiency improvement and risk control in clinical practice. Furthermore, the coordination and intelligence of its components are relatively low.

[0004] However, the existing liposuction devices have the following problems in actual clinical applications: Operation is highly dependent on manual control of the handpiece, which easily leads to fatigue of medical staff and affects surgical precision. Regarding component replacement, the modularity of components is insufficient, the connection between the liposuction cannula and the handpiece is complex, replacement is time-consuming, and it is prone to contamination. In terms of sealing, the negative pressure leakage rate is high, usually exceeding 0.1 ml / min, increasing the risk of cross-infection. Regarding intelligence, there is a lack of real-time data feedback on liposuction volume, temperature, and suction frequency, resulting in low surgical controllability. In summary, existing traditional liposuction devices struggle to balance ease of operation, efficient component replacement, safety, and surgical controllability, failing to meet clinical needs for efficient and safe applications. Summary of the Invention

[0005] The technical problem to be solved by the present invention is the low liposuction efficiency and safety of existing liposuction devices.

[0006] To solve the above-mentioned technical problems, the present invention provides a liposuction device, specifically adopting the following technical solution:

[0007] This invention provides a liposuction device, comprising: a suction handle module, a liposuction cannula module, a negative pressure module, and a monitoring and control module. The liposuction cannula module is detachably connected to the suction handle module. The negative pressure module is connected to the liposuction cannula module via the suction handle module. The monitoring and control module is connected to the suction handle module, the liposuction cannula module, and the negative pressure module. The suction handle module can drive the liposuction cannula module to perform linear reciprocating motion at a target suction frequency, thereby enabling the liposuction cannula module to perform liposuction. The negative pressure module can provide negative pressure to the liposuction cannula module according to a target negative pressure value. The monitoring and control module can collect monitoring data and determine the target suction frequency and target negative pressure value based on the monitoring data.

[0008] This liposuction device addresses the problems of traditional liposuction devices by integrating an automatic suction handle module, a detachable connection structure between the suction handle module and the liposuction cannula module, and an intelligent monitoring and control module, achieving multi-dimensional optimization: The automatic suction handle module reduces the workload of medical staff and avoids operational errors, thus improving surgical precision. The detachable connection structure shortens the replacement time of the liposuction cannula module and reduces contamination residue. The intelligent monitoring and control module can collect and feedback key monitoring data in real time, and determine the target suction frequency and target negative pressure value based on the monitoring data, enabling precise control of the liposuction operation of the liposuction cannula module according to the target suction frequency and target negative pressure value. This effectively improves the liposuction efficiency and safety of the device.

[0009] In one alternative implementation, the negative pressure module includes: a negative pressure input interface module, a negative pressure regulating valve module, a negative pressure output interface module, and a fat storage bottle module. The negative pressure input interface module receives input negative pressure. The negative pressure regulating valve module adjusts the negative pressure supplied to the liposuction cannula module by the negative pressure output interface module according to a target negative pressure value. The fat storage bottle module stores the aspirated material from the liposuction cannula module.

[0010] In one alternative implementation, the aforementioned monitoring data includes: aspirated material weight, aspirated fat density, fat layer thickness, instantaneous tissue resistance, resistance change rate, blood percentage in the aspirated material, and real-time negative pressure monitoring value. The monitoring and control module includes: a weight sensor and an optical sensor connected to the fat storage bottle module; an ultrasonic sensor and a force sensor connected to the suction handle module; a negative pressure sensor connected to the negative pressure output interface module; and a control processing module. The weight sensor can be used to collect the weight of the aspirated material. The optical sensor can be used to detect the aspirated fat density and blood percentage in the aspirated material. The ultrasonic sensor can be used to measure the fat layer thickness. The force sensor can be used to collect instantaneous tissue resistance. The negative pressure sensor can be used to collect real-time negative pressure monitoring value. The control processing module can be used to determine the resistance change rate based on the instantaneous tissue resistance, and, based on the aspirated material weight, aspirated fat density, fat layer thickness, instantaneous tissue resistance, resistance change rate, blood percentage in the aspirated material, and real-time negative pressure monitoring value, determine the target suction frequency and target negative pressure value through a multimodal fusion deep learning model.

[0011] In one alternative implementation, the aforementioned multimodal fusion deep learning model includes: a data preprocessing layer, a modality feature extraction layer, a dynamic feature fusion layer, and a DRL decision layer. The data preprocessing layer receives and preprocesses monitoring data, outputting preprocessed monitoring data. The modality feature extraction layer extracts features from the preprocessed monitoring data, outputting multiple single-modality feature vectors. The dynamic feature fusion layer fuses these single-modality feature vectors, outputting a comprehensive feature vector. The DRL decision layer determines and outputs the target twitching frequency and the target negative pressure value based on the comprehensive feature vector.

[0012] In one alternative implementation, the data preprocessing layer is specifically used to standardize, denoise, and spatiotemporally align the monitoring data. The dynamic feature fusion layer is specifically used to dynamically allocate weights corresponding to multiple single-modal feature vectors using a multi-head attention mechanism to perform feature fusion and determine a comprehensive feature vector.

[0013] In one alternative implementation, the aforementioned DRL decision layer adopts the Actor-Critic framework.

[0014] In one alternative implementation, the monitoring and control module further includes a display module. The display module can be used to display monitoring data, target twitching frequency, target negative pressure value, and the operating status of the twitching handle module and the negative pressure module.

[0015] In one alternative implementation, the aforementioned pull-handle module includes: a drive module, a temperature control module, and a shock absorption module. The drive module drives the liposuction cannula module to perform linear reciprocating motion. The temperature control module adjusts the temperature of the drive module according to a preset temperature. The shock absorption module dampens the vibration of the drive module.

[0016] In one alternative implementation, the aforementioned pull-handle module includes: a first connecting module, a locking module, and an unlocking module. The liposuction cannula module includes: a second connecting module. The first connecting module and the second connecting module are detachably connected. The locking module is connected to both the first and second connecting modules and is used to lock and fix the first and second connecting modules. The unlocking module is connected to the locking module and is used to control the locking module to release the locking and fixing of the first and second connecting modules.

[0017] In one alternative implementation, the aforementioned liposuction cannula module includes a cannula module and a liposuction cannula module. The liposuction cannula module is disposed inside the cannula module and is connected to a negative pressure module and a suction handle module. The cannula module can be used to create a liposuction space at the target liposuction area. The liposuction cannula module can be used to perform liposuction within the liposuction space at a target suction frequency and a target negative pressure value. Attached Figure Description

[0018] Figure 1 A schematic diagram of the structural composition of the liposuction device provided in the embodiments of this application;

[0019] Figure 2 This is a schematic diagram of the structure of the liposuction device provided in the embodiments of this application;

[0020] Figure 3 A schematic diagram of the architecture of the pull handle module provided in an embodiment of this application;

[0021] Figure 4 A schematic diagram of the architecture of the liposuction cannula module provided in the embodiments of this application;

[0022] Figure 5 A schematic diagram of the architecture of the negative pressure module provided in the embodiments of this application;

[0023] Figure 6 A schematic diagram of the architecture of the monitoring and control module provided in the embodiments of this application;

[0024] Figure 7 This is a schematic diagram of the structure of a multimodal fusion deep learning model provided in an embodiment of this application;

[0025] Figure 8 This is a schematic diagram of the display interface of the display module provided in an embodiment of this application. Detailed Implementation

[0026] The embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described below do not represent all embodiments consistent with this application. They are merely examples of systems and methods consistent with some aspects of this application as detailed in the claims.

[0027] In the field of medical aesthetics and plastic surgery, liposuction, as a core technique for improving body contours and removing excess fat in specific areas, is widely used in fat reshaping treatments for various regions such as the abdomen, legs, and face. With the increasing demand for improved appearance, the frequency of liposuction procedures continues to grow, placing higher demands on the safety, efficiency, and ease of operation of liposuction equipment. As a core instrument, the performance of the liposuction device directly affects the liposuction time, fat removal precision, and postoperative recovery results. Especially in large-scale clinical applications, the stability and reliability of the equipment are crucial factors in ensuring surgical safety and reducing the risk of complications.

[0028] Currently, liposuction is typically performed manually by medical staff, who use a reciprocating suction handle to draw fat particles into a collection device through a liposuction needle under negative pressure. While this type of liposuction device has developed a relatively mature operating procedure over time, its technical design remains at the level of basic functionality, failing to fully consider the needs for efficiency improvement and risk control in clinical practice. Furthermore, the coordination and intelligence of its components are relatively low.

[0029] However, the existing liposuction devices have the following problems in actual clinical applications: Operation is highly dependent on manual control of the handpiece, which easily leads to fatigue of medical staff and affects surgical precision. Regarding component replacement, the modularity of components is insufficient, the connection between the liposuction cannula and the handpiece is complex, replacement is time-consuming, and it is prone to contamination. In terms of sealing, the negative pressure leakage rate is high, usually exceeding 0.1 ml / min, increasing the risk of cross-infection. Regarding intelligence, there is a lack of real-time data feedback on liposuction volume, temperature, and suction frequency, resulting in low surgical controllability. In summary, existing traditional liposuction devices struggle to balance ease of operation, efficient component replacement, safety, and surgical controllability, failing to meet clinical needs for efficient and safe applications.

[0030] To address the aforementioned issues, this application provides a liposuction device comprising: a suction handle module, a liposuction cannula module, a negative pressure module, and a monitoring and control module. This liposuction device, by integrating an automatic suction handle module, a detachable connection structure between the suction handle module and the liposuction cannula module, and an intelligent monitoring and control module, specifically solves the problems of traditional liposuction devices, achieving multi-dimensional optimization: the automatic suction handle module reduces the workload of medical staff and avoids operational deviations, thereby improving surgical precision. The detachable connection structure shortens the replacement time of the liposuction cannula module and reduces contamination residue. The intelligent monitoring and control module can provide real-time feedback of key monitoring data and determine the target suction frequency and target negative pressure value based on the monitoring data, achieving precise control of the liposuction operation of the liposuction cannula module. This effectively improves the liposuction efficiency and safety of the device.

[0031] The solutions provided in the embodiments of this application will be described below with reference to the accompanying drawings.

[0032] Specifically, Figure 1 This is a schematic diagram of the structural composition of the liposuction device provided in the embodiments of this application, as shown below. Figure 1 As shown, the liposuction device 100 provided in this embodiment includes: a pull handle module 110, a liposuction cannula module 120, a negative pressure module 130, and a monitoring and control module 140. The liposuction cannula module 120 is detachably connected to the pull handle module 110, the negative pressure module 130 is connected to the liposuction cannula module 120 via the pull handle module 110, and the monitoring and control module 140 is connected to the pull handle module 110, the liposuction cannula module 120, and the negative pressure module 130.

[0033] Specifically, Figure 2 This is a schematic diagram of the structure of the liposuction device provided in the embodiments of this application, as shown below. Figure 1 and Figure 2 As shown, the pull handle module 110 can be used to drive the cannula liposuction needle module 120 to perform linear reciprocating motion at a target pull frequency, so that the cannula liposuction needle module 120 can perform liposuction operation.

[0034] The negative pressure module 130 can be used to provide negative pressure to the cannula liposuction needle module 120 according to the target negative pressure value.

[0035] The monitoring and control module 140 can be used to collect monitoring data and determine the target twitching frequency and target negative pressure value based on the monitoring data.

[0036] In this way, the monitoring and control module 140 can determine the target traction frequency and target negative pressure value based on monitoring data, so as to precisely control the liposuction cannula module to perform liposuction. This effectively avoids excessive or insufficient fat removal due to improper operation, ensuring that the liposuction effect reaches the ideal state, while reducing the risk of damage to surrounding normal tissues. Furthermore, both the liposuction cannula module 120 and the negative pressure module 130 can be uniformly controlled by the monitoring and control module 140, eliminating the need for operators to manually adjust the parameters (traction frequency and negative pressure value) of the two components separately, greatly simplifying the operation process. Simultaneously, the monitoring and control module 140 can automatically adjust the target traction frequency and target negative pressure value according to monitoring data, making the liposuction process smoother and more efficient, shortening the operation time, reducing patient pain and surgical risks, and improving the safety of the liposuction process.

[0037] In some embodiments, Figure 3 This is a schematic diagram of the architecture of the pull handle module provided in the embodiments of this application, as shown below. Figure 3 As shown, the pull handle module 110 may include: a drive module 111, a temperature control module 112, and a shock absorption module 113.

[0038] The drive module 111 can be used to drive the liposuction cannula module 120 to perform linear reciprocating motion. For example, the drive module 111 may include a linear magnetic axis motor.

[0039] The temperature control module 112 can be used to adjust the temperature of the drive module 111 according to a preset temperature. For example, the temperature control module 112 may include an aluminum alloy heat sink. In this way, the linear magnetic shaft motor, in conjunction with the aluminum alloy heat sink, can achieve a temperature ≤45℃ during continuous operation for 8 hours.

[0040] The shock absorption module 113 can be used to dampen the drive module 111. For example, the shock absorption module 113 may include: an elastic support assembly, specifically including: a rubber damping pad and an air spring.

[0041] In this way, the drive module 111 can precisely control the linear reciprocating motion of the liposuction cannula module 120 (specifically, the liposuction cannula module) according to the target traction frequency, realizing the automated operation of the liposuction cannula module traction process, reducing manual intervention, and improving work efficiency and operational accuracy. The temperature control module 112 ensures that the power mechanism operates stably in a suitable temperature environment, extending the service life of the equipment. The vibration damping module 113 can effectively absorb and reduce the vibration and impact generated by the drive module 111 during operation, improving the stability and reliability of the liposuction device and reducing the impact of vibration on the operational accuracy of the liposuction cannula.

[0042] In some embodiments, Figure 4 This is a schematic diagram of the architecture of the liposuction cannula module provided in the embodiments of this application, as shown below. Figure 4 As shown, the liposuction cannula module 120 includes a cannula module 121 and a liposuction cannula module 122. The liposuction cannula module 122 is disposed inside the cannula module 121 and is connected to the negative pressure module 130 and the suction handle module 110. The cannula module 121 can be used to form a liposuction space at the target liposuction site. The liposuction cannula module 122 can be used to perform liposuction operations within the liposuction space at a target suction frequency and a target negative pressure value.

[0043] In this way, the cannula module 121 creates a stable liposuction space at the target liposuction site, avoiding repeated friction between the liposuction cannula module 122 and subcutaneous tissue, thus reducing mechanical damage to blood vessels, nerves, and connective tissue. Simultaneously, the cannula module 121 can form a directional liposuction channel, allowing the liposuction cannula module 122 to perform liposuction in a specific direction, thereby improving the accuracy and safety of the liposuction procedure.

[0044] In some embodiments, to achieve a detachable connection between the liposuction cannula module 120 and the pull handle module 110, such as... Figure 3 and Figure 4 As shown, the pull handle module 110 further includes: a first connection module 114, a locking module 115, and an unlocking module 116. The liposuction cannula module 120 further includes: a second connection module 123.

[0045] The first connecting module 114 and the second connecting module 123 are detachably connected. For example, the first connecting module 114 and the second connecting module 123 can be a V-shaped guide groove mating structure. Specifically, the first connecting module 114 can be a V-shaped groove, and the second connecting module 123 can be a V-shaped convex rail. Alternatively, the first connecting module 114 can be a V-shaped convex rail, and the second connecting module 123 can be a V-shaped groove.

[0046] The locking module 115 is connected to the first connecting module 114 and the second connecting module 123 respectively, and is used to lock and fix the first connecting module 114 and the second connecting module 123.

[0047] The cooperation between the first connecting module 114 and the second connecting module 123 improves connection stability, and the locking module 115 further enhances locking force. During liposuction, the liposuction cannula module is subjected to various external forces. This dual-protection structure effectively prevents the separation of the liposuction cannula module 120 from the pull handle module 110, ensuring the stable fixation of the liposuction cannula module 120 during surgery, reducing surgical risks, and improving the safety of liposuction.

[0048] The unlocking module 116 is connected to the locking module 115 and is used to control the locking module 115 to release the locking and fixing of the first connecting module 114 and the second connecting module 123. For example, the unlocking module 116 can be a sliding unlocking component. This facilitates one-handed unlocking by the operator, further improving the ease of operation of the liposuction device.

[0049] In some embodiments, Figure 5 This is a schematic diagram of the architecture of the negative pressure module provided in the embodiments of this application, as shown below. Figure 5 As shown, the negative pressure module 130 includes: a negative pressure input interface module 131, a negative pressure regulating valve module 132, a negative pressure output interface module 133, and a fat storage bottle module 134. The negative pressure input interface module 131 can be used to receive input negative pressure. For example, the negative pressure input interface module 131 can be connected to a vacuum pump to receive input negative pressure. The negative pressure regulating valve module 132 can be used to adjust the negative pressure supplied to the liposuction cannula module 120 by the negative pressure output interface module 133 according to a target negative pressure value. The fat storage bottle module 134 can be used to store the aspirated material from the liposuction cannula module 120.

[0050] In some embodiments, the monitoring data acquired by the monitoring and control module 140 may include: aspirate weight, aspirated fat density, fat layer thickness, instantaneous tissue resistance, resistance change rate, blood content of aspirate, and real-time negative pressure monitoring value.

[0051] Specifically, the monitoring data is mainly divided into physical property parameters of adipose tissue (i.e., weight of aspirated material, density of aspirated fat, and thickness of the fat layer), operational resistance parameters (i.e., instantaneous tissue resistance and rate of change of resistance), and safety monitoring parameters (i.e., blood percentage of aspirated material and real-time negative pressure monitoring value). The physical property parameters of adipose tissue reflect the amount of liposuction and the liposuction site. The operational resistance parameters reflect the interaction force between the liposuction cannula and the tissue and can be used to predict changes in tissue type (e.g., from the fat layer to the fascia layer). The safety monitoring parameters reflect the risk of tissue damage and ensure the accuracy and safety of the actual negative pressure. Thus, based on the above monitoring data, the monitoring and control module 140 can effectively and accurately determine the target suction frequency and target negative pressure value.

[0052] Specifically, Figure 6 This is a schematic diagram of the architecture of the monitoring and control module provided in the embodiments of this application, as shown below. Figure 6As shown, the monitoring and control module 140 may specifically include: a weight sensor 141, an optical sensor 142, an ultrasonic sensor 143, a force sensor 144, a negative pressure sensor 145, and a control processing module 146. Specifically, the weight sensor 141 and optical sensor 142 are connected to the fat storage bottle module 134; the ultrasonic sensor 143 and force sensor 144 are connected to the pull handle module 110; the negative pressure sensor 145 is connected to the negative pressure output interface module 133; and the control processing module 146 is also included.

[0053] Specifically, the weight sensor 141 can be used to collect the weight of the aspirated material. The optical sensor 142 can be used to detect the density of the aspirated fat and the blood content of the aspirated material. The ultrasound sensor 143 can be used to measure the thickness of the fat layer. The force sensor 144 can be used to collect instantaneous tissue resistance. The negative pressure sensor 145 can be used to collect real-time negative pressure monitoring values.

[0054] The control processing module 146 can be used to determine the resistance change rate based on instantaneous tissue resistance, and, based on the weight of the aspirate, the density of the aspirated fat, the thickness of the fat layer, the instantaneous tissue resistance, the resistance change rate, the blood ratio of the aspirate, and the real-time negative pressure monitoring value, determine the target twitching frequency and the target negative pressure value through a multimodal fusion deep learning model.

[0055] In some embodiments, Figure 7 This is a schematic diagram of the structure of the multimodal fusion deep learning model provided in the embodiments of this application, such as... Figure 7 As shown, the multimodal fusion deep learning model 200 includes: a data preprocessing layer 201, a modal feature extraction layer 202, a dynamic feature fusion layer 203, and a DRL decision layer 204.

[0056] The data preprocessing layer 201 can be used to receive monitoring data, perform data preprocessing, and output preprocessed monitoring data.

[0057] Specifically, the data preprocessing layer 201 can be used for preprocessing monitoring data, such as standardization, noise reduction, and spatiotemporal alignment.

[0058] For example, the data preprocessing layer 201 can use min-max normalization to map the monitoring data to the [0,1] interval to eliminate the dimensional differences between different parameters. The data preprocessing layer 201 can select a denoising method based on the data characteristics. For example, a sliding window mean filter can be used for instantaneous tissue resistance and resistance change rate to filter out high-frequency noise. Mean filtering can be used for aspirate weight and fat layer thickness to balance denoising effect and processing efficiency. The data preprocessing layer 201 can standardize the sampling frequency of the monitoring data (e.g., 10Hz, 1 sample every 0.1s), and linear interpolation can be used to supplement the data for the slower-sampled blood proportion of the aspirate (e.g., sampling frequency 2Hz) to ensure synchronization in the time dimension.

[0059] In this way, the data preprocessing layer 201 can eliminate noise, dimensional differences, and temporal misalignments in the original monitoring data, providing high-quality input for subsequent feature extraction and avoiding model decision bias caused by low-quality data. Simultaneously, customized preprocessing strategies are implemented for the characteristics of different monitoring data, improving data consistency while preserving key information and reducing the difficulty of model learning.

[0060] The modal feature extraction layer 202 can be used to extract features from the preprocessed monitoring data and output multiple single-modal feature vectors.

[0061] For example, the modal feature extraction layer 202 can employ a two-layer fully connected network to extract features from the weight and density of the pre-processed aspirate, such as weight fluctuation features and density fluctuation features. The modal feature extraction layer 202 can also employ a 1D convolutional layer to extract features from the thickness of the pre-processed fat layer, such as the spatial distribution features of fat layers at different depths, including the surface fat thickness gradient. Furthermore, the modal feature extraction layer 202 can use a gated recurrent unit (GRU) to extract features from the instantaneous tissue resistance and resistance change rate after pre-processing, capturing the temporal trend of resistance changes, such as a sudden increase in resistance indicating fascia contact. The modal feature extraction layer 202 can also employ a one-layer fully connected network combined with exponential function activation to amplify the feature weights of high blood proportions in the pre-processed aspirate. Finally, the modal feature extraction layer 202 can extract statistical features such as the deviation between the actual value and the historical mean, and the frequency of negative pressure fluctuations from the pre-processed real-time negative pressure monitoring values, and output a feature vector through the fully connected layer.

[0062] In this way, the modal feature extraction layer 202 can transform the raw monitoring data into more representative high-order features, highlighting the physical meaning of each parameter (such as the time-series characteristics of resistance change rate and the safety characteristics of blood percentage). Furthermore, dedicated extractors are designed for the characteristics of different types of monitoring data to maximize the retention of key information from single-modal data, laying the foundation for subsequent fusion.

[0063] The dynamic feature fusion layer 203 can be used to fuse multiple single-modal feature vectors and output a comprehensive feature vector.

[0064] The dynamic feature fusion layer 203 can be used to: dynamically allocate the weights corresponding to multiple single-modal feature vectors using a multi-head attention mechanism to perform feature fusion and determine the comprehensive feature vector.

[0065] Specifically, the dynamic feature fusion layer 203 can achieve dynamic weight allocation through a multi-head attention mechanism. For example, when the feature vector of the blood proportion in the aspirate shows high risk (e.g., corresponding feature value > 0.9), the multi-head attention mechanism can increase its weight (e.g., from the usual 10% to 30%), while reducing the weight of efficacy parameters such as aspirate weight. When the extraction feature of fat layer thickness shows that the fat is thick (e.g., feature value > 0.8), the multi-head attention mechanism can increase its weight along with that of transient tissue resistance (e.g., up to 40% in total).

[0066] In this way, the dynamic feature fusion layer 203 can dynamically prioritize single-modal feature vectors through a multi-head attention mechanism. Under different application scenarios (e.g., high bleeding risk, thick fat layer), it can adaptively highlight the influence of key parameters and overcome the limitations of fixed-weight fusion. The comprehensive feature vector not only retains the integrity of multimodal information, but also focuses on core features through weight adjustment, improving the efficiency and accuracy of subsequent decision layers.

[0067] DRL decision layer 204 can be used to determine and output the target twitching frequency and target negative pressure value based on the comprehensive feature vector.

[0068] In some embodiments, the DRL decision layer 204 may employ an Actor-Critic framework. Specifically, the DRL decision layer 204 may determine and output the target twitching frequency and the target negative pressure value through the Actor-Critic architecture of deep reinforcement learning (DRL).

[0069] The DRL decision layer 204 can achieve end-to-end decision-making based on the fused comprehensive features, directly outputting control parameters (i.e., twitching frequency and negative pressure value) that meet the needs of liposuction operations, without the need for manual intervention. Furthermore, by dynamically optimizing decisions through a reinforcement learning reward mechanism, it can achieve an adaptive balance between liposuction efficiency and tissue safety, making it more intelligent and adaptable than traditional fixed-rule control.

[0070] In some embodiments, the multimodal fusion deep learning model is a pre-trained model. The multimodal fusion deep learning model can be trained based on historical data, namely historical monitoring data and corresponding historical twitching frequency and historical negative pressure value, to obtain a trained and optimized multimodal fusion deep learning model, which can then be applied to the control processing module 146.

[0071] In some embodiments, such as Figure 6 As shown, the monitoring and control module 140 also includes a display module 147. The display module 147 can display monitoring data, target twitching frequency, target negative pressure value, and the working status of the twitching handle module 110 and the negative pressure module 130. This allows operators to intuitively understand the working status of the liposuction device and view parameters such as monitoring data, target twitching frequency, and target negative pressure value.

[0072] For example, Figure 8 This is a schematic diagram of the display interface of the display module provided in the embodiments of this application, as shown below. Figure 8 As shown, the display interface 801 of the display module displays the following parameters: operation time, real-time negative pressure monitoring value, target tumbling frequency, target negative pressure value, weight of the sucked-out material, negative pressure status, tumbling status, handle status, and electronic scale status (i.e., weight sensor status).

[0073] The liposuction device provided in the above embodiments of this application includes: a suction handle module, a liposuction cannula module, a negative pressure module, and a monitoring and control module. This liposuction device, by integrating an automatic suction handle module, a detachable connection structure between the suction handle module and the liposuction cannula module, and an intelligent monitoring and control module, specifically addresses the problems of traditional liposuction devices, achieving multi-dimensional optimization: the automatic suction handle module reduces the workload of medical staff and avoids operational deviations to improve surgical precision. The detachable connection structure shortens the replacement time of the liposuction cannula module and reduces contamination residue. The intelligent monitoring and control module can collect and feedback key monitoring data in real time, and determine the target suction frequency and target negative pressure value based on the monitoring data, thereby achieving precise control of the liposuction operation of the liposuction cannula module according to the target suction frequency and target negative pressure value. This effectively improves the liposuction efficiency and safety of the liposuction device.

[0074] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0075] In the description of this invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0076] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0077] Similar parts between the embodiments provided in this application can be referred to mutually. The specific implementation methods provided above are only a few examples under the overall concept of this application and do not constitute a limitation on the scope of protection of this application. For those skilled in the art, any other implementation methods extended from the solution of this application without creative effort shall fall within the scope of protection of this application.

Claims

1. A liposuction device, characterized in that, include: The device comprises a pull handle module, a liposuction cannula module, a negative pressure module, and a monitoring and control module; wherein the liposuction cannula module is detachably connected to the pull handle module, the negative pressure module is connected to the liposuction cannula module through the pull handle module, and the monitoring and control module is connected to the pull handle module, the liposuction cannula module, and the negative pressure module; The pull handle module is used to drive the liposuction cannula module to perform linear reciprocating motion at a target pull frequency, so that the liposuction cannula module can perform liposuction operation. The negative pressure module is used to provide negative pressure to the liposuction cannula module according to the target negative pressure value; The monitoring and control module is used to collect monitoring data and determine the target twitching frequency and the target negative pressure value based on the monitoring data. The monitoring data includes: aspirate weight, aspirated fat density, fat layer thickness, instantaneous tissue resistance, resistance change rate, blood content of aspirate, and real-time negative pressure monitoring value. The monitoring and control module includes a control processing module; the control processing module is used to determine the resistance change rate based on the instantaneous tissue resistance, and, based on the weight of the aspirate, the density of the aspirated fat, the thickness of the fat layer, the instantaneous tissue resistance, the resistance change rate, the blood content of the aspirate, and the real-time negative pressure monitoring value, determine the target twitching frequency and the target negative pressure value through a multimodal fusion deep learning model. The multimodal fusion deep learning model includes: a data preprocessing layer, a modal feature extraction layer, a dynamic feature fusion layer, and a DRL decision layer; wherein, the data preprocessing layer is used to receive the monitoring data and perform data preprocessing, and output the preprocessed monitoring data; the modal feature extraction layer is used to extract features from the preprocessed monitoring data respectively, and output multiple single-modal feature vectors; the dynamic feature fusion layer is used to fuse the multiple single-modal feature vectors, and output a comprehensive feature vector; the DRL decision layer is used to determine and output the target twitching frequency and the target negative pressure value based on the comprehensive feature vector.

2. The liposuction device according to claim 1, characterized in that, The negative pressure module includes: a negative pressure input interface module, a negative pressure regulating valve module, a negative pressure output interface module, and a fat storage bottle module; wherein... The negative pressure input interface module is used to receive input negative pressure; The negative pressure regulating valve module is used to adjust the negative pressure output interface module to provide negative pressure to the liposuction cannula module according to the target negative pressure value; The fat storage bottle module is used to store the aspirate from the liposuction cannula module.

3. The liposuction device according to claim 2, characterized in that, The monitoring and control module further includes: a weight sensor and an optical sensor connected to the fat storage bottle module; an ultrasonic sensor and a force sensor connected to the pull handle module; and a negative pressure sensor connected to the negative pressure output interface module. The weight sensor is used to collect the weight of the aspirated material; the optical sensor is used to detect the density of the aspirated fat and the blood content of the aspirated material; the ultrasonic sensor is used to measure the thickness of the fat layer; the force sensor is used to collect the instantaneous tissue resistance; and the negative pressure sensor is used to collect the real-time negative pressure monitoring value.

4. The liposuction device according to claim 1, characterized in that, The data preprocessing layer is specifically used to: standardize, denoise, and perform spatiotemporal alignment on the monitoring data; The dynamic feature fusion layer is specifically used to: dynamically allocate the weights corresponding to the multiple single-modal feature vectors using a multi-head attention mechanism to perform feature fusion and determine the comprehensive feature vector.

5. The liposuction device according to claim 1, characterized in that, The DRL decision layer adopts the Actor-Critic framework.

6. The liposuction device according to any one of claims 1-5, characterized in that, The monitoring and control module further includes: a display module; The display module is used to display the monitoring data, the target twitching frequency, the target negative pressure value, and the working status of the twitching handle module and the negative pressure module.

7. The liposuction device according to claim 1, characterized in that, The pull-out handle module includes: a drive module, a temperature control module, and a shock absorption module; wherein... The drive module is used to drive the liposuction cannula module to perform linear reciprocating motion; The temperature control module is used to adjust the temperature of the drive module according to a preset temperature. The vibration damping module is used to dampen the vibration of the drive module.

8. The liposuction device according to claim 1, characterized in that, The pull handle module includes: a first connection module, a locking module, and an unlocking module; the liposuction cannula module includes: a second connection module; The first connection module and the second connection module are detachably connected. The locking module is connected to the first connecting module and the second connecting module respectively, and is used to lock and fix the first connecting module and the second connecting module. The unlocking module is connected to the locking module and is used to control the locking module to release the locking of the first connecting module and the second connecting module.

9. The liposuction device according to claim 1, characterized in that, The liposuction cannula module includes a cannula module and a liposuction cannula module. The liposuction cannula module is disposed inside the cannula module and is connected to the negative pressure module and the suction handle module. The cannula module is used to create a liposuction space at the target liposuction site; The liposuction needle module is used to perform liposuction within the liposuction space at the target pumping frequency and the target negative pressure value.

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