Joint injury early warning system and device based on temperature-pressure sensing
Through the temperature-pressure-aware joint damage warning system, data is collected using a flexible composite sensor, combined with the space-time registration matrix and damage index judgment, the problem of low warning accuracy in the existing technology is solved, and a higher success rate and comfort of damage identification are achieved.
Patent Information
- Application Number
- CN202510849861.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-24
- Publication Date
- 2025-08-15
AI Technical Summary
The existing joint injury warning system leads to low warning accuracy through single mechanical detection or single temperature detection, which easily falsely predicts fatigue caused by normal movement as damage.
A joint injury warning system based on temperature-pressure perception is adopted. The temperature and pressure at the joint are collected through a flexible composite sensor, a spatiotemporal registration matrix is established, the temperature gradient and distribution entropy are calculated, and the damage type is judged and early warning is performed based on the joint damage index and standardized values.
The detection rate of acute ligament tear is improved, the success rate of injury identification is enhanced, and the comfort and signal stability of the person to be tested is improved through flexible load sensors.
Smart Images
Figure CN120477718A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of data processing technology, and specifically to a joint injury early warning system and device based on temperature-pressure perception. Background Art
[0002] Rehabilitation robots are currently a crucial topic for early warning of joint injuries. They can monitor ligament load and inflammation in real time during training, preventing acute injuries like anterior cruciate ligament tears. They can also provide dynamic home assessments for patients with osteoarthritis and rheumatoid arthritis, optimizing medication and rehabilitation plans. Therefore, a joint injury system is needed.
[0003] Existing joint injuries are mostly detected through single mechanical testing or single temperature testing, which leads to inaccurate early warning of joint injuries and may mistakenly report fatigue caused by normal exercise as injury. Summary of the Invention
[0004] In order to solve the technical problem of low early warning accuracy, this application provides a joint injury early warning system and device based on temperature-pressure sensing. The technical solutions adopted are as follows:
[0005] In the first aspect, the present application proposes a joint injury early warning system based on temperature-pressure perception, which includes the following modules:
[0006] The data acquisition module collects the temperature and pressure of the joints of the person being tested through a flexible composite sensor, and establishes a spatiotemporal registration matrix to match the temperature and pressure;
[0007] The injury identification module calculates the temperature gradient and distribution entropy based on all temperatures and pressures collected at the same time; and calculates the joint injury index based on the temperature gradient and distribution entropy;
[0008] The damage identification and correction module collects the average temperature values at different times to calculate the base temperature value; calculates the temperature fluctuation value based on the base temperature value; and calculates the normalized value based on the difference between the temperature at each time and the base temperature value and the fluctuation value;
[0009] The damage type judgment module determines the damage type based on the correlation between all pressures and temperatures at the same time;
[0010] The injury warning module provides injury warning based on joint injury coefficient and standardization, and gives suggestions based on the injury type.
[0011] In the above scheme, this application improves the detection rate of acute ligament tears through dual-modal fusion, and through the spatiotemporal registration matrix, it allows pressure and temperature to collect data without delay at the same location, and then based on the correlation analysis of pressure and temperature, it makes the success rate of specific injury identification higher. In addition, this application greatly improves the comfort of the person to be tested by using flexible load sensors, and makes the signal stability higher when the person to be tested moves slightly.
[0012] In one embodiment, the base material of the flexible load sensor is a polyimide (PI) film; the temperature unit is composed of an NTC thermistor array; and the pressure unit is a piezoresistive nanosilver wire grid.
[0013] In one embodiment, the thickness of the polyimide film is 0.1 mm, and the bending radius is less than or equal to 3 mm; the accuracy of the NTC thermistor array is 0.1 degrees Celsius; the range of the piezoresistive nanosilver wire grid is 0 to 100 kPa, and the sensitivity is 0.35 kPa -1 PVDF piezoelectric fiber power density is 0.8mW / cm 3 .
[0014] In one embodiment, the joint damage index is positively correlated with the temperature gradient and negatively correlated with the distribution entropy of pressure.
[0015] In one embodiment, the method for collecting the average temperature values at different times to calculate the base temperature value is:
[0016] All temperature values at each moment are calculated as the temperature at each moment; the average value of the temperatures collected at multiple moments is calculated as the temperature base value.
[0017] In one embodiment, the method for calculating the temperature fluctuation value according to the temperature base value is:
[0018] The temperature standard deviation is calculated based on the temperature of each measurement and the temperature base value, and the obtained standard deviation is used as the fluctuation value.
[0019] In one embodiment, the method for calculating the normalized value based on the difference between the temperature at each moment and the temperature base value and the fluctuation value is:
[0020] T new represents the temperature measured after exercise, μ T represents the base temperature value, σ T represents the fluctuation value, T n Represents a normalized value.
[0021] In one embodiment, the correlation coefficient is calculated using the Pearson correlation coefficient.
[0022] In one embodiment, in the injury warning module, when the joint injury index is greater than 0.7 and the standardized value is greater than 2, the rehabilitation robot will issue a warning to the person being tested; after the warning, when the correlation coefficient is greater than or equal to 0.8, it is mechanical damage, and the rehabilitation robot will give mechanical intervention suggestions; if the correlation coefficient is less than or equal to 0.3, it is inflammatory damage, and the rehabilitation robot will give anti-inflammatory treatment suggestions; when the correlation coefficient is between 0.3-0.8, the injury is in the latent period.
[0023] On the other hand, an embodiment of the present application also provides a joint injury warning device based on temperature-pressure perception, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements a module of a joint injury warning system based on temperature-pressure perception as described above.
[0024] The beneficial effects of this application are:
[0025] This application improves the detection rate of acute ligament tears through dual-modal fusion, and through the spatiotemporal registration matrix, it allows pressure and temperature data to be collected without delay at the same location. The subsequent correlation analysis based on pressure and temperature makes the success rate of specific injury identification higher. This application also greatly improves the comfort of the person to be tested by using flexible load sensors, and makes the signal stability higher when the person to be tested moves slightly. BRIEF DESCRIPTION OF THE DRAWINGS
[0026] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0027] Figure 1 This is a flow chart of a joint injury warning system based on temperature-pressure perception provided in one embodiment of the present application. DETAILED DESCRIPTION
[0028] In order to further illustrate the technical means and effects adopted by this application to achieve the predetermined invention purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features and effects of the joint injury early warning system and device based on temperature-pressure sensing proposed in this application. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics of one or more embodiments may be combined in any suitable form.
[0029] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
[0030] Embodiments of a joint injury early warning system and device based on temperature-pressure sensing:
[0031] The specific scheme of the joint injury early warning system based on temperature-pressure perception provided by this application is described in detail below with reference to the accompanying drawings.
[0032] See also Figure 1 , which shows a flow chart of a joint injury early warning system based on temperature-pressure sensing provided by an embodiment of the present application. The system includes the following modules:
[0033] The data acquisition module in this application consists of a sensing layer and a processing layer. The sensing layer primarily consists of a flexible load sensor array. The rehabilitation robot uses this sensing layer to contact human joints, thereby collecting information from these joints. The flexible load sensor's base material is polyimide (PI) film; the temperature unit is an NTC thermistor array; the pressure unit is a piezoresistive silver nanowire grid; and the sensing layer also includes embedded PVDF piezoelectric fibers to convert walking kinetic energy into electrical energy.
[0034] In this embodiment, the thickness of the polyimide film is 0.1 mm, and the bending radius is less than or equal to 3 mm; the accuracy of the NTC thermistor array is 0.1 degrees Celsius; the range of the piezoresistive nanosilver wire grid is 0 to 100 kPa, and the sensitivity is 0.35 kPa -1 PVDF piezoelectric fiber power density is 0.8mW / cm 3 .
[0035] A spatiotemporal registration matrix is established, and the temperature and pressure sampling points are collected at the same time and location. In this embodiment, the number of sampling points is 50. When measuring the temperature and pressure of the person being measured, the person is required to sit still for a period of time to ensure that the initial temperature and pressure distribution is not affected by other factors.
[0036] In this way, the pressure and temperature of the joints of the person being tested are collected through the sensing layer.
[0037] At this point, the temperature and pressure at the joint are collected.
[0038] The damage identification module constructs a temperature distribution map and a pressure thermodynamic map for all temperatures and pressures collected at the current moment.
[0039] Through the analysis of the temperature distribution diagram, it can be seen that when the joint is normal, the temperature of the temperature distribution diagram is relatively even. However, if there is damage, the temperature distribution in the temperature distribution diagram will change. For example, in acute injury, a "focal high temperature area" will appear, and in chronic injury, a "crater-like distribution" (a high temperature band in the center and a low temperature ring on the periphery) will appear. That is, the damaged part of the joint will have a high temperature due to inflammation, and the rest of the body will be at a low temperature.
[0040] Therefore, for the temperature distribution graph obtained from all temperatures collected at each moment, the temperature gradient is calculated for the temperature distribution graph. The temperature gradient reflects the temperature difference between the center and the periphery of the temperature distribution graph. The larger the temperature gradient, the more it indicates that the joint is damaged.
[0041] Through the analysis of pressure thermodynamic maps, it can be seen that healthy joints show a "symmetrical butterfly-shaped" distribution, while injured joints show abnormal patterns such as "unilateral high-pressure island" or "dumbbell-shaped high-pressure band".
[0042] Therefore, for the pressure heat map composed of all pressures collected at each moment, the distribution entropy of all pressures is calculated. The distribution entropy reflects the uniformity of pressure. The pressure of healthy joints is uniform and has a high degree of uniformity, while the uniformity of damaged joints is low. Therefore, the smaller the information entropy, the more it indicates that the joint is damaged.
[0043] The joint damage index is constructed based on the temperature gradient and the distribution entropy of pressure.
[0044] The joint damage index is positively correlated with the temperature gradient and negatively correlated with the distribution entropy of pressure.
[0045] It should be noted that positive correlation means that when one variable increases, the other variable also increases, and the two variables change in the same direction. When one variable changes from large to small or from small to large, the other variable also changes from large to small or from small to large; the specific relationship is determined by actual application and this application does not impose any special restrictions.
[0046] It should be noted that negative correlation means that when one variable increases, the other variable decreases accordingly, and the two variables change in opposite directions. When one variable changes from large to small or from small to large, the other variable also changes from small to large or from large to small. The specific relationship is determined by actual application and this application does not impose any special restrictions.
[0047] Preferably, in this embodiment, the expression of the joint damage index is:
[0048] DI = a1×ΔT+a2×(1-Hp), ΔT represents the temperature gradient, Hp represents the distribution entropy of pressure, a1 and a2 are weight coefficients, and DI is the joint injury index; the values of a1 and a2 are 0.7 and 0.3 respectively, that is, higher weight is given to temperature and lower weight is given to pressure.
[0049] At this point, the joint damage index of the person being tested is obtained.
[0050] Injury identification and correction module, since different people have different body temperature characteristics, for example, athletes have a low basal body temperature but large fluctuations, and the elderly have a high and unstable basal body temperature. In order to prevent false alarms, this application performs secondary injury identification on the person being tested.
[0051] First, calculate all the temperature values at each moment as the temperature at each moment. Measure the temperature of the person being measured multiple times. Calculate the average of all the measured temperatures as the base temperature value, which is the temperature benchmark for the person being measured.
[0052] The temperature standard deviation is then calculated based on each measured temperature and the base temperature value, and the resulting standard deviation is used as the fluctuation value. This means that when the person being measured is sitting still, the temperature value will only fluctuate within the fluctuation value range.
[0053] After the person under test has performed a certain amount of exercise, the rehabilitation robot is used again to obtain their temperature at each moment. The temperature at that moment is then compared with the temperature reference and fluctuation value to obtain a standardized value.
[0054] The expression of the normalized value is:
[0055] T new represents the temperature measured after exercise, μ T represents the base temperature value, σ T represents the fluctuation value, T n Represents a normalized value.
[0056] The normalized value represents a multiple of the fluctuation value. For example, a normalized value of 1 indicates that the temperature fluctuation of the joint after exercise is within the fluctuation value range; a normalized value of 2 indicates that the temperature fluctuation of the joint after exercise is within 2 times the fluctuation value range. Existing data shows that if the joints of the human body are not damaged after exercise, the normalized value will not be greater than 2.
[0057] Therefore, a secondary judgment can be made based on the normalized value.
[0058] At this point, the standardized value is obtained.
[0059] The injury type determination module uses a correlation between pressure and temperature, as joint injuries can be classified as either mechanical or inflammatory. For example, in acute ligament tears, concentrated mechanical stress directly leads to local tissue damage and acute inflammation. Consequently, high-pressure and high-temperature areas completely overlap, resulting in a positive correlation between temperature and pressure. In late-stage osteoarthritis, the subchondral bone sclerosis region experiences extremely high pressure, but a lack of blood flow causes a decrease in temperature, resulting in a negative correlation.
[0060] Therefore, the damage type is judged based on the correlation between pressure and temperature. Therefore, for all temperatures and pressures collected at the current moment, the correlation coefficient between pressure and temperature is obtained through a correlation algorithm. In this embodiment, the correlation coefficient is obtained by the Pearson correlation coefficient.
[0061] At this point, the damage type can be determined based on the correlation coefficient.
[0062] Injury warning module: when the joint injury index is greater than 0.7 and the standardized value is greater than 2, the rehabilitation robot will issue an early warning to the person being tested.
[0063] In addition, after the early warning, when the correlation coefficient is greater than or equal to 0.8, it is considered to be mechanical injury, and the rehabilitation robot will give mechanical intervention suggestions; if the correlation coefficient is less than or equal to 0.3, it is considered to be inflammatory injury, and the rehabilitation robot will give anti-inflammatory treatment suggestions; when the correlation coefficient is between 0.3-0.8, the injury is considered to be in the latent period.
[0064] At this point, the damage warning is completed.
[0065] Based on the same inventive concept as the above method, an embodiment of the present invention also provides a joint injury warning device based on temperature-pressure perception, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements any one of the modules in the above-mentioned joint injury warning system based on temperature-pressure perception.
[0066] It should be noted that the above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the scope of protection of the present application.
[0067] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.
Claims
1. A joint injury early warning system based on temperature-pressure sensing, characterized in that: The system includes the following modules: The data acquisition module collects the temperature and pressure of the joints of the person being tested through a flexible composite sensor, and establishes a spatiotemporal registration matrix to match the temperature and pressure; The injury identification module calculates the temperature gradient and distribution entropy based on all temperatures and pressures collected at the same time; and calculates the joint injury index based on the temperature gradient and distribution entropy; The damage identification and correction module collects the average temperature values at different times to calculate the base temperature value; calculates the temperature fluctuation value based on the base temperature value; and calculates the normalized value based on the difference between the temperature at each time and the base temperature value and the fluctuation value; The damage type judgment module determines the damage type based on the correlation between all pressures and temperatures at the same time; The injury warning module provides injury warning based on joint injury coefficient and standardization, and gives suggestions based on the injury type.
2. The temperature-pressure sensing-based joint injury early warning system according to claim 1, characterized in that: The base material of the flexible load sensor is a polyimide (PI) film; the temperature unit is composed of an NTC thermistor array; and the pressure unit is a piezoresistive nanosilver wire grid.
3. The joint injury early warning system based on temperature-pressure sensing according to claim 1, characterized in that: The polyimide film has a thickness of 0.1 mm and a bending radius of 3 mm or less. The NTC thermistor array has an accuracy of 0.1 degrees Celsius. The piezoresistive nanosilver wire grid has a range of 0 to 100 kPa and a sensitivity of 0.35 kPa. -1 PVDF piezoelectric fiber power density is 0.8mW / cm 3 .
4. The joint injury early warning system based on temperature-pressure sensing according to claim 1, characterized in that: The joint damage index is positively correlated with the temperature gradient and negatively correlated with the distribution entropy of pressure.
5. The joint injury early warning system based on temperature-pressure sensing according to claim 1, characterized in that: The method for collecting the temperature mean at different times to calculate the temperature base value is: All temperature values at each moment are calculated as the temperature at each moment; the average value of the temperatures collected at multiple moments is calculated as the temperature base value.
6. The joint injury early warning system based on temperature-pressure sensing according to claim 1, characterized in that: The method for calculating the temperature fluctuation value according to the temperature base value is: The temperature standard deviation is calculated based on the temperature of each measurement and the temperature base value, and the obtained standard deviation is used as the fluctuation value.
7. A joint injury early warning system based on temperature-pressure sensing as claimed in claim 6, characterized in that: The method for calculating the normalized value based on the difference between the temperature at each moment and the temperature base value and the fluctuation value is: T new represents the temperature measured after exercise, μ T represents the base temperature value, σ T represents the fluctuation value, T n Represents a normalized value.
8. The joint injury early warning system based on temperature-pressure sensing as claimed in claim 1, characterized in that: The correlation coefficient is calculated using the Pearson correlation coefficient.
9. The joint injury early warning system based on temperature-pressure sensing according to claim 1, characterized in that: In the injury warning module, when the joint injury index is greater than 0.7 and the standardized value is greater than 2, the rehabilitation robot will issue a warning to the person being tested; after the warning, when the correlation coefficient is greater than or equal to 0.8, it is mechanical damage, and the rehabilitation robot will give mechanical intervention suggestions; if the correlation coefficient is less than or equal to 0.3, it is inflammatory damage, and the rehabilitation robot will give anti-inflammatory treatment suggestions; when the correlation coefficient is between 0.3-0.8, the injury is in the latent period.
10. A joint injury warning device based on temperature-pressure sensing, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, it implements a module of a joint injury early warning system based on temperature-pressure perception as described in any one of claims 1-9.