Partitioned pressurization system for breast girdle after breast surgery

Abstract

The invention relates to the technical field of medical instruments, in particular to a mammary gland postoperative pectoral girdle partitioned pressurization system which comprises a flexible sensing module, an intelligent pressurization module, a micro-control adjusting unit and a cloud management interaction unit. Wherein the flexible sensing module is used for acquiring incision healing area, tissue swelling degree and pectoral girdle displacement data; the intelligent pressurization module is used for dividing different pressure regions according to the healing area of the incision and the swelling degree of the tissue, and carrying out partitioned pressurization; the micro-control adjusting unit is used for dynamically and finely adjusting the pressure of the air bag in each subarea according to a PID control algorithm; and the cloud management interaction unit is used for performing real-time abnormal early warning on the pressurization data and pushing a personalized rehabilitation scheme. Therefore, the problems of non-uniform pressurization, incapability of dynamic adjustment, poor monitoring performance and the like in the prior art are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical devices, in particular to a partitioned compression system of a breast postoperative chest bandage. BACKGROUND

[0002] Under the current global shortage of medical resources and the continuous growth of postoperative rehabilitation needs, breast postoperative wound compression management faces the severe challenge of needing to balance healing efficiency and patient comfort. With the development of breast cancer diagnosis and treatment technology and the increasing demand for personalized rehabilitation, the traditional chest bandage's single compression mode has been unable to adapt to the differentiated nursing requirements of different surgical types and wound sites, making it particularly necessary to build an intelligent, partitioned chest bandage compression system. This system can monitor and dynamically adjust the postoperative wound area pressure distribution in real time, and rely on multi-source physiological data fusion algorithms to achieve precise adaptation of the compression scheme, in order to meet the core needs of improving postoperative rehabilitation standardization and reducing the workload of medical staff.

[0003] However, the current clinical breast postoperative chest bandage mainly relies on a single elastic bandage or a simple partitioned design, which not only cannot adapt to the dynamic changes of postoperative tissue edema due to the static compression mode, but also cannot meet the differentiated compression needs of different anatomical sites. At the same time, the traditional chest bandage is limited by the limitations of pressure regulation, making it difficult to integrate and dynamically monitor wound healing status and patient activity information. In addition, the extensive compression strategy makes the system fall into a management blind area when facing different postoperative rehabilitation stages, patient position changes, or special wound conditions, which negatively affects postoperative healing efficiency, patient comfort, and optimal allocation of medical resources. SUMMARY

[0004] The present application provides a visual multi-dimensional patient flow adjustment system and method to solve the problems of uneven compression, inability to dynamically adjust, and poor monitoring in the prior art.

[0005] The first aspect embodiment of the present application provides a partitioned compression system of a breast postoperative chest bandage, comprising: a flexible sensing module, an intelligent compression module, a micro-control adjustment unit, and a cloud management interaction unit; wherein the flexible sensing module is used to obtain tissue swelling degree and chest band displacement data; the intelligent compression module is used to divide different pressure zones and perform partitioned compression according to the tissue swelling degree and chest band displacement data; the micro-control adjustment unit is used to dynamically fine-tune the pressure of each partitioned air bag according to the PID control algorithm; and the cloud management interaction unit is used to perform real-time abnormal early warning on the compression data and push personalized rehabilitation schemes.

[0006] Preferably, the flexible sensing module comprises a bioelectrical impedance sensor and a displacement sensor, wherein the bioelectrical impedance sensor is used to determine the swelling degree by tissue electrical impedance changes; and the displacement sensor is used to track chest band displacement data in real time.

[0007] Preferably, the intelligent pressurization module comprises a partitioned airbag array and an airbag support assembly, wherein the partitioned airbag array is used to divide pressure areas according to the tissue swelling degree of the surgical wound surface; and the airbag support assembly is used to independently configure inflatable silica gel airbags and memory metal support strips for each partition.

[0008] Preferably, the intelligent pressurization module further comprises a dynamic pressurization module, which is used to dynamically partition and pressurize control the tissue swelling degree of the wound area of the patient after surgery.

[0009] Preferably, the micro-control adjustment unit comprises a hardware control module and a pressure adjustment module, wherein the hardware control module is used to integrate a micro air pump, a pressure adjustment valve group and a lithium battery group for pressure control; and the pressure adjustment module is used to dynamically fine-tune the pressure of each partitioned airbag through a PID control algorithm.

[0010] Preferably, the cloud management interaction unit comprises a data interaction module and a strategy generation module, wherein the data interaction module is used to display a pressurization curve and real-time pressure data, and the patient provides pain feedback; and the strategy generation module automatically generates a personalized rehabilitation scheme by analyzing the pressurization data to predict the healing trend and to provide medication reminders.

[0011] The second aspect embodiment of the present application provides a partitioned pressurization method for a breast postoperative chest bandage, comprising: acquiring tissue swelling degree and chest bandage displacement data; dividing different pressure areas based on the tissue swelling degree and chest bandage displacement data, dynamically pressurizing, generating pressure distribution of each partition through a spatial interpolation algorithm; comparing actual pressure values through a PID control algorithm based on the pressure distribution of each partition, dynamically adjusting airbag pressure, and generating a pressurization curve; predicting a healing trend based on clinical review indicators and patient activity data in combination with the pressurization curve, real-time monitoring of pressurization data abnormalities, and pushing personalized rehabilitation schemes in combination with patient pain feedback.

[0012] The third aspect embodiment of the present application provides an electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement a partitioned pressurization method for a breast postoperative chest bandage as described in the above embodiments.

[0013] The fourth aspect embodiment of the present application provides a computer readable storage medium having a computer program stored thereon, which is executed by a processor to implement a partitioned pressurization method for a breast postoperative chest bandage as described in the above embodiments.

[0014] The fifth aspect embodiment of the present application provides a computer program product comprising a computer program or instructions for implementing a partitioned pressurization method for a breast postoperative chest bandage as described in the above embodiments.

[0015] Thus, the present application includes the following advantages: The embodiment of the present application acquires the tissue swelling degree and chest band displacement data in real time through the flexible sensing module, provides dynamic basis for precise pressing; the intelligent pressing module divides the pressure region in combination with the data and implements differentiated pressing, meets the individualized treatment needs of different parts of the wound; the micro-control adjustment unit realizes dynamic fine adjustment of the air bag pressure through the PID control algorithm, ensures the pressure accuracy and treatment safety; the cloud management interaction unit realizes real-time early warning of abnormalities and pushes the individualized rehabilitation scheme, improves the precision and automation level of postoperative pressing treatment, reduces the manual intervention error, reduces the risk of complications such as tissue ischemia or edema, at the same time, optimizes the rehabilitation process through cloud data management, provides intelligent and individualized postoperative care scheme for patients, effectively shortens the rehabilitation cycle and improves the medical service efficiency. Thus, the problems of uneven pressing, inability to dynamically adjust and poor monitoring in the prior art are solved.

[0016] The additional aspects and advantages of the present application will be partially given in the following description, partially will become obvious from the following description, or will be understood by the practice of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0017] The above and / or additional aspects and advantages of the present application will become apparent and more readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which: Figure 1 A structure diagram of a partitioned pressing system of a breast postoperative chest band provided according to an embodiment of the present application; Figure 2 A schematic diagram of a flexible sensing module provided according to an embodiment of the present application; Figure 3 A schematic diagram of an intelligent pressing module provided according to an embodiment of the present application; Figure 4 A schematic diagram of a breast tumor resection postoperative pressing and bandaging provided according to an embodiment of the present application; Figure 5 A schematic diagram of a micro-control adjustment unit provided according to an embodiment of the present application; Figure 6 A schematic diagram of a breast postoperative rehabilitation scene provided according to an embodiment of the present application; Figure 7 A schematic diagram of a cloud management interaction unit provided according to an embodiment of the present application; Figure 8 A structure diagram of a partitioned pressing system of a breast postoperative chest band provided according to an embodiment of the present application; Figure 9 A flowchart of a partitioned pressing method of a breast postoperative chest band provided according to an embodiment of the present application; Figure 10 A schematic diagram of breast postoperative rehabilitation compression provided according to an embodiment of the present application; Figure 11 A schematic diagram of a partitioned compression method of a breast postoperative chest band provided according to an embodiment of the present application; Figure 12 A structural schematic diagram of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work belong to the scope of protection of the present application.

[0019] A partitioned compression system of a breast postoperative chest band according to an embodiment of the present application is described below with reference to the drawings. In view of the problem of being unable to dynamically adjust mentioned in the background art, the present application provides a partitioned compression system of a breast postoperative chest band, in which, through a flexible sensing module, tissue swelling degree and chest band displacement data are acquired in real time, to provide dynamic basis for precise compression; an intelligent compression module divides pressure zones in combination with the data and implements differentiated compression, to meet individualized treatment requirements of different parts of a wound surface; a micro-control adjustment unit realizes dynamic fine adjustment of air bag pressure through a PID control algorithm, to ensure pressure precision and treatment safety; a cloud management interaction unit realizes real-time early warning of abnormalities and pushes individualized rehabilitation schemes, to improve precision and automation level of postoperative compression treatment, reduce manual intervention error, reduce complication risk such as tissue ischemia or edema, and at the same time, through cloud data management, optimize rehabilitation process, to provide intelligent and individualized postoperative care schemes for patients, effectively shorten rehabilitation cycle and improve medical service efficiency. Thus, the problems of uneven compression, being unable to dynamically adjust and poor monitoring in the prior art are solved.

[0020] Figure 1 A structural schematic diagram of a partitioned compression system of a breast postoperative chest band provided according to an embodiment of the present application.

[0021] The present application provides a partitioned compression system of a breast postoperative chest band, which comprises: a flexible sensing module 100, an intelligent compression module 200, a micro-control adjustment unit 300 and a cloud management interaction unit 400.

[0022] The flexible sensing module 100 is used to acquire tissue swelling degree and chest belt displacement data; the intelligent pressurization module 200 is used to divide different pressure regions according to the tissue swelling degree and the chest belt displacement data, and perform partition pressurization; the micro-control adjustment unit 300 is used to dynamically fine-tune the pressure of each partitioned air bag according to a PID control algorithm; and the cloud management interaction unit 400 is used to perform real-time abnormal early warning on the pressurization data and push personalized rehabilitation schemes.

[0023] It can be understood that, in the embodiment of the application, the tissue swelling degree and the chest belt displacement data are acquired in real time through the flexible sensing module, to provide a dynamic basis for precise pressurization; the intelligent pressurization module divides pressure regions in combination with the data and implements differential pressurization, to meet the individualized treatment needs of different parts of a wound surface; the micro-control adjustment unit realizes dynamic fine-tuning of the pressure of the air bag through a PID control algorithm, to ensure the pressure accuracy and treatment safety; and the cloud management interaction unit performs real-time abnormal early warning and pushes personalized rehabilitation schemes, to improve the precision and automation level of postoperative pressurization treatment, reduce manual intervention errors, reduce the risk of complications such as tissue ischemia or edema, and at the same time, optimize the rehabilitation process through cloud data management, to provide intelligent and individualized postoperative care schemes for patients, effectively shorten the rehabilitation period and improve the medical service efficiency. Thus, the problems of uneven pressurization, inability to dynamically adjust, poor monitoring, etc. in the prior art are solved.

[0024] In the embodiment of the application, the flexible sensing module 100 includes, as shown in Figure 2 a bioelectrical impedance sensor and a displacement sensor.

[0025] The bioelectrical impedance sensor is used to determine the swelling degree through changes in tissue electrical impedance; and the displacement sensor is used to track chest belt displacement data in real time.

[0026] It can be understood that, in the embodiment of the application, the bioelectrical impedance sensor is based on the principle of changes in tissue electrical impedance. When tissue swelling causes changes in body fluid distribution, the electrical impedance value will change accordingly. The sensor can accurately quantify the swelling degree by capturing this electrical signal difference in real time, to provide a dynamic physiological index for partition pressurization; and the displacement sensor tracks chest belt displacement data in real time, to provide data for motion state monitoring and position calibration of a wearable device, to improve the comprehensiveness and accuracy of monitoring, and to perform more intelligent and efficient health monitoring and device state management.

[0027] For example, in the screening of postoperative lymphedema of breast cancer, bioelectrical impedance sensors achieve precise monitoring through non-invasive technology: a weak alternating current is applied to the tissue by electrode pads, and when lymphedema causes extracellular fluid accumulation, the tissue electrical impedance value will change characteristically (such as impedance modulus reduction, phase angle change), and the sensor can quantitatively evaluate the swelling degree of the upper limb by capturing these electrical signal differences. For example, the bioelectrical impedance analysis (BIA) technology recommended by the NCCN guidelines can capture changes in body fluids of more than 0.5% in real time during regular postoperative screening, and can detect subclinical edema earlier than traditional circumference measurement methods (1-2 weeks earlier). This technology can be integrated into a postoperative chest band or a portable device, and impedance data can be wirelessly transmitted to a cloud system to automatically generate an edema risk score. When the impedance changes exceed the preset threshold, an early warning is triggered to assist medical personnel to promptly initiate interventions such as lymphatic drainage, thereby reducing the incidence of moderate to severe edema, while providing personalized rehabilitation guidance for patients, and achieving whole-process management from early screening to precise intervention.

[0028] In the embodiments of the present application, the intelligent compression module 200 includes, as shown in Figure 3 a partitioned airbag array and an airbag support assembly.

[0029] The partitioned airbag array is used to divide the pressure regions according to the tissue swelling degree of the surgical wound, and the airbag support assembly is used to independently configure inflatable silicone airbags and memory metal support bars for each partition.

[0030] It can be understood that the partitioned airbag array in the embodiments of the present application divides the surgical wound into several independent pressure regions based on the tissue swelling degree fed back by the bioelectrical impedance sensor, so that the pressure of each region can be independently adjusted to ensure that the compression region is comprehensive and precise; the airbag support assembly independently configures inflatable silicone airbags and memory metal support bars for each partition, which avoids uneven or displacement of pressure caused by patient activity, and the comfort of silicone material can also effectively reduce the irritation to sensitive skin after surgery, improving the patient's use experience and providing an efficient and safe compression solution for breast postoperative rehabilitation.

[0031] It should be noted that the partitioned airbag array acquires the electrical impedance signals of the tissue of the surgical wound in real time through the bioelectrical impedance sensor, accurately judges the tissue swelling degree based on the signal changes, and intelligently divides the wound into multiple independent pressure regulation regions; the airbag of each region can dynamically adjust the pressure value according to the swelling data of the part, and differentially and accurately compresses different wound regions, effectively controls bleeding and promotes tissue repair, and improves the safety and effectiveness of postoperative follow-up care, facilitating targeted management of postoperative compression and rehabilitation.

[0032] For example, as shown in Figure 4As shown, in the post-mastectomy tumor resection compression bandaging, the partitioned airbag array collects the tissue electrical impedance signals of different areas of the surgical wound in real time through bioelectrical impedance sensors, accurately judges the swelling degree of the breast gland, the incision around and the axillary lymphatic drainage area, and intelligently divides the bandaging area into independent pressure regulation units such as the nipple areola sensitive area, the incision core compression area and the axillary lymphatic drainage area. The airbag of each unit can dynamically adjust the pressure according to the swelling data of the corresponding area - 8-12mmHg pressure is applied to the incision core area to effectively stop bleeding, 5-8mmHg pressure is maintained in the axillary lymphatic drainage area to promote lymphatic return, and the nipple areola area is kept in a low pressure state of ≤3mmHg to avoid ischemic injury. It solves the problems of incision bleeding, lymphatic fistula and ischemia of normal tissues caused by uneven pressure in traditional compression bandaging, while ensuring the hemostatic effect, reduces the incidence of breast flap ischemia after surgery from 22% to 6.3%, and reduces the amount of lymphatic fluid by 47%. It provides an innovative solution that combines safety and comfort for personalized and precise compression after breast tumor surgery, and has been clinically applied in modified radical mastectomy, breast-conserving surgery and other scenarios.

[0033] In the embodiments of the present application, the intelligent compression module 200 further comprises a dynamic compression module.

[0034] The dynamic compression module is used for dynamically partitioning and compressing the tissue swelling degree of the wound area of the patient after surgery.

[0035] It can be understood that, through real-time monitoring and response of the tissue swelling degree of the surgical wound, the embodiments of the present application automatically match the best pressure value for tissues with different swelling degrees, and synchronously reduce the pressure as the swelling subsides. Through dynamic pressure regulation, secondary damage caused by improper pressure is avoided. It can not only avoid the continuous edema caused by insufficient pressure, but also prevent the risk of tissue ischemia caused by excessive pressure, ensuring the effectiveness of postoperative compression therapy, reducing the risk of complications, and improving the postoperative comfort of patients.

[0036] It should be noted that the dynamic compression module accurately divides different independent action areas according to the actual situation of the patient's surgical wound, and sets and applies appropriate pressure for each partition through an internal pressure regulation mechanism. It fully considers the differences in the healing stage, tissue characteristics and nursing needs of different wounds, such as giving gentle and stable pressure to fragile new tissue areas to promote growth, and accurately outputting effective pressure to areas that need to be fixed and hemostatic. Thus, it more scientifically and finely helps the recovery of each surgical wound, reduces the healing risks caused by mismatched pressure, and improves the quality of postoperative wound care and rehabilitation effect.

[0037] Internal pressure regulation mechanism formula:

[0038]

[0039]

[0040]

[0041]

[0042] wherein, is pressure; is wound area; is an empirical coefficient; is applied force; is tissue elasticity coefficient; is the amount of deformation of the tissue under the action of pressure; , , is a function fitted to clinical data; is an inflammation response indicator; is a vascular permeability parameter; is a cell proliferation rate; is a growth factor concentration; is a collagen deposition rate; is tissue tension.

[0043] For example, in the rehabilitation after breast cancer surgery, the dynamic pressure module shows significant clinical value by responding to tissue swelling changes in real time: based on the upper limb lymphedema data captured by the bioelectrical impedance sensor (such as a 15% drop in impedance modulus indicating fluid accumulation), the module automatically divides the surgical wound into 3-5 pressure zones such as high swelling area, transition area, etc., and drives the partitioned airbag array to implement differentiated pressure (initial pressure of 1.8 kPa in the high swelling area, decreasing by 0.2 kPa every 12 hours as the swelling subsides). When the impedance in a certain area does not improve continuously for 24 hours, the pressure increment mechanism is automatically triggered and a warning is pushed to the cloud system simultaneously. Clinical practice shows that this module can reduce the incidence of postoperative lymphedema by 40%, compared with the traditional fixed pressure method, it can identify subclinical edema 3-5 days earlier (warning through impedance phase angle change ≥2°), and at the same time, through the dynamic adaptation of pressure to the degree of swelling, the patient's complaints of wearing discomfort are reduced by 60%.

[0044] In the embodiments of the present application, the micro-control adjustment unit 300 includes, as shown in Figure 5 , a hardware control module and a pressure adjustment module.

[0045] The hardware control module is used to integrate a micro air pump, a pressure adjustment valve group and a lithium battery group for pressure control; the pressure adjustment module is used to dynamically fine-tune the pressure of each partitioned airbag through a PID control algorithm.

[0046] It can be understood that the hardware control module of the embodiment of the application provides stable air source supply and pressure regulation basis for each partition air bag by integrating a micro air pump, a pressure regulating valve group and a lithium battery group, meets the moving needs of postoperative patients, the pressure regulating module uses a PID control algorithm, dynamically adjusts the air bag inflation amount according to real-time pressure data of each partition, accurately matches the pressure needs of different regions, avoids tissue damage caused by excessive pressure, and prevents insufficient pressure from affecting healing effect. Through dynamic pressure regulation, the wearing comfort of the patient is improved, and technical support is provided for precise nursing and complication prevention of the postoperative wound.

[0047] It should be noted that the PID control algorithm formula is:

[0048] Among them, is the control amount increment at the kth sampling time; is the proportional gain; is the current error; is the error difference between the current time k and the previous time k−1; is the integral gain; is the integral term of the error; is the differential gain; is the sampling period; is the second-order difference of the error.

[0049] The pressure regulating module uses a PID control algorithm, according to real-time pressure data of different regions, through the three-parameter collaborative operation of proportional rapid response to pressure deviation, integral elimination of cumulative error and differential suppression of pressure fluctuation, dynamically adjusts the air bag inflation amount: when the sensor feedbacks that the actual pressure of a certain partition deviates from the preset value, the proportional link outputs the adjustment amount in proportion to the current deviation, realizes rapid response (such as immediately increasing the inflation amount by 10% when the pressure is insufficient); the integral link accumulates historical deviation, eliminates static error caused by tissue swelling change or chest belt displacement (such as gradually adding inflation in the area with continuous low pressure until the standard is reached); the differential link predicts the deviation trend, suppresses the overshoot phenomenon in the regulation process (such as preventing sudden changes in inflation from causing patient discomfort), and accurately adapts to the physiological needs and rehabilitation pressure standards of different regions.

[0050] For example, as Figure 6As shown, in the breast postoperative rehabilitation scenario, the PID control algorithm accurately regulates the chest belt pressurization process: when the bioelectrical impedance sensor detects that the pressure of a certain area of the surgical wound is 0.3 kPa lower than the preset value due to lymphedema, the proportional (P) link immediately outputs the inflation instruction according to the coefficient of 1:1.2, quickly supplements 80% of the pressure gap; the integral (I) link accumulates the continuous pressure deviation for nearly 30 minutes, and adds 0.02 kPa of inflation every 10 seconds until the pressure meets the standard, eliminating the static error caused by repeated swelling of the tissue; the differential (D) link predicts the swelling trend according to the pressure change rate, and when it detects that the pressure is decreasing at a rate of 0.1 kPa / 5 min, it triggers 0.1 kPa of preventive inflation in advance to inhibit the exacerbation of edema. Through high-frequency sampling and operation of 10 times per second, the algorithm controls the accuracy of the pressure of each partition air bag to be ±0.03 kPa, shortens the pressurization response time from 15 minutes of traditional manual adjustment to 30 seconds during the peak period of postoperative edema, and adjusts the pressure curve in real time (such as automatically decreasing from 1.5 kPa to 1.2 kPa on the 3rd day after the operation as the swelling subsides), which reduces the risk of tissue ischemia by 60% and the subjective pain score of the patient by 40% compared with the conventional pressurization method.

[0051] In the embodiment of the present application, the cloud management interaction unit 400 includes, as shown in Figure 7 The data interaction module and the strategy generation module.

[0052] The data interaction module is used to display the pressurization curve and real-time pressure data, and to perform pain feedback; the strategy generation module automatically generates a personalized rehabilitation plan by analyzing the pressurization data to predict the healing trend and to perform medication reminders.

[0053] It can be understood that the data interaction module of the present application presents the dynamic changes of the pressure of each partition through the visual pressurization curve, so that the patient can perform pain feedback according to his own comfort, improving the participation and subjective initiative in the rehabilitation process; the strategy generation module accurately predicts the healing trend of the wound by analyzing the pressurization data for a long time, automatically generates a rehabilitation plan that adapts to individual differences, and intelligently pushes medication reminders according to the treatment cycle, performing whole-process intervention from pressure management to overall rehabilitation. It provides an objective efficacy evaluation basis for medical staff, optimizes the rehabilitation efficiency through personalized strategies, reduces the risk of complications, and enables patients to obtain more accurate and convenient postoperative care experience.

[0054] It should be noted that the strategy generation module predicts healing trends by analyzing pressure data, automatically generates personalized rehabilitation plans, and provides medication reminders. First, it analyzes the pressure data of each zone, extracts pressure change characteristics, and compares them with the pressure data and healing progress of patients undergoing similar surgeries in the historical rehabilitation case database. Through a comparative learning algorithm, it calculates the deviation between the current pressure plan and the optimal healing path, predicting the wound healing trend. At the same time, it generates personalized pressure strategy adjustment suggestions based on individual patient parameters and automatically associates medication plans with rehabilitation milestones. It generates medication reminders through a time-event trigger mechanism for precise rehabilitation management.

[0055] Contrastive learning algorithm formula:

[0056] in, For query samples; Positive samples; Negative samples; It is a similarity function; Temperature coefficient; The loss function; To determine the range of parameters for summation; It is a logarithmic function; is the base of the natural logarithm.

[0057] This application proposes a zoned compression system for a post-masturbation chest band. A flexible sensing module acquires real-time data on tissue swelling and chest band displacement, providing dynamic data for precise compression. An intelligent compression module divides pressure zones based on this data and implements differentiated compression to meet the personalized treatment needs of different wound sites. A micro-control adjustment unit uses a PID control algorithm to dynamically fine-tune the airbag pressure, ensuring pressure accuracy and treatment safety. A cloud management interaction unit provides real-time alerts for anomalies and pushes personalized rehabilitation plans, improving the accuracy and automation of post-operative compression therapy, reducing human intervention errors, and lowering the risk of complications such as tissue ischemia or edema. Simultaneously, cloud data management optimizes the rehabilitation process, providing patients with intelligent and personalized post-operative care plans, effectively shortening the rehabilitation cycle and improving medical service efficiency. This solves the problems of uneven compression, lack of dynamic adjustment, and poor monitoring in existing technologies.

[0058] The following will illustrate a zonal compression system for a post-masturbation chest band through a specific embodiment, such as... Figure 8 As shown, it includes: A flexible and breathable material chest strap body uses a partitioned pressure system, the chest strap body uses a medical grade skin-friendly elastic fabric to ensure the comfort and safety of long-term wear. The inner surface of the chest strap uses a 0.3mm ultra-thin flexible PCB substrate, integrating an AD5940 bioelectric impedance sensor and a BMI160 MEMS displacement sensor, which is attached to the inner surface of the chest strap in the wound area. The bioelectric impedance sensor detects tissue impedance changes with a 100kHz, 100μA weak current, accurately quantifying the degree of edema (precision ±0.5%), while the displacement sensor uses a three-axis accelerometer and gyroscope fusion algorithm to track the three-dimensional displacement of the chest strap at 10Hz high frequency sampling, triggering a calibration signal when the offset exceeds 5mm, achieving non-invasive real-time monitoring of swelling status and wearing position, providing dynamic data support for compression therapy. These sensors are connected to the subsequent processing module through a flexible circuit board, ensuring the stability and reliability of data transmission.

[0059] A medical grade TPU film is used to form 5 independent air bag partitions (central wound area, double upper swelling area, double lower fixed area), each air bag is equipped with a 0.1mm nickel-titanium alloy memory metal strip, which can maintain an arc shape support with body temperature. When the bioelectric impedance sensor detects a 10% decrease in partition impedance (swelling intensifies), the dynamic compression module automatically increases the pressure in that area by 0.2kPa (pressure range 0.5-2.0kPa adjustable), while maintaining the air bag shape through the memory metal strip; The outside of the air bag is wrapped with a medical silicone sponge pad, the inner layer of which is designed with a microporous breathable design to cooperate with the memory metal strip, achieving "precise compression + flexible adaptation". When the patient moves, the air bag can adapt to the body posture and deform, improving the wearing comfort by 60%.

[0060] The TMP600 micro-pump (power consumption ≤0.5W), 50ms response proportional electromagnetic valve group and 1500mAh lithium polymer battery are integrated at the hardware level and placed in the waterproof cabin on the side of the chest strap; The software level uses an incremental PID algorithm (Kp=0.8, Ki=0.2, Kd=0.1) to calculate the pressure deviation in real time with a period of 200ms: when the measured pressure deviates from the target value by more than 0.1kPa, the proportional link adjusts the air pump inflation amount immediately; The integral link corrects the long-term pressure drift every 10 minutes; The differential link suppresses the inflation overshoot, ultimately achieving a pressure regulation accuracy of ±0.03kPa, meeting the safety control requirements of postoperative compression therapy, while ensuring 72 hours of continuous endurance.

[0061] The cloud management interaction unit realizes functions relying on the Internet cloud platform. The patient interacts with the system through the matching smart phone application. The data interaction module displays the pressure curves of each partition in real time in the form of visual charts on the mobile phone application interface. The patient can manually input the pain score (1-10) through the buttons on the interface according to his own feelings. The strategy generation module deeply analyzes the compression data, tissue swelling degree and chest band displacement data uploaded to the cloud, and uses the contrast learning algorithm to predict the healing trend of the patient's surgical wound. When the analysis result shows an abnormality, when the patient's pressure deviation is >0.3kPa for 24 consecutive hours and the pain score is >6, the system immediately pushes the warning information through the mobile application, and automatically generates a personalized rehabilitation program according to the individual situation of the patient, including diet suggestions, activity precautions, etc. It can also remind the patient to take medicine according to the set time.

[0062] When the patient wears the postoperative chest band for breast surgery, the flexible sensing module starts working immediately, continuously collects the pressure distribution and chest band displacement data of each partition, and transmits these data to the micro-control adjustment unit. The pressure adjustment module in the micro-control adjustment unit analyzes the sensing data according to the preset pressure standard and PID control algorithm, and judges whether the pressure of each partition needs to be adjusted. If adjustment is needed, the micro-pump and pressure regulating valve group in the hardware control module are controlled to inflate and deflate the corresponding air bag, realizing the dynamic adjustment of the pressure. At the same time, the micro-control adjustment unit uploads the processed data to the cloud management interaction unit, and the cloud management interaction unit stores and analyzes the data. Once an abnormal situation is detected, the system immediately pushes the warning information to the patient, and generates a personalized rehabilitation program feedback to the patient's mobile application, so as to realize the intelligent and personalized management of the postoperative chest band partition compression for breast surgery, and promote the postoperative rehabilitation of the patient.

[0063] In summary, this embodiment utilizes medical-grade skin-friendly elastic fabric and an inner microporous breathable design, combined with a memory metal strip to achieve flexible adaptation. The airbag can adaptively deform with the patient's posture during movement, improving wearing comfort by 60% and ensuring comfort and safety during prolonged wear. Regarding monitoring functions, integrated bioelectrical impedance sensors and displacement sensors can accurately quantify the degree of edema (accuracy ±0.5%) and track the three-dimensional displacement of the chest strap in real time, achieving non-invasive real-time monitoring of swelling status and wearing position, providing dynamic data support for compression therapy. In terms of compression therapy... The device features five independent airbag zones that can automatically and dynamically adjust pressure based on swelling levels, achieving "precise pressurization + flexible adaptation" to meet the safety control requirements of postoperative pressure therapy. The hardware boasts a low-power design ensuring 72 hours of continuous operation and is housed in a side-mounted waterproof compartment. The software utilizes an incremental PID algorithm to achieve high-precision pressure adjustment (±0.03kPa). The cloud management interaction unit can display data in real time, push alerts, generate personalized rehabilitation plans and medication reminders, etc., realizing intelligent and personalized management of postoperative chest band pressure therapy and effectively promoting postoperative recovery.

[0064] Next, referring to the accompanying drawings, a method for applying zonal pressure to a chest band after breast surgery, according to an embodiment of this application, is described.

[0065] like Figure 9 As shown, this method of applying zoned pressure to a chest band after breast surgery includes the following steps: In step S101, data on the degree of tissue swelling and chest band displacement are obtained.

[0066] Among them, the degree of tissue swelling refers to the quantitative state of local tissue volume increase caused by abnormal accumulation of interstitial fluid. The degree of edema can be accurately characterized by detecting changes in tissue impedance through technologies such as bioelectrical impedance analysis.

[0067] It is understood that the embodiments of this application use bioelectrical impedance to precisely quantify the edema status (accuracy ±0.5%), providing real-time dynamic data for the zonal compression of the chest band after breast surgery. This allows the system to automatically trigger pressure adjustment in the corresponding area based on the increase in swelling, ensuring that the compression treatment is precisely matched to the changes in tissue swelling, avoiding insufficient or excessive pressure. This helps to assess the recovery of the surgical wound and the treatment effect, and provides a scientific basis for adjusting the zonal compression plan of the chest band. Under the premise of protecting skin health, it promotes the postoperative recovery of patients and reduces the probability of complications.

[0068] In step S102, based on the degree of tissue swelling and chest band displacement data, different pressure zones are divided, dynamic pressurization is performed, and the pressure distribution of each zone is generated through a spatial interpolation algorithm.

[0069] The spatial interpolation algorithm is a mathematical method for estimating the attribute value of an unknown point based on the attribute values of known spatial discrete points, which is based on the assumption of spatial correlation and uses the data of adjacent points or other sampling points to predict the attribute value of the target position.

[0070] It can be understood that, by using the spatial interpolation algorithm, the discrete sensor pressure data can be converted into continuous and comprehensive surgical wound pressure distribution information, effectively filling the pressure data gap in the un-covered area of the sensor, scientifically dividing the pressure area combined with the real-time body state of the patient, dynamically optimizing the estimation results of each partition pressure, ensuring that each partition pressure fits the human body curve and swelling changes, avoiding discomfort and risks caused by improper local pressure, bringing more comfortable and efficient postoperative care to the patient, and accelerating the healing process of the surgical wound.

[0071] It should be noted that the spatial interpolation algorithm formula is:

[0072] wherein, is the pressure value at the point to be interpolated x; is the pressure value measured by the i th sensor; is the Euclidean distance between the point to be interpolated and the i th sensor; is the distance weight power parameter; is the number of known points participating in interpolation.

[0073] In step S103, based on the partition pressure distribution, the actual pressure value is compared through the PID control algorithm, and the gas bag pressure is dynamically adjusted to generate a pressurization curve.

[0074] The PID control algorithm is a classic feedback control algorithm that dynamically adjusts the output to achieve fast response, eliminate static deviation, and suppress fluctuations, so that the system is stable and tends to the target value, by proportion, integral, and differential three links to comprehensive operation on system error.

[0075] It can be understood that, by real-time analysis of the partition pressure distribution data, the application embodiment uses the proportional link to quickly respond to the pressure deviation, the integral link to eliminate the static error, and the differential link to suppress the pressure fluctuation, dynamically adjusts the inflation amount of each gas bag, and avoids the continuous deviation caused by sensor error or tissue swelling change. Through the proportional term, a second-level response is achieved (such as rapid inflation when the pressure is insufficient), the integral term ensures that the pressure is long-term stable at the target value (error <±1mmHg), and the differential term buffers the pressure mutation caused by patient activity (suppression overshoot ≤2mmHg), generating a smooth and physiological pressure curve, which promotes wound healing and avoids complications caused by excessive pressure, and improves the safety and effectiveness of postoperative rehabilitation.

[0076] For example, asFigure 10 As shown, in the breast postoperative rehabilitation scenario, when the bioelectrical impedance sensor detects that the swelling intensifies and the target pressure needs to be raised from 1.0 kPa to 1.2 kPa, the PID control algorithm starts dynamic adjustment: the proportional link (Kp = 0.8) instantly calculates and increases the air volume of the micro air pump within 200 ms after the actual pressure is first detected to be 1.05 kPa (deviation + 0.15 kPa), quickly reducing the pressure difference; the integral link (Ki = 0.2) continuously accumulates small deviations (such as the pressure slowly falling to 1.15 kPa due to tissue fluid absorption) within the next 10 minutes, gradually correcting long-term drift and avoiding underpressure; the derivative link (Kd = 0.1) detects that the inflation rate is too fast (predicting the risk of overshoot) when the pressure approaches 1.2 kPa, automatically inhibits the air pump output, and prevents the pressure from suddenly increasing to 1.25 kPa. Through the cooperation of the three links, the pressure is finally stabilized at 1.2 ± 0.03 kPa within 3 adjustment cycles, generating a smooth pressure curve that quickly responds to swelling changes and avoids pressure fluctuations that can irritate the wound, ensuring the accuracy and safety of postoperative compression therapy.

[0077] In step S104, based on the clinical review indicators and patient activity data, combined with the compression curve, the healing trend is predicted, the compression data anomaly is monitored in real time, and the personalized rehabilitation scheme is pushed combined with the patient's pain feedback.

[0078] It can be understood that the embodiments of the present application predict the healing process through deep mining and trend analysis of historical data, discover potential recovery problems in advance, monitor compression data anomalies in real time, timely warn of risks such as insufficient pressure or overpressure, avoid the impact of improper pressure on rehabilitation effects and even cause tissue damage, and at the same time, combined with the patient's subjective pain feedback, generate a highly adaptive personalized rehabilitation scheme for individual conditions, including targeted diet, activity guidance, and medication reminders, etc., to improve the patient's rehabilitation experience and significantly improve the rehabilitation efficiency, providing safer, more efficient, and more personalized postoperative rehabilitation management for patients.

[0079] According to the embodiments of this application, a method for zonal compression of a chest band after breast surgery is proposed. A flexible sensing module acquires real-time data on tissue swelling and chest band displacement, providing dynamic basis for precise compression. An intelligent compression module combines data to divide pressure zones and implement differentiated compression, meeting the personalized treatment needs of different wound sites. A micro-control adjustment unit uses a PID control algorithm to dynamically fine-tune the airbag pressure, ensuring pressure accuracy and treatment safety. A cloud management interaction unit provides real-time warnings of abnormalities and pushes personalized rehabilitation plans, improving the accuracy and automation of postoperative compression treatment, reducing human intervention errors, and lowering the risk of complications such as tissue ischemia or edema. Simultaneously, cloud data management optimizes the rehabilitation process, providing patients with intelligent and personalized postoperative care plans, effectively shortening the rehabilitation cycle and improving medical service efficiency. This solves the problems of uneven compression, lack of dynamic adjustment, and poor monitoring in existing technologies.

[0080] The following specific embodiment will illustrate a method for zonal compression of a chest band after breast surgery, such as... Figure 11 As shown, it includes: The main body of the chest strap is made of medical-grade skin-friendly elastic fabric, with an inner surface covered by a 0.3mm ultra-thin flexible PCB substrate. It integrates an AD5940 bioelectrical impedance sensor, a BMI160 MEMS displacement sensor, and a microcontroller unit for data processing and control. The chest strap is heat-sealed with a medical-grade TPU film to form five independent airbag zones: a central wound zone, bilateral upper swelling zones, and bilateral lower fixation zones. Each airbag contains a 0.1mm nickel-titanium alloy shape memory metal strip and is wrapped with a medical-grade silicone sponge pad. Furthermore, the waterproof compartment on the side of the chest strap integrates a TMP600 micro air pump, a proportional solenoid valve assembly, and a 1500mAh lithium polymer battery. It also comes with a smartphone application and an internet cloud platform for data interaction, analysis, and rehabilitation plan delivery.

[0081] Once the patient has fitted the post-masturbation chest band, the flexible sensing module immediately activates. The AD5940 bioelectrical impedance sensor detects changes in tissue impedance using a weak current of 100kHz and 100μA, transmitting the signal to the microcontroller unit for processing. This accurately quantifies the degree of tissue swelling with an precision of ±0.5%. For example, when abnormal fluid accumulation in the interstitial space of the central wound area causes a decrease in impedance, the sensor can capture and output the corresponding quantitative data in real time. Simultaneously, the BMI160MEMS displacement sensor samples at a high frequency of 10Hz using a triaxial accelerometer and gyroscope, transmitting the collected three-dimensional displacement data of the chest band to the microcontroller unit. When the chest band shifts by more than 5mm, the displacement sensor triggers a calibration signal, alerting the patient or medical staff to adjust the chest band position promptly, ensuring the accuracy of the monitoring data.

[0082] After receiving the data of tissue swelling degree and chest belt displacement, the micro-control unit calculates the pressure distribution of each region of the chest belt based on the spatial correlation assumption and the inverse distance weighted spatial interpolation algorithm (of course, other suitable algorithms such as Kriging method can also be used). Knowing the pressure and swelling state data collected by the sensors arranged at the points of the chest belt (such as the central wound area, the upper swelling area, the lower fixed area and other discrete points), the algorithm estimates the pressure values of the regions not covered by the sensors (such as the edge of the chest belt and the transition area of the human body curve) according to the data of the adjacent points and their spatial distance weights. For example, when the central sensor in the upper swelling area detects that the tissue swelling is aggravated and the pressure is insufficient, the algorithm will calculate the pressure compensation value of the positions not arranged with sensors around the region, generate a continuous pressure distribution cloud map covering the entire chest belt, and then scientifically divide different pressure regions to provide a basis for subsequent dynamic pressure.

[0083] Based on the generated pressure distribution of each partition, the PID control algorithm in the micro-control unit starts to work. Taking the central wound area as an example, when the bioelectric impedance sensor detects that the swelling is aggravated, the system increases the target pressure of the region from 1.0 kPa to 1.2 kPa. The proportional element (Kp=0.8) calculates and sends instructions to the hardware control module to increase the inflation amount of the micro air pump within 200 ms after detecting that the actual pressure is 1.05 kPa (deviation +0.15 kPa from the target value) for the first time, quickly reducing the pressure difference. In the next 10 minutes, the integral element (Ki=0.2) continuously accumulates the small pressure deviations caused by factors such as tissue fluid absorption (such as the pressure slowly falling to 1.15 kPa), gradually corrects the long-term pressure drift, and avoids the occurrence of under-pressure. When the pressure approaches 1.2 kPa, the derivative element (Kd=0.1) detects that the inflation rate is too fast, predicts that there is an overshoot risk, and automatically suppresses the output power of the air pump to prevent the pressure from suddenly increasing to 1.25 kPa. Through the cooperative work of the proportional, integral and derivative elements, the pressure is finally stabilized at 1.2±0.03 kPa within 3 adjustment cycles, generating a smooth and treatment-demanding pressure curve.

[0084] The micro-control unit uploads the processed data to the cloud management interaction unit. The cloud platform combines clinical review indicators (such as regularly collected wound healing image data, blood test indicators, etc.), activity data (such as daily walking steps, exercise duration, etc.) manually input by the patient through the smart phone application, and the generated pressure curve, and uses a contrast learning algorithm to predict the healing trend of the patient's surgical wound. At the same time, the cloud platform monitors the pressure data in real time, and when the patient's continuous 24-hour pressure deviation is >0.3kPa and the patient's feedback pain score through the mobile phone application is >6 points, the system immediately pushes warning information to the patient through the mobile phone application. In addition, according to the individual situation of the patient (such as age, physical basic condition, surgical method, etc.), a personalized rehabilitation plan is automatically generated, including targeted dietary suggestions (such as high-protein, high-vitamin diet to promote wound healing), activity precautions (such as avoiding excessive upper limb activity to pull the wound), and medication reminders according to the set time, realizing intelligent and personalized management of the postoperative chest band zoned compression of the breast, and promoting the postoperative rehabilitation of the patient.

[0085] In summary, the embodiment of the present application uses a medical-grade skin-friendly elastic fabric combined with an ultra-thin flexible substrate, which has both comfort and safety, and ensures long-term wear without burden. In terms of sensing and monitoring, high-precision bioelectric impedance and displacement sensors accurately capture tissue swelling and chest band displacement in real time, with an error as low as ±0.5%, providing reliable data foundation for treatment. In terms of pressure regulation, the spatial interpolation algorithm combined with the PID control algorithm scientifically divides the pressure region and realizes high-precision dynamic adjustment of ±0.03kPa, making the pressure fit the human body curve and swelling changes, and improving the treatment accuracy. In terms of data processing and feedback, the cloud platform integrates multiple data sources, which can not only accurately predict the healing trend, but also monitor abnormalities in real time, trigger an alarm when the continuous 24-hour pressure deviation is >0.3kPa and the pain score is >6 points, and customize rehabilitation programs and medication reminders according to individual differences, truly realizing intelligent and personalized postoperative rehabilitation management, effectively accelerating the patient's rehabilitation process, and reducing the risk of complications.

[0086] Figure 12 A structural schematic diagram of an electronic device provided by the embodiment of the present application is provided. The electronic device can include: a memory 1201, a processor 1202, and a computer program stored in the memory 1201 and executable on the processor 1202.

[0087] The processor 1202 implements the breast postoperative chest band zoned compression method provided in the above embodiment when executing the program.

[0088] Further, the electronic device further includes: a communication interface 1203 for communication between the memory 1201 and the processor 1202.

[0089] The memory 1201 is configured to store a computer program executable in the processor 1202.

[0090] The memory 1201 can include a high-speed RAM memory, and can further include a nonvolatile memory, such as at least one disk memory.

[0091] If the memory 1201, the processor 1202 and the communication interface 1203 are independently implemented, the communication interface 1203, the memory 1201 and the processor 1202 can be connected to each other through a bus and complete the communication between each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 12 Only one thick line is used in the figure to represent the bus, but it does not mean that there is only one bus or only one type of bus.

[0092] Optionally, in a specific implementation, if the memory 1201, the processor 1202 and the communication interface 1203 are integrated on a chip, the memory 1201, the processor 1202 and the communication interface 1203 can complete the communication between each other through an internal interface.

[0093] The processor 1202 can be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement one or more embodiments of the present application.

[0094] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by the processor to implement the method for partitioned pressurization of a breast postoperative chest bandage.

[0095] In addition, the embodiment of the present application further provides a computer program product, which includes a computer program or instructions, and the computer program or instructions are executed to implement the method for partitioned pressurization of a breast postoperative chest bandage.

[0096] In the description of the application, reference to "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" etc., means that a particular feature, structure, material or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. The illustrative appearances of the above-mentioned terms in various places in the specification are not necessarily referred to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples. Moreover, the terminology "first", "second" etc. is used merely as a designation, and does not imply or imply a relative importance or a specific ordering between the indicated features. Thus, a feature described as "first" can implicitly or explicitly be included in at least one of the features described as "second" etc. In the description of the application, the meaning of "plurality" is at least two, for example two, three, etc., unless otherwise explicitly specified.

[0097] Furthermore, the terms "first", "second", etc. are used merely as a designation and do not imply or suggest relative importance or imply a specific ordering of the indicated technical features. Thus, a feature defined as "first", can implicitly or explicitly include at least one of the features defined as "second" etc. In the description of the application, the meaning of "plurality" is at least two, for example two, three, etc., unless otherwise explicitly specified.

[0098] Any process or method descriptions or descriptions of the flow diagrams in the present application can be understood as representing code modules, segments, or portions of code which include one or more executable instructions for implementing specific logic functions (or steps) in the process, and the various embodiments of the application can include additional or fewer processes, steps, operations, or segments of code, and the representation of the processes or methods in the flow diagrams can not be dependent on the particular order of the steps or the segments of code. The various embodiments of the application can be implemented in hardware, software, firmware, or a combination thereof.

[0099] It should be understood that portions of the application can be implemented in hardware, software, firmware, or combinations thereof. In the above embodiments, the various steps or methods can be implemented in software or firmware that is stored in memory and executed by a suitable instruction execution system. As with a hardware implementation, the methods and steps of the embodiments, in an alternative implementation, can be implemented by either one or both of the following: as permutations of logical hardware circuitry having certain input and / or output signals, as combinations of rules-based logic having certain inputs and / or outputs, or any combination thereof.

[0100] Those of ordinary skill in the art can understand that all or part of the steps carried out by the above-mentioned embodiments can be completed by programs instructing related hardware, and the programs can be stored in a computer readable storage medium, and when executed, include one or a combination of steps of the method embodiments.

[0101] Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary, and are not to be interpreted as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A zoned compression system for a post-mastrectomy chest binder, characterized in that, include: The system includes a flexible sensing module, an intelligent pressurization module, a micro-control adjustment unit, and a cloud management interaction unit; among which... The flexible sensing module is used to acquire data on the degree of tissue swelling and chest girder displacement. The intelligent pressurization module is used to divide different pressure zones and perform zoned pressurization based on the degree of tissue swelling and chest band displacement data; The micro-control adjustment unit is used to dynamically fine-tune the airbag pressure in each zone according to the PID control algorithm. The cloud management interaction unit is used to provide real-time anomaly warnings for pressurized data and to push personalized rehabilitation plans.

2. The zonal compression system for a post-masturbation chest band according to claim 1, characterized in that, The flexible sensing module includes a bioelectrical impedance sensor and a displacement sensor. The bioelectrical impedance sensor is used to determine the degree of swelling by changes in tissue electrical impedance; the displacement sensor is used to track chest strap displacement data in real time.

3. The zonal compression system for a post-mastrectomy chest band according to claim 1, characterized in that, The intelligent pressurization module includes a zoned airbag array and an airbag support component. The zoned airbag array is used to divide the pressure zone according to the degree of tissue swelling of the surgical wound. The airbag support component is used to independently configure an inflatable silicone airbag and a memory metal support strip for each zone.

4. The zonal compression system for a post-mastrectomy chest band according to claim 1, characterized in that, The intelligent pressurization module also includes a dynamic pressurization module, which is used to dynamically control the degree of tissue swelling in the surgical wound area after the patient's surgery.

5. The zonal compression system for a post-mastrectomy chest band according to claim 1, characterized in that, The micro-control adjustment unit includes a hardware control module and a pressure adjustment module. The hardware control module is used to integrate a micro air pump, a pressure regulating valve group, and a lithium battery pack for pressure control. The pressure adjustment module is used to dynamically fine-tune the pressure of each airbag zone through a PID control algorithm.

6. The zonal compression system for a post-mastrectomy chest band according to claim 1, characterized in that, The cloud management interaction unit includes a data interaction module and a strategy generation module. The data interaction module is used to display the pressure curve and real-time pressure data, and the patient provides pain feedback. The strategy generation module analyzes the pressure data to predict the healing trend, automatically generates personalized rehabilitation plans, and provides medication reminders.

7. A method for applying zoned pressure to a chest binder after breast surgery, characterized in that, include: Acquire data on the degree of tissue swelling and chest girdle displacement; Based on the tissue swelling degree and chest girdle displacement data, different pressure zones are divided, dynamic pressurization is applied, and the pressure distribution of each zone is generated through a spatial interpolation algorithm. Based on the pressure distribution of each zone, the pressure of each airbag is dynamically adjusted by comparing the actual pressure value using a PID control algorithm, thereby generating a pressurization curve. Based on clinical follow-up indicators and patient activity data, combined with the pressure curve, the healing trend is predicted, abnormal pressure data is monitored in real time, and personalized rehabilitation plans are pushed based on patient pain feedback.

8. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, the processor executing the program to implement the method for applying zonal pressure to a chest band after breast surgery as described in claim 7.

9. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed, they implement the method for applying zonal pressure to a chest band after breast surgery as described in claim 7.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed, they implement the method for applying zonal pressure to a chest band after breast surgery as described in claim 7.

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