Temperature control method and system for physiotherapy hot compress patch

Abstract

The invention discloses a temperature control method and system for a physiotherapy hot compress patch, and relates to the field of biological feature recognition. The method is applied to an MCU control module and comprises the steps that basic information of a target patient is obtained, the basic information comprises multiple pieces of sub-basic information, and the multiple pieces of sub-basic information comprise a hot compress part, age, gender, hot compress time and disease information; generating a first prediction curve of the skin temperature change of the hot compress part based on the basic information; the heating module is controlled to conduct skin testing on the hot compress part, and a skin temperature change curve is obtained; based on the skin temperature change curve, the first prediction curve is corrected, and a second prediction curve of the skin temperature change of the hot compress part is generated; and controlling the heating module to perform hot compress heating based on the second prediction curve. By implementing the technical scheme provided by the invention, the problem that the temperature control of the physiotherapy hot compress patch is too single is solved.

Description

Technical Field

[0001] The present application relates to the technical field of biometric identification, and in particular to a temperature control method and system for a physiotherapy hot compress patch. Background Art

[0002] As people's lifestyles change, the incidence of chronic pain diseases has gradually increased, such as cervical spondylosis, frozen shoulder, arthritis, etc. In the past, hot towels were applied to the painful area to speed up blood circulation in the painful area to relieve the discomfort caused by the pain. However, this method is inefficient and very troublesome, so a physiotherapy hot compress patch that simulates the effect of hot towels was designed.

[0003] The current physiotherapy hot compress patches evenly arrange the heating wires on the adhesive surface, and then the MCU control module controls the output unit to release PWM electric pulses to make the heating wires continuously heat up, and then adjusts the duty cycle of the PWM electric pulses to achieve temperature control of the heating wires. However, today's physiotherapy hot compress patches face the problem of too single temperature control. Even if there are multiple adjustable temperature gears pre-set, due to individual differences between patients, in many cases the physiotherapy effect of the hot compress patch cannot be effectively exerted. Summary of the invention

[0004] In view of the problem that the temperature control of current physiotherapy hot compress patches is too single, the present application provides a temperature control method and system for a physiotherapy hot compress patch.

[0005] In a first aspect, the present application provides a method for controlling the temperature of a physiotherapy hot compress patch, the method comprising: Obtaining basic information of the target patient, wherein the basic information includes a plurality of sub-basic information, and the plurality of sub-basic information includes hot compress site, age, gender, hot compress time and disease information; Based on the basic information, generating a first prediction curve of skin temperature change at the hot compress site; Controlling the heating module to perform skin testing on the hot compress area to obtain a skin temperature change curve; Based on the skin temperature change curve, the first prediction curve is corrected to generate a second prediction curve of the skin temperature change at the hot compress part; Based on the second prediction curve, the heating module is controlled to perform hot compress heating.

[0006] Optionally, querying historical user information with the highest similarity to the basic information and its corresponding historical skin temperature change curve from a preset user information database, wherein the basic information and the historical user information each correspond to a similarity value on a plurality of sub-basic information; Based on the similarity values ​​of the plurality of sub-basic information, querying the preset user information database for a plurality of historical skin temperature change curves corresponding to each of the sub-basic information; Determining, according to the slope distribution of the plurality of historical skin temperature change curves corresponding to the plurality of sub-basic information, the influence coefficients of the plurality of sub-basic information on the historical skin temperature change curves corresponding to the historical user information; Based on the influence coefficients of the plurality of sub-basic information, the historical skin temperature change curve corresponding to the historical user information is adjusted to obtain the first prediction curve.

[0007] Optionally, a principal component analysis is performed on the plurality of sub-basic information to determine a main influence coefficient corresponding to each time point in the historical skin temperature change curve corresponding to the historical user information; Based on the main influence coefficient corresponding to each time point, the historical skin temperature change curve corresponding to the historical user information is adjusted to generate the first prediction curve.

[0008] Optionally, the controlling the heating module to perform a skin test on the hot compress area specifically includes: Obtaining a time period corresponding to a fluctuation curve in the first prediction curve, and setting the time period corresponding to the fluctuation curve as a test time for the skin test; A plurality of monitoring points are set during the test time, wherein each monitoring point corresponds to a heating power; During the test, when the monitoring point is reached, the heating module is controlled to adjust to the heating power corresponding to each monitoring point.

[0009] Optionally, based on the plurality of monitoring points set during the test time, a plurality of skin temperature test curves are obtained; Similarity calculation is performed between the plurality of skin temperature test curves and the first prediction curve, and the skin temperature test curve with the highest similarity is selected as the skin temperature change curve.

[0010] Optionally, extracting a plurality of key feature points of the skin temperature change curve and a plurality of key feature points of the first prediction curve, and comparing the plurality of key feature points of the two one by one to obtain a difference sequence between the skin temperature change curve and the first prediction curve; Based on the difference sequence, the default correction factor is adjusted to obtain a comprehensive correction factor; The first prediction curve is adjusted using the comprehensive correction factor to obtain a second prediction curve.

[0011] Optionally, after controlling the heating module to perform hot compress heating based on the second prediction curve, the method further includes: Obtain feedback from target patients; The feedback information is matched with a power adjustment table to obtain an adjustment amplitude and an adjustment rate corresponding to the feedback information.

[0012] In a second aspect, the present application provides a temperature control system for a physiotherapy hot compress patch, wherein the system is an MCU control module, and the MCU control module includes an acquisition module, a processing module, and a sending module, wherein: The acquisition module is used to acquire basic information of the target patient, wherein the basic information includes a plurality of sub-basic information, and the plurality of sub-basic information includes hot compress site, age, gender, hot compress time and disease information; The processing module is used to generate a first prediction curve of the skin temperature change of the hot compress part based on the basic information; control the heating module to perform a skin test on the hot compress part to obtain a skin temperature change curve; based on the skin temperature change curve, correct the first prediction curve to generate a second prediction curve of the skin temperature change of the hot compress part; The sending module is used to control the heating module to perform hot compress heating based on the second prediction curve.

[0013] In a third aspect, the present application provides an electronic device comprising a processor, a memory, a user interface and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a method as described in any one of the first aspects.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, the method as described in any one of the first aspects is executed.

[0015] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Regarding the problem of the single control method of the current physiotherapy hot compress patch, this application first matches a skin temperature change curve that is most similar to the patient's physical condition from the preset user information library based on the patient's basic information, so that when the MCU control module controls the heating module to heat the hot compress patch according to the temperature change curve, it can have a better physiotherapy effect on the patient; however, due to the individual differences in physical conditions of different patients, relying solely on the above-mentioned temperature change curve may not be able to adapt to the patient's physical condition. Therefore, this application conducts actual skin tests on patients to obtain the patient's skin temperature changes, and then infers the patient's blood circulation based on the skin temperature changes. The principle is that when the patient's blood circulation is poor, the blood cannot effectively bring heat to the whole body, resulting in a higher rate of increase in the skin temperature of the hot compress area, and vice versa. Based on this principle, this application corrects the skin temperature change curve that is most similar to the patient's physical condition according to the results of the skin test, so as to obtain a personalized temperature change curve that is closer to the patient's physical condition, so that the subsequent heating of the hot compress patch can have a better physiotherapy effect.

[0016] 2. In order to improve the reference value of the first prediction curve of skin temperature changes at the hot compress site during skin testing, this application adjusts the historical skin temperature change curve that is most similar to the basic information of the target patient to make it fit the physical condition of the target patient as much as possible. Specifically, the influence of each factor in the basic information on the skin temperature is analyzed separately to obtain the influence coefficients of multiple factors. Then, during the use of the hot compress patch by the patient, the influence of each factor will also change with the increase of heating time. Therefore, by performing principal component analysis on each factor at different time points, the main influence coefficients at different time points are obtained, and then the temperature value at each time point in the historical skin temperature change curve is adjusted based on the main influence coefficient to obtain the first prediction curve, thereby improving the reference value of the first prediction curve. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a structural schematic diagram of a therapeutic hot compress patch provided in an embodiment of the present application.

[0018] Figure 2 It is a flow chart of a temperature control method of a therapeutic hot compress patch provided in an embodiment of the present application.

[0019] Figure 3 It is a structural schematic diagram of a temperature control system of a therapeutic hot compress patch provided in an embodiment of the present application.

[0020] Figure 4 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0021] Explanation of the reference numerals: 1. Acquisition module; 2. Processing module; 3. Sending module; 400. Electronic device; 401. Processor; 402. Communication bus; 403. User interface; 404. Network interface; 405. Memory. DETAILED DESCRIPTION

[0022] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0023] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0024] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0025] As a device that simulates the effect of hot towel compress, the structure of the physiotherapy hot compress is as follows: Figure 1 As shown, it includes an adhesive surface, a heating wire, a temperature detection circuit, an output unit and an MCU control module. In this structure, the heating wire is evenly arranged on the adhesive surface. The MCU control module controls the output unit to release PWM electric pulses to make the heating wire continuously generate heat. The temperature detection circuit detects the temperature of the heating wire and feeds the temperature of the heating wire back to the MCU control module. At this time, the MCU module can adjust the duty cycle of the PWM electric pulse to achieve temperature control of the heating wire.

[0026] However, today's physiotherapy hot compress patches face the problem of overly single temperature control. Even if multiple adjustable temperature levels are pre-set, the physiotherapy effect of the hot compress patch cannot be effectively exerted in many cases due to individual differences between patients. In addition, when adjusting the temperature of the physiotherapy hot compress patch, it is more inclined to subjective judgment, resulting in the hot compress effect not being optimal, especially for middle-aged and elderly patients, because they have poor temperature perception and are unable to accurately judge the optimal hot compress temperature.

[0027] In order to solve the above problems, the present application provides a temperature control method for a physiotherapy hot compress patch, which is applied to an MCU control module, such as Figure 1 As shown, the method includes steps S101 to S105, which are as follows: S101. Obtain basic information of the target patient, where the basic information includes multiple sub-basic information, including hot compress site, age, gender, hot compress time, and disease information.

[0028] In the above steps, the MCU control module can be understood as a control instrument, which is divided into two modes: automatic adjustment and active adjustment. In automatic adjustment, the user inputs basic information on the control instrument, and the control instrument calculates the adjustment temperature suitable for the physiotherapy hot compress patch based on the basic information. Active adjustment is that the user directly sets the temperature of the physiotherapy hot compress patch for adjustment. The user can pre-enter the basic information of the target patient, where the basic information includes but is not limited to the hot compress site, age, gender, hot compress time, number of hot compresses, and disease information. At this time, the MCU control module converts the basic information to a standard data table and distinguishes the labels. When automatic adjustment is required, the MCU control module calls the standard data table with the corresponding label to obtain the basic information of the target patient.

[0029] S102: Generate a first prediction curve of skin temperature change at the hot compress site based on the basic information.

[0030] In the above steps, the first prediction curve can be understood as the temperature trend curve of the skin temperature of the target patient's hot compress part during the hot compress process. Therefore, in order to make the first prediction curve more consistent with the skin temperature change of the target patient. This application queries the historical user information with the highest similarity to the basic information and its corresponding historical skin temperature change curve from the preset user information library; since the basic information of the target patient is not exactly the same as the historical user information, it is necessary to make some adjustments to the historical skin temperature change curve to make it more consistent with the basic information of the target patient; at this time, the basic information of the target patient is split into multiple basic sub-information, and then each basic sub-information is matched with the preset user information library to obtain multiple historical skin temperature change curves corresponding to each basic sub-information. In the matching process, in order to ensure the output of the matching results, the matching range of each basic sub-information needs to be set in advance. The matching range should not be too large. The specific setting standard is determined according to the information distribution of each historical user information in the preset user information library. Then, the slope distribution of multiple historical skin temperature change curves corresponding to each basic sub-information is analyzed. The slope distribution can reflect the degree of influence of the basic sub-information on the skin temperature change. During the analysis process, the slope curves of the multiple historical skin temperature change curves corresponding to the basic sub-information are averaged and fused to obtain a fused slope curve; then, the fused slope curves of the multiple basic sub-information are compared to obtain the influence coefficients of the multiple basic sub-information on the skin temperature change; finally, the influence coefficients of the multiple basic sub-information are used to adjust each temperature point in the historical skin temperature change curve corresponding to the historical user information to generate a first prediction curve.

[0031] In a possible implementation, when the physiotherapy hot compress patch is applied to the hot compress area, as the hot compress time increases, the dominant position of different basic sub-information on skin temperature will change; for example, in the early stage of hot compress, due to differences in body structure, the hot compress area will be dominant, and the influence of age and gender differences on skin temperature is not as obvious as that of the hot compress area, while in the middle stage of hot compress, due to different skin metabolism and blood circulation in different age groups, the influence of age and gender differences on skin temperature is more obvious. Therefore, when the influence coefficients of multiple basic sub-information are used to adjust each temperature point in the historical skin temperature change curve, the adjustment strategy of different hot compress stages needs to be changed. Specifically, firstly, principal component analysis of multiple sub-basic information at different hot compress stages can be performed, which can be obtained by comparing the fusion slope curve corresponding to each basic sub-information. For example, if the fusion slope curve of the first basic sub-information is faster than the fusion slope curve of the second basic sub-information in the early stage of hot compress, it means that the first basic sub-information is more dominant. In this way, the dominant basic sub-information (main influence coefficient) at each temperature point (time point) can be further obtained, and then the proportion of the main influence coefficient at each time point can be increased. Finally, the historical skin temperature change curve corresponding to the historical user information can be adjusted to obtain the first prediction curve, so that the first prediction curve is more in line with the physical condition of the target patient.

[0032] S103, controlling the heating module to perform a skin test on the hot compress area to obtain a skin temperature change curve.

[0033] In the above steps, the first prediction curve is only an inferred skin temperature change curve for the target patient, which may be different from the actual situation. Therefore, it is necessary to conduct skin tests on the hot compress area of ​​the target patient and combine the actual situation with the inferred data to obtain the personalized hot compress needs of the target patient.

[0034] When conducting skin tests, in order to avoid blind testing, the present application selects the fluctuation curve in the first prediction curve as reference data for the skin test, wherein the fluctuation curve specifically refers to an interval range with a larger fluctuation amplitude and frequency in the predicted skin temperature change curve, indicating that the data within the interval contains more noise; then, the time period during which the fluctuation curve lasts is set as the test time of the skin test, and the upper and lower limits of the heating power corresponding to the fluctuation curve are set as the upper and lower limits of the heating power for the skin test; then, multiple monitoring points are evenly set within the test time, wherein one monitoring point corresponds to one heating power; during the test, when the monitoring point is reached, the heating module is controlled to adjust to the heating power corresponding to the monitoring point, and the actual skin temperature change data of the target patient is detected.

[0035] In order to find the skin temperature change curve that is most suitable for correcting the first prediction curve, the skin temperature test curves detected at multiple monitoring points are obtained, and then the similarity between the multiple skin temperature test curves and the non-fluctuation curve part in the first prediction curve is calculated, and the skin temperature test curve with the highest similarity is selected as the skin temperature change curve for subsequent correction. It should be explained that since the fluctuation curve is an inferred curve, many irrelevant factors are introduced into it. If the noise in the fluctuation curve is removed, the fluctuation curve will be a regular stable curve. However, in the actual process, noise removal is more complicated and the effect is not good. Therefore, the present application chooses to calculate the similarity between multiple skin temperature test curves and the non-fluctuation curve part in the first prediction curve, thereby indirectly performing noise reduction processing on the fluctuation curve part, and treating the most similar skin temperature test curve as the stable curve after the fluctuation curve is denoised, so that the skin temperature change curve used for the first prediction curve in the future is more valuable for correction.

[0036] S104. Based on the skin temperature change curve, the first prediction curve is corrected to generate a second prediction curve of the skin temperature change at the hot compress site.

[0037] In the above steps, although the skin temperature change curve can be regarded as the stable curve after denoising corresponding to the fluctuation curve, the skin temperature change curve is only a curve segment and cannot completely replace the fluctuation curve. It is necessary to consider its adaptability in the entire first prediction curve, and then adjust the fluctuation amplitude of the fluctuation curve, so as to adjust the first prediction curve within a reasonable fluctuation range. Based on this, when correcting the first prediction curve, the skin temperature change curve is used as a reference to adjust the first prediction curve. Specifically, multiple key feature points of the skin temperature change curve and multiple key feature points of the first prediction curve are extracted respectively, and the key feature points of the two correspond one to one. The key feature points include but are not limited to the starting point, peak point, temperature drop starting point, temperature rise starting point, temperature change slope stabilization point, and temperature change slope turning point. Then, the multiple key feature points of the two are compared one by one to obtain the difference sequence between the skin temperature change curve and the first prediction curve. In the difference sequence, each sequence value represents an attribute offset between the skin temperature change curve and the first prediction curve. Then, based on the difference sequence, the default correction factor is adjusted to obtain a comprehensive correction factor. Specifically, the following formula can be used: In the above formula, is the default correction factor, is the comprehensive correction factor, The weight coefficient set for the i-th sequence value in the difference sequence, is the i-th sequence value, is the mean of the difference series.

[0038] It should be noted that in order to make the impact of different sequence values ​​on the default correction factor within a relatively reasonable range, Each sequence value is normalized; then, based on the weight coefficient corresponding to each sequence value, the weighted sum of the difference sequence is obtained, and finally, the weighted sum is used to correct the default correction factor to ensure that the generated comprehensive correction factor can accurately reflect the difference between the skin temperature change curve and the first prediction curve, and reasonably adjust the prediction curve.

[0039] Finally, the comprehensive correction factor is multiplied by the fluctuation curve part in the first prediction curve, and the newly generated curve is smoothed to obtain the second prediction curve.

[0040] S105. Based on the second prediction curve, control the heating module to perform hot compress heating.

[0041] In the above steps, the second prediction curve is used as the basis for temperature adjustment of the physiotherapy hot compress patch, so that the blood circulation of the target patient is better improved, thereby enhancing the physiotherapy effect of the physiotherapy hot compress patch.

[0042] In a possible implementation, the feedback information of the target patient can be further combined on the basis of the second prediction curve to improve the comfort of use for the target patient. The feedback information is the temperature of the active adjustment model input. At this time, the feedback information is matched with the power adjustment table to obtain the adjustment amplitude and adjustment rate corresponding to the feedback information, so as to meet the needs of more patients.

[0043] Reference Figure 3 The present application also provides a temperature control system for a physiotherapy hot compress patch, the system is an MCU control module, the MCU control module includes an acquisition module 1, a processing module 2 and a sending module 3, wherein: Acquisition module 1, used to acquire basic information of the target patient, the basic information includes multiple sub-basic information, and the multiple sub-basic information includes hot compress site, age, gender, hot compress time and disease information; Processing module 2 is used to generate a first prediction curve of skin temperature change at the hot compress part based on the basic information; control the heating module to perform skin test on the hot compress part to obtain a skin temperature change curve; based on the skin temperature change curve, correct the first prediction curve to generate a second prediction curve of skin temperature change at the hot compress part; The sending module 3 is used to control the heating module to perform hot compress heating based on the second prediction curve.

[0044] In a possible implementation, historical user information with the highest similarity to the basic information and its corresponding historical skin temperature change curve are searched from a preset user information database, wherein the basic information and the historical user information each correspond to a similarity value in multiple sub-basic information; Based on the similarity values ​​of the plurality of sub-basic information, a plurality of historical skin temperature change curves corresponding to each sub-basic information are queried from a preset user information database; Determining, according to the slope distribution of the plurality of historical skin temperature change curves corresponding to the plurality of sub-basic information, the influence coefficient of the plurality of sub-basic information on the historical skin temperature change curve corresponding to the historical user information; Based on the influence coefficients of the plurality of sub-basic information, the historical skin temperature change curve corresponding to the historical user information is adjusted to obtain a first prediction curve.

[0045] In a possible implementation, principal component analysis is performed on the plurality of sub-basic information to determine the main influence coefficient corresponding to each time point in the historical skin temperature change curve corresponding to the historical user information; Based on the main influence coefficient corresponding to each time point, the historical skin temperature change curve corresponding to the historical user information is adjusted to generate a first prediction curve.

[0046] In a possible implementation, controlling the heating module to perform a skin test on the hot compress site specifically includes: Obtaining a time period corresponding to a fluctuation curve in the first prediction curve, and setting the time period corresponding to the fluctuation curve as a test time for the skin test; Multiple monitoring points are set during the test time, wherein each monitoring point corresponds to a heating power; During the test, when the monitoring point is reached, the heating module is controlled to adjust to the heating power corresponding to each monitoring point.

[0047] In a possible implementation, multiple skin temperature test curves are obtained based on multiple monitoring points set during the test time; Similarity calculation is performed between the plurality of skin temperature test curves and the first prediction curve, and the skin temperature test curve with the highest similarity is selected as the skin temperature change curve.

[0048] In a possible implementation, multiple key feature points of the skin temperature change curve and multiple key feature points of the first prediction curve are extracted, and the multiple key feature points of the two are compared one by one to obtain a difference sequence between the skin temperature change curve and the first prediction curve; Based on the difference sequence, the default correction factor is adjusted to obtain the comprehensive correction factor; The first prediction curve is adjusted using a comprehensive correction factor to obtain a second prediction curve.

[0049] In a possible implementation, after controlling the heating module to perform hot compress heating based on the second prediction curve, the method further includes: Obtain feedback from target patients; The feedback information is matched with the power adjustment table to obtain the adjustment amplitude and adjustment rate corresponding to the feedback information.

[0050] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0051] The present application also discloses an electronic device. Figure 4 , Figure 4 The electronic device 400 may include: at least one processor 401 , at least one network interface 404 , a user interface 403 , a memory 405 , and at least one communication bus 402 .

[0052] The communication bus 402 is used to realize the connection and communication between these components.

[0053] The user interface 403 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 403 may also include a standard wired interface and a wireless interface.

[0054] The network interface 404 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0055] Among them, the processor 401 may include one or more processing cores. The processor 401 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 405, and calling data stored in the memory 405. Optionally, the processor 401 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 401 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 401, and it can be implemented separately through a chip.

[0056] Among them, the memory 405 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 405 includes a non-transitory computer-readable storage medium. The memory 405 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 405 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 405 may optionally also be at least one storage device located away from the aforementioned processor 401. Refer to Figure 4 , the memory 405 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a temperature control method of a physiotherapy hot compress patch.

[0057] exist Figure 4In the electronic device 400 shown, the user interface 403 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 401 can be used to call the application program storing a temperature control method of a physiotherapy hot compress patch in the memory 405, and when executed by one or more processors 401, the electronic device 400 executes one or more of the methods described in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited to the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0058] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0059] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0060] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0061] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0062] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0063] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0064] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not described in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A temperature control method for a physiotherapy hot compress patch, characterized in that: Applied to an MCU control module, the method includes: Obtaining basic information of the target patient, wherein the basic information includes a plurality of sub-basic information, and the plurality of sub-basic information includes hot compress site, age, gender, hot compress time and disease information; Based on the basic information, generating a first prediction curve of skin temperature change at the hot compress site; Controlling the heating module to perform skin testing on the hot compress area to obtain a skin temperature change curve; Based on the skin temperature change curve, the first prediction curve is corrected to generate a second prediction curve of the skin temperature change at the hot compress part; Based on the second prediction curve, the heating module is controlled to perform hot compress heating.

2. The method according to claim 1, characterized in that The first prediction curve of the skin temperature change at the hot compress site is generated based on the basic information, specifically: Querying the historical user information with the highest similarity to the basic information and the corresponding historical skin temperature change curve from the preset user information database, wherein the basic information and the historical user information each correspond to a similarity value on a plurality of sub-basic information; Based on the similarity values ​​of the plurality of sub-basic information, querying the preset user information database for a plurality of historical skin temperature change curves corresponding to each of the sub-basic information; Determining, according to the slope distribution of the plurality of historical skin temperature change curves corresponding to the plurality of sub-basic information, the influence coefficients of the plurality of sub-basic information on the historical skin temperature change curves corresponding to the historical user information; Based on the influence coefficients of the plurality of sub-basic information, the historical skin temperature change curve corresponding to the historical user information is adjusted to obtain the first prediction curve.

3. The method according to claim 2, characterized in that The adjusting the historical skin temperature change curve corresponding to the historical user information based on the influence coefficients of the plurality of sub-basic information to obtain the first prediction curve specifically includes: Performing principal component analysis on the plurality of sub-basic information to determine the main influence coefficient corresponding to each time point in the historical skin temperature change curve corresponding to the historical user information; Based on the main influence coefficient corresponding to each time point, the historical skin temperature change curve corresponding to the historical user information is adjusted to generate the first prediction curve.

4. The method according to claim 1, characterized in that The controlling the heating module to perform skin testing on the hot compress part specifically includes: Obtaining a time period corresponding to a fluctuation curve in the first prediction curve, and setting the time period corresponding to the fluctuation curve as a test time for the skin test; A plurality of monitoring points are set during the test time, wherein each monitoring point corresponds to a heating power; During the test, when the monitoring point is reached, the heating module is controlled to adjust to the heating power corresponding to each monitoring point.

5. The method according to claim 4, characterized in that The obtaining of the skin temperature change curve is specifically as follows: Based on the plurality of monitoring points set during the test time, a plurality of skin temperature test curves are obtained; Similarity calculation is performed between the plurality of skin temperature test curves and the first prediction curve, and the skin temperature test curve with the highest similarity is selected as the skin temperature change curve.

6. The method according to claim 1, characterized in that The step of correcting the first prediction curve based on the skin temperature change curve to generate a second prediction curve of the skin temperature change at the hot compress site specifically includes: Extracting a plurality of key feature points of the skin temperature change curve and a plurality of key feature points of the first prediction curve, and comparing the plurality of key feature points of the two one by one to obtain a difference sequence between the skin temperature change curve and the first prediction curve; Based on the difference sequence, the default correction factor is adjusted to obtain a comprehensive correction factor; The first prediction curve is adjusted using the comprehensive correction factor to obtain a second prediction curve.

7. The method according to claim 1, characterized in that After controlling the heating module to perform hot compress heating based on the second prediction curve, the method further includes: Obtain feedback from target patients; The feedback information is matched with a power adjustment table to obtain an adjustment amplitude and an adjustment rate corresponding to the feedback information.

8. A temperature control system for a physiotherapy hot compress patch, characterized in that: The system is an MCU control module, and the MCU control module comprises an acquisition module (1), a processing module (2) and a sending module (3), wherein: The acquisition module (1) is used to acquire basic information of the target patient, wherein the basic information includes a plurality of sub-basic information, and the plurality of sub-basic information includes hot compress site, age, gender, hot compress time and disease information; The processing module (2) is used to generate a first prediction curve of skin temperature change at the hot compress site based on the basic information; control the heating module to perform a skin test on the hot compress site to obtain a skin temperature change curve; and correct the first prediction curve based on the skin temperature change curve to generate a second prediction curve of skin temperature change at the hot compress site; The sending module (3) is used to control the heating module to perform hot compress heating based on the second prediction curve.

9. An electronic device, characterized in that: The electronic device (400) comprises a processor (401), a memory (405), a user interface (403) and a network interface (404), wherein the memory (405) is used to store instructions, the user interface (403) and the network interface (404) are used to communicate with other devices, and the processor (401) is used to execute the instructions stored in the memory (405) so that the electronic device (400) executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

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