A method for skin tightening by superficial liposuction

Abstract

The application discloses a kind of shallow liposuction skin tightening methods, it is related to medical cosmetology technical field, the method is by integrating micro tension sensor array in the side wall of liposuction needle tube, the longitudinal and transverse tension data of subcutaneous tissue at different depths are collected in real time during needle tube advancement;The collected data are compared with the pre-stored skin elasticity modulus database, to determine whether the current liposuction level is in the preset shallow safe tightening zone;When the judgment result is in the safe tightening zone and the real-time tension is lower than the threshold value, the gradient radiofrequency electrode of needle tube outer wall is automatically triggered, and the radiofrequency heat energy is released according to the deep-middle-shallow three-level energy progression mode, and collagen contraction and new growth are stimulated simultaneously;Tension change is continuously monitored and energy parameters are dynamically adjusted until the target tightness is reached.The method realizes the closed-loop control of "perception-judgment-response" during operation, significantly reduces the postoperative skin relaxation rate, significantly improves the immediate postoperative tightness, and can be widely used in the precision improvement of body sculpture surgery.

Description

Technical Field

[0001] This invention relates to the field of medical aesthetics technology, specifically to a method for skin tightening through superficial liposuction. Background Technology

[0002] Existing superficial liposuction skin tightening methods still have the following drawbacks in practical use:

[0003] Superficial liposuction, a core technique in body sculpting, reshapes body contours by removing subdermal fat. Compared to traditional deep liposuction, superficial liposuction preserves the subdermal vascular network and fibrous septa, theoretically promoting postoperative skin retraction. However, clinical practice shows that postoperative skin laxity and uneven surface texture remain major technical challenges in this field. Statistics show that even with superficial liposuction, significant skin laxity still occurs in 15%-20% of cases within 6 months post-surgery, severely impacting surgical outcomes and patient satisfaction.

[0004] Existing superficial liposuction techniques have the following structural defects:

[0005] First, determining the liposuction depth relies on empiricism. During the procedure, surgeons estimate the cannula's location by touch and sight, lacking objective biomechanical quantitative indicators. Due to individual differences in skin thickness, fat density, and fascia adhesion, experiential judgment often leads to deviations in liposuction depth—too deep, damaging the subdermal supporting structures and causing the skin to lose its elasticity and retraction foundation post-surgery; too shallow, leaving excess fat and resulting in insignificant shaping effects. This "blind operation" mode makes it difficult to control the match between post-operative skin retraction force and the thickness of the remaining fat layer.

[0006] Second, the timing of skin tightening intervention is delayed. Current skin tightening techniques (such as monopolar radiofrequency and focused ultrasound) are mostly performed independently after liposuction, with a time lag of several weeks to months between the procedure and the actual liposuction. At this point, the subcutaneous tissue has already begun its wound repair process, and fibrous scarring has begun to form, making it difficult for external energy to penetrate to the target layer and effectively stimulate collagen remodeling. More importantly, postoperative tightening cannot precisely target specific anatomical layers exposed at specific moments during the procedure, missing the critical window period when the fresh wound surface is most receptive to energy stimulation.

[0007] Third, there is a lack of individualized dynamic regulation mechanisms. The biomechanical characteristics of different anatomical locations (such as the abdomen and thighs) and different individuals (such as age and differences in skin elasticity) vary significantly, but current technologies use standardized operating procedures and have not established a personalized parameter adjustment system based on real-time feedback. This "one-size-fits-all" approach leads to both overtreatment (excessive skin tightening and hardening) and undertreatment (little improvement in skin laxity) in some patients.

[0008] In recent years, although there have been attempts to introduce sensing or radiofrequency technologies into the field of liposuction, none have broken through the technical bottleneck of the separation of "sensing-decision-execution". For example, some studies have integrated temperature or pressure sensors into liposuction cannulas, but these are only used for safety monitoring or data recording and have not been linked to energy output control. Other solutions fix radiofrequency electrodes to the outer wall of the cannula, but energy release relies on manual adjustment by the physician, failing to form an automatic feedback loop based on tissue state parameters. These fragmented improvements have failed to fundamentally solve the technical problem of uncontrollable skin retraction in superficial liposuction. Summary of the Invention

[0009] The purpose of this invention is to provide a superficial liposuction skin tightening method to solve the above-mentioned problems.

[0010] To achieve the above objectives, the present invention provides the following technical solution: a superficial liposuction skin tightening method, comprising the following steps:

[0011] Step 1: During the advancement of the liposuction cannula, a miniature tension sensor array integrated into the side wall of the cannula is used to collect longitudinal and transverse tension data of subcutaneous tissue at different depths in real time;

[0012] Step 2: Input the longitudinal tension data and transverse tension data into the control unit, compare and analyze them with the pre-stored skin elastic modulus database for this area, and determine whether the current liposuction layer is in the preset shallow safety tightening band.

[0013] Step 3: When the judgment result is that the current liposuction layer is in the shallow safety tightening band and the real-time tension data is lower than the preset threshold, the control unit automatically triggers the gradient radiofrequency electrode on the outer wall of the liposuction cannula, and releases radiofrequency thermal energy in a three-level energy progression mode of deep-middle-shallow, simultaneously stimulating subcutaneous collagen contraction and regeneration.

[0014] Step 4: Continuously monitor changes in subcutaneous tissue tension and dynamically adjust radiofrequency energy output parameters until the real-time tension data reaches the target tightness range, thereby obtaining an immediate postoperative tightening effect that matches the individual's skin biomechanical characteristics.

[0015] Furthermore, the micro tension sensor array includes at least three sets of strain-type tension sensors arranged at intervals along the needle tube axis. Each set of sensors includes longitudinal sensing elements and transverse sensing elements arranged perpendicularly to each other, for synchronously acquiring tissue resistance data in the needle tube advance direction and tissue extensibility data perpendicular to the needle tube direction.

[0016] Furthermore, the comparative analysis with the pre-stored skin elastic modulus database includes:

[0017] The tissue stiffness index at the current site is calculated based on the tension data collected in real time.

[0018] The tissue stiffness index was matched with the standard elastic modulus range of the corresponding anatomical location and liposuction depth in the database;

[0019] When the tissue stiffness index deviates from the standard range by more than the preset tolerance, a layer deviation warning signal is generated or the needle advance speed is automatically adjusted.

[0020] Furthermore, the criteria for determining the effectiveness of the superficial safety tightening band are: the subcutaneous fat layer thickness is 2-3mm, and the real-time tension data is within 60%-80% of the individual's maximum skin retraction force.

[0021] Furthermore, the deep-medium-shallow three-level energy progression mode includes:

[0022] Level 1: Releases mid-frequency radio frequency energy to a region 5-8mm in front of the needle tip, with a power density of 20-30W / cm² and a duration of 3-5 seconds, inducing deep collagen fiber contraction.

[0023] Level 2: High-frequency radio frequency energy is released to the area 2-5mm in front of the needle tip, with a power density of 15-25W / cm² and a duration of 2-4 seconds, to stimulate the remodeling of middle collagen.

[0024] Level 3: Releases mixed-frequency radio frequency energy to a 0-2mm depth area in front of the needle tip, with a power density of 10-20W / cm² and a duration of 1-3 seconds, to promote the tightening of the superficial dermis.

[0025] The energy release at each level is linked to the needle advancement speed, ensuring that the energy application area is synchronized with the real-time liposuction layer.

[0026] Furthermore, the dynamic adjustment of the radio frequency energy output parameters includes:

[0027] Calculate the skin retraction response index based on the real-time rate of change of tension data;

[0028] When the retraction response index is higher than the preset upper limit, reduce the RF power density or shorten the action time to prevent excessive tightening;

[0029] When the retraction response index is lower than the preset lower limit, the radio frequency power density is increased or the action time is extended to enhance the tightening effect;

[0030] When the retraction response index is within the target range, maintain the current parameters and record the energy-response correlation data for that site, which will be used for predictive parameter presets for subsequent sites.

[0031] Furthermore, the method also includes a preoperative individualized database construction step:

[0032] High-frequency ultrasound was used to obtain data on skin thickness, dermal collagen density, and subcutaneous fat distribution in the target area.

[0033] A finite element model of the individual's skin viscoelasticity was established based on the acquired data.

[0034] Simulate tissue tension distribution under different liposuction depths and paths to generate individualized standard elastic modulus ranges and safety tightening band parameters;

[0035] Individualized parameters are imported into the control unit, replacing the general database as the benchmark for intraoperative comparison.

[0036] Furthermore, the closed-loop response time of the real-time acquisition and automatic trigger control is no more than 200 milliseconds, ensuring that the spatiotemporal synchronization error between the radio frequency energy release and the current liposuction layer is less than 2mm.

[0037] Furthermore, the method also includes a postoperative outcome prediction and verification step:

[0038] Based on the tension data, energy output parameters, and final retraction response index of each acquisition site during the operation, a predictive model for the postoperative tightness evolution of the surgical area is constructed.

[0039] Postoperatively, skin elasticity data in this area were collected periodically and compared with the prediction model for verification.

[0040] Based on the feedback from the validation results, the parameter weights of the individualized database are optimized for precise control of the patient's subsequent treatment.

[0041] Furthermore, the method is implemented using a superficial liposuction skin tightening system, the system comprising:

[0042] The liposuction cannula has a micro tension sensor array integrated on its sidewall and gradient radio frequency electrodes arranged on its outer wall.

[0043] The control unit has a built-in skin elastic modulus database and a real-time data processing module, which is used to perform tension data comparison and analysis, safety tightening belt judgment and radio frequency trigger control;

[0044] The radio frequency energy generator is connected to the control unit, receives trigger commands, and outputs radio frequency energy in a three-level mode: deep, medium, and shallow.

[0045] The human-computer interaction interface is used to display the real-time tension curve, the current liposuction layer position, and the radiofrequency energy application area.

[0046] Compared with existing technologies, the superficial liposuction skin tightening method provided by the present invention has the following beneficial effects:

[0047] First, it achieves real-time quantitative perception and closed-loop control of skin retraction force during superficial liposuction. Through a micro-tension sensor array integrated into the liposuction cannula, it acquires dynamic biomechanical data of subcutaneous tissue for the first time during the liposuction operation, transforming the traditional "blind operation" that relies on experience-based judgment into precise control based on objective data, resulting in a decreasing trend in the incidence of postoperative skin laxity.

[0048] Secondly, a synchronous and coordinated mechanism for liposuction and skin tightening during the operation was established. Through the automatic linkage control of real-time tension data and gradient radiofrequency energy, graded thermal energy intervention was implemented at the immediate sites along the path of the liposuction cannula. This fully utilizes the optimal response window of the fresh tissue wound, resulting in improved skin tightness immediately after the operation compared to traditional staged operations, thus avoiding the need for a second tightening surgery.

[0049] Third, a technical path for personalized precision medicine has been constructed; an individualized skin viscoelasticity model is established based on preoperative ultrasound data, and energy parameters are dynamically adjusted during the operation based on the real-time retraction response index, so that the treatment plan is highly adapted to the patient's specific biomechanical characteristics, solving the problem of overtreatment or undertreatment caused by traditional standardized operations.

[0050] Fourth, it significantly improves surgical safety and predictability of results; through the pre-setting of the superficial safety tightening band and real-time deviation warning, it effectively prevents damage to the support structure caused by excessive suction; the postoperative tightness evolution prediction model built based on intraoperative data realizes the transformation from "empirical estimation" to "data verification" of the effect evaluation mode. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0052] Figure 1 This is a schematic diagram of the overall system architecture of the present invention;

[0053] Figure 2 This is a schematic diagram of the needle structure of the present invention;

[0054] Figure 3 This is a schematic diagram of the closed-loop control logic of the present invention. Detailed Implementation

[0055] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0056] Please see Figure 1-3A superficial liposuction skin tightening method includes the following steps:

[0057] Step 1: During the advancement of the liposuction cannula, a miniature tension sensor array integrated into the side wall of the cannula is used to collect longitudinal and transverse tension data of subcutaneous tissue at different depths in real time;

[0058] Step 2: Input the longitudinal tension data and transverse tension data into the control unit, compare and analyze them with the pre-stored skin elastic modulus database for this area, and determine whether the current liposuction layer is in the preset superficial safety tightening band.

[0059] Step 3: When the judgment result is that the current liposuction layer is in the shallow safety tightening band and the real-time tension data is lower than the preset threshold, the control unit automatically triggers the gradient radiofrequency electrode on the outer wall of the liposuction cannula, and releases radiofrequency thermal energy in a three-level energy progression mode of deep-middle-shallow, simultaneously stimulating subcutaneous collagen contraction and regeneration.

[0060] Step 4: Continuously monitor changes in subcutaneous tissue tension and dynamically adjust radiofrequency energy output parameters until the real-time tension data reaches the target tightness range, thereby obtaining an immediate postoperative tightening effect that matches the individual's skin biomechanical characteristics.

[0061] Example 1: System Overall Architecture and Workflow

[0062] The superficial liposuction skin tightening system of this embodiment includes a liposuction cannula, a control unit, a radio frequency energy generator, a high-frequency ultrasound preoperative assessment module, and a human-computer interaction interface.

[0063] The liposuction cannula employs a double-layered structure. The inner layer is a traditional negative pressure liposuction channel with a diameter of 2.5-3.5mm and multiple suction holes on its sidewalls. The outer cannula integrates a micro-tension sensor array on its sidewalls and features gradient radiofrequency electrodes. The cannula tip is designed with a blunt, rounded shape to reduce the risk of tissue damage.

[0064] The control unit has a built-in ARM Cortex-M7 processor running a real-time operating system, responsible for data acquisition, algorithm processing, and command output. The RF power generator uses a solid-state RF source with a frequency range of 0.5-40MHz, adjustable output power of 0-100W, and a response time of less than 10ms.

[0065] Preoperatively, high-frequency ultrasound was used to collect data on skin thickness, dermal collagen density, and subcutaneous fat distribution in the target area, establishing an individualized finite element model of skin viscoelasticity. This model was then integrated with a pre-stored general database of skin elastic modulus to generate an individualized parameter set for intraoperative comparison.

[0066] During the procedure, the physician performs routine superficial liposuction using a cannula. As the cannula is advanced, a miniature tension sensor array collects tissue tension data in real time at a sampling rate of 1000Hz. After preprocessing by a signal conditioning circuit, the data is transmitted to the control unit. The control unit runs a multi-threaded processing program: the main thread executes tension data analysis and layer determination algorithms, while the interrupt thread responds to emergency safety events.

[0067] When the current site meets the radiofrequency triggering conditions, the control unit sends a trigger command to the radiofrequency energy generator, specifying the energy level, power density, and treatment time. Radiofrequency energy is released to the target tissue via gradient radiofrequency electrodes, simultaneously completing liposuction and tightening operations. The human-machine interface displays the tension curve, current layer position, radiofrequency treatment area, and system status in real time for physician monitoring.

[0068] The miniature tension sensor array includes at least three sets of strain-type tension sensors arranged at intervals along the needle tube axis. Each set of sensors includes longitudinal sensing elements and transverse sensing elements arranged perpendicularly to each other, for simultaneously acquiring tissue resistance data in the needle tube advance direction and tissue extensibility data perpendicular to the needle tube direction.

[0069] The comparative analysis with a pre-existing skin elastic modulus database includes:

[0070] The tissue stiffness index at the current site is calculated based on the tension data collected in real time.

[0071] The tissue stiffness index was matched with the standard elastic modulus range of the corresponding anatomical location and liposuction depth in the database;

[0072] When the tissue stiffness index deviates from the standard range by more than the preset tolerance, a layer deviation warning signal is generated or the needle advance speed is automatically adjusted.

[0073] Example 2: Construction and Personalized Integration of Skin Elastic Modulus Database

[0074] The skin elastic modulus database in this application is constructed based on large-scale clinical sample collection, ensuring the scientific validity and universality of the technical solution.

[0075] During the database construction phase, clinical data from 12 medical aesthetic centers across the country were collected, with a total sample size of 3,850 cases, covering healthy adults aged 18-55 years with a BMI of 18-28. The samples were divided into two groups by gender (2,980 females and 870 males), five groups by age group (18-25 years, 26-35 years, 36-45 years, and 46-55 years), and five regions by anatomical location: abdomen, thigh (anterior / medial / lateral), upper arm (medial / posterior), waist, and buttocks.

[0076] For each sample, preoperatively, high-frequency ultrasound (15MHz frequency, 0.1mm axial resolution) was used to measure the full-thickness skin, dermal layer, and subcutaneous fat layer thickness; shear wave elastography was used to measure the skin elastic modulus; intraoperatively, under standard anesthesia, the tension sensor array of this invention was used to collect tissue tension data at different liposuction depths (preserving fat layer thicknesses of 1mm, 2mm, 3mm, 4mm, and 5mm). After desensitization, all data were used to establish a database containing seven-dimensional parameters including age, gender, location, skin thickness, fat thickness, elastic modulus, and tension data.

[0077] The database was trained using a random forest algorithm to establish a predictive model that ranges from demographic characteristics and anatomical parameters to standard elastic modulus ranges. The model achieved a cross-validation accuracy of 92.3%, providing initial parameter recommendations for new patients based on characteristics of similar populations.

[0078] In the individualized fusion phase, preoperative ultrasound data is input into finite element analysis software (such as ABAQUS) to establish a three-layer biomechanical model including skin, fat, and fascia, tailored to each patient. This model simulates tissue deformation and stress distribution at different liposuction depths, generating an individualized standard elastic modulus range for that patient. This range is then weighted and fused with a database-recommended range (70% weight for individualized data, 30% weight for database data) to form the final parameter set for intraoperative comparison. This fusion strategy ensures individual suitability while avoiding biases that might arise from insufficient data in purely individual modeling.

[0079] The criteria for judging a superficial safety tightening band are: the thickness of the subcutaneous fat layer is 2-3mm, and the real-time tension data is within 60%-80% of the individual's maximum skin retraction force.

[0080] The three-level energy progression pattern of deep-medium-shallow includes:

[0081] Level 1: Releases mid-frequency radio frequency energy to a region 5-8mm in front of the needle tip, with a power density of 20-30W / cm² and a duration of 3-5 seconds, inducing deep collagen fiber contraction.

[0082] Level 2: High-frequency radio frequency energy is released to the area 2-5mm in front of the needle tip, with a power density of 15-25W / cm² and a duration of 2-4 seconds, to stimulate the remodeling of middle collagen.

[0083] Level 3: Releases mixed-frequency radio frequency energy to a 0-2mm depth area in front of the needle tip, with a power density of 10-20W / cm² and a duration of 1-3 seconds, to promote the tightening of the superficial dermis.

[0084] The energy release at each level is linked to the needle advancement speed, ensuring that the energy application area is synchronized with the real-time liposuction layer.

[0085] Example 3: Physical Structure and Directional Energy Release of Gradient Radio Frequency Electrodes

[0086] The specific arrangement and insulation design of the gradient radio frequency electrodes 12 on the outer wall of the needle are key technologies for achieving precise energy release and avoiding epidermal damage.

[0087] The electrode structure adopts a "spiral-spaced" composite layout. For example... Figure 2 As shown, the outer wall of the needle is machined with three parallel spiral grooves, each 0.3 mm deep, with a pitch of 15 mm and a helix angle of 30°. Platinum-iridium alloy electrode wires with a diameter of 0.2 mm are embedded within the grooves, forming three sets of spiral electrodes 121, 122, and 123, corresponding to the deep, medium, and shallow energy release levels, respectively. The three sets of electrodes are staggered by 5 mm axially to ensure continuous coverage of the energy application area.

[0088] The electrode insulation design employs a multi-layer structure: the electrode wire surface is coated with a polyimide insulating layer (0.05mm thick, withstand voltage >500V); the spiral groove is filled with a composite insulating material of alumina ceramic powder and medical silicone, which is cured at high temperature and then polished to be flush with the outer wall of the needle; the outer layer of the needle is covered with a 0.1mm thick Parylene C insulating coating, and only the exposed area of ​​the electrode is laser-etched to create a precise energy release window.

[0089] Directed energy release is achieved through the following mechanisms:

[0090] (1) Deep electrode 121: The window is located at the bottom of the spiral groove, facing the outside of the needle tube, and releases medium frequency radio frequency (2MHz). The wavelength is relatively long and the penetration depth is 5-8mm. It mainly acts on the deep fat and superficial fascia junction area to induce deep collagen contraction.

[0091] (2) Intermediate electrode 122: The window is located on the side of the spiral groove, facing downwards, releasing high-frequency radio frequency (6MHz), penetrating to a depth of 2-5mm, acting on the middle fat septum, stimulating the contraction and remodeling of the fibrous septum.

[0092] (3) Shallow electrode 123: The window is located at the top of the spiral groove, facing obliquely upward, releasing mixed frequency radio frequency (6MHz+20MHz). The short wave component is concentrated at a depth of 1-2mm, and the long wave component assists in heating the shallow dermis, promoting immediate tightening and long-term collagen regeneration.

[0093] The directionality of energy release also relies on impedance matching design. Control unit 2 monitors the impedance value of the electrode-tissue interface in real time and dynamically adjusts the radio frequency and output power to ensure that energy forms a focused thermal zone at the target layer, rather than diffusing into the epidermis or deeper tissues. Thermal field simulations and in vitro experiments show that this design ensures that the epidermal temperature rises by no more than 2°C, the target layer temperature reaches 55-65°C (the optimal temperature for collagen contraction), and the deep tissue temperature remains below 45°C, effectively preventing thermal damage.

[0094] The three-stage energy progression timing is linked to the needle advance speed. The standard advance speed is set at 2mm / s. The deep electrode is triggered when the needle advances 5mm, with an action time of 2.5 seconds; the intermediate electrode is triggered when it passes the same point, with an action time of 1.5 seconds; and the shallow electrode is triggered when the needle retracts or during the next advance cycle, with an action time of 1 second. An encoder monitors the needle displacement in real time to ensure precise correspondence between energy release and needle tip position.

[0095] Dynamic adjustment of radio frequency energy output parameters includes:

[0096] Calculate the skin retraction response index based on the real-time rate of change of tension data;

[0097] When the retraction response index is higher than the preset upper limit, reduce the RF power density or shorten the action time to prevent excessive tightening;

[0098] When the retraction response index is lower than the preset lower limit, the radio frequency power density is increased or the action time is extended to enhance the tightening effect;

[0099] When the retraction response index is within the target range, maintain the current parameters and record the energy-response correlation data for that site, which will be used for predictive parameter presets for subsequent sites.

[0100] Example 4: Anti-interference acquisition and real signal identification of tension data

[0101] Intraoperative tension acquisition faces multiple sources of interference: hydrodynamic fluctuations caused by negative pressure aspiration, mechanical vibrations caused by fat particles clogging the needle, motion artifacts introduced by the physician's hand tremors, and electromagnetic interference during radiofrequency energy release. This application employs a multi-dimensional algorithm design to ensure that the sensor identifies the true skin tension signal.

[0102] At the hardware level, the miniature tension sensor array employs a silicon piezoresistive sensor manufactured using MEMS technology. It has a measurement range of 0-500 kPa, a sensitivity of 0.1 kPa, and a natural frequency higher than 10 kHz, enabling it to effectively respond to rapid changes in tissue tension. The sensor surface is covered with a biocompatible silicone film to isolate direct contact with negative pressure fluid while simultaneously transmitting tissue mechanical stress. The array is arranged in a "3+2" pattern: three sets of main sensors (8 mm apart) are equidistantly arranged along the needle axis, each set containing two sensing elements, one longitudinal and one transverse; two additional reference sensors are placed 2 mm from the needle tip to detect the pre-tension signal of the tissue about to contact the needle tip.

[0103] The signal conditioning circuit uses an instrumentation amplifier for differential amplification, achieving a common-mode rejection ratio greater than 100dB, effectively suppressing radio frequency electromagnetic interference. A hardware filter is set before analog-to-digital conversion, with a cutoff frequency of 50Hz, to filter out high-frequency noise and power frequency interference.

[0104] At the software algorithm level, the control unit runs adaptive filtering and pattern recognition algorithms, specifically including:

[0105] (1) Baseline drift correction: The moving average algorithm is used to calculate the dynamic baseline with a time window of 500ms to eliminate the influence of slowly changing hydrostatic pressure.

[0106] (2) Artifact identification and removal: An interference feature library is established, including step high pressure caused by blockage (rise time <10ms, amplitude >200kPa), periodic fluctuations caused by hand tremors (frequency 2-8Hz), and random noise of negative pressure fluctuations (wide spectrum and low amplitude). Real-time data is matched with the feature library. When the similarity exceeds the threshold, it is marked as an artifact, and the data in that period is not used for subsequent judgment.

[0107] (3) Extraction of true tension: The wavelet transform algorithm is used to decompose the signal into components of different frequencies. Skin tissue tension is mainly manifested as low-frequency slow-change components (<5Hz), while interference is mostly high-frequency or step components. By reconstructing the low-frequency components, the true tissue tension signal is obtained.

[0108] (4) Multi-sensor fusion: Kalman filtering is performed on the longitudinal tension data of the three main sensors to improve the signal-to-noise ratio by utilizing spatial redundancy; the transverse tension data is used to determine whether the needle has shifted laterally and to assist in hierarchical positioning.

[0109] Clinically validated, the aforementioned anti-interference algorithm improves the signal-to-noise ratio of tension measurement from 20dB to 45dB at the hardware level, and achieves an artifact removal accuracy of 96.8%, ensuring that control decisions are based on the true biomechanical state of the tissue.

[0110] The method also includes a preoperative individualized database construction step:

[0111] High-frequency ultrasound was used to obtain data on skin thickness, dermal collagen density, and subcutaneous fat distribution in the target area.

[0112] A finite element model of the individual's skin viscoelasticity was established based on the acquired data.

[0113] Simulate tissue tension distribution under different liposuction depths and paths to generate individualized standard elastic modulus ranges and safety tightening band parameters;

[0114] Individualized parameters are imported into the control unit, replacing the general database as the benchmark for intraoperative comparison.

[0115] The closed-loop response time of real-time acquisition and automatic trigger control is no more than 200 milliseconds, ensuring that the spatiotemporal synchronization error between radiofrequency energy release and the current liposuction layer is less than 2mm.

[0116] The method also includes steps for predicting and verifying postoperative outcomes:

[0117] Based on the tension data, energy output parameters, and final retraction response index of each acquisition site during the operation, a predictive model for the postoperative tightness evolution of the surgical area is constructed.

[0118] Postoperatively, skin elasticity data in this area were collected periodically and compared with the prediction model for verification.

[0119] Based on the feedback from the validation results, the parameter weights of the individualized database are optimized for precise control of the patient's subsequent treatment.

[0120] Example 5: Specific Implementation of Closed-Loop Control Algorithm

[0121] The core control algorithm of control unit 2 adopts a hierarchical structure, including a data layer, a decision layer, and an execution layer.

[0122] The data layer is responsible for acquiring, preprocessing, and extracting sensor data. It completes an AD sampling every 1ms and an anti-interference algorithm every 10ms, outputting the longitudinal tension value Fz, the transverse tension value Fx, and the tension change rate dFz / dt at the current location.

[0123] The decision-making layer operates on a state machine model, defining four working states:

[0124] Status S0 (Ready): The needle has not yet contacted the tissue or has just entered the subcutaneous tissue, the tension value is below the threshold, and the system is ready;

[0125] Status S1 (Liposuction): Tension value enters the normal range, perform regular liposuction, and do not trigger radiofrequency.

[0126] State S2 (Tightening): If the safety tightening belt is determined to be in place and the tension is lower than the target value, radio frequency energy release is triggered;

[0127] Status S3 (Alarm): abnormal tension or layer deviation, sound and light prompts are issued, and adjustment of operation is recommended.

[0128] State transition conditions are determined comprehensively based on multi-dimensional parameters:

[0129] S0→S1: Fz>Fth1 (contact threshold) and dFz / dt>0 (continuous entry);

[0130] S1→S2: current depth d∈[dmin,dmax] (safe tightening range) and Fz<Ftarget (insufficient tension requiring tightening);

[0131] S2→S1: Fz≥Ftarget (target reached) or action time t>tmax (timeout protection);

[0132] Any state→S3: Fz>Fmax (overload) or d<dmin (too deep) or d>dmax (too shallow).

[0133] The execution layer is responsible for real-time adjustment of radio frequency parameters. A PID control algorithm is adopted, which takes the difference between Ftarget and real-time Fz as the input, and outputs the radio frequency power adjustment amount ΔP. Feedforward control is also introduced to predict the change of tissue tension at the next moment according to the advancing speed of the needle tube, adjust energy output in advance, and compensate for system response delay.

[0134] The method is implemented by a shallow liposuction skin tightening system, and the system comprises:

[0135] A liposuction needle tube, the side wall of which is integrated with a micro tension sensor array, and the outer wall of which is provided with gradient radio frequency electrodes;

[0136] A control unit, which has a built-in skin elastic modulus database and a real-time data processing module, and is used for performing tension data comparison and analysis, safe tightening zone judgment and radio frequency trigger control;

[0137] A radio frequency energy generator, which is connected to the control unit, receives trigger instructions and outputs radio frequency energy in a three-level mode of deep-medium-shallow;

[0138] A human-computer interaction interface, which is used for displaying real-time tension curve, current liposuction layer position and radio frequency energy action area.

[0139] The above merely describes some exemplary embodiments of the present invention by way of illustration. It goes without saying that for those of ordinary skill in the art, various modifications can be made to the described embodiments in different ways without departing from the spirit and scope of the present invention. Therefore, the above accompanying drawings and description are illustrative in nature and should not be construed as limiting the protection scope of the claims of the present invention.

Claims

1. A method for superficial liposuction and skin tightening, characterized in that, Includes the following steps: Step 1: During the advancement of the liposuction cannula, a miniature tension sensor array integrated into the side wall of the cannula is used to collect longitudinal and transverse tension data of subcutaneous tissue at different depths in real time; Step 2: Input the longitudinal tension data and transverse tension data into the control unit, compare and analyze them with the pre-stored skin elastic modulus database for this area, and determine whether the current liposuction layer is in the preset shallow safety tightening band. Step 3: When the judgment result is that the current liposuction layer is in the shallow safety tightening band and the real-time tension data is lower than the preset threshold, the control unit automatically triggers the gradient radiofrequency electrode on the outer wall of the liposuction cannula, and releases radiofrequency thermal energy in a three-level energy progression mode of deep-middle-shallow, simultaneously stimulating subcutaneous collagen contraction and regeneration. Step 4: Continuously monitor changes in subcutaneous tissue tension and dynamically adjust radiofrequency energy output parameters until the real-time tension data reaches the target tightness range, thereby obtaining an immediate postoperative tightening effect that matches the individual's skin biomechanical characteristics.

2. The method for superficial liposuction skin tightening according to claim 1, characterized in that, The micro-tension sensor array includes at least three sets of strain-type tension sensors arranged at intervals along the needle tube axis. Each set of sensors includes longitudinal sensing elements and transverse sensing elements arranged perpendicularly to each other, used to simultaneously acquire tissue resistance data in the needle tube advance direction and tissue extensibility data perpendicular to the needle tube direction.

3. The method for superficial liposuction skin tightening according to claim 1, characterized in that, The comparative analysis with the pre-stored skin elastic modulus database includes: The tissue stiffness index at the current site is calculated based on the tension data collected in real time. The tissue stiffness index was matched with the standard elastic modulus range of the corresponding anatomical location and liposuction depth in the database; When the tissue stiffness index deviates from the standard range by more than the preset tolerance, a layer deviation warning signal is generated or the needle advance speed is automatically adjusted.

4. The method for superficial liposuction and skin tightening according to claim 1, characterized in that, The criteria for determining the superficial safety tightening band are: the thickness of the subcutaneous fat layer is 2-3mm, and the real-time tension data is within 60%-80% of the individual's maximum skin retraction force.

5. The method for superficial liposuction skin tightening according to claim 1, characterized in that, The deep-medium-shallow three-level energy progression mode includes: Level 1: Releases mid-frequency radio frequency energy to a region 5-8mm in front of the needle tip, with a power density of 20-30W / cm² and a duration of 3-5 seconds, inducing deep collagen fiber contraction. Level 2: High-frequency radio frequency energy is released to the area 2-5mm in front of the needle tip, with a power density of 15-25W / cm² and a duration of 2-4 seconds, to stimulate the remodeling of middle collagen. Level 3: Releases mixed-frequency radio frequency energy to a 0-2mm depth area in front of the needle tip, with a power density of 10-20W / cm² and a duration of 1-3 seconds, to promote the tightening of the superficial dermis. The energy release at each level is linked to the needle advancement speed, ensuring that the energy application area is synchronized with the real-time liposuction layer.

6. The method for superficial liposuction skin tightening according to claim 1, characterized in that, The dynamically adjusted radio frequency energy output parameters include: Calculate the skin retraction response index based on the real-time rate of change of tension data; When the retraction response index is higher than the preset upper limit, reduce the RF power density or shorten the action time to prevent excessive tightening; When the retraction response index is lower than the preset lower limit, the radio frequency power density is increased or the action time is extended to enhance the tightening effect; When the retraction response index is within the target range, maintain the current parameters and record the energy-response correlation data for that site, which will be used for predictive parameter presets for subsequent sites.

7. The method for superficial liposuction skin tightening according to claim 1, characterized in that, The method also includes a preoperative individualized database construction step: High-frequency ultrasound was used to obtain data on skin thickness, dermal collagen density, and subcutaneous fat distribution in the target area. A finite element model of the individual's skin viscoelasticity was established based on the acquired data. Simulate tissue tension distribution under different liposuction depths and paths to generate individualized standard elastic modulus ranges and safety tightening band parameters; Individualized parameters are imported into the control unit, replacing the general database as the benchmark for intraoperative comparison.

8. The method for superficial liposuction skin tightening according to claim 1, characterized in that, The closed-loop response time of the real-time acquisition and automatic trigger control is no more than 200 milliseconds, ensuring that the spatiotemporal synchronization error between the radio frequency energy release and the current liposuction layer is less than 2mm.

9. The method for superficial liposuction skin tightening according to claim 1, characterized in that, The method also includes postoperative outcome prediction and verification steps: Based on the tension data, energy output parameters, and final retraction response index of each acquisition site during the operation, a predictive model for the postoperative tightness evolution of the surgical area is constructed. Postoperatively, skin elasticity data in this area are collected periodically and compared with the prediction model for verification. Based on the feedback from the validation results, the parameter weights of the individualized database are optimized for precise control of the patient's subsequent treatment.

10. The method according to any one of claims 1-9, characterized in that, The method is implemented using a superficial liposuction skin tightening system, the system comprising: The liposuction cannula has a micro tension sensor array integrated on its sidewall and gradient radio frequency electrodes arranged on its outer wall. The control unit has a built-in skin elastic modulus database and a real-time data processing module, which is used to perform tension data comparison and analysis, safety tightening belt judgment and radio frequency trigger control; The radio frequency energy generator is connected to the control unit, receives trigger commands, and outputs radio frequency energy in a three-level mode: deep, medium, and shallow. The human-computer interaction interface is used to display the real-time tension curve, the current liposuction layer position, and the radiofrequency energy application area.

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