A treatment method and system based on automated spectrum infrared rehabilitation equipment

Abstract

This invention relates to the field of rehabilitation equipment technology, and more specifically, to a treatment method and system based on an automated spectrum infrared rehabilitation device. The method includes: acquiring infrared thermograms of a patient's body and calculating the reliability of the infrared thermograms, wherein the reliability is negatively correlated with the patient's heart rate and current room temperature; acquiring images of the infrared thermograms within a preset time period whose reliability is greater than a preset threshold, using these as target images, and performing grayscale processing on the target images to obtain grayscale images; and performing edge detection on the grayscale images to extract lesion regions. This invention calculates the degree of abnormality in the lesion region by using the maximum grayscale value of pixels in the lesion region and the variance of the grayscale values ​​of all pixels, and uses the degree of abnormality in the lesion region to weight and correct the power emitted by the spectrum infrared device, thereby improving the treatment effect on the patient's lesion region.

Description

Technical Field

[0001] This invention relates to the field of rehabilitation equipment technology. More specifically, this invention relates to a treatment method and system based on an automated spectral infrared rehabilitation device. Background Technology

[0002] Traditional rehabilitation therapy methods mainly include physical therapy, drug therapy, and surgical treatment. While these methods can alleviate patients' symptoms, their therapeutic effects are limited and they have certain side effects. In recent years, with the continuous development of artificial intelligence technology, rehabilitation therapy equipment based on infrared thermal imaging technology and bio-wave therapy technology has gradually become a research hotspot.

[0003] In related technologies, for example, Chinese patent document with publication number CN221867134U discloses an automated spectrum infrared rehabilitation bed device. This patent document uses the structure of the adjusting component and the treatment component to adjust the height of the treatment component, so that the treatment component is close to or far away from the human body. When the treatment component irradiates the human patient, it can play a therapeutic role on the patient's lesion. Moreover, the treatment component can be moved to the patient's lesion part by sliding rails and sliders, so as to accurately treat the patient's lesion.

[0004] When using infrared rehabilitation equipment, it is necessary to locate the affected areas on the patient's body using a thermal imaging camera before performing infrared treatment. However, the ambient temperature and the patient's level of anxiety during the treatment can affect the patient's physical condition and thus the identification of the affected areas, resulting in poor treatment outcomes. Summary of the Invention

[0005] This invention provides a treatment method and system based on an automated spectrum infrared rehabilitation device, aiming to solve the problem in related technologies that the ambient temperature and the patient's stress level during medical treatment can affect the patient's body and thus affect the identification of the patient's lesion site, resulting in poor treatment effect.

[0006] In a first aspect, the present invention provides a treatment system based on an automated spectrum infrared rehabilitation device, comprising a processor and a memory, characterized in that the automated spectrum infrared rehabilitation device includes an infrared spectrum shield 14 for emitting infrared rays, the memory stores a computer program, and the processor executes the computer program to implement the following method, the method comprising: acquiring an infrared thermogram of a patient's body and calculating the reliability of the infrared thermogram, the reliability being negatively correlated with the patient's heart rate and current room temperature; acquiring an image of the infrared thermogram with a reliability greater than a preset threshold within a preset time period as a target image, and performing grayscale processing on the target image to obtain a grayscale image; performing edge detection on the grayscale image to extract lesion regions, and calculating the abnormality degree of the lesion regions, the abnormality degree being positively correlated with the ratio of the maximum grayscale value of pixels in the lesion regions to the variance of the grayscale values ​​of all pixels; weighting the basic treatment power of infrared light according to the abnormality degree of the lesion regions to obtain a final treatment power, and treating the lesion regions based on the final treatment power of the infrared light.

[0007] Furthermore, the final treatment power is calculated using the following formula: In the formula, The final treatment power for lesion area i. The degree of abnormality in lesion region i. This is the basic treatment power for infrared rehabilitation equipment.

[0008] Furthermore, the degree of abnormality in lesion region i is calculated using the following formula: In the formula, This indicates the degree of abnormality in lesion region i. This represents the maximum grayscale value of the pixel in the lesion region i. This represents the number of pixels in lesion region i. This represents the grayscale value of pixel C. This represents the average grayscale value of all pixels in the lesion region i. This represents the standard normalization function.

[0009] Furthermore, it also includes: in response to the situation where the confidence level of multiple infrared thermal images is greater than a preset threshold within a preset time period, selecting the image with the lowest confidence level among the multiple infrared thermal images as the target image.

[0010] Furthermore, the reliability of the infrared thermal image is calculated using the following formula: In the formula, This indicates the confidence level of the i-th infrared thermal image. This represents the heart rate within a preset time period before acquiring the i-th infrared thermal image. This represents the average indoor temperature within a preset time period before acquiring the i-th infrared thermal image.

[0011] Furthermore, the empirical value for the preset time is 60 seconds.

[0012] Furthermore, edge detection is performed on the grayscale image, including: edge detection of the grayscale image using the Canny edge detection method.

[0013] Furthermore, the empirical value of the preset threshold is 0.3.

[0014] Furthermore, extracting the lesion area also includes: obtaining the coordinates of the center point of the lesion area, and controlling the infrared spectrum cover 14 to move to the lesion area to treat the lesion area.

[0015] Beneficial effects:

[0016] (i) Based on the temperature environment and heart rate of the patient when the infrared thermogram of the patient's body is collected, the reliability of the infrared thermogram is calculated, and the infrared thermogram with the highest reliability is selected, which improves the accuracy of subsequent calculation of the degree of abnormality in the lesion area.

[0017] (ii) The maximum gray value of the pixel in the lesion area and the variance of the gray values ​​of all pixels are used to calculate the degree of abnormality of the lesion area. The degree of abnormality of the lesion area is then used to weight and correct the power emitted by the spectrum infrared device, thereby improving the treatment effect on the lesion area of ​​the patient. Attached Figure Description

[0018] By referring to the accompanying drawings, several embodiments of the invention are illustrated by way of example and not limitation, and the same or corresponding reference numerals denote the same or corresponding parts, wherein:

[0019] Figure 1 This is a schematic diagram illustrating an infrared rehabilitation device according to an embodiment of the present invention;

[0020] Figure 2 This is a flowchart illustrating the calculation of the final treatment power according to an embodiment of the present invention.

[0021] Figure Labels

[0022] 11. Infrared rehabilitation equipment; 12. Bed board; 13. Slide rail; 14. Infrared spectrum cover; 15. Camera device. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] like Figure 1 As shown, in one embodiment, the infrared rehabilitation device 11 includes a bed board 12, a camera device 15, and an infrared spectrum cover 14. The infrared spectrum cover 14 can concentrate infrared energy within a specific range to improve the therapeutic effect. The infrared rays emitted by the infrared spectrum cover 14 irradiate the patient, which can have a therapeutic effect on the affected area. A slide rail 13 is provided on the bed board 12, and the infrared spectrum cover 14 is mounted on the slide rail 13. The slide rail 13 can move the infrared spectrum cover 14 to the patient's affected area for treatment. Specifically, the patient lies on the bed board 12, and the camera device 15 identifies the patient's affected area. Then, the slide rail 13 is controlled to move the infrared spectrum cover 14 to the patient's affected area, and finally, the infrared spectrum cover 14 emits infrared rays to treat the affected area. In this embodiment, the camera device 15 is an infrared thermal imaging camera. An infrared thermal imager is an instrument specifically used to capture and display infrared thermal images radiated by objects. These devices can detect infrared radiation emitted from the human body surface and convert it into a visible thermal image. This image can be used to display a thermal map of the human body temperature distribution in real time and can be used to analyze the thermal image to identify specific areas of temperature difference, thus facilitating the diagnosis of lesions.

[0025] In one embodiment, when using the infrared rehabilitation device 11, it is necessary to locate the affected area on the patient's body using a thermal imaging camera before applying infrared therapy. However, the ambient temperature and the patient's level of anxiety during the consultation can affect the patient's physical condition, thus impacting the identification of the affected area and resulting in poor treatment outcomes. Therefore, the following steps are adopted to improve the treatment effect on the patient.

[0026] like Figure 2 As shown, S101: Acquire an infrared thermogram of the patient's body.

[0027] In one embodiment, the patient lies supine on the bed board 12 of the infrared rehabilitation device 11. Infrared thermal images of the patient's body are captured by a camera device 15 at preset time intervals within a preset time period. The patient's heart rate and room temperature are also recorded within a preset time period prior to the acquisition of the thermal image. The room temperature can be obtained using a temperature sensor positioned on one side of the bed board 12, close to the patient's body, enabling the measurement of the temperature near the patient and improving the accuracy of subsequent treatment steps.

[0028] Collecting a patient's heart rate, including through mattress sensors, is a non-invasive and comfortable health monitoring method. These technologies typically utilize devices such as pressure sensors, capacitive sensors, or accelerometers to monitor and analyze a patient's physiological signals, particularly heart rate, in real time. For example, pressure sensors are commonly used to detect pressure changes on a mattress. Each time the heart beats, blood is pumped throughout the body, especially to the chest area, and the body's minute vibrations create slight pressure fluctuations on the mattress surface. These fluctuations can be captured by pressure sensors. Pressure sensors can monitor in real time based on changes in body weight, breathing, and the slight pressure fluctuations caused by heartbeats. By analyzing these minute pressure changes on the mattress surface, the sensor can calculate the heart rate.

[0029] In one embodiment, it should be noted that the patient's heart rate and room temperature are collected within a preset time before the infrared thermogram is acquired. The preset time is 60 seconds. The reason for this is that the normal heart rate of a human body refers to the number of heartbeats per minute in a normal person at rest. Therefore, using 60 seconds makes it easier to count the patient's heart rate.

[0030] S102: Filter out the target image.

[0031] In one embodiment, after acquiring an infrared thermogram of the patient's body, it is necessary to identify the lesion area based on the temperature distribution of the infrared thermogram. However, if the patient is in a high-temperature environment when acquiring the infrared thermogram, or if the patient's heart rate increases due to stress, leading to faster blood flow and higher body temperature, this will affect the overall temperature of the subsequent infrared thermogram and the accuracy of calculating the degree of abnormality in the lesion area. Therefore, it is necessary to calculate the reliability of the infrared thermogram, which is negatively correlated with the patient's heart rate and the current room temperature.

[0032] In one embodiment, the reliability of each infrared thermogram within a preset time period can be calculated. Higher room temperature and a higher patient heart rate indicate that the patient's body temperature is higher than normal, and the reliability of the infrared thermogram acquired in this case is lower. Conversely, lower room temperature and a more normal patient heart rate indicate that the patient's body temperature is closer to normal, and the reliability of the infrared thermogram acquired in this case is higher.

[0033] In one embodiment, the confidence level of the infrared thermal image is calculated using the following formula: In the formula, This indicates the confidence level of the i-th infrared thermal image. This represents the heart rate within a preset time period before acquiring the i-th infrared thermal image. This represents the average indoor temperature within a preset time period before acquiring the i-th infrared thermal image.

[0034] In another embodiment, the formula for calculating the confidence level of an infrared thermal image can also be transformed as follows: ; In the formula, This indicates the confidence level of the i-th infrared thermal image. This represents the heart rate within a preset time period before acquiring the i-th infrared thermal image. Standard heart rate This represents the average indoor temperature within a preset time period before acquiring the i-th infrared thermogram. In this embodiment, the normal heart rate for an adult is 60-100 beats per minute, so the median value can be used as the standard heart rate, for example, the standard heart rate A is 80. By using the above calculation formula, the standard heart rate of the human body is taken into account. The reliability of the infrared thermogram is calculated based on the difference between the current patient's heart rate and the standard heart rate, thus improving the accuracy of the calculation.

[0035] In one embodiment, images with a confidence level greater than a preset threshold within a preset time period are selected as target images. However, if multiple infrared thermal images within the preset time period have a confidence level greater than the preset threshold, the image with the lowest confidence level among the multiple infrared thermal images is selected as the target image. In this embodiment, the empirical value of the preset threshold is 0.8. In other embodiments, the empirical value of the preset threshold can be 0.85 or 0.9, etc., and can be adjusted according to the specific implementation.

[0036] For example, with a preset time period of 5 minutes, an infrared thermogram of the patient's body is acquired every 60 seconds, for a total of five infrared thermograms. The confidence level of the first infrared thermogram is then calculated as follows: The credibility of the second infrared thermal image is... The credibility of the third infrared thermal image is... The credibility of the fourth infrared thermal image is: The credibility of the fifth infrared thermal image is .like , and If all values ​​are greater than the preset threshold, then a comparison is made. , and The size of the values ​​is used to select the infrared thermal image corresponding to the largest value as the target image.

[0037] In another embodiment, after calculating the confidence level of multiple infrared thermal images within a preset time period, the image with the lowest confidence level among the multiple infrared thermal images can be directly selected as the target image.

[0038] S103: Extract the lesion area from the target image.

[0039] In one embodiment, infrared thermal imaging indirectly reflects physiological changes within the body by measuring the temperature distribution on the body surface. Areas with higher temperatures may be due to the following reasons: Inflammation: Inflammation typically leads to increased local blood flow, causing a rise in temperature in the area. In infrared thermal images, inflamed areas may appear as areas with higher temperatures. Tumors: Tumor tissue, especially malignant tumors, may also cause local temperature increases due to increased angiogenesis or metabolism; these areas may appear as warmer in thermal imaging. Infection: Local immune responses caused by infection can also lead to fever, resulting in an increase in temperature in the affected area. Therefore, lesion areas can be extracted based on the temperature distribution in the image.

[0040] In one embodiment, extracting the lesion region from the target image first requires converting the target image to grayscale. The main purpose of grayscale conversion is to transform a color image into a grayscale image, where the value of each pixel represents brightness or temperature intensity (grayscale value). A higher grayscale value indicates a higher temperature. Furthermore, for pixel-based grayscale value-based segmentation and analysis algorithms (such as thresholding and edge detection), grayscale images reduce processing complexity. This facilitates subsequent extraction of the lesion region and calculation of its abnormality level.

[0041] In one embodiment, the target image is converted to grayscale to obtain a grayscale image. Edge detection is then performed on the grayscale image to extract the lesion region. The Canny edge detection method can be used to perform edge detection on the grayscale image to obtain the lesion region. It should be noted that before performing edge detection on the grayscale image, a filter (such as a Gaussian filter) can be used to smooth the image to reduce the impact of noise on edge detection.

[0042] S104: Calculate the degree of abnormality in the lesion area.

[0043] In one embodiment, after edge detection of the grayscale image, at least one lesion region is obtained. Then, the degree of abnormality of each lesion region is calculated. The degree of abnormality is positively correlated with the ratio of the maximum grayscale value of a pixel in the lesion region to the variance of the grayscale values ​​of all pixels. The larger the grayscale value of a pixel in the lesion region, the higher the temperature of the lesion region, indicating a more severe condition. Therefore, the degree of abnormality of each lesion region can be calculated to characterize the severity of the condition.

[0044] In one embodiment, the degree of abnormality in each lesion region is calculated using the following formula: In the formula, This indicates the degree of abnormality in lesion region i. This represents the maximum grayscale value of the pixel in the lesion region i. This represents the number of pixels in lesion region i. This represents the grayscale value of pixel C. This represents the average grayscale value of all pixels in the lesion region i. This represents the standard normalization function.

[0045] in, The larger the value of , the higher the maximum temperature value of lesion region i, indicating the presence of severely affected areas within the lesion region, and thus a greater degree of abnormality in lesion region i. The larger the variance of the grayscale values ​​of all pixels in the lesion region, the greater the fluctuation in the grayscale values ​​of all pixels in the lesion region, meaning there are temperatures significantly different from the maximum temperature value (i.e., lower temperatures exist), and in this case, the less abnormal the lesion region i is. Conversely, the smaller the variance of the grayscale values ​​of all pixels in the lesion region, the smaller the fluctuation in the grayscale values ​​of all pixels in the lesion region, meaning there are more temperatures close to the maximum temperature value, and in this case, the overall temperature of lesion region i is higher, and the greater the degree of abnormality in lesion region i.

[0046] S105: Weight the basic treatment power of the infrared rehabilitation device 11 to obtain the final treatment power.

[0047] In one embodiment, the baseline treatment power of infrared light is weighted according to the degree of abnormality of the lesion area to obtain the final treatment power, and the lesion area is treated based on the final treatment power of infrared light.

[0048] In one embodiment, the final treatment power is calculated using the following formula: In the formula, The final treatment power for lesion area i. The degree of abnormality in lesion region i. This is the basic treatment power for the infrared rehabilitation device 11.

[0049] In one embodiment, after obtaining the lesion area, the coordinates of the center point of the lesion area can be obtained, and the infrared spectrum cover 14 can be controlled to move to the lesion area. Then, the infrared spectrum cover 14 can be controlled to emit infrared rays according to the final treatment power to treat the lesion area.

[0050] The present invention also provides a treatment system based on an automated spectral infrared rehabilitation device, the system comprising a processor and a memory, the memory storing computer program instructions, which, when executed by the processor, implement a treatment method based on an automated spectral infrared rehabilitation device according to the first aspect of the present invention.

[0051] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and therefore will not be described in detail here.

[0052] In this invention, the aforementioned memory can be any tangible medium containing or storing a program that can be used or combined with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc., or any other medium that can be used to store desired information and can be accessed by an application, module, or both. Any such computer storage medium can be part of a device or accessible to or connected to a device. Any application or module described in this invention can be implemented using computer-readable / executable instructions that can be stored or otherwise maintained by such a computer-readable medium.

[0053] In the description of this specification, "multiple" or "several" means at least two, such as two, three or more, unless otherwise explicitly specified.

[0054] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0055] The embodiments described above are merely examples of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A treatment system based on an automated spectral infrared rehabilitation device, comprising a processor and a memory, characterized in that, The automated infrared spectrum rehabilitation device includes an infrared spectrum shield for emitting infrared rays, the memory stores a computer program, and the processor executes the computer program to implement the following method, the method comprising: Infrared thermograms of the patient's body are acquired, and the reliability of the infrared thermograms is calculated. The reliability is negatively correlated with the patient's heart rate and the current room temperature. The infrared thermal image with a confidence level greater than a preset threshold within a preset time period is acquired as the target image, and the target image is grayscale processed to obtain a grayscale image. Edge detection is performed on the grayscale image to extract the lesion region, and the degree of abnormality of the lesion region is calculated. The degree of abnormality is positively correlated with the ratio of the maximum grayscale value of the pixels in the lesion region to the variance of the grayscale values ​​of all pixels. The base treatment power of infrared light is weighted according to the degree of abnormality in the lesion area to obtain the final treatment power.

2. The treatment system based on automated spectrum infrared rehabilitation equipment according to claim 1, characterized in that, The final treatment power is calculated using the following formula: ； In the formula, The final treatment power for lesion area i. The degree of abnormality in lesion region i. This is the basic treatment power for infrared rehabilitation equipment.

3. The treatment system based on automated spectrum infrared rehabilitation equipment according to claim 2, characterized in that, The degree of abnormality in lesion region i is calculated using the following formula: ; In the formula, This indicates the degree of abnormality in lesion region i. This represents the maximum grayscale value of the pixel in the lesion region i. This represents the number of pixels in lesion region i. This represents the grayscale value of pixel C. This represents the average grayscale value of all pixels in the lesion region i. This represents the standard normalization function.

4. The treatment system based on automated spectrum infrared rehabilitation equipment according to claim 1, characterized in that, Also includes: In response to the situation where the confidence level of multiple infrared thermal images is greater than a preset threshold within a preset time period, the image with the lowest confidence level among the multiple infrared thermal images is selected as the target image.

5. The treatment system based on automated spectrum infrared rehabilitation equipment according to claim 1, characterized in that, The confidence level of the infrared thermal image is calculated using the following formula: ； In the formula, This indicates the confidence level of the i-th infrared thermal image. This represents the heart rate within a preset time period before acquiring the i-th infrared thermal image. This represents the average indoor temperature within a preset time period before acquiring the i-th infrared thermal image. It is represented as a normalization function.

6. The treatment system based on automated spectrum infrared rehabilitation equipment according to claim 5, characterized in that, The preset time is 60 seconds.

7. The treatment system based on automated spectrum infrared rehabilitation equipment according to claim 1, characterized in that, Edge detection of the grayscale image includes: Edge detection is performed on the grayscale image using the Canny edge detection method.

8. The treatment system based on automated spectrum infrared rehabilitation equipment according to claim 1, characterized in that, Extracting the lesion area also includes: Obtain the coordinates of the center point of the lesion area and control the infrared spectrum cover to move to the lesion area.

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