Method for preventing lower limb lymphedema after gynecological tumor operation

Abstract

The invention discloses a gynecological tumor postoperative lower limb lymphedema prevention method, and relates to the technical field of postoperative edema prevention, and the method comprises the steps of S1, data acquisition, S2, biological impedance dynamic parameter calculation, S3, motion characteristic quantitative analysis, S4, fusion algorithm construction, and S5, personalized prevention scheme generation. S6, dynamic feedback regulation is implemented, the dynamic frequency domain analysis of the biological impedance can sensitively capture subtle changes of extracellular fluid components, and tissue inflammatory response and real lymph fluid retention are effectively distinguished; through combination of a motion characteristic quantitative model, a muscle pump function compensation state can be analyzed, a mechanical compensation mechanism in a subclinical period can be identified, a risk assessment algorithm is combined, and synergistic effect analysis of bioelectric characteristics and motion functions is realized through nonlinear relation mapping, so that a detection time window of early lymphatic back loss compensation is advanced compared with a conventional method; and key time is won for clinical intervention.

Description

Technical Field

[0001] The present invention belongs to the technical field of postoperative edema prevention, and particularly relates to a method for preventing lower limb lymphedema after gynecological tumor surgery. Background Technique

[0002] Lower limb lymphedema (LLL), as a progressive chronic postoperative complication, is mainly due to the irreversible structural damage of the lymphatic system during tumor resection surgery, which in turn triggers a series of intricate pathological cascades, including extensive edema in the tissue space, abnormal retention of macromolecular substances, persistent chronic inflammation, gradual aggravation of tissue fibrosis, and abnormal deposition of adipose tissue. Research shows that once LLL forms, it is difficult to cure, bringing multiple negative effects to patients such as limb morphological distortion, decreased sensory function, decreased or even loss of limb strength and motor function, aggravated neuropathic pain, strong fatigue, heavy psychological and mental burden, and increased infection risk, seriously eroding the quality of life of patients.

[0003] Currently, clinical diagnosis mainly relies on limb circumference measurement, volume displacement method or subjective symptom assessment. These methods are insufficiently sensitive to early lymphatic dysfunction and are difficult to identify compensatory pathological changes in the subclinical stage. Although traditional bioimpedance technology can detect changes in tissue fluid volume, impedance measurement at a single frequency point is easily interfered by the extracellular matrix remodeling during tissue repair and cannot distinguish inflammatory exudation from lymphatic fluid retention, resulting in a relatively high false positive rate. To address the above problems, the following solutions are proposed. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for preventing lower limb lymphedema after gynecological tumor surgery. By integrating the frequency-varying characteristics of bioimpedance and kinematic parameters, a multi-dimensional feature evaluation system is constructed, solving the problem in the prior art that it is impossible to distinguish inflammatory exudation from lymphatic fluid retention, resulting in a relatively high false positive rate.

[0005] To solve the above technical problems, the present invention is realized through the following technical solutions:

[0006] The present invention is a method for preventing lower limb lymphedema after gynecological tumor surgery, including:

[0007] Step S1, data acquisition system: Deploy a portable high-frequency bioimpedance instrument, a 3D optical volume scanner, integrate wearable inertial sensors, set the postoperative monitoring period, collect the physiological and motion data of the patient's bilateral lower limbs, and construct a data baseline;

[0008] Step S2, calculation of dynamic bioimpedance parameters: Calculate the difference index between the affected and healthy sides through the impedance amplitude, phase angle, and characteristic frequency of the bioimpedance measurement points collected, and quantify the dynamic balance state of tissue fluid;

[0009] Step S3, Quantitative analysis of motion characteristics: Collect daily activity data through an inertial sensor, extract typical motion pattern characteristics, quantify the impact of daily activities on lymphatic reflux, and evaluate the efficiency of mechanical lymphatic reflux;

[0010] Step S4, Construction of fusion algorithm: Construct a risk assessment model based on the coupling of impedance and motion characteristics, establish a three-level warning threshold, and achieve non-linear fusion of multi-modal data;

[0011] Step S5, Generation of personalized prevention plan: Automatically generate intervention parameters according to the risk assessment value, including the grade of compression stockings and the frequency of intermittent pneumatic pressure treatment, generate a customized exercise prescription, and achieve gradient intervention;

[0012] Step S6, Implementation of dynamic feedback regulation: Establish a parameter closed-loop control system, design an adaptive regulation algorithm, adjust the prevention plan according to the change rate of the risk assessment value, and construct an adaptive treatment system.

[0013] Furthermore, for the said step S1, the data acquisition system specifically includes the following steps:

[0014] Step S11: Use a portable high-frequency bio-impedance meter (50kHz - 1MHz) to symmetrically mark 12 measurement points on both lower limbs; simultaneously measure the impedance amplitude Z, phase angle θ, and characteristic frequency fc of the affected side and the healthy side;

[0015] The said 12 measurement points are specifically 3 points at the root of the thigh, 3 points at the knee joint, 3 points in the middle of the calf, and 3 points at the ankle joint;

[0016] Step S12: Adopt a 3D optical volume scanner (accuracy ±0.5mm 3 ) to establish a three-dimensional model database of the patient's lower limbs and quantify the change in limb circumference (sensitivity of 0.3cm difference);

[0017] Step S13: Wear a 9-axis IMU sensor (sampling rate 100Hz) at the ankle joint and knee joint of the affected limb to collect the heel strike impact force, the change rate of knee flexion angle, and the ankle dorsiflexion maintenance time in real-time during the gait cycle;

[0018] Step S14: Conduct baseline measurements on the 1st, 3rd, and 7th days after surgery, and then once a week for 3 months to establish an individualized risk evolution curve.

[0019] Furthermore, in the said step S2, the formulas for calculating the difference indices of the affected and healthy sides in the calculation of bio-impedance dynamic parameters are respectively:

[0020] Reflecting the change in extracellular fluid volume, ΔZ > 15% indicates interstitial fluid accumulation;

[0021] Δθ > 2° indicates endothelial cell injury;

[0022] Δfc > 8% corresponds to the pre-fibrotic stage;

[0023] Where ΔZ is the percentage difference in bilateral impedance, Δθ is the phase angle difference, and Δfc is the relative difference in characteristic frequency.

[0024] Furthermore, in step S3, the quantitative analysis of motion characteristics specifically includes the following steps:

[0025] Step S31: Collect daily activity data through an IMU. The collected data are respectively:

[0026] Heel strike impact force: Calculated by double integration of acceleration, and the threshold is set to 2.5 m / s 2 (Exceeding 1.2 times the body weight exacerbates lymphatic vessel injury);

[0027] Knee flexion rate of change: Normally, it should reach 25 - 35° / s. When the rate of change is less than 15° / s, it indicates insufficient muscle pump function;

[0028] Ankle dorsiflexion maintenance time ratio: The average time ratio in healthy people is 45%. When the time ratio is less than 30%, exercise intervention is required;

[0029] Step S32: Extract the characteristics of typical motion patterns through the formula. The formula is:

[0030]

[0031] Where F motion is the comprehensive quantitative index of lower limb motor function, ω1, ω2, ω3 are all weight coefficients, a max is the maximum acceleration of heel strike, α is the knee flexion angle, is the rate of change of knee angle, T dorsiflexion is the ratio of ankle dorsiflexion time.

[0032] Furthermore, in step S4, the construction of the fusion algorithm specifically includes the following steps:

[0033] Step S41: Based on the calculated difference indexes of the affected and healthy sides, construct a risk assessment model based on the impedance-motion feature coupling:

[0034]

[0035] Where CRI is the comprehensive risk index, e is the natural constant, k is the impedance adjustment factor, ΔZ×Δθ / Δfc is the impedance feature coupling term, τ is the motion feature normalization coefficient, and Fmation is the comprehensive value of motion features;

[0036] Step S42: Establish the third-level warning thresholds, specifically as follows:

[0037] Low risk: CRI < 2.3 (sensitivity 85%, specificity 79%);

[0038] Medium risk: 2.3 ≤ CRI < 3.8 (positive likelihood ratio 4.2);

[0039] High risk: CRI ≥ 3.8.

[0040] Furthermore, for the said step S5, the generation of a personalized prevention plan specifically includes the following steps:

[0041] Step S51: Automatically generate intervention parameters according to the CRI value. When the CRI value is at low risk, adjust the pressure of the compression stockings to 15 - 20 mmHg, with intermittent pneumatic compression treatment twice a day; when the CRI value is at medium risk, adjust the pressure of the compression stockings to 20 - 30 mmHg, with intermittent pneumatic compression treatment four times a day; when the CRI value is at high risk, adjust the pressure of the compression stockings to 30 - 40 mmHg, with intermittent pneumatic compression treatment six times a day;

[0042] Step S52: Generate a customized exercise prescription, including:

[0043] S521. Gait correction parameter: Limit the ankle dorsiflexion angle θdorsiflexion ∈ [18°, 25°];

[0044] S522. Exercise intensity control: Dynamically adjust the target heart rate range according to the F motion value. The specific operation steps are as follows:

[0045] S5221: Calculate the maximum heart rate HR max ;

[0046] S5222. Match the F motion coefficient: When F motion <1.2, it is determined as low-intensity exercise, and select a coefficient of 0.4 - 0.5; when 1.2 ≤ F motion <2.0, it is classified as medium-intensity exercise, and select a coefficient of 0.5 - 0.6; when F motion ≥2.0, it is defined as high-intensity exercise, and select a coefficient of 0.6 - 0.7;

[0047] S5223. Calculate the target heart rate: Substitute the selected F motion coefficient into the formula:

[0048] Target heart rate = (HR max - HR rest ) × F motion coefficient + HR rest ;

[0049] Wherein, HR rest is the resting heart rate.

[0050] Furthermore, in step S6, implementing dynamic feedback regulation specifically includes the following steps:

[0051] Step S61, establishing a parameter closed-loop control system: setting the threshold of the weekly change rate of CRI, ΔCRI / Δt ≤ 0.15 / week;

[0052] ΔCRI / Δt > 0.2: Upgrading the treatment plan (such as increasing the pressure level and shortening the re-evaluation period to 3 days);

[0053] ΔCRI / Δt < -0.1: Initiating a dosage reduction program;

[0054] Step S62, adaptive regulation algorithm:

[0055]

[0056] Wherein, P new is the parameter of the new treatment plan, P old is the parameter of the original treatment plan, η is the learning rate, is the change rate of CRI over time, and the sigmoid function is used to smooth the adjustment amplitude.

[0057] The present invention has the following beneficial effects:

[0058] 1. By integrating the frequency-varying characteristics of bioimpedance and kinematic parameters, the present invention constructs a multi-dimensional feature evaluation system, breaking through the limitations of traditional single physiological index detection; the dynamic frequency-domain analysis of bioimpedance can sensitively capture the subtle changes in the composition of extracellular fluid, effectively distinguishing tissue inflammatory reactions from real lymphatic fluid retention; combined with the motion feature quantification model, it can analyze the compensatory state of the muscle pump function, identify the mechanical compensatory mechanism in the subclinical stage, and through the composite risk assessment algorithm, the synergistic effect analysis of bioelectrical characteristics and motor function is realized through non-linear relationship mapping, advancing the detection time window of early lymphatic return decompensation compared with conventional methods, winning crucial time for clinical intervention. This multi-modal data fusion strategy can reduce the misjudgment rate caused by individual physiological differences.

[0059] 2. Through the standardized data acquisition process and the algorithm-driven analysis module, the present invention realizes objective and quantitative risk assessment, reduces the subjective deviation of manual interpretation, and the treatment control interface integrated in the device supports the execution of automated programs, enabling basic intervention measures to be implemented in community medical scenarios. The dynamic feedback mechanism continuously evaluates the intervention effect and intelligently adjusts the subsequent treatment intensity, avoiding the waste of resources caused by ineffective medical behaviors.

[0060] 3. The personalized prevention plan generated by the risk assessment model of the present invention can dynamically adjust the intervention parameters according to the real-time status of the patient. The pressure treatment sets three pressure gradients and combines the intelligent adjustment of the intermittent inflation frequency to ensure the balance between the lymphatic drainage efficiency and tissue tolerance; the exercise prescription limits the dorsiflexion angle of the ankle joint and controls the dynamic heart rate to avoid sports injuries while promoting lymphatic return. The closed-loop feedback system automatically triggers the treatment plan upgrade or reduction program by monitoring the change rate of the risk index, making the intervention intensity match the disease development in real time. This dynamic adjustment mechanism avoids over-treatment or under-treatment of traditional static plans and improves the individualization level and clinical safety of preventive measures.

[0061] Of course, it is not necessary for any product implementing the present invention to achieve all the above-mentioned advantages simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0063] Figure 1 It is a schematic flow chart of a method for preventing lower limb lymphedema after gynecological tumor surgery according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0064] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0065] Please refer to Figure 1 As shown, the present invention is a method for preventing lower limb lymphedema after gynecological tumor surgery, including:

[0066] Step S1. Data acquisition system:

[0067] Step S11: Use a portable high-frequency bioimpedance analyzer (50 kHz - 1 MHz) to symmetrically mark 12 measurement points on both lower limbs; synchronously measure the impedance amplitude Z, phase angle θ, and characteristic frequency fc of the affected side and the healthy side.

[0068] The 12 measurement points are specifically 3 points at the root of the thigh, 3 points at the knee joint, 3 points in the middle of the calf, and 3 points at the ankle joint.

[0069] Step S12: Use a 3D optical volume scanner (accuracy ±0.5 mm 3 ) to establish a three-dimensional model database of the patient's lower limb and quantify the change in limb circumference (sensitivity of 0.3 cm difference);

[0070] Step S13: Wear 9-axis IMU sensors (sampling rate 100 Hz) at the ankle joint and knee joint of the affected limb to collect the heel strike impact force, the change rate of knee joint flexion angle, and the ankle dorsiflexion maintenance time during the gait cycle in real time;

[0071] Step S14: Perform baseline measurements on the 1st, 3rd, and 7th days after surgery, and then once a week for 3 months to establish an individualized risk evolution curve;

[0072] Step S2: Calculation of dynamic bioimpedance parameters: Calculate the difference index between the affected and healthy sides through the resistance amplitude, phase angle, and characteristic frequency of the bioimpedance measurement points collected, and quantify the dynamic balance state of tissue fluid:

[0073] Reflecting the change in extracellular fluid volume, ΔZ>15% indicates interstitial fluid accumulation;

[0074] Δθ>2° indicates endothelial cell damage;

[0075] Δfc>8% corresponds to the pre-fibrotic stage;

[0076] In the formula, ΔZ is the percentage difference in bilateral impedance, Δθ is the phase angle difference, and Δfc is the relative difference in characteristic frequency;

[0077] Step S3: Quantitative analysis of motion characteristics:

[0078] Step S31: Collect daily activity data through IMU. The collected data are respectively:

[0079] Heel strike impact force: Calculated by double integration of acceleration, and the threshold is set at 2.5 m / s 2 (exceeding 1.2 times the body weight exacerbates lymphatic vessel injury);

[0080] Knee flexion change rate: It should reach 25 - 35 o / s normally. When the change rate is less than 15 o / s, it indicates insufficient muscle pump function;

[0081] Ankle dorsiflexion maintenance time ratio: The average time ratio in healthy people is 45%. When the time ratio is less than 30%, exercise intervention is required;

[0082] Step S32: Extract the characteristics of typical motion patterns through the formula. The formula is:

[0083]

[0084] In the formula, F motion is a comprehensive quantitative index of lower limb motor function, ω1, ω2, ω3 are all weight coefficients, a max is the maximum acceleration of heel contact with the ground, α is the knee flexion angle, is the knee joint angle change rate, T dorsiflexion is the proportion of ankle dorsiflexion time;

[0085] Step S4, Fusion algorithm construction:

[0086] Step S41: Based on the calculated difference indexes of the affected and healthy sides, construct a risk assessment model based on impedance-motion feature coupling:

[0087]

[0088] In the formula, CRI is the comprehensive risk index, e is the natural constant, k is the impedance adjustment factor, ΔZ×Δθ / Δfc is the impedance feature coupling term, τ is the motion feature normalization coefficient, Fmation is the comprehensive value of motion features;

[0089] Step S42: Establish a three-level warning threshold, specifically:

[0090] Low risk: CRI < 2.3 (sensitivity 85%, specificity 79%);

[0091] Medium risk: 2.3 ≤ CRI < 3.8 (positive likelihood ratio 4.2);

[0092] High risk: CRI ≥ 3.8;

[0093] Step S5, Generation of personalized prevention plan:

[0094] Step S51: Automatically generate intervention parameters according to the CRI value. When the CRI value is at low risk, adjust the pressure of the compression stockings to 15 - 20 mmHg, and perform intermittent pneumatic compression therapy 2 times a day; when the CRI value is at medium risk, adjust the pressure of the compression stockings to 20 - 30 mmHg, and perform intermittent pneumatic compression therapy 4 times a day; when the CRI value is at high risk, adjust the pressure of the compression stockings to 30 - 40 mmHg, and perform intermittent pneumatic compression therapy 6 times a day;

[0095] Step S52: Generate a customized exercise prescription, including:

[0096] S521. Gait correction parameters: Limit the ankle dorsiflexion angle θdorsiflexion ∈ [18°, 25°];

[0097] S522. Exercise intensity control: Dynamically adjust the target heart rate range according to the F motion value. The specific operation steps are as follows:

[0098] S5221: Calculate the maximum heart rate HR through the Gellish formula max ;

[0099] S5222. Match the F motion Coefficient: When F motion < 1.2, it is determined as low-intensity exercise, and the coefficient 0.4 - 0.5 is selected; when 1.2 ≤ F motion < 2.0, it is classified as medium-intensity exercise, and the coefficient 0.5 - 0.6 is selected; when F motion ≥ 2.0, it is defined as high-intensity exercise, and the coefficient 0.6 - 0.7 is selected;

[0100] S5223. Calculate the target heart rate: Substitute the selected F motion Coefficient into the formula:

[0101] Target heart rate = (HR max - HR rest ) × F motion Coefficient + HR rest ;

[0102] In the formula, HR rest is the resting heart rate;

[0103] Step S6. Implement dynamic feedback regulation:

[0104] Step S61. Establish a parameter closed-loop control system: Set the CRI weekly change rate threshold ΔCRI / Δt ≤ 0.15 / week;

[0105] ΔCRI / Δt > 0.2: Upgrade the treatment plan (such as increasing the pressure level and shortening the re-evaluation period to 3 days);

[0106] ΔCRI / Δt < -0.1: Initiate the dose reduction program;

[0107] Step S62. Adaptive adjustment algorithm:

[0108]

[0109] In the formula, P new is the parameter of the new treatment plan, P old is the parameter of the original treatment plan, η is the learning rate, is the CRI change rate over time, and the sigmoid function is used to smooth the adjustment amplitude.

[0110] A specific application of this embodiment is:

[0111] Patient information: The patient is a 52-year-old female who underwent radical hysterectomy for endometrial cancer (including bilateral pelvic lymph node dissection), and the monitoring process was initiated on the first day after the operation.

[0112] Step S1. Implementation of multi-dimensional data collection:

[0113] Use a BioScan-LF high-frequency bioimpedance analyzer to attach electrodes to the patient's bilateral lower limbs at standard anatomical sites:

[0114] At the root of the thigh: 10 cm below the anterior superior iliac spine, 2 cm lateral to the femoral artery pulsation point, and 5 cm medial to the greater trochanter;

[0115] At the knee joint: 5 cm above the upper edge of the patella, the midpoint of the patella, and 3 cm medial to the head of the fibula;

[0116] In the middle of the lower leg: 15 cm below the tibial tuberosity, the highest point of the soleus muscle belly, and 8 cm above the Achilles tendon;

[0117] At the ankle joint: the tip of the medial malleolus, the tip of the lateral malleolus, and the dorsalis pedis artery pulsation point;

[0118] Use a VoluSense3DPro scanner (resolution 0.2 mm) to construct a three-dimensional model of the patient's lower limbs, and mark key anatomical structures such as the great saphenous vein walking area and the popliteal fossa lymph-rich area. The initial scan data shows that the volume of the right lower limb is 4820 mL, and the volume of the left lower limb is 4795 mL (the difference < 0.5%);

[0119] Wear an I Motion-S2 inertial sensor on the knee joint and ankle joint of the right lower limb (the surgical side), and set the monitoring period from 8:00 to 20:00 every day;

[0120] Step 2. Dynamic bioimpedance analysis:

[0121] Table 1: Measurement data on the first day after surgery

[0122]

[0123] Step 3. Extraction of motion characteristics:

[0124] Collect typical gait data on the third day after surgery:

[0125] Peak value of heel strike impact force: right limb 1.8 g vs left limb 2.1 g (decrease of 14.3%);

[0126] Rate of change of knee flexion angle: right limb 15° / s vs left limb 22° / s;

[0127] Percentage of ankle dorsiflexion maintenance time: right limb 31% vs left limb 42%;

[0128] Substitute into the motion characteristic formula:

[0129] F motion = 0.4×1.8 + 0.3×∫15dt + 0.3×3100

[0130] = 0.72 + 4.5 + 9.3

[0131] = 14.52;

[0132] Step 4, Fusion algorithm construction:

[0133] Calculate the composite risk index:

[0134]

[0135] Evaluation result: CRI = 1.32 < 2.3 → Low risk level;

[0136] Step 5, Implementation of personalized prevention plan:

[0137] Hardware intervention parameters: Compression stockings: Select Med i-20 type gradient compression stockings (20 mmHg at the ankle, 15 mmHg at the knee);

[0138] Inflatable treatment: Twice a day, 20 minutes each time (Pressure waveform: Rise to 50 mmHg in 12 s, maintain for 8 s, decompress in 2 s);

[0139] Exercise prescription:

[0140] Gait training: Limit the right ankle dorsiflexion angle to 20° ± 2°;

[0141] Heart rate control: The target heart rate range is set to (220 - 52) × 50% - 60% = 84 - 101 bpm;

[0142] Step 6, Dynamic feedback regulation:

[0143] Monitoring data in the 7th week after surgery:

[0144] The CRI value rises to 2.95 (ΔCRI / Δt = 0.21 / week > 0.2 threshold);

[0145] The system triggers a plan upgrade:

[0146] P new = P old × (1 + 0.15 × sigmoid(0.21))

[0147] = P old × (1 + 0.15 × 0.552)

[0148] = P old × 1.083;

[0149] Specific adjustments: Upgrade the compression stockings to 25 - 30 mmHg medical grade; Increase the inflatable treatment to 4 times a day; Increase the massage intensity to 0.35 N / cm 2;

[0150] Implementation effect:

[0151] Follow-up after 3 months of surgery showed that: the volume of the right lower limb was 4895 mL vs 4810 mL for the left lower limb (difference 1.76%); the CRI value was stable in the range of 2.1 - 2.5; no typical signs of lymphedema such as skin fibrosis occurred.

[0152] In the description of this specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in connection with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0153] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not elaborate all the details, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A method for preventing lower limb lymphedema after gynecological tumor surgery, characterized in that, The prevention method includes the following steps: Step S1, data acquisition system: Deploy a portable high-frequency bioimpedance meter, a 3D optical volume scanner, integrate wearable inertial sensors, set the postoperative monitoring period, collect the physiological and motion data of the patient's bilateral lower limbs, and construct a data baseline; Step S2, calculation of bioimpedance dynamic parameters: Calculate the difference index between the affected and healthy sides through the resistance impedance amplitude, phase angle, and characteristic frequency of the bioimpedance measurement points obtained by collection, and quantify the dynamic balance state of tissue fluid; Step S3, quantitative analysis of motion characteristics: Collect daily activity data through inertial sensors, extract the characteristics of typical motion patterns, quantify the impact of daily activities on lymphatic return, and evaluate the efficiency of mechanical lymphatic return; Step S4, construction of fusion algorithm: Construct a risk assessment model based on the coupling of impedance-motion characteristics, establish a three-level warning threshold, and realize the non-linear fusion of multi-modal data; Step S5, generation of personalized prevention plan: Automatically generate intervention parameters according to the risk assessment value, including the pressure sock grade and the intermittent pneumatic compression treatment frequency, generate a customized exercise prescription, and realize gradient intervention; Step S6, implementation of dynamic feedback regulation: Establish a parameter closed-loop control system, design an adaptive regulation algorithm, adjust the prevention plan according to the change rate of the risk assessment value, and construct an adaptive treatment system.

2. The preventive method for lower limb lymphedema after gynecological tumor surgery according to claim 1, characterized in that, In step S1, the data acquisition system specifically includes the following steps: Step S11: Use a portable high-frequency bioimpedance meter to symmetrically mark 12 measurement points on the bilateral lower limbs; synchronously measure the resistance impedance amplitude Z, phase angle θ, and characteristic frequency fc of the affected and healthy sides; The specific 12 measurement points are 3 points at the root of the thigh, 3 points at the knee joint, 3 points in the middle of the calf, and 3 points at the ankle joint; Step S12: Use a 3D optical volume scanner to establish a three-dimensional model database of the patient's lower limbs and quantify the change in limb circumference; Step S13: Wear 9-axis IMU sensors at the ankle joint and knee joint of the affected limb to collect the heel strike impact force, the change rate of knee joint flexion angle, and the ankle dorsiflexion maintenance time during the gait cycle in real time; Step S14: Perform baseline measurements on the 1st, 3rd, and 7th days after surgery, and then once a week for 3 months to establish an individualized risk evolution curve.

3. A method for preventing lower limb lymphedema after gynecological tumor surgery according to claim 1, characterized in that, In step S2, the formulas for calculating the difference indexes of the affected and healthy sides in the calculation of bioimpedance dynamic parameters are respectively: In the formula, ΔZ is the bilateral impedance difference percentage, Δθ is the phase angle difference, and Δfc is the relative difference in characteristic frequency.

4. A method for preventing lower limb lymphedema after gynecological tumor surgery according to claim 1, characterized in that, In step S3, the quantitative analysis of motion characteristics specifically includes the following steps: Step S31: Collect daily activity data through IMU, and the collected data are respectively: Heel strike impact force: Calculated by double integration of acceleration, with the threshold set at 2.5 m / s 2 ; Knee joint flexion change rate: It normally needs to reach 25-35o / s. When the change rate is less than 15o / s, it indicates insufficient muscle pump function; Percentage of ankle dorsiflexion maintenance time: The average time percentage of healthy people is 45%. When the time percentage is less than 30%, exercise intervention is required; Step S32: Extract the characteristics of typical motion patterns through the formula. The formula is: where F motion is the comprehensive quantitative index of lower limb motor function, ω1, ω2, ω3 are all weight coefficients, and a max is the maximum acceleration at heel contact, α is the knee flexion angle, is the knee angle change rate, and T dorsiflexion is the proportion of ankle dorsiflexion time.

5. A method for preventing lower limb lymphedema after gynecological tumor surgery according to claim 1, characterized in that, In step S4, the construction of the fusion algorithm specifically includes the following steps: Step S41: Based on the calculated difference indexes of the affected and healthy sides, construct a risk assessment model based on the coupling of impedance-motion characteristics: where CRI is the comprehensive risk index, e is the natural constant, k is the impedance adjustment factor, ΔZ×Δθ / Δfc is the impedance characteristic coupling term, τ is the motion characteristic normalization coefficient, and F mation is the comprehensive value of motion characteristics; Step S42: Establish the three - level early warning thresholds, specifically as follows: Low risk: CRI < 2.3; Medium risk: 2.3 ≤ CRI < 3.8; High risk: CRI ≥ 3.

8.

6. A method for preventing lower limb lymphedema after gynecological tumor surgery according to claim 1, characterized in that, In step S5, the generation of the personalized prevention plan specifically includes the following steps: Step S51: Automatically generate intervention parameters according to the CRI value. When the CRI value is at low risk, the pressure of the compression stockings is adjusted to 15 - 20 mmHg, and intermittent pneumatic compression therapy is performed 2 times a day; when the CRI value is at medium risk, the pressure of the compression stockings is adjusted to 20 - 30 mmHg, and intermittent pneumatic compression therapy is performed 4 times a day; when the CRI value is at high risk, the pressure of the compression stockings is adjusted to 30 - 40 mmHg, and intermittent pneumatic compression therapy is performed 6 times a day; Step S52: Generate a customized exercise prescription, including: S521. Gait correction parameter: Defining the ankle dorsiflexion angle θ dorsiflexion ∈ [18°, 25°]; S522. Exercise intensity control: Dynamically adjust the target heart rate range according to the F motion value. The specific operation steps are as follows: S5221: Calculate the maximum heart rate HR through the Gellish formula max ; S5222, Matching F motion Coefficient: When F motion < 1.2, it is determined as low-intensity exercise, and the coefficient 0.4 - 0.5 is selected; when 1.2 ≤ F motion < 2.0, it is classified as medium-intensity exercise, and the coefficient 0.5 - 0.6 is selected; when F motion ≥ 2.0, it is defined as high-intensity exercise, and the coefficient 0.6 - 0.7 is selected; S5223. Calculate the target heart rate: Substitute the selected F motion coefficient into the formula: Target heart rate = (HR max - HR rest ) × F motion Coefficient + HR rest ; where HR rest is the resting heart rate.

7. A method for preventing lower limb lymphedema after gynecological tumor surgery according to claim 1, characterized in that, In step S6, the implementation of dynamic feedback regulation specifically includes the following steps: Step S61: Establish a parameter closed - loop control system: Set the CRI weekly change rate threshold ΔCRI / Δt ≤ 0.15 / week; ΔCRI / Δt > 0.2: Upgrade the treatment plan; ΔCRI / Δt < - 0.1: Initiate the dose - reduction program; Step S62: Adaptive adjustment algorithm where, P new is the parameter of the new treatment plan, P old is the parameter of the original treatment plan, η is the learning rate, is the change rate of CRI over time, and the sigmoid function is used to smoothly adjust the amplitude.

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