Pressure monitoring device and monitoring method for evaluating pressure sore risk

Abstract

The invention discloses a pressure monitoring device and method for evaluating pressure sore risk, and relates to the technical field of medical equipment. The system comprises a pressure sensing unit used for collecting pressure distribution data between the body surface of a patient and a supporting surface; the distance measuring device is used for measuring the distance between the device and the body surface of the patient. According to the method, information of three different dimensions of pressure distribution, body surface image and deep thermal imaging is subjected to fusion analysis, a pressure sensor positions a high-risk pressed area, a high-definition color image is used for identifying macroscopic skin damage and color change, infrared thermal imaging can penetrate through a surface layer, and the image can be used for identifying the skin damage and color change. According to the method, deep tissue temperature abnormity caused by ischemia and inflammation is sensitively captured, and the three types of information are integrated into a quantitative comprehensive risk score through a weighting algorithm, so that an evaluation result does not depend on subjective experience of nursing personnel any more and is converted into objective and quantifiable accurate diagnosis, and the screening accuracy of high-risk patients is remarkably improved.

Description

Technical Field

[0001] This invention belongs to the field of medical device technology, and in particular relates to a pressure monitoring device and monitoring method for assessing the risk of pressure ulcers. Background Technology

[0002] Pressure ulcers, also known as pressure injuries, are soft tissue ulcers and necrosis caused by prolonged pressure on local tissues, which leads to impaired blood circulation, resulting in persistent ischemia, hypoxia, and malnutrition of the skin and subcutaneous tissues. Pressure ulcers are common in patients who are bedridden or wheelchair-bound for extended periods, causing not only great suffering to patients but also increasing the burden of medical care.

[0003] Currently, assessment tools such as the Braden and Norton scales are commonly used in clinical practice to predict the risk of pressure ulcers. These methods mainly rely on the subjective observation and palpation of nursing staff, which has disadvantages such as inconsistent assessment standards, reliance on personal experience, and inability to quantify. Although some pressure monitoring pads and other devices can measure the distribution of pressure on the body surface, they usually only provide pressure data and cannot directly observe and assess the morphology, area, and deep tissue condition of existing pressure ulcers. For existing pressure ulcers, the traditional assessment method is to manually measure the length and width of the wound with a ruler and estimate the depth with a probe. This method has large errors, is inconvenient to operate, and is difficult to accurately assess irregularly shaped wounds and complex sinus tracts.

[0004] To address this issue, we provide a pressure monitoring device and method for assessing the risk of pressure ulcers. Summary of the Invention

[0005] The purpose of this invention is to provide a pressure monitoring device and method for assessing the risk of pressure ulcers, which solves the problems of current pressure ulcer assessment methods that rely on the experience of medical staff for judgment, resulting in large errors, inconvenience in operation, and difficulty in accurately assessing irregularly shaped wounds and complex sinus tracts.

[0006] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution.

[0007] This invention relates to a pressure monitoring device for assessing the risk of pressure ulcers, comprising:

[0008] The pressure sensing unit collects pressure distribution data between the patient's body surface and the supporting surface;

[0009] A distance measuring device that measures the distance to the patient's body surface;

[0010] A photometer provides illumination and acquires high-resolution color images of the patient's body surface;

[0011] An infrared thermal imager receives infrared radiation emitted by human tissue and converts it into a thermal image.

[0012] The touchscreen displays a pressure distribution map and the identification results of pressure ulcer wounds;

[0013] A pressure ulcer identification and assessment unit, used to assess pressure ulcer conditions, comprising:

[0014] The image fusion module fuses the color image acquired by the photometric device and the thermal image acquired by the infrared thermal imager.

[0015] The wound recognition module automatically identifies and draws the boundaries of pressure ulcer wounds using image recognition algorithms;

[0016] The area calculation module calculates the actual area of ​​the pressure ulcer wound based on the identified wound boundary and the scale data provided by the ranging device.

[0017] The risk assessment module is used to integrate the pressure distribution data, wound area data, and deep tissue inflammation information reflected by the thermogram to generate a comprehensive pressure ulcer risk assessment report.

[0018] The present invention is further configured such that the image fusion module employs a fusion algorithm based on feature point registration and weighted averaging to fuse the color image and the thermal image, and the fusion process follows the formula:

[0019] F(x,y)=α·C'(x,y)+(1-α)·T'(x,y)

[0020] Where F(x, y) is the pixel value at coordinates (x, y) after fusion, C'(x, y) is the pixel value of the color image after geometric correction and color space conversion, T'(x, y) is the pixel value of the thermal image after geometric correction and grayscale normalization, and α is the weighting coefficient, which ranges from 0 to 1 and is used to adjust the contribution of color information and thermal information.

[0021] The present invention is further configured such that the wound recognition module adopts a semantic segmentation model based on the deep learning U-Net architecture, and optimizes the model using the Dice loss function, the loss function of which follows the formula:

[0022] DiceLoss=1-(2·|X∩Y|+ε) / (|X|+|Y|+ε)

[0023] Where X is the binary mask of the wound region predicted by the model, Y is the labeled mask of the real wound region, |X∩Y| is the size of the intersection of the predicted and real regions, |X| and |Y| are the sizes of the predicted and real regions, respectively, and ε is a smoothing constant used to prevent the denominator from being zero.

[0024] The present invention is further configured such that the area calculation module performs calculations based on the binary mask output by the wound recognition module and the scale information provided by the ranging device, and the formula for calculating the actual area of ​​the wound is:

[0025] WoundArea = N·(S)²

[0026] Where WoundArea is the calculated actual physical area of ​​the wound, N is the total number of pixels identified as the wound in the binary mask, and S is the actual physical size of each pixel.

[0027] The present invention is further configured such that the risk assessment module uses a multi-factor linear weighted model to generate a comprehensive risk score, the calculation formula of which is:

[0028] RiskScore=w1·F_p+w2·F_a+w3·F_t

[0029] RiskScore is the final calculated standardized pressure ulcer risk score. F_p is the pressure risk factor based on pressure sensor unit data, F_a is the wound area risk factor based on area calculation module, F_t is the deep tissue thermodynamic risk factor based on infrared thermal imaging data, and w1, w2, and w3 are the weight coefficients of each risk factor.

[0030] The invention is further configured such that the pressure sensing unit is a pressure distribution matrix sensor, which is composed of pressure sensors distributed in an array; the ranging device adopts a laser ranging sensor and an ultrasonic ranging sensor; and the light measuring device includes an LED fill light and a high-resolution color camera.

[0031] The present invention is further configured such that the pressure sensing unit, the ranging device, the light measuring device, and the infrared thermal imager are electrically connected to a central processing unit. The central processing unit is used to process the data, output the processed data to the pressure ulcer wound recognition and assessment unit for comparison and analysis, and output the final data to the touch screen for feedback.

[0032] A monitoring method for pressure monitoring devices used to assess the risk of pressure ulcers includes the following steps:

[0033] S1: Place the pressure sensing unit under the patient's body area where pressure ulcers are prone to occur, and obtain real-time pressure distribution data through the pressure sensing unit;

[0034] S2: Simultaneously acquire color images and thermal images of the area using a ranging device, a light measuring device, and an infrared thermal imager;

[0035] S3: The image fusion module performs semantic segmentation on the image, automatically identifies the wound area, necrotic tissue, granulation tissue, etc., and accurately delineates the wound boundary;

[0036] S4: The area calculation module establishes the conversion relationship between image pixels and actual millimeters based on the actual distance and shooting parameters provided by the ranging device, thereby calculating the actual perimeter and area of ​​the wound boundary;

[0037] S5: Analyze the thermogram to determine the inflammation status of deep tissues in the wound and the direction and depth of sinuses based on areas of abnormal temperature;

[0038] S6: The risk assessment module will perform a weighted calculation based on the calculated wound area, the maximum pressure and pressure gradient of the area provided by the pressure sensing unit, and the area and average temperature value of the high-temperature area around the wound in the thermal image, and finally generate a quantified risk score, which will be displayed on the touch screen.

[0039] The present invention has the following beneficial effects.

[0040] 1. This invention integrates and analyzes information from three different dimensions: pressure distribution, surface images, and deep thermal imaging. Pressure sensors locate high-risk pressure areas, high-definition color images are used to identify visible skin damage and color changes, and infrared thermal imaging can penetrate the surface to sensitively capture abnormal temperatures in deep tissues caused by ischemia and inflammation. Through a weighted algorithm, these three types of information are integrated into a quantitative comprehensive risk score, so that the assessment results no longer rely on the subjective experience of nursing staff, but are transformed into objective, quantifiable, and accurate diagnoses, significantly improving the accuracy of high-risk patient screening and early warning capabilities.

[0041] 2. The wound recognition module of this invention is based on the deep learning U-Net architecture. It automatically analyzes images, accurately delineates irregular wound boundaries, and accurately distinguishes different tissues such as necrotic tissue and granulation tissue. The area calculation module then converts the pixel area into the actual physical area based on the distance measurement data, completing the manual measurement that used to take several minutes. This ensures the consistency and reliability of the data, making clinical records, efficacy tracking, and scientific research data analysis more accurate. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below.

[0043] Figure 1 A schematic diagram of the system principle of a pressure monitoring device and monitoring method for assessing the risk of pressure ulcers.

[0044] Figure 2 A schematic diagram of the system principle of the pressure ulcer identification and assessment unit in a pressure monitoring device and monitoring method for assessing pressure ulcer risk. Detailed Implementation

[0045] The technical solutions of the present invention will be described below with reference to the accompanying drawings. The described embodiments are only some embodiments of the present invention, and not all embodiments.

[0046] Example 1

[0047] Please see Figures 1-2 The present invention is a pressure monitoring device for assessing the risk of pressure ulcers, comprising:

[0048] The pressure sensing unit collects pressure distribution data between the patient's body surface and the supporting surface;

[0049] A distance measuring device that measures the distance to the patient's body surface;

[0050] A photometer provides illumination and acquires high-resolution color images of the patient's body surface;

[0051] An infrared thermal imager receives infrared radiation emitted by human tissue and converts it into a thermal image.

[0052] The touchscreen displays a pressure distribution map and the identification results of pressure ulcer wounds;

[0053] Pressure ulcer identification and assessment unit, used to assess pressure ulcer conditions, includes:

[0054] The image fusion module fuses the color image acquired by the photometer and the thermal image acquired by the infrared thermal imager.

[0055] The wound recognition module automatically identifies and draws the boundaries of pressure ulcer wounds using image recognition algorithms;

[0056] The area calculation module calculates the actual area of ​​the pressure ulcer wound based on the identified wound boundary and the scale data provided by the ranging device.

[0057] The risk assessment module integrates pressure distribution data, wound area data, and deep tissue inflammation information reflected by thermograms to generate a comprehensive pressure ulcer risk assessment report.

[0058] The image fusion module employs a fusion algorithm based on feature point registration and weighted averaging to fuse the color image and the thermal image. The fusion process follows the formula:

[0059] F(x,y)=α·C'(x,y)+(1-α)·T'(x,y)

[0060] Where F(x, y) is the pixel value at coordinates (x, y) after fusion, C'(x, y) is the pixel value of the color image after geometric correction and color space conversion, T'(x, y) is the pixel value of the thermal image after geometric correction and grayscale normalization, and α is the weighting coefficient, which ranges from 0 to 1 and is used to adjust the contribution of color information and thermal information.

[0061] The wound recognition module employs a semantic segmentation model based on the deep learning U-Net architecture, and optimizes the model using the Dice loss function, which follows the formula:

[0062] DiceLoss=1-(2·|X∩Y|+ε) / (|X|+|Y|+ε)

[0063] Where X is the binary mask of the wound region predicted by the model, Y is the labeled mask of the real wound region, |X∩Y| is the size of the intersection of the predicted and real regions, |X| and |Y| are the sizes of the predicted and real regions, respectively, and ε is a smoothing constant used to prevent the denominator from being zero.

[0064] The area calculation module performs calculations based on the binary mask output by the wound recognition module and the scale information provided by the ranging device. The formula for calculating the actual wound area is as follows:

[0065] WoundArea = N·(S)²

[0066] Where WoundArea is the calculated actual physical area of ​​the wound, N is the total number of pixels identified as the wound in the binary mask, and S is the actual physical size of each pixel.

[0067] The present invention is further configured such that the risk assessment module uses a multi-factor linear weighted model to generate a comprehensive risk score, the calculation formula of which is:

[0068] RiskScore=w1·F_p+w2·F_a+w3·F_t

[0069] RiskScore is the final calculated standardized pressure ulcer risk score. F_p is the pressure risk factor based on pressure sensor unit data, F_a is the wound area risk factor based on area calculation module, F_t is the deep tissue thermodynamic risk factor based on infrared thermal imaging data, and w1, w2, and w3 are the weight coefficients of each risk factor.

[0070] The pressure sensing unit is a pressure distribution matrix sensor, which consists of pressure sensors arranged in an array. The ranging device uses a laser ranging sensor and an ultrasonic ranging sensor. The light measuring device includes an LED fill light and a high-resolution color camera.

[0071] The pressure sensing unit, ranging device, light measuring device, and infrared thermal imager are electrically connected to a central processing unit. The central processing unit processes the data, outputs the processed data to the pressure ulcer wound recognition and assessment unit for comparison and analysis, and outputs the final data to the touch screen for feedback.

[0072] A monitoring method for pressure monitoring devices used to assess the risk of pressure ulcers includes the following steps:

[0073] S1: Place the pressure sensing unit under the patient's body area where pressure ulcers are prone to occur, and obtain real-time pressure distribution data through the pressure sensing unit;

[0074] S2: Simultaneously acquire color images and thermal images of the area using a ranging device, a light measuring device, and an infrared thermal imager;

[0075] S3: The image fusion module performs semantic segmentation on the image, automatically identifies the wound area, necrotic tissue, granulation tissue, etc., and accurately delineates the wound boundary;

[0076] S4: The area calculation module establishes the conversion relationship between image pixels and actual millimeters based on the actual distance and shooting parameters provided by the ranging device, thereby calculating the actual perimeter and area of ​​the wound boundary;

[0077] S5: Analyze the thermogram to determine the inflammation status of deep tissues in the wound and the direction and depth of sinuses based on areas of abnormal temperature;

[0078] S6: The risk assessment module will perform a weighted calculation based on the calculated wound area, the maximum pressure and pressure gradient of the area provided by the pressure sensing unit, and the area and average temperature value of the high-temperature area around the wound in the thermal image, and finally generate a quantified risk score, which will be displayed on the touch screen.

[0079] Table 1:

[0080] step Operations / Components Detailed Implementation Device layout Pressure sensing unit The pressure distribution matrix sensor pad is placed under the sheet at the patient's sacrum and coccyx. Data collection Distance measuring device, light measuring device, infrared thermal imager Adjust the equipment bracket so that the laser rangefinder determines the distance between the camera and the body surface to be 30cm. Simultaneously turn on the color camera with LED fill light and the infrared thermal imager to collect clear color images and thermal images of the sacral and coccygeal regions, respectively. Image processing and fusion Image fusion module A weighted average algorithm based on feature point registration is used to fuse color images with thermal images to simultaneously display visible wound surfaces and abnormally heated areas deep within tissues. Wound recognition Wound recognition module The color image and the fused image are input into a deep learning model based on the U-Net architecture (optimized using the Dice loss function). The model automatically identifies and accurately delineates the wound boundary, necrotic tissue (yellow), and newly formed granulation tissue (red) areas. Area calculation Area calculation module Based on the distance measurement data of 30cm and the camera parameters, the actual physical size S corresponding to each pixel in the image is calculated. Based on the binary mask output by the wound recognition module, the total number of pixels N in the wound area is counted. Substituting into the formula WoundArea=N·S², the actual physical area of ​​the wound (4.5cm²) is calculated. risk assessment Risk assessment module The system integrates three data points: the maximum pressure value (e.g., 65 mmHg) is extracted from the pressure distribution data; based on the calculated wound area (4.5 cm²), the average temperature of the high-temperature area at the wound edge is analyzed from the thermal image (e.g., 1.8°C higher than the surrounding normal skin); and a comprehensive risk score is calculated using a linear weighted model (weights w1=0.4, w2=0.3, w3=0.3). The system simultaneously displays the pressure distribution cloud map of the sacrum and coccyx, color image, thermal image, automatically drawn wound boundary map, and the final quantified risk score (e.g., RiskScore=7.8 / 10) and a brief assessment report on a touchscreen, indicating "High risk, requires increased turning and pressure relief measures."

[0081] The preferred embodiments of the present invention disclosed above are only for the purpose of illustrating the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation described herein. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can better understand and utilize the present invention.

Claims

1. A pressure monitoring device for assessing the risk of pressure ulcers, characterized in that, include: The pressure sensing unit collects pressure distribution data between the patient's body surface and the supporting surface; A distance measuring device that measures the distance to the patient's body surface; A photometer provides illumination and acquires high-resolution color images of the patient's body surface; An infrared thermal imager receives infrared radiation emitted by human tissue and converts it into a thermal image. The touchscreen displays a pressure distribution map and the identification results of pressure ulcer wounds; A pressure ulcer identification and assessment unit, used to assess pressure ulcer conditions, comprising: The image fusion module fuses the color image acquired by the photometric device and the thermal image acquired by the infrared thermal imager. The wound recognition module automatically identifies and draws the boundaries of pressure ulcer wounds using image recognition algorithms; The area calculation module calculates the area based on the identified wound boundary and the scale data provided by the ranging device. The risk assessment module integrates the pressure distribution data, wound area data, and deep tissue inflammation information reflected in the thermogram.

2. The pressure monitoring device for assessing pressure ulcer risk according to claim 1, characterized in that: The image fusion module employs a fusion algorithm based on feature point registration and weighted averaging to fuse the color image and the thermal image. The fusion process follows the formula: F(x,y)=α·C'(x,y)+(1-α)·T'(x,y) Where F(x, y) is the pixel value at coordinates (x, y) after fusion, C'(x, y) is the pixel value of the color image after geometric correction and color space conversion, T'(x, y) is the pixel value of the thermal image after geometric correction and grayscale normalization, and α is the weighting coefficient, which ranges from 0 to 1 and is used to adjust the contribution of color information and thermal information.

3. The pressure monitoring device for assessing pressure ulcer risk according to claim 1, characterized in that: The wound recognition module employs a semantic segmentation model based on the deep learning U-Net architecture, and optimizes the model using the Dice loss function, which follows the formula: DiceLoss=1-(2·|X∩Y|+ε) / (|X|+|Y|+ε) Where X is the binary mask of the wound region predicted by the model, Y is the labeled mask of the real wound region, |X∩Y| is the size of the intersection of the predicted and real regions, |X| and |Y| are the sizes of the predicted and real regions, respectively, and ε is a smoothing constant used to prevent the denominator from being zero.

4. The pressure monitoring device for assessing pressure ulcer risk according to claim 1, characterized in that: The area calculation module performs calculations based on the binary mask output by the wound recognition module and the scale information provided by the ranging device. The formula for calculating the actual wound area is as follows: WoundArea = N·(S)² Where WoundArea is the calculated actual physical area of ​​the wound, N is the total number of pixels identified as wounds in the binary mask of the wound, and S is the actual physical size corresponding to each pixel, thus calculating the actual area of ​​the pressure ulcer wound.

5. The pressure monitoring device for assessing pressure ulcer risk according to claim 1, characterized in that: The risk assessment module uses a multi-factor linear weighted model to generate a comprehensive risk score, and its calculation formula is as follows: RiskScore=w1·F_p+w2·F_a+w3·F_t RiskScore is the final standardized pressure ulcer risk score. F_p is the pressure risk factor based on pressure sensor unit data, F_a is the wound area risk factor based on area calculation module, F_t is the deep tissue thermodynamic risk factor based on infrared thermal imaging data, and w1, w2, and w3 are the weight coefficients of each risk factor, generating a comprehensive pressure ulcer risk assessment report.

6. The pressure monitoring device for assessing pressure ulcer risk according to claim 1, characterized in that: The pressure sensing unit is a pressure distribution matrix sensor, which consists of pressure sensors arranged in an array. The ranging device uses a laser ranging sensor and an ultrasonic ranging sensor. The light measuring device includes an LED fill light and a high-resolution color camera.

7. The pressure monitoring device for assessing pressure ulcer risk according to claim 1, characterized in that: The pressure sensing unit, ranging device, light measuring device, and infrared thermal imager are electrically connected to a central processing unit. The central processing unit is used to process the data, output the processed data to the pressure ulcer wound recognition and assessment unit for comparison and analysis, and output the final data to the touch screen for feedback.

8. A pressure monitoring method for assessing the risk of pressure ulcers, characterized in that: Includes the following steps: S1: Place the pressure sensing unit under the patient's body area where pressure ulcers are prone to occur, and obtain real-time pressure distribution data through the pressure sensing unit; S2: Simultaneously acquire color images and thermal images of the area using a ranging device, a light measuring device, and an infrared thermal imager; S3: The image fusion module performs semantic segmentation on the image, automatically identifies the wound area, necrotic tissue, granulation tissue, etc., and accurately delineates the wound boundary; S4: The area calculation module establishes the conversion relationship between image pixels and actual millimeters based on the actual distance and shooting parameters provided by the ranging device, thereby calculating the actual perimeter and area of ​​the wound boundary; S5: Analyze the thermogram to determine the inflammation status of deep tissues in the wound and the direction and depth of sinuses based on areas of abnormal temperature; S6: The risk assessment module will perform a weighted calculation based on the calculated wound area, the maximum pressure and pressure gradient of the area provided by the pressure sensing unit, and the area and average temperature value of the high-temperature area around the wound in the thermal image, and finally generate a quantified risk score, which will be displayed on the touch screen.

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