CN-121971044-A - Pressure sore risk dynamic evaluation and mattress pressure regulating system

CN121971044ACN 121971044 ACN121971044 ACN 121971044ACN-121971044-A

Abstract

The invention provides a dynamic pressure sore risk assessment method and a mattress pressure regulation system, and belongs to the technical field of medical equipment and intelligent nursing. The system comprises a multi-physical-field sensing layer, a data preprocessing and feature extraction layer, a dynamic risk fusion calculation layer, a grading early warning and decision layer and a closed-loop execution layer, wherein the sensing layer integrates multi-type sensors and electronic medical record interfaces, acquires mechanics, physiology and microenvironment parameters of a pressed region and basic information of a patient in real time, the preprocessing layer extracts feature parameters after data processing, fits nutrition correction coefficients, calculates temperature and humidity stimulation coefficients, the fusion calculation layer maps the multi-dimensional parameters into dynamic risk indexes DRI through a weighted fusion algorithm model and also supports machine learning nonlinear mapping, the early warning decision layer performs grading early warning according to DRI values, change trends and deep tissue injury precursor modes and identifies dominant risk factors, and the closed-loop execution layer performs etiology targeted intervention according to the early warning grades and the dominant risk factors.

Inventors

ZHANG ZIMO
ZHANG ZHIJUN
ZHU YUBO
YANG LIANGCHEN
GAO ZIYAN
ZHAO RUIQI
XU YICHEN

Assignees

南通大学

Dates

Publication Date: 20260505
Application Date: 20260318

Claims (10)

1. A dynamic evaluation method for pressure sore risk and a mattress pressure regulating system are characterized by comprising a multi-physical-field sensing layer, a data preprocessing and feature extracting layer, a dynamic risk fusion calculating layer, a grading early warning and decision making layer and a closed-loop executing layer, The multi-physical sensing layer is arranged in a flexible sensing area of the pressed surface of the medical mattress, is used for collecting data and transmitting the data to the data preprocessing and feature extracting layer, and comprises a plurality of sensors and interface units; The sensor comprises a high-density flexible pressure sensor array, a two-dimensional shear force sensing unit, a multispectral tissue blood oxygen sensor and a digital temperature and humidity sensor; The interface unit comprises a time counter and an electronic medical record interface; the data preprocessing and feature extraction layer adopts an embedded micro-processing unit and is used for receiving the original acquired data of the multi-physical-field sensing layer and completing data preprocessing, feature parameter extraction and correction coefficient/stimulation coefficient calculation; The dynamic risk fusion calculation layer is used for calculating a dynamic risk index based on the data output by the data preprocessing and feature extraction layer and normalizing the calculated dynamic risk index; the grading early warning and decision layer carries out risk early warning based on the dynamic risk index, identifies dominant risk factors, provides intervention decision basis for the closed loop execution layer, and simultaneously transmits early warning information to the nursing terminal of the nurse station; The closed-loop execution layer executes accurate intervention operation with etiology pertinence based on the early warning level and dominant risk factors of the hierarchical early warning and decision layer.
2. The method for dynamically evaluating risk of pressure sores and the mattress pressure regulating system according to claim 1, wherein the high-density flexible pressure sensor array is characterized in that a capacitive flexible pressure sensor is adopted, the arrangement density is 2/cm 2 , the detection range is 0-100 mmHg, the detection precision is +/-1 mmHg, the two-dimensional shear force sensing unit covers a pressure-bearing area of the mattress in a grid shape, the two-dimensional shear force sensing unit is arranged in the two-dimensional shear force sensing unit and the high-density flexible pressure sensor array, the multispectral tissue blood oxygen sensor is arranged in the area of the high-density flexible pressure sensor array, and the multispectral tissue blood oxygen sensor adopts a photoelectric plethysmography technology, emits 660nm/940 nm dual-wavelength light and is used for monitoring blood oxygen saturation and blood perfusion state of subcutaneous tissues of the pressure-bearing part in real time; The digital temperature and humidity sensor is used for collecting real-time temperature and relative humidity of a contact surface of a patient and a mattress, the time technology is used for recording the mechanical load accumulation duration and the bad microclimate duration, and the electronic medical record interface is in butt joint with a hospital electronic medical record system by adopting an HL7FHIR standard protocol.
3. The method for dynamically evaluating risk of pressure sores and the mattress pressure regulating system according to claim 2, wherein the sampling frequency of each unit of the multiple physical sensing layers is 10 Hz, the clock synchronization precision is controlled within 10 ms, the acquired data of all sensing units are transmitted to the data preprocessing and characteristic extracting layer through Bluetooth 5.0 wireless communication, the data transmission rate is more than or equal to 1 Mbps, and the transmission distance is less than or equal to 10 m.
4. The method for dynamically evaluating risk of pressure sores and the mattress pressure regulating system according to claim 1, wherein the data preprocessing and feature extraction layer comprises the following processing steps: S1, preprocessing original data: Filtering, denoising and interpolating are carried out on the original analog signals acquired by the multi-physical field sensing layer, invalid data caused by environmental interference and sensor drift are eliminated, missing sampling points are complemented, and standardized digital signals are obtained; s2, extracting characteristic parameters: Extracting core characteristic parameters of pressure sore risk assessment from the preprocessed data, wherein the core characteristic parameters comprise mechanical characteristics, physiological characteristics, micro-environment characteristics and time characteristics S3, calculating correction coefficients and stimulation coefficients: based on temperature and humidity detection data, calculating a temperature and humidity stimulation coefficient, wherein the two coefficients are normalized to a 0-1 interval, and a specific calculation formula is as follows: Nutritional correction factor = 0.2 x serum albumin level (g/L) +0.3 x hemoglobin concentration (g/L)/10, if the patient incorporates diabetes, the factor is multiplied by 0.8 correction; The temperature and humidity stimulation coefficient=0.4× (actual temperature-32 ℃) plus 0.6× (actual humidity-60%)/10, when the temperature is less than or equal to 32 ℃ and the humidity is less than or equal to 60% RH, the corresponding item is 0, the whole coefficient is 0, and only when the temperature/humidity exceeds the threshold value, the forward stimulation value is calculated to reflect the damage degree of the microenvironment.
5. The method for dynamically evaluating risk of pressure sores and the mattress pressure regulating system according to claim 4, wherein the dynamic risk fusion calculation layer is used for calculating a dynamic risk index DRI, a basic algorithm of the DRI calculation method is an explicit weighted fusion formula, all input parameters are normalized to a 0-1 interval, consistency of calculation results is guaranteed, and the formula is: DRI= [ (vertical pressure integral×0.6) + (shear force intensity×0.4) ]×accumulation duration ≡ [ (tissue blood oxygen saturation×0.7+blood perfusion index×0.3) ×nutrition correction coefficient ] +temperature and humidity stimulation coefficient In the formula, the vertical pressure integral multiplied by 0.6+shearing force intensity multiplied by 0.4 is equivalent mechanical stress and used for reflecting the core mechanical factors of pressure sore formation, the tissue blood oxygen saturation multiplied by 0.7+blood flow perfusion index multiplied by 0.3 is a tissue perfusion state and used for reflecting the tissue ischemia and hypoxia degree of a pressed part, the accumulated time length is the time dimension weighting of mechanical load, the nutrition correction coefficient is the personalized correction of the individual physiological state, and the temperature and humidity stimulation coefficient is an additional risk factor of a microenvironment.
6. The method for dynamically evaluating risk of pressure sores and the mattress pressure regulating system according to claim 5, wherein the dynamic risk fusion calculation layer further adopts a machine learning method, takes clinical large sample data (comprising multi-physical field perception data of patients with different weights, basic diseases and bedridden durations and pressure sore occurrence ending data) as a training set, takes pressure sore occurrence probability as a label, and trains to obtain a nonlinear mapping model; After model deployment is completed, the feature parameters can be received in real time and DRI can be output, incremental learning is supported, model parameters are continuously optimized according to clinical actual data, and risk prediction accuracy is improved.
7. The method for dynamically evaluating risk of pressure sores and the mattress pressure regulating system according to claim 6, wherein the hierarchical early warning and decision layer is based on DRI output by a dynamic risk fusion calculation layer, and performs secondary risk early warning in combination with DRI change trend and deep tissue injury precursor mode, and the secondary risk early warning judgment rule is as follows: (1) Primary early warning, namely triggering when any one of the following conditions is met, wherein the early warning grade is yellow, prompting the low-moderate risk of the pressure sore, and reinforcing monitoring is needed: ① The dynamic risk index DRI is more than or equal to 2.0 (the baseline level is 1.0, namely, the baseline level is 1.5 times higher) and the duration is more than or equal to 5min; ② The pressure-time integral (PTI) is more than or equal to 32 mmHg.2h (tissue reversible damage threshold), namely the vertical pressure is more than or equal to 32mmHg and the duration is more than or equal to 2h; (2) The advanced early warning is triggered when any one of the following conditions is met, the early warning grade is red, the high risk of the pressure sore is prompted, and the early warning is needed to be immediately interfered: ① Identifying a deep tissue injury precursor mode that the shearing force intensity is more than or equal to 20N and the local tissue blood oxygen saturation is less than 40 percent (even if the surface pressure is less than 32 mmHg); ② Calculating the DRI first derivative once every 5 minutes, wherein the slope of three continuous sampling periods (15 min) is more than or equal to 0.1, namely the DRI is in a rapid rising trend, and the risk is continuously worsened; ③ DRI is more than or equal to 3.5 and the duration is more than or equal to 3min, namely the risk of pressure sores reaches a high value; After triggering early warning, the system identifies dominant risk factors formed by the current pressure sore through characteristic parameter contribution rate analysis, wherein the dominant risk factors are divided into five types and can exist independently or in a compound mode: The vertical pressure is too high, the pressure peak value is more than or equal to 60mmHg or the pressure-time integral is more than or equal to 32 mmHg.2h, and the contribution rate is more than or equal to 40%; The shearing force is overlarge, the shearing force intensity is more than or equal to 20N or the shearing force-time integral is more than or equal to 10 N.min, and the contribution rate is more than or equal to 40%; Tissue ischemia, wherein the tissue blood oxygen saturation is less than 60 percent or the blood flow perfusion index is less than 0.5, and the contribution rate is more than or equal to 40 percent; Humidity of the microenvironment is more than or equal to 70 percent RH, the duration is more than or equal to 30 minutes, or the temperature and humidity stimulation coefficient is more than or equal to 0.5, and the contribution rate is more than or equal to 30 percent; And the composite high risk is that the two or more risk factors exceed the standard at the same time, and the contribution rate of a single class is more than or equal to 20 percent.
8. The method for dynamically assessing risk of pressure sores and the mattress pressure regulating system according to claim 7, wherein the closed-loop execution layer comprises an air bag array pressure regulating module, an electric back plate angle regulating module, a micro-environment regulating module and a nursing terminal prompting module.
9. The method for dynamically evaluating risk of pressure sores and the mattress pressure regulating system according to claim 8, wherein the air bag array pressure regulating module comprises an air bag array which is positioned in 16 independent partitions in the mattress, the single air bag pressure regulating range is 5-40mmHg, the regulating precision is +/-0.5 mmHg, and each partition can independently regulate pressure, synchronously regulate pressure or regulate pressure in a gradient way and corresponds to different pressed parts of a patient.
10. The method for dynamically assessing risk of pressure sores and the system for regulating pressure of a mattress according to claim 9, wherein the specific intervention instructions, parameters and execution steps of the closed-loop execution layer are as follows: the specific intervention instructions, parameters and execution steps are as follows: The intervention instruction aiming at the vertical pressure is to control the partial decompression of the air sac of the corresponding area to 15-20mmHg or execute the alternate inflation and deflation operation of 5 minutes inflation/3 minutes deflation; The intervention instruction aiming at the overlarge shearing force is that the angle of the bed head backboard is automatically reduced to be less than or equal to 30 degrees, and the air bag array is regulated to form a gradient supporting structure with 5mmHg gradient from the foot to the head, so as to counteract the gravity sliding trend of the trunk; the intervention instruction aiming at tissue ischemia is that high-frequency micro-motion intervention with the micro-motion amplitude of +/-5 mm and the frequency of 10 times/min is implemented on an ischemia area to interrupt the continuous ischemia process and prevent reperfusion injury; the intervention instruction aiming at the humidity of the microenvironment is that a micro fan and a semiconductor refrigeration module are started, the local temperature and humidity of a pressed area are regulated to 28-32 ℃ and 40-60% RH, and prompt information for changing a bed sheet is pushed to a nursing terminal; The intervention instruction aiming at the composite high risk is that all intervention operations corresponding to a single risk factor are comprehensively executed, comprehensive prompt information comprising the type of the risk factor, intervention measures and nursing suggestions is pushed to a nursing terminal, and the comprehensive prompt information is synchronously updated to the hospital electronic medical record system.

Description

Pressure sore risk dynamic evaluation and mattress pressure regulating system Technical Field The invention belongs to the technical field of medical equipment and intelligent nursing, and particularly relates to a pressure sore risk dynamic assessment and mattress pressure regulation system. Background Pressure sores, also known as pressure injuries, are one of the most common complications of long-term bedridden patients, and are related to multiple factors such as vertical pressure, shearing force, tissue tolerance, micro-environment climate, mechanical load accumulation time and the like, so that the rehabilitation process of the patients is seriously affected, and the clinical nursing burden is increased. The existing pressure sore risk assessment means mainly depend on medical staff to carry out subjective scoring by adopting tools such as Braden scale, norton scale and the like at regular intervals, the assessment mode is separated from a specific pathophysiological mechanism formed by pressure sore, macroscopic judgment is completed only by clinical experience, obvious hysteresis exists, and dynamic evolution trend of pressure sore risk of a patient cannot be captured in real time. In recent years, although a part of pressure reducing mattresses integrate a pressure monitoring function, the monitoring dimension is single, local pressure reducing operation can be triggered only based on a single vertical pressure threshold (for example, more than 32 mmHg), key pathogenic factors of pressure sore formation such as shearing force, tissue ischemia and hypoxia state, contact surface temperature and humidity cannot be synchronously perceived, fusion analysis capability of multidimensional monitoring data is lacking, and dynamic calculation and predictive intervention of pressure sore risk cannot be realized. The key defects of the prior art are concentrated in four aspects, namely, the sensing dimension is single, key factors such as shearing force, friction force, tissue perfusion, micro-environment temperature and humidity are ignored to form a monitoring blind area, the risk assessment is delayed, the manual assessment at a discrete time point cannot reflect real-time change of risks, the regulation strategy is blind, the pressure reduction behavior and the pressure sore causative agent are disjointed, the average pressure is reduced only by simple alternate inflation and deflation, the shearing force cannot be relieved pertinently, the local blood supply is improved, and the like, the monitoring on Deep Tissue Injury (DTI) is insufficient, the deep tissue injury mostly occurs in subcutaneous soft tissues, the surface pressure is often free from obvious abnormality, and the early identification and early warning are difficult to realize in the prior art. In summary, there is a need for a pressure sore risk assessment and adjustment system capable of realizing multidimensional real-time monitoring, dynamic quantitative assessment and etiology targeted intervention in order to solve the defects of the prior art and improve the clinical effect of pressure sore prevention and control. Disclosure of Invention The application aims to solve the technical problems that in the prior art, the pressure sore prevention and control technology has single perception dimension, lag in risk assessment and blind regulation strategy, and deep tissue damage monitoring blind areas exist, and the dynamic quantification of the pressure sore risk and the targeted and accurate intervention of the cause cannot be realized. In order to achieve the above purpose, the present application provides the following technical solutions: a dynamic evaluation method for pressure sore risk and a mattress pressure regulating system comprise a multi-physical-field sensing layer, a data preprocessing and feature extracting layer, a dynamic risk fusion calculating layer, a grading early warning and decision making layer and a closed-loop executing layer, The multi-physical sensing layer is arranged in a flexible sensing area of the pressed surface of the medical mattress, is used for collecting data and transmitting the data to the data preprocessing and feature extracting layer, and comprises a plurality of sensors and interface units; The sensor comprises a high-density flexible pressure sensor array, a two-dimensional shear force sensing unit, a multispectral tissue blood oxygen sensor and a digital temperature and humidity sensor; The interface unit comprises a time counter and an electronic medical record interface; the data preprocessing and feature extraction layer adopts an embedded micro-processing unit and is used for receiving the original acquired data of the multi-physical-field sensing layer and completing data preprocessing, feature parameter extraction and correction coefficient/stimulation coefficient calculation; The dynamic risk fusion calculation layer is used for calculating a dynamic risk index based on the data output by