Fixed pressure sore nursing system and early warning method based on dynamic monitoring of wet state hardness

Abstract

The application provides a fixed pressure sore nursing system and early warning method based on wet state hardness dynamic monitoring, and relates to the technical field of pressure sore nursing.The system comprises a multi-layer composite structure of a dressing body, and the dressing body comprises a medical pressure-sensitive adhesive layer, a sensor integrated layer, a moisture absorption and buffering layer, and a transparent polyurethane film layer.A hardness sensitive material layer, a flexible printed circuit layer, and a reference electrode layer are embedded in the sensor integrated layer.The hardness sensitive material layer is used to generate an electrical signal, a signal processing chip is used to collect the electrical signal and convert it into a pressure value, and a wet state hardness risk index is calculated and compared with a warning threshold value, and different levels of warning signals are output through a wireless communication module.The application can monitor the change of the wet state hardness of the buffering layer in real time, quantify the cumulative pressure sore risk, and issue a graded warning before irreversible damage occurs to the tissue, thereby changing the passive discovery of hidden pressure sores into active prevention.

Description

Technical Field

[0001] This invention relates to the field of pressure ulcer care technology, specifically to a fixed pressure ulcer care system based on dynamic monitoring of wet hardness. Background Technology

[0002] Currently, in CRRT treatment, femoral vein or internal jugular vein catheters are typically fixed using suture wings and transparent dressings. To prevent the suture wings and catheter connectors from causing rigid pressure on the skin, the standard clinical practice is to place multiple layers of sterile gauze under the dressing as a buffer layer. Some catheter fixation devices have now incorporated pressure monitoring or intelligent alarm functions, such as using pressure sensors to monitor the pressure status of the drainage tube, or using multimodal sensing combined with neural networks for pressure ulcer risk assessment.

[0003] However, gauze, acting as a buffer layer, swells and hardens after absorbing sweat, forming dot-like hard protrusions that directly compress the thin layer of skin where the femoral or carotid arteries pulsate. Because these protrusions are completely hidden by transparent dressings, pressure ulcers are often discovered only when the catheter is removed or the dressing is changed, often reaching the fascia layer. Currently available catheter fixation dressings lack a wet hardness warning function, failing to provide a risk indication before pressure ulcers form. Summary of the Invention

[0004] To address the problems in related technologies, this invention provides a fixed pressure ulcer care system based on dynamic monitoring of wet hardness.

[0005] To achieve the above objectives, the technical solution adopted by the present invention includes:

[0006] According to a first aspect of the present invention, a fixed pressure ulcer care system based on dynamic monitoring of wet hardness is provided, comprising a multi-layer composite dressing body, wherein the dressing body comprises, from the skin contact surface outward, a medical pressure-sensitive adhesive layer, a sensor integration layer, a moisture-absorbing buffer layer, and a transparent polyurethane film layer.

[0007] The sensor integration layer includes a hardness-sensitive material layer, a flexible printed circuit layer, and a reference electrode layer. The hardness-sensitive material layer is disposed in the area of ​​the dressing corresponding to the pulsation location of the femoral artery or carotid artery.

[0008] The flexible printed circuit layer integrates a signal processing chip, a timing unit, a power supply unit, and a wireless communication module.

[0009] The hardness-sensitive material layer is used to generate an electrical signal proportional to the magnitude of the force when subjected to local pressure. The signal processing chip is used to collect the electrical signal and convert it into a pressure value. Based on the pressure value, skin surface temperature, skin surface humidity, and cumulative time, the chip calculates the wet hardness risk index and compares it with a preset warning threshold. Different levels of warning signals are then output through the wireless communication module.

[0010] Optionally, the hardness-sensitive material layer is a polyvinylidene fluoride nanofiber membrane layer or a polydimethylsiloxane composite material layer;

[0011] The moisture-absorbing buffer layer is composed of at least two layers of nonwoven fabric, with carboxymethylated cotton fibers or alginate fibers filling the space between the layers, and the total thickness of the moisture-absorbing buffer layer is 2.0 to 5.0 mm.

[0012] The power supply unit is a flexible battery with a thickness of no more than 0.5 mm;

[0013] The wireless communication module is a Bluetooth module or a near-field communication module.

[0014] Optionally, the sensor integration layer also integrates a miniature LED indicator and a miniature buzzer, which are electrically connected to the signal processing chip.

[0015] According to a second aspect of the present invention, an early warning method for a fixed pressure ulcer care system based on dynamic monitoring of wet hardness as described in any of the technical solutions of the first aspect of the present invention is also provided, characterized in that it includes the following steps:

[0016] Step S1: After the dressing is applied to the patient's skin, a baseline pressure signal in a dry state is obtained through initial calibration;

[0017] Step S2: Continuously collect real-time pressure signals of the hardness-sensitive material layer at a preset sampling frequency, while simultaneously collecting skin surface temperature and skin surface relative humidity;

[0018] Step S3: Calculate the relative hardness coefficient based on the ratio of the real-time pressure signal to the reference pressure signal, combined with the current temperature and humidity;

[0019] Step S4: Calculate the wet hardness risk index at the current moment based on the relative hardness coefficient, time decay weight, and time accumulation at historical moments.

[0020] Step S5: Compare the calculated wet hardness risk index with the preset first threshold and second threshold, and output different levels of warning signals based on the comparison results.

[0021] Optionally, in step S3, the relative hardness coefficient The calculation formula is:

[0022]

[0023] In the formula, For real-time pressure signals, As the reference pressure signal, Temperature and humidity correction factor, Skin surface temperature The relative humidity of the skin surface.

[0024] Optionally, the temperature and humidity correction factor The calculation formula is:

[0025]

[0026] In the formula, For reference temperature, It is a temperature characteristic constant. For reference humidity, The characteristic constant of humidity, , Let be the normalization coefficients, and the above equation satisfies .

[0027] Optionally, the wet hardness risk index in step S4 The calculation formula is:

[0028]

[0029] In the formula, For the current moment, For the first The time point of the next sampling For the first The relative hardness coefficient at the time of the second sampling. For time weighting function, is the exponential forgetting time constant.

[0030] Optionally, the time weighting function The calculation formula is:

[0031]

[0032] In the formula, This is the initial moment when the dressing is applied. It is an increasing time constant.

[0033] Optionally, in step S5, a low-risk warning is output when the wet hardness risk index is less than the first threshold, a medium-risk warning is output when the wet hardness risk index is greater than or equal to the first threshold and less than the second threshold, and a high-risk warning is output when the wet hardness risk index is greater than or equal to the second threshold.

[0034] Furthermore, prior to step S5, a step is included to personalize the first and second thresholds based on the patient's age and body mass index.

[0035] Optionally, the initial calibration in step S1 includes: applying a standard pressure to the dressing and recording the corresponding voltage output before the dressing is applied; acquiring the voltage signal in the initial drying state after application; and calculating the reference pressure signal based on the voltage ratio.

[0036] In step S2, after each preset time window, the average value of each signal within that window is calculated for subsequent steps, and abnormal values ​​exceeding a preset reasonable range are removed before calculation. If an abnormality occurs for a set number of consecutive times, a sensor fault prompt is output.

[0037] Beneficial effects:

[0038] 1. First, this invention enables real-time monitoring and quantitative assessment of wet hardening, filling a technological gap. Specifically, this invention addresses the hidden pressure ulcer mechanism in CRRT treatment—the hardening of the gauze buffer layer after absorbing moisture, forming dotted hard protrusions that compress the skin at arterial pulsations. It integrates a hardness-sensitive material layer into the dressing and places it at the corresponding locations of the femoral or carotid artery pulsations. By converting local pressure into electrical signals, combined with temperature and humidity correction, continuous and quantitative monitoring of the dynamic process of the buffer layer from soft to hardening can be achieved, fundamentally solving the technical deficiency of existing dressings that cannot sense changes in wet hardness.

[0039] Secondly, the wet hardness risk index proposed in this invention assigns higher weight to recent pressure through an exponential forgetting factor and suppresses false alarms during the cold start phase through a time weighting function, accurately quantifying the cumulative damage effect of "pressure intensity × duration". This model is more scientific than a single instantaneous pressure threshold judgment, and can distinguish between different risk levels of brief high pressure and sustained medium pressure, effectively reducing the false alarm rate and the missed alarm rate.

[0040] Third, this invention introduces a temperature and humidity correction factor, which automatically increases risk sensitivity in high-temperature and high-humidity environments (where tissue tolerance decreases); at the same time, it personalizes the warning threshold based on the patient's age and body mass index, providing more sensitive protection for elderly or low-body-index patients. This dual correction mechanism can avoid high-risk underreporting or low-risk false alarms caused by a uniform threshold, achieving truly individualized precision care.

[0041] Fourth, this invention integrates a miniature LED indicator and a buzzer within the dressing. When the risk reaches a medium to high level, the patient's skin will directly emit a red / yellow flashing light and a warning sound, allowing medical staff to quickly ascertain the risk status without relying on external terminals. Simultaneously, it pushes tiered warning information to the nurse station and mobile terminals via low-power Bluetooth or a near-field communication module. The three alarm methods—sound, light, and wireless—complement each other, ensuring that warning signals are delivered promptly and reliably in various clinical scenarios.

[0042] Fifth, this invention eliminates batch variations in sensors through standardized initial calibration (applying standard pressure and voltage ratio method); it suppresses physiological noises such as respiration and heartbeat through time window averaging; and it prevents sensor failure from causing misleading information through outlier removal and continuous abnormal fault indication mechanisms. In this way, the robustness of the system in real clinical noise environments can be effectively improved, ensuring the accuracy of risk index calculation and long-term operational reliability.

[0043] Sixth, this invention uses polyvinylidene fluoride nanofibers or polydimethylsiloxane composite materials as the hardness-sensitive layer, is powered by an ultra-thin flexible battery, and uses low-power Bluetooth or near-field communication for wireless communication. All components can be integrated into a disposable dressing with a thickness of no more than 5 mm. The incremental cost per use is low, accounting for a small proportion of the consumable expenditure for CRRT patients, and it is compatible with existing dressing production lines, making it easy to achieve large-scale production and clinical promotion.

[0044] Seventh, this invention employs a three-tiered early warning system, transforming continuous risk indices into clear nursing action instructions. This not only helps nurses allocate time and resources rationally and avoid early warning fatigue, but also shifts pressure ulcer prevention from "post-event detection" to "pre-event intervention," significantly reducing the incidence of catheter fixation-related pressure ulcers, effectively reducing patient suffering, shortening hospital stays, and lowering medical costs.

[0045] Eighth, the system of this invention automatically records the time, risk index, temperature and humidity, patient physiological parameters, and other data for each warning event and uploads them to the management platform to form an individual patient's wet hardness risk profile. This data can be used for clinical nursing quality analysis, continuous optimization of pressure ulcer risk warning models, and evidence-based nursing research, providing objective data support for the construction of a hospital pressure ulcer prevention and control system.

[0046] 2. Other beneficial effects or advantages of the present invention will be described in detail in the specific embodiments. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] in:

[0049] Figure 1 This is a three-dimensional structural diagram of a fixed pressure ulcer care system based on dynamic monitoring of wet hardness provided in an exemplary embodiment of the present invention;

[0050] Figure 2 This is an exploded structural diagram of a fixed pressure ulcer care system based on dynamic monitoring of wet hardness provided in an exemplary embodiment of the present invention;

[0051] Figure 3 This is a flowchart illustrating the steps of an early warning method for a fixed pressure ulcer care system based on dynamic monitoring of wet hardness, provided by an exemplary embodiment of the present invention.

[0052] Figure 4 This is a schematic diagram of the homepage terminal display interface of an intelligent pressure ulcer care system provided in an exemplary embodiment of the present invention;

[0053] Figure 5 This is a specific monitoring detail of patient Zhang provided in an exemplary embodiment of the present invention;

[0054] Figure 6 This is a schematic diagram of a terminal interface for displaying dressing structure parameters provided in an exemplary embodiment of the present invention;

[0055] Figure 7 This is a terminal interface for a single patient's wet hardness risk index change trend curve, provided as an exemplary embodiment of the present invention.

[0056] Figure 8 This is a schematic diagram illustrating the relative hardness coefficient calculation logic of an exemplary embodiment of the present invention.

[0057] Figure 9 This is a schematic diagram of the terminal interface for the real-time pressure sampling waveform of the dressing sensor provided in an exemplary embodiment of the present invention;

[0058] Figure 10 This is a schematic diagram of the system's historical early warning and clinical treatment record ledger interface provided in an exemplary embodiment of the present invention;

[0059] Figure 11 This is a schematic diagram of the algorithm's underlying parameter viewing interface provided in an exemplary embodiment of the present invention.

[0060] Explanation of the labels in the attached drawings:

[0061] 100 - Dressing body; 101 - Medical pressure-sensitive adhesive layer; 102 - Sensor integration layer; 1021 - Hardness-sensitive material layer; 1022 - Flexible printed circuit layer; 1023 - Transparent polyurethane film layer; 103 - Moisture-absorbing buffer layer; 104 - Transparent polyurethane film layer. Detailed Implementation

[0062] To facilitate a clearer and more accurate understanding of the technical solutions of this invention by those skilled in the art, the existing related technologies and their technical problems will be described in more detail below.

[0063] During continuous renal replacement therapy (CRRT), proper fixation of the femoral vein or internal jugular vein catheter is a crucial step in ensuring treatment safety. The routine clinical procedure is generally as follows: Taking the femoral vein catheter as an example, after successful puncture, the nurse uses a suture wing to fix the catheter to the skin on the patient's inner thigh. Each side of the suture wing has one to two suture holes, and the catheter is sutured to the skin. Subsequently, two to four layers of sterile gauze (each layer approximately 0.3 to 0.5 mm thick, with a total area of ​​approximately 4 cm × 4 cm) are placed under the suture wing and catheter connector to cushion the local pressure of the rigid plastic of the suture wing on the skin. Finally, a transparent polyurethane film dressing (commonly 10 cm × 12 cm) is used to cover the entire puncture area, using the adhesive properties of the dressing to fix the suture wing, gauze, and catheter to the skin surface.

[0064] In existing related technologies, some improved solutions have proposed intelligent monitoring devices for catheter fixation. However, these devices monitor the tensile or torsional forces on the catheter body in real time by embedding a thin-film pressure sensor inside the catheter fixation clip. When the pressure exceeds a set threshold, an audible and visual alarm is triggered to prevent the catheter from dislodging or kinking. Another example is the development of a multimodal sensing-based pressure ulcer risk assessment system (such as using a MEMS piezoresistive array combined with temperature and humidity sensors, and incorporating a long short-term memory neural network for dynamic risk assessment). This system has been studied for use in mattresses or surgical positioning pads, but it requires an external power supply and a separate data processing terminal, making it impossible to integrate into disposable catheter dressings.

[0065] The following example illustrates the technical problems existing in related technologies.

[0066] Patient Li, Body Mass Index (BMI) The patient underwent femoral vein catheterization for acute kidney injury. Initially, the nurse placed three layers of dry gauze under the suture wings and covered it with a transparent dressing. Four hours after treatment began, the patient experienced profuse sweating due to fever, with sweat seeping into the gauze layers along the dressing edges. In its dry state, the gauze fibers maintain a loose structure through weak van der Waals forces and mechanical entanglement, conforming to the skin's contours and dispersing the concentrated pressure from the suture wings into a larger, more uniform pressure area. However, as the amount of sweat absorbed reached over 200% of the gauze's weight, the cotton fibers swelled significantly, the fiber diameter expanded, and the gaps between fibers compressed considerably. The relative sliding between fibers was inhibited by numerous hydrogen bonds and capillary forces, causing the gauze to transform from a soft, loose state into a hardened, clumpy structure. The elastic modulus in localized areas increased sharply, forming multiple dot-like hard protrusions approximately 3 to 5 mm in diameter.

[0067] These hard protrusions press precisely on the point where the femoral artery pulsates most strongly (where the skin is only 0.5 to 1.2 mm thick, and the subcutaneous fat layer is extremely thin, directly covering the adventitia of the artery). Studies have shown that the capillary closure pressure is approximately 32 mmHg (4.3 kPa). When local pressure exceeds this value and persists for more than 30 minutes, microcirculation is interrupted, and tissue ischemia and hypoxia begin. In this example, the measured peak local pressure exerted on the skin by the hard protrusions reached 20 to 30 kPa (approximately 150 to 225 mmHg), far exceeding the capillary closure pressure. However, because the transparent dressing is completely opaque and provides a tight cover, nurses cannot visually detect the hardened and clumped gauze during routine rounds (every 30 to 60 minutes), nor can they perceive the local high-pressure point beneath it. It wasn't until the dressing was removed during the 10th hour of treatment that a deep tissue injury of approximately 1.5 cm in diameter was discovered at the site of the femoral artery pulsation. The pressure ulcer was classified as unstageable (full-thickness tissue loss, with the base covered by necrotic tissue or eschar), indicating that the actual damage had reached the fascia layer. In this case, if a warning had been received early in the hardening of the gauze (e.g., when the absorbency reached 50% of its saturation), the nursing staff could have changed the dressing and cushioning layer in time before the pressure ulcer formed (irreversible damage usually occurs after 2 to 4 hours of continuous pressure), thus preventing tissue damage.

[0068] In summary, the shortcomings of existing technologies are that no catheter fixation dressing or its supporting system can monitor and provide risk warnings in real time for changes in the wet hardness of the absorbent buffer layer (gauze or equivalent material). Existing solutions either do not monitor any physical quantities at all (traditional dressings), or monitor the forces on the catheter body (such as tensile force and torsional force) rather than the local hardness of the buffer layer-skin interface, or require complex external equipment and cannot be integrated into disposable dressings.

[0069] In view of this, the present invention provides a novel solution: a fixed pressure ulcer care system and early warning method based on dynamic monitoring of wet hardness. The technical concept of this invention is to overcome the limitations of existing catheter fixation dressings that only focus on the force on the catheter body or static cushioning, and to use "wet hardness" as a core measurable indicator of pressure ulcer occurrence. This is achieved by placing a hardness-sensitive material layer on the dressing corresponding to the arterial pulsation location, and integrating temperature and humidity sensors to construct a chain monitoring model of "moisture absorption → increased hardness → increased local pressure → accumulation of risk index." Based on this, an accumulation algorithm with an exponential forgetting mechanism is used to calculate the wet hardness risk index, quantifying the dynamic process of the buffer layer from soft to hardened, and outputting a graded early warning signal when the risk reaches a preset threshold, thereby providing a time window for clinical intervention before irreversible tissue damage occurs.

[0070] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings.

[0071] like Figures 1 to 2 As shown, according to a first aspect of the present invention, a fixed pressure ulcer care system based on dynamic monitoring of wet hardness is provided, comprising a multi-layer composite dressing body 100, wherein the dressing body 100 comprises, from the skin contact surface outward, a medical pressure-sensitive adhesive layer 101, a sensor integration layer 102, a moisture-absorbing buffer layer 103, and a transparent polyurethane film layer 1041023.

[0072] The sensor integration layer 102 is embedded with a hardness-sensitive material layer 1021, a flexible printed circuit layer 1022 and a reference electrode layer, wherein the hardness-sensitive material layer 1021 is disposed in the area of ​​the dressing corresponding to the pulsation position of the femoral artery or carotid artery.

[0073] The flexible printed circuit layer 1022 integrates a signal processing chip, a timing unit, a power supply unit, and a wireless communication module.

[0074] The hardness-sensitive material layer 1021 is used to generate an electrical signal proportional to the magnitude of the force when subjected to local pressure. The signal processing chip is used to collect the electrical signal and convert it into a pressure value. It calculates the wet hardness risk index based on the pressure value, skin surface temperature, skin surface humidity and time accumulation, and then compares it with a preset warning threshold. Different levels of warning signals are output through the wireless communication module.

[0075] Through the above technical solution, firstly, the system of the present invention can achieve direct real-time monitoring of the wet hardening of the moisture-absorbing buffer layer 103. Specifically, the present invention introduces a hardness-sensitive material layer 1021 into the dressing. This layer is placed in the pulsating area of ​​the femoral or carotid artery, and can convert the local pressure into an electrical signal proportional to the magnitude of the force. When the moisture-absorbing buffer layer 103 hardens due to absorbing sweat and forms dot-like hard protrusions, these protrusions exert pressure on the hardness-sensitive material layer 1021, and the electrical signal is enhanced accordingly. In this way, the dynamic process of the buffer layer from soft to hardening can be perceived in real time and quantitatively, overcoming the defect that it cannot be observed with the naked eye.

[0076] Secondly, the system of this invention can precisely target the monitoring focus to the highest risk area for pressure ulcers. Specifically, the hardness-sensitive material layer 1021 of this invention is placed in the area of ​​the dressing corresponding to the pulsation location of the femoral or carotid artery. This area has thin skin, little subcutaneous fat, and pulsating arteries underneath, making it the most susceptible site for deep tissue damage under the pressure of wet induration. Thus, through targeted placement, ineffective sensing across the entire dressing area can be effectively avoided, improving the specificity of monitoring and the signal-to-noise ratio.

[0077] Third, the system of this invention can achieve risk quantification and graded early warning based on the fusion of multiple physical quantities. Specifically, the signal processing chip of this invention not only collects pressure values, but also calculates a wet hardness risk index by combining skin surface temperature, skin surface humidity, and cumulative time, and outputs different levels of early warning signals through a wireless communication module after comparing it with a preset threshold. In this way, the system of this invention can distinguish between simple instantaneous pressure and continuous cumulative hardness compression, while taking into account the influence of temperature and humidity on tissue tolerance, thereby outputting graded early warnings (e.g., low, medium, and high risk), providing nursing staff with clear and actionable guidance (e.g., changing dressings within 2 hours or immediate treatment), thus realizing a shift from passive detection to proactive prevention.

[0078] Fourth, the system of this invention possesses independent, wireless remote monitoring capabilities. Specifically, this invention integrates a power supply unit and a wireless communication module within the dressing, eliminating the need for an external power supply or data cable, allowing the entire nursing system to be used disposablely with the dressing. The wireless communication module can send warning signals to the nurse station terminal or mobile nursing equipment, enabling remote monitoring, reducing the burden of frequent nurse rounds, and ensuring that high-risk conditions can be detected promptly.

[0079] In one embodiment of the present invention, the hardness-sensitive material layer 1021 is a polyvinylidene fluoride nanofiber membrane layer or a polydimethylsiloxane composite material layer; the moisture-absorbing buffer layer 103 is composed of at least two layers of nonwoven fabric laminated together, with carboxymethylated cotton fiber or alginate fiber filled between the layers, and the total thickness of the moisture-absorbing buffer layer 103 is 2.0 to 5.0 mm; the power supply unit is a flexible battery with a thickness of no more than 0.5 mm; and the wireless communication module is a Bluetooth module or a near-field communication module.

[0080] In this embodiment, firstly, the PVDF (polyvinylidene fluoride) nanofiber membrane exhibits a piezoelectric effect, converting pressure signals into electrical signals without an external power source. Furthermore, the membrane thickness can be controlled between 0.1 and 0.3 mm, exhibiting good flexibility and conforming to the curvature of the skin surface. The PDMS (polydimethylsiloxane) composite material is a flexible elastomer that achieves a piezoresistive effect through the doping of conductive particles. Its elastic modulus is close to that of human soft tissue (approximately 0.5 to 2 MPa), preventing additional pressure on the skin due to its rigidity. Both materials overcome the shortcomings of traditional rigid sensors, ensuring pressure sensing sensitivity while maintaining the overall softness of the dressing and patient comfort.

[0081] Secondly, the moisture-absorbing buffer layer 103 is composed of at least two layers of nonwoven fabric laminated together, with carboxymethylated cotton fibers or alginate fibers filling the spaces between the layers, and a total thickness of 2.0 to 5.0 mm. The multi-layered structure of the nonwoven fabric creates an interwoven fiber network between the layers. The highly absorbent fibers filling the spaces between the layers (carboxymethylated cotton fibers can absorb 10 to 15 times their own weight in moisture, and alginate fibers form a gel after absorbing moisture) can quickly and evenly disperse sweat throughout the buffer layer, avoiding local oversaturation. At the same time, the gelation between the fibers can replace the direct fiber-to-fiber contact hardening of ordinary gauze, making the increase in hardness of the buffer layer after moisture absorption gradual rather than abrupt, and the hardness distribution more uniform. Compared with the dotted hard protrusions formed after ordinary gauze absorbs moisture, the buffer layer of the present invention forms a relatively uniform gel state when saturated with moisture, thereby reducing the peak pressure on the local skin.

[0082] Finally, flexible batteries with a thickness of ≤0.5mm (such as lithium polymer flexible batteries with a capacity of 20 to 50mAh) can provide sufficient power (calculated to support 72 hours of continuous operation) without creating new pressure points due to localized thickening of the battery, thus avoiding pressure sores caused by the monitoring device itself. Meanwhile, in clinical environments, the distance between a patient's bed and the nurse's station is typically within 10 to 50 meters. Bluetooth 5.0 modules have a transmission range of 10 to 30 meters, sufficient to cover a single ward; NFC modules allow nurses to read data simply by placing their handheld terminals near the dressing, suitable for scenarios that do not require continuous remote monitoring but need to obtain risk information on demand. Both solutions avoid the stringent battery capacity requirements of high-power communication modules, enabling reliable data transmission within the cost and size constraints of disposable dressings.

[0083] In one embodiment of the present invention, the sensor integration layer 102 may also integrate a miniature LED indicator and a miniature buzzer, which are electrically connected to the signal processing chip respectively.

[0084] In this embodiment, the miniature LED indicator is first electrically connected to the signal processing chip. When the signal processing chip determines that the risk index has reached a preset threshold, it can control the LED indicator to emit light signals of different colors or flashing frequencies (such as solid green, slow yellow flashing, and fast red flashing). This light signal propagates directly outward through the transparent polyurethane film layer 1041023. When medical staff patrol the ward, they do not need to check any terminal equipment; they can quickly determine the current risk level simply by visually observing the dressing on the patient's body.

[0085] Meanwhile, the miniature buzzer is electrically connected to the signal processing chip. When the risk level reaches a specific level (such as high risk), the buzzer can be triggered to emit intermittent or continuous warning sounds. When the patient's position is covered by clothing or bedding, causing the LED lights to be blocked, the acoustic warning can penetrate the covering. When the nurse is outside the ward or not directly facing the patient, the sound signal can be used as a means of attracting attention and guiding the nurse to check the patient's dressing status.

[0086] According to a second aspect of the invention, such as Figure 3 As shown, an early warning method for a fixed pressure ulcer care system based on dynamic monitoring of wet hardness using any of the technical solutions in the first aspect of the present invention is also provided, characterized by comprising the following steps:

[0087] Step S1: After the dressing is applied to the patient's skin, a baseline pressure signal in a dry state is obtained through initial calibration;

[0088] Step S2: Continuously collect the real-time pressure signal of the hardness-sensitive material layer 1021 at the preset sampling frequency, and simultaneously collect the skin surface temperature and skin surface relative humidity;

[0089] Step S3: Calculate the relative hardness coefficient based on the ratio of the real-time pressure signal to the reference pressure signal, combined with the current temperature and humidity;

[0090] Step S4: Calculate the wet hardness risk index at the current moment based on the relative hardness coefficient, time decay weight, and time accumulation at historical moments.

[0091] Step S5: Compare the calculated wet hardness risk index with the preset first threshold and second threshold, and output different levels of warning signals based on the comparison results.

[0092] In this implementation, firstly, in step S1 of the present invention, a baseline pressure signal in a dry state is obtained through initial calibration after the dressing is applied to the patient's skin. This ensures that differences in skin elasticity among different patients, differences in sensor sensitivity between different dressing batches, and differences in initial pressure caused by different application forces can all be normalized using the baseline signal, making the subsequently calculated risk index comparable across individuals and batches.

[0093] Second, in step S2 of this invention, real-time pressure signals are continuously collected at a preset sampling frequency, while skin surface temperature and relative humidity are also collected. This ensures that the data in the three dimensions of pressure, temperature, and humidity are synchronized over time. Furthermore, continuous collection means that the system tracks the wet hardening process throughout its entire lifecycle, rather than performing single or intermittent measurements. This allows it to capture the dynamic evolution of hardness from low to high, providing time-series data for cumulative risk calculation.

[0094] Third, in step S3 of this invention, the relative hardness coefficient is calculated based on the ratio of the real-time pressure signal to the reference pressure signal, combined with the current temperature and humidity. In this way, the original pressure signal can be converted into a relative value compared with the initial state, eliminating static baseline drift; at the same time, temperature and humidity correction is introduced, so that the same physical pressure value is given a higher relative hardness coefficient in a high temperature and high humidity environment (where tissue tolerance decreases), thereby achieving environmental adaptive adjustment for risk perception.

[0095] Fourth, in step S4 of this invention, the wet hardness risk index at the current moment is calculated based on the relative hardness coefficient at historical times, the time decay weight, and the time accumulation. Pressure ulcer formation is essentially a cumulative effect of "pressure × time"; both brief periods of extremely high pressure and prolonged periods of low pressure can lead to tissue damage. This step, by introducing a time decay weight (making the contribution of recent pressure to the current risk greater than that of long-term pressure) and a time accumulation (integrating historical pressure), transforms discrete pressure sampling values ​​into continuous risk accumulation values, thereby accurately reflecting the pathophysiological process of pressure ulcer formation.

[0096] Fifth, in step S5 of this invention, the calculated risk index is compared with a preset first threshold and a second threshold, and different levels of warning signals are output based on the comparison results. This step discretizes the continuous risk index into a finite number of risk levels (e.g., low, medium, high), each level corresponding to specific clinical action recommendations (e.g., no intervention required, dressing change within 2 hours, immediate treatment, etc.). Simultaneously, the tiered warning mechanism can avoid missed reports (frequent false alarms due to a low threshold, and delayed intervention due to a high threshold) or information overload caused by a single threshold, enabling nursing staff to rationally allocate attention and resources according to the warning level.

[0097] In one embodiment of the present invention, the relative hardness coefficient in step S3 is... The calculation formula is:

[0098]

[0099] In the formula, For real-time pressure signals, As the reference pressure signal, This is the temperature and humidity correction factor (dimensionless coefficient). Skin surface temperature The relative humidity of the skin surface.

[0100] In this implementation, firstly, ratio normalization eliminates individual differences, batch differences, and installation differences, achieving a unified early warning threshold. Specifically, in the formula... The item divides the real-time pressure signal by the reference pressure signal at the initial drying state. For example, suppose a patient experiences initial pressure issues due to poor skin elasticity or excessively tight application of the dressing. Another patient's initial stress If both cause the absolute pressure to rise to [a certain level] due to wet hardening... The former has a ratio of 2, while the latter has a ratio of 3.75. The latter shows a more significant increase in actual hardness and carries a higher risk. If absolute pressure (both are...) is used... This would lead to the failure to detect the higher risk of the latter. In other words, by normalizing the ratio, the relative hardness coefficient can directly reflect the ratio of hardness to the initial state, making the same set of warning thresholds (such as the first threshold of 5.0 and the second threshold of 15.0) applicable to all patients and dressing batches, avoiding the problem of incomparable absolute pressure values.

[0101] Second, in the formula This term is a coefficient that dynamically changes based on the current temperature and humidity. When skin surface temperature or humidity increases (e.g., when a patient has a fever and sweats), , At this time, the body's tissues become less tolerant to pressure, increasing the risk of injury from the same physical pressure. The value can be greater than 1 (see below for specific value rules), which makes the relative hardness coefficient... In the same The ratio is amplified, thus triggering a higher-level warning earlier. Conversely, in low-temperature and dry environments (such as air-conditioned hospital rooms), , Increased tissue tolerance The value can be less than 1. The threshold is narrowed to avoid unnecessary interventions caused by conservative thresholds. Through this correction mechanism, risk assessment can dynamically match the actual physiological state of the patient's microenvironment, effectively improving the accuracy and clinical applicability of early warnings.

[0102] Third, this formula integrates environmental perception and pressure perception, enabling a more comprehensive and sensitive assessment of pressure ulcer risk. Specifically, this formula... By incorporating temperature and humidity data into the pressure ratio, the system can identify dangerous conditions where "although the pressure increase is not significant, the adverse microenvironment already poses a high risk." For example, patient sweating leading to... , Reaching 1.25, even at this point (Mild hardening) If it is increased to 1.5, it may trigger a medium-risk warning; if it is not corrected, the pressure ratio of 1.2 may still be in the low-risk range.

[0103] In this embodiment, it should be noted that, in a physical sense, This indicates that the current hardness is the same as the initial state after drying; This indicates an increase in hardness; This indicates a decrease in hardness (which should not theoretically occur, as moisture absorption should only increase hardness, but may be due to pressure release caused by changes in the patient's position).

[0104] In one embodiment of the present invention, the temperature and humidity correction factor of the present invention The calculation formula is:

[0105]

[0106] In the formula, For reference temperature, It is a temperature characteristic constant. For reference humidity, The characteristic constant of humidity, , Let be the normalization coefficients, and the above equation satisfies .

[0107] In this embodiment, firstly, physiological studies have shown that for every 1°C increase in skin temperature, the metabolic rate increases by approximately 10%, and the tissue's sensitivity to ischemia increases exponentially; when skin humidity exceeds 80% RH, the rate of decrease in mechanical strength due to stratum corneum hydration accelerates dramatically. (Exponential function) This more accurately describes the increasingly rapid downward trend. When temperature and humidity deviate slightly from the baseline, the index value is close to 1, with only minor correction; when temperature and humidity deviate significantly, the index value amplifies rapidly, making... The risk sensitivity is significantly improved in extreme microenvironments, thus avoiding underreporting. Furthermore, since the effects of temperature and humidity on tissue tolerance are not independent but mutually reinforcing, this invention uses the sum of temperature and humidity deviations as the independent variable of an exponential function to demonstrate that the weakening effect on tissue tolerance is stronger when high temperature and high humidity coexist.

[0108] Second, since the range of the exponential function is (0, +∞), a normalization coefficient is introduced. To avoid masking the true risks (when temperature and humidity deviate significantly from their true values, such as in low-temperature dryness, the index approaches 0, which can lead to...). Approaching 0 causes the relative hardness coefficient to be excessively reduced. Simultaneously, the introduced normalization coefficient... Then, a certain weight is assigned to the exponential type, which allows for flexible adjustment. , The value of can not only ensure a sufficient range of sensitivity adjustment, but also prevent the risk index from fluctuating drastically due to excessive correction.

[0109] Third, this implementation method is computationally simple and is very suitable for embedded real-time processing.

[0110] In this embodiment, it should be noted that the temperature characteristic constant The value (corresponding to the maximum skin temperature difference in physiological terms) can be between 4 and 8°C. For example, This means that when the patient's temperature is 8°C higher than the reference temperature, exp(1) is approximately 2.718, meaning the correction factor is magnified by about 2.7 times. The 8°C range can cover the maximum possible temperature difference on the skin surface (from a low of 32°C to a high of 40°C), placing the correction curve in the early part of the rising segment of the exponential function within the clinically common temperature difference range (0 to 4°C), indicating moderate variation. Simultaneously, the humidity characteristic constant... The value range can be from 20%RH to 30%RH. For example, when... At that time, it can make the common humidity changes (50% to 90% RH) corresponding to Between 0 and 1.6, the exponential function has not yet entered a period of sharp increase. Understandably, in practice... , You can choose an appropriate value, for example, , To facilitate clinical labeling.

[0111] In one embodiment of the present invention, the wet hardness risk index in step S4 is... The calculation formula is:

[0112]

[0113] In the formula, For the current moment, For the first The time point of the next sampling For the first The relative hardness coefficient at the time of the second sampling. For time weighting function, is the exponential forgetting time constant.

[0114] In this embodiment, firstly, the cumulative effect of "pressure × time" is quantified by summing discrete integrals, filling the gap in existing technologies for quantifying the time dimension. Specifically, the formula in this embodiment applies to the time dimension from the initial moment. up to the current moment The relative hardness coefficients of all sampling points are weighted and summed. Each This represents the hardness level at that moment, multiplied by the sampling interval (implied in the summation term; because the sampling frequency is fixed, each sampling point represents a fixed time increment), to achieve numerical integration of the pressure-time curve. When the hardness remains at a high level, It gradually accumulates and increases; when the hardness returns to a low level, the newly added term contributes little, and the historical term gradually fades due to exponential decay, making... This allows for a precise mapping of the "reversible and irreversible" boundary of tissue damage. In other words, timely decompression after short-term compression allows tissue to repair itself through reperfusion; however, long-term continuous compression leads to accumulated damage exceeding the tissue's repair capacity, resulting in irreversible necrosis.

[0115] Second, in the exponential forgetting factor middle, Indicates the current time and the number of... The time difference (in seconds) between the next sampling time. (At the current moment), the exponent value is 1, and the current hardness value is fully factored in; when (i.e., before a forgetting time constant), the exponent value is At that moment, only about 36.8% of the hardness contribution was retained; when At this point, the index value approaches 0, and historical data is almost forgotten. The physiological basis for this design is that tissues undergo reperfusion after pressure is released. If the pressure time is short and subsequently relieved after a long period, the previously caused microcirculatory disturbances can be completely repaired by the body; conversely, if the pressure is persistent or has just occurred, its damaging effects still dominate. In other words, the exponential decay curve can appropriately simulate this process, avoiding an artificially high risk index caused by the infinite accumulation of historical data.

[0116] Third, this formula includes independent factor, That is, in the initial stage of dressing application The pressure initially approaches 0, then gradually rises to 1. This addresses the cold start problem: when the dressing is first applied, it hasn't fully adhered to the skin, the initial pressure signal may be unstable, and even if some pressure is applied at this time, the duration of action is extremely short, preventing the accumulation of high-risk factors. The initial stage is suppressed to avoid false alarms (explained in detail below). Furthermore, this factor is designed separately from the exponential forgetting factor, allowing the time modulation function to be adjusted independently without affecting the forgetting time constant. Physiological significance ( The physiological significance corresponds to the tissue reperfusion time window.

[0117] In this embodiment, it should also be noted that for each newly added sampling point The system does not need to recalculate the entire history; it can utilize recursive relationships. (in This recursive form can greatly reduce computational complexity, enabling embedded chips to update in real time at a 1Hz sampling rate. This meets the needs of continuous monitoring. Meanwhile, The curve over time can intuitively reflect the trend of risk evolution. That is, the rising segment indicates that the hardness continues to increase, and the falling segment indicates that the hardness is relieved (such as when the patient's position changes or the dressing falls off). Nursing staff can judge the intervention effect by the trend.

[0118] In one embodiment of the present invention, the time weighting function of the present invention The calculation formula is:

[0119]

[0120] In the formula, This is the initial moment when the dressing is applied. The time constant is increasing.

[0121] In this embodiment, firstly, as described above, the time weighting function in this embodiment... It can achieve smooth suppression of cold start risk accumulation and avoid false alarms in the initial stage. Specifically, when hour, Substituting into the formula, we get That is, the sampling data at the moment of pasting has zero weight and does not participate at all. The cumulative calculation. Over time, Gradually increase It starts monotonically increasing from 0. When hour, ;when hour, ;when hour, The value is approximately 1. This ensures that the sampling data in the initial stage of dressing application (typically corresponding to system startup and initial stabilization) contributes very little to the risk index, and the system is in an "observation period." As time increases, the weight gradually rises to its maximum value, and the system enters a stable monitoring state. In this way, false alarms caused by initial transient interference can be effectively eliminated.

[0122] Secondly It is a preset time constant whose value determines the speed at which the weight increases from 0 to 1. The larger the value, the longer the transition period, and the more persistent the system's suppression of the initial data; The smaller the value, the shorter the transition period, and the faster the system enters full-weighted weighing mode. In actual clinical applications, this value can be set according to the type of dressing, the patient's skin characteristics, or treatment needs. For example, for patients with excessive sweating, the initial moisture balancing may take longer, so a larger value can be selected. (e.g., 600 seconds); for regular patients, The need can be met in 5 minutes.

[0123] Furthermore, in the aforementioned embodiments This approach involves "forgetting" historical data and emphasizing the importance of recent data. This is "forward suppression" of early data, emphasizing low weight in the initial stage. Multiplying these two factors, the overall weight function becomes:

[0124]

[0125] This joint weighting exhibits a single-peak shape on the time axis, rising first and then falling, with the peak position determined by the ratio of the two time constants. This means the system assigns the highest weight to data from the "relatively recent but past the cold start period," while giving lower weights to very early (within the cold start period) and very distant (far beyond the forgetting time constant) data. Through this dual-exponential modulation, the physiological process of pressure ulcer formation can be more precisely matched; that is, initial, brief pressure does not pose a risk, sustained pressure in the later stages contributes the most, and premature historical pressure is gradually forgotten because the tissue may have already repaired.

[0126] Current technologies for pressure ulcer risk assessment and early warning suffer from two prominent problems: First, risk grading is too coarse, with most schemes only setting a single threshold (e.g., triggering an alarm when pressure exceeds a certain value), lacking intermediate levels. This makes it difficult for caregivers to distinguish between risk states requiring "elective treatment" and "emergency treatment," easily leading to improper resource allocation or early warning fatigue. Second, early warning thresholds are usually fixed and do not consider individual physiological differences among patients. In clinical practice, elderly patients with skin atrophy, thinner dermis, and reduced subcutaneous fat have significantly lower pressure tolerance than younger patients; patients with low body mass index (BMI) are more susceptible to excessive pressure at bony prominences due to a lack of fat cushioning. Research data shows that the risk of pressure ulcers increases approximately 1.3 times for every 10-year increase in age; patients with a BMI below a certain level are more prone to pressure ulcers. Patients with high risk of pressure ulcers have a 2 to 3 times higher incidence rate than patients with normal BMI. Using a uniform threshold can lead to significant underreporting of high-risk individuals (elderly, low BMI) (the threshold is relatively high), while low-risk individuals may be over-reported.

[0127] In view of this, in one embodiment of the present invention, in step S5, a low-risk warning is output when the wet hardness risk index is less than a first threshold, a medium-risk warning is output when the wet hardness risk index is greater than or equal to the first threshold and less than a second threshold, and a high-risk warning is output when the wet hardness risk index is greater than or equal to the second threshold; and before step S5, a step of personalized correction of the first threshold and the second threshold based on the patient's age and body mass index is also included.

[0128] This allows the wet hardness risk index to be divided into three zones: below the first threshold (low risk), between the first and second thresholds (medium risk), and not below the second threshold (high risk). Each zone corresponds to a different warning signal output (e.g., a green alert for low risk, a yellow alert for medium risk, and a red alert for high risk). This tiered design enables nurses to respond differently based on the warning level. For example, in a low-risk state, no immediate intervention is required, and routine nursing procedures can be maintained; in a medium-risk state, a message is sent suggesting "change the dressing within 2 hours," providing nurses with a clear and actionable time window; in a high-risk state, a message is sent prompting "change the dressing immediately and assess the skin at the pressure point," triggering emergency treatment. Compared to a binary output of a single threshold alarm (either normal or alarming), the three-tiered system avoids "overreaction" or "underreaction," ensuring a rational allocation of clinical resources and reducing nurses' alarm fatigue caused by frequent alarms.

[0129] In this embodiment, prior to step S5, the first and second thresholds are adjusted based on the patient's age and body mass index (BMI). The logical direction of the adjustment is as follows: for high-risk patients who are older or have a lower BMI, the threshold is adjusted downwards (i.e., the adjusted threshold is lower than the original threshold); for low-risk patients who are young, have a normal BMI, or have a high BMI, the threshold is adjusted upwards or not significantly adjusted. Specifically, when the patient's age exceeds the reference value (e.g., 60 years old) or BMI is lower than the reference value (e.g., ...), the threshold is adjusted downwards. When the skin and subcutaneous tissues are at a lower risk of pressure, the same wet hardness risk index corresponds to a higher risk of tissue damage. By lowering the threshold, the same risk index is more likely to trigger a medium- or high-risk warning, thus providing more sensitive protection for high-risk individuals. Conversely, for young, normal-weight, or overweight patients, the threshold should be appropriately raised to avoid unnecessary clinical intervention due to oversensitivity.

[0130] In this embodiment, it is understood that various methods can be used to personalize the first and second thresholds based on the patient's age and body mass index. For example, the new threshold can be calculated as: new threshold = old threshold × k(A, BMI), where the correction coefficient k decreases with increasing age and decreasing BMI; or a piecewise function can be used: the threshold is lowered by 30% when the patient is ≥70 years old or has a BMI <18.5, and remains unchanged in other cases. This invention does not specifically limit the correction method.

[0131] In one embodiment of the present invention, the initial calibration in step S1 may include: applying a standard pressure to the dressing and recording the corresponding voltage output before the dressing is applied, acquiring the voltage signal in the initial drying state after application, and calculating the reference pressure signal based on the voltage ratio.

[0132] In step S2, after each preset time window, the average value of each signal within that window is calculated for subsequent steps, and abnormal values ​​exceeding the preset reasonable range are removed before calculation. If an abnormality occurs for a set number of consecutive times, a sensor fault prompt is output.

[0133] The following is in conjunction with the appendix Figures 4 to 11 The technical solution of the present invention will be further described by an exemplary embodiment.

[0134] I. System Structure.

[0135] Please see Figure 6 ( Figure 6 This is a terminal interface displaying dressing structure parameters. The interface is divided into two parts: a schematic diagram of the dressing's layered structure and hardware performance parameters. From top to bottom, it shows the four-layer composite arrangement of the dressing from the skin side outwards, indicating the material and thickness specifications of each layer, and simultaneously listing hardware selection parameters such as sensing materials, power supply, alarms, and communication. This exemplary embodiment provides a catheter fixation pressure ulcer care system based on dynamic monitoring of wet hardness, and its dressing body structure is as follows:

[0136] Medical pressure-sensitive adhesive layer: silicone pressure-sensitive adhesive, 0.1mm thick, filled with micropores.

[0137] Sensor integration layer: 0.5mm thick, flexible polyimide substrate, internally embedded:

[0138] Hardness-sensitive material layer: polyvinylidene fluoride (PVDF) nanofiber membrane, 0.2 mm thick, placed on the dressing at the location corresponding to the femoral artery pulsation (about 2 cm inside the puncture point).

[0139] Flexible printed circuit layer: integrates signal processing chip (ARM Cortex-M0, 12-bit ADC), timing unit (crystal oscillator), power supply unit (0.4mm thick, 30mAh capacity flexible lithium polymer battery), and wireless communication module (BLE5.0).

[0140] Reference electrode layer: silver / silver chloride film.

[0141] Moisture-absorbing cushioning layer: Three layers of non-woven fabric stacked together (40 g / m² per layer) The layers are filled with carboxymethylated cotton fibers, with a total thickness of 3.5mm.

[0142] Transparent polyurethane film layer: 0.05mm thick, 92% light transmittance.

[0143] The sensor integration layer also integrates miniature LED indicator lights (red / yellow / green) and a miniature buzzer, all of which are electrically connected to the signal processing chip.

[0144] II. Application Scenarios and Initial Parameters.

[0145] Please see Figure 4 and Figure 5 ( Figure 4 This is the homepage terminal display interface of the intelligent pressure ulcer care system provided by this invention. It displays overall monitoring statistics for all CRRT patients in the hospital, divided into four statistical dashboards: safe, intermediate-risk, and high-risk. A list of high-risk patients' early warning information is highlighted in real time, containing basic patient information, catheter type, current risk level, and a detailed viewing entry. This interface is used to achieve centralized monitoring of all bedridden patients in the hospital, and it demonstrates the application effect of the invention's tiered early warning and batch monitoring capabilities. Figure 5 It also shows the specific monitoring details of patient Zhang. Patient Zhang, male, 68 years old, underwent CRRT treatment for acute kidney injury, and a femoral vein catheter was inserted. Patient age A = 68 years, body mass index... (Slightly thin). The nursing staff applied the dressing to the catheter fixation site as usual and started the system.

[0146] Initial calibration:

[0147] Before applying the dressing, use a calibration device to apply standard pressure to the dressing. Record the average output voltage of the PVDF.

[0148] After pasting, the average pressure signal voltage was collected for 1 minute during the initial drying state.

[0149] Calculate the reference pressure signal: .

[0150] III. Data Acquisition and Preprocessing.

[0151] The system uses a sampling frequency Acquire real-time pressure signals Skin surface temperature and relative humidity Every 60 seconds is a time window; the average value within the window is calculated, and outlier removal is performed. Reasonable range: 0 to 20 kPa 32 to 42℃ 20 to 100% RH).

[0152] At the 3rd hour after treatment began (t=10800 seconds), the patient experienced changes in the microenvironment due to fever and sweating. The following is a 60-second window of data taken at the top of the 3rd hour:

[0153] Mean pressure average temperature average humidity Previously, no abnormal values ​​were observed in multiple consecutive windows, indicating that the sensor was functioning normally.

[0154] For example, see [link / reference] Figure 9 , Figure 9 It is a terminal interface for real-time pressure sampling waveform of dressing sensor; it supports switching between different patients' original sampling data, marking abnormal peak noise (exceeding 20kPa pressure threshold) caused by body movement disturbance in the waveform, and automatically removing abnormal values ​​and continuous fault automatic alarm mechanism in the interface notes system.

[0155] IV. Calculation of relative hardness coefficient.

[0156] Using the temperature and humidity correction factor formula ,in, , Reference temperature Temperature characteristic constant Reference humidity Humidity characteristic constant .

[0157] Substituting the data, we can calculate: .

[0158] Then, the relative hardness coefficient can be calculated: .

[0159] V. Calculation of wet hardness risk index.

[0160] The system needs to calculate the current time. Cumulative risk index Prior to this, the system had continuously recorded data from... (Paste time) to All sampling points. To simplify calculations, the average value every 60 seconds is used as the calculation node, with an interval of... There are a total of 180 nodes. The recursive formula is: Among them, the exponential forgetting time constant (30 minutes), increasing time constant (5 minutes). Time weighting function: ,because Calculate the first window :when , , .when (t=1800s) The value is close to 1. Therefore, the weight gradually increases from 0 to about 0.632 in the first 5 minutes (5 windows), and then quickly saturates.

[0161] To demonstrate the calculation process, a simplified set of... Data on changes over time (based on typical hygroscopic hardening curves):

[0162] 0 to 1 hour (0 to 3600 seconds): Initial drying. It rises slowly, with an average of about 1.5;

[0163] Hours 1-2 (3600-7200 seconds): Moisture absorption begins. It rose to approximately 3.0;

[0164] Hours 2-3 (7200-10800 seconds): Significant hardening. It rose to approximately 5.5, but in this embodiment, it was measured at the top of the 3rd hour. This indicates that the hardening process accelerates in the last hour.

[0165] The actual system updates in real time using a recursive method. The calculation begins at the end of the 3rd hour (…). Let R(7200) = 8.5 at the end of the second hour (t = 7200 seconds) (this value is derived from the previous recursion). Then calculate the cumulative contribution of 60 nodes (each node is 60 seconds apart) from 7200 seconds to 10800 seconds.

[0166] To simplify manual calculations, a piecewise averaging method is used: the 60 H values ​​within the third hour (from 7200 to 10800 seconds) are approximated as a linearly increasing sequence. Let H(7200) = 4.0 at the beginning of the hour and H(10800) = 7.17 at the end, with an average... However, weighting needs to be done point by point because each point... Within that hour, they were all close to 1 ( The value can be approximated as 1. At the same time, the exponent forgetting term in the recursive formula needs to be considered.

[0167] Actual recursion: Executed once every 60 seconds Therefore, the decay factor for each node is 0.9672.

[0168] We can approximate this using a geometric series summation: starting from the 7200th second, let the initial... Then, 60 consecutive nodes, each contributing... ( The value increased linearly from 4.0 to 7.17, with a step size of (7.17 - 4.0) / 59 ≈ 0.0537. Finally... .

[0169] First item .

[0170] Second term: Approximately The common ratio q = 0.9672, and the sum of 60 terms S = 26.36. However... Not constant, more precisely, the average H = (4.0 + 7.17) / 2 = 5.585, then the second term ≈ 5.585 × 26.36 = 147.2. However, this is an overestimation because the weighting of more distant nodes is smaller. Since... Linear increase, weighted average can be used: Considering exponential weighting, closer nodes have greater weights, and the nearest node H is larger, so the actual second term should be slightly higher than the result calculated using the arithmetic mean H. For accuracy, an integral approximation is used: Let... Where k=1.60, and the time starts from 7200 seconds. Let... This represents the number of intervals from the current time (j=0 corresponds to the nearest point). Therefore, contribution = .in The approximate value is calculated to be 152.3.

[0171] Then R(10800) = 1.15 + 152.3 = 153.45.

[0172] For example, see [link / reference] Figure 7 , Figure 7 It is a terminal interface for a single patient's wet hardness risk index change trend curve; the interface has a patient filtering drop-down control, which can switch to view the risk index change curve of different hospitalized patients within 12 hours. The graph is marked with high and low warning threshold lines after personalized correction by age and BMI, and the three risk intervals of safe, medium and high risk are divided by three background colors.

[0173] For the calculation logic of relative hardness coefficient, please refer to [link / reference]. Figure 8 , Figure 8 This is an interface explaining the logic of relative hardness coefficient calculation; it uses a business process text link to show the calculation link of pressure acquisition, benchmark comparison, temperature and humidity correction, and hardness output, and the text summarizes the calculation principle of the relative hardness coefficient H(t) of this invention, reflecting the core algorithm design idea of ​​the system backend to integrate multiple parameters such as pressure, temperature, and humidity for hardness quantification.

[0174] VI. Personalized threshold correction.

[0175] The system presets a first threshold (the low-risk / medium-risk boundary). The second threshold (the dividing line between medium and high risk) Personalized adjustments are made based on the patient's age and BMI.

[0176] Calculation formula (exemplary linear correction method):

[0177]

[0178] Substituting into the calculation, we can obtain .

[0179] Corrected threshold:

[0180]

[0181]

[0182] Because the patient is older but has a lower BMI, the effects of these two factors partially cancel each other out, resulting in a very small correction. If the patient is 70 years old and has a BMI of 28, then... The threshold value was 0.58, and the values ​​increased to 77.59 and 181.03. In this case, the threshold value increased slightly after correction, meaning the warning sensitivity decreased slightly. However, since the patient was thin (low BMI increases risk) but 68 years old, the risk was not extremely high, and the overall sensitivity remained basically the same.

[0183] VII. Risk Level Assessment and Early Warning Output.

[0184] The current wet hardness risk index R=153.45, which is much higher than the corrected high-risk threshold. The system has determined it to be high-risk.

[0185] At this time, the signal processing chip performs the following operations:

[0186] The miniature LED indicator switches to a bright red flashing mode (frequency 3Hz).

[0187] The miniature buzzer emits a continuous warning sound (lasting 5 seconds, which the patient can manually mute).

[0188] The wireless communication module (BLE5.0) pushes a red alert to the nurse station terminal and mobile nursing terminal: "High risk warning: wet hardness risk index 153.45, which has exceeded the high risk threshold of 106.06. Please change the dressing immediately and fully assess the skin of the pressure area."

[0189] At the same time, the system automatically records this warning event (timestamp, patient ID, risk index, peak pressure 1.56 kPa, temperature 38.2℃, humidity 82%RH) and uploads it to the data management platform.

[0190] For example, see [link / reference] Figure 10 , Figure 10 It is the system's historical early warning and clinical treatment record ledger interface; it stores the early warning time, patient information, calculated risk value, environmental temperature and humidity, and clinical treatment content in tabular form, which is used to realize early warning data archiving and clinical retrospection, and meet the hospital's pressure ulcer quality control data retention needs.

[0191] VIII. Clinical Follow-up.

[0192] Upon receiving the alert, the nurse immediately went to the ward, removed the dressing, and found that the absorbent cushioning layer had severely hardened and compacted. A 0.8cm diameter pressure sore was present on the skin at the femoral artery pulsation site, but it had not yet ulcerated. The nurse changed the dressing and applied pressure-reducing measures, preventing further damage to deeper tissues. The patient's subsequent CRRT treatment was successful, and no pressure sores developed.

[0193] In addition, please see Figure 11 , Figure 11 This is the algorithm's underlying parameter viewing interface of the present invention; the interface lists all fixed parameters of the algorithm, such as temperature, humidity correction constant, forgetting time constant, basic warning threshold, and sampling frequency. The nursing login account only has parameter viewing permissions and no modification permissions; these are used to provide fixed parameter basis for the calculation of risk index and correction coefficient in the background.

[0194] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A fixed pressure ulcer care system based on dynamic monitoring of wet hardness, characterized in that, The dressing body includes a multi-layered composite structure, wherein the dressing body comprises, from the skin contact surface outwards: a medical pressure-sensitive adhesive layer, a sensor integration layer, a moisture-absorbing buffer layer, and a transparent polyurethane film layer; The sensor integration layer includes a hardness-sensitive material layer, a flexible printed circuit layer, and a reference electrode layer. The hardness-sensitive material layer is disposed in the area of ​​the dressing corresponding to the pulsation location of the femoral artery or carotid artery. The flexible printed circuit layer integrates a signal processing chip, a timing unit, a power supply unit, and a wireless communication module. The hardness-sensitive material layer is used to generate an electrical signal proportional to the magnitude of the force when subjected to local pressure. The signal processing chip is used to collect the electrical signal and convert it into a pressure value. Based on the pressure value, skin surface temperature, skin surface humidity, and cumulative time, the chip calculates the wet hardness risk index and compares it with a preset warning threshold. Different levels of warning signals are then output through the wireless communication module.

2. The fixed pressure ulcer care system based on dynamic monitoring of wet hardness according to claim 1, characterized in that, The hardness-sensitive material layer is a polyvinylidene fluoride nanofiber membrane or a polydimethylsiloxane composite material layer. The moisture-absorbing buffer layer is composed of at least two layers of nonwoven fabric, with carboxymethylated cotton fibers or alginate fibers filling the space between the layers, and the total thickness of the moisture-absorbing buffer layer is 2.0 to 5.0 mm. The power supply unit is a flexible battery with a thickness of no more than 0.5 mm; The wireless communication module is a Bluetooth module or a near-field communication module.

3. The fixed pressure ulcer care system based on dynamic monitoring of wet hardness according to claim 1, characterized in that, The sensor integration layer also integrates a miniature LED indicator and a miniature buzzer, which are electrically connected to the signal processing chip.

4. The early warning method for a fixed pressure ulcer care system based on dynamic monitoring of wet hardness as described in any one of claims 1-3, characterized in that, Includes the following steps: Step S1: After the dressing is applied to the patient's skin, a baseline pressure signal in a dry state is obtained through initial calibration; Step S2: Continuously collect real-time pressure signals of the hardness-sensitive material layer at a preset sampling frequency, while simultaneously collecting skin surface temperature and skin surface relative humidity; Step S3: Calculate the relative hardness coefficient based on the ratio of the real-time pressure signal to the reference pressure signal, combined with the current temperature and humidity; Step S4: Calculate the wet hardness risk index at the current moment based on the relative hardness coefficient, time decay weight, and time accumulation at historical moments. Step S5: Compare the calculated wet hardness risk index with the preset first threshold and second threshold, and output different levels of warning signals based on the comparison results.

5. The early warning method according to claim 4, characterized in that, The relative hardness coefficient in step S3 The calculation formula is: ； In the formula, For real-time pressure signals, As the reference pressure signal, Temperature and humidity correction factor, Skin surface temperature The relative humidity of the skin surface.

6. The early warning method according to claim 5, characterized in that, The temperature and humidity correction factor The calculation formula is: ； In the formula, For reference temperature, It is a temperature characteristic constant. For reference humidity, The characteristic constant of humidity, , Let be the normalization coefficients, and the above equation satisfies .

7. The early warning method according to claim 4, characterized in that, wet hardness risk index in step S4 The calculation formula is: ； In the formula, For the current moment, For the first The time point of the next sampling For the first The relative hardness coefficient at the time of the second sampling. For time weighting function, is the exponential forgetting time constant.

8. The early warning method according to claim 7, characterized in that, The time weighting function The calculation formula is: ； In the formula, This is the initial moment when the dressing is applied. It is an increasing time constant.

9. The early warning method according to claim 4, characterized in that, In step S5, a low-risk warning is output when the wet hardness risk index is less than the first threshold, a medium-risk warning is output when the wet hardness risk index is greater than or equal to the first threshold and less than the second threshold, and a high-risk warning is output when the wet hardness risk index is greater than or equal to the second threshold. Furthermore, prior to step S5, a step is included to personalize the first and second thresholds based on the patient's age and body mass index.

10. The early warning method according to claim 4, characterized in that, The initial calibration in step S1 includes: applying standard pressure to the dressing and recording the corresponding voltage output before the dressing is applied; acquiring the voltage signal in the initial drying state after application; and calculating the reference pressure signal based on the voltage ratio. In step S2, after each preset time window, the average value of each signal within that window is calculated for subsequent steps, and abnormal values ​​exceeding a preset reasonable range are removed before calculation. If an abnormality occurs for a set number of consecutive times, a sensor fault prompt is output.

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