Intelligent turning-over assisting system and method for obese patient in hospital

Abstract

The invention provides an intelligent turning-over assisting system and method for obese patients during hospital, and relates to the technical field of intelligent medical nursing, and the system comprises a split pressure sensing unit which is configured to monitor the regional pressure of different limb parts of the patients; the tissue hypoxia monitoring unit is configured to be used for monitoring tissue oxygenation degrees of different local tissues of the patient; the nursing decision module is configured to obtain risk area information for the pressure sores according to the area pressure and the tissue oxygenation degree, and the risk area information comprises the risk area position and the risk level; if it is judged that the patient does not have the operative wound, a first turning-over strategy for guiding the nursing mode of the patient is generated according to the risk area information, and the first turning-over strategy comprises the turning-over direction, the supporting part and the turning-over frequency. According to the system, pressure sore risk assessment is upgraded from subjective experience judgment of nurses to multi-dimensional physiological data driving, the problems of missed judgment and misjudgment caused by experience difference in traditional nursing are solved, and the system is particularly suitable for clinical scenes with complex body position pressure of obese patients.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent medical care, in particular to an intelligent turning-over assisting system and method for obese patients during hospitalization. BACKGROUND

[0002] During the hospitalization of obese patients, especially in hot weather, pressure sores may occur, therefore, nurses will have some operations to prevent the occurrence of pressure sores during the nursing process, such as regularly or irregularly assisting the patient to turn over, but the current turning-over method (turning-over direction and support position) is determined by nurses subjectively depending on personal experience, and the frequency of turning over is often related to the intensity of workload during the shift, which shows that the hospital lacks standardized operation execution guidance in the prevention of pressure sores of obese patients, and due to the different conditions of hospitalized patients and the serious differentiation of nursing experience of nurses, the pressure sore rate of obese patients during hospitalization is high. SUMMARY

[0003] In view of the above defects or deficiencies in the prior art, the present application aims to provide an intelligent turning-over assisting system and method for obese patients during hospitalization, so as to standardize the nursing decision for obese patients.

[0004] In a first aspect, the present application provides an intelligent turning-over assisting system for obese patients during hospitalization, comprising: a clinical sign acquisition module, the clinical sign acquisition module comprising: a split body pressure sensing unit, the split body pressure sensing unit being configured to monitor the regional pressure of different limb parts of the patient; a tissue hypoxia monitoring unit, the tissue hypoxia monitoring unit being configured to monitor the tissue oxygenation of different local tissues of the patient; a nursing decision module, the nursing decision module being configured to: obtain risk area information for pressure sores according to the regional pressure and the tissue oxygenation, the risk area information comprising a risk area position and a risk level; determine whether the patient has a surgical wound; if not, generate a first turning-over strategy for guiding the nursing method of the patient according to the risk area information, the first turning-over strategy comprising a turning-over direction, a support part and a turning-over frequency.

[0005] According to the technical solution provided by the present application, the nursing decision module is further configured to: if the patient has a surgical wound, generate a second turning-over strategy for guiding the postoperative nursing method of the patient according to the risk area information and the wound information corresponding to the surgical wound.

[0006] According to the technical solution provided in this application, the split pressure sensing unit includes a flexible distributed pressure sensing mattress, which has multiple acquisition areas. The sensor array density of each acquisition area is adjusted according to the patient's body mass index. The sensor array density of the acquisition area corresponding to the limb with high risk of pressure ulcers is greater than that of the other acquisition areas.

[0007] According to the technical solution provided in this application, the tissue hypoxia monitoring unit includes a near-infrared spectroscopy monitoring patch group, which is attached to the limb site at high risk of pressure ulcers.

[0008] According to the technical solution provided in this application, the nursing decision module includes a risk grading unit, which is configured to obtain risk area information for pressure ulcers based on the regional pressure and the tissue oxygenation. The risk classification unit is specifically configured for: The region threshold rule base is retrieved and traversed to obtain the region threshold set corresponding to the patient's body mass index. The region threshold set includes the region threshold corresponding to each collection region. The region threshold rule base includes multiple body mass index intervals and a preset region threshold set corresponding to each body mass index interval. If the real-time pressure on a limb is greater than the threshold of the corresponding area of ​​the collection area and continues for a first preset duration, then the limb is marked as a level 1 risk point with a risk level of level 1. If the real-time pressure of the first-level risk point continues to rise within a second preset time period, then the first-level risk point will be upgraded to a second-level risk point. If the rate of continuous decline in tissue oxygenation at the first-level risk point / the second-level risk point is greater than or equal to the first preset rate of change, then the point is upgraded to a third-level risk point.

[0009] According to the technical solution provided in this application, the nursing decision-making module includes a judgment unit, which is connected to the hospital's electronic medical record system via a medical data interface. The judgment unit is configured to: Retrieve the patient's target electronic medical record from the electronic medical record system; Determine whether the patient has surgical wounds based on the target electronic medical record; The target electronic medical record includes the patient's surgical information and incision information. The surgical information includes the surgical date and surgical type, and the incision information includes the number of incisions, the location of the incisions, and the type of incision. The trauma information is obtained from the surgical information and the incision information.

[0010] According to the technical solution provided in this application, the nursing decision module includes an analysis unit, which is configured to generate a first turning strategy to guide the patient's nursing care based on the trauma information and the risk area information. The analysis unit is specifically configured for: Based on the location of the risk area, identify the pressure release target area, which is the limb area where the secondary risk point and the tertiary risk point are located; The turning direction is determined based on the pressure release target area, wherein the pressure release target area includes the left limb and the right limb, and the turning direction is the opposite side of the limb corresponding to the pressure release target area; The supporting part is defined as the large joint protuberance on the opposite side of the limb corresponding to the pressure release target area; If the patient's limb has the aforementioned level 3 risk points, the turning frequency is set to a first preset frequency. If the patient's limb only has the aforementioned level 2 risk points, the turning frequency is set to a second preset frequency, where the second preset frequency is less than the first preset frequency.

[0011] According to the technical solution provided in this application, the analysis unit is specifically configured for: A basic rollover strategy set is generated based on the risk area information. The basic rollover strategy set includes at least two candidate strategies, and the candidate strategies include candidate rollover directions and corresponding candidate support positions. Retrieve the wound positioning contraindication rule library and extract the contraindicated positions associated with the trauma information. The contraindicated positions include positions that prohibit compression and positions that prohibit traction. From the set of basic turning strategies, candidate strategies that conform to the forbidden positions are selected, and the candidate strategies are used as the second turning strategy.

[0012] According to the technical solution provided in this application, the analysis unit is further configured to: If all candidate strategies in the basic turning strategy set violate the taboo position, then the in-situ suspension decompression strategy will be adopted as the second turning strategy.

[0013] Secondly, this application proposes an intelligent turning assistance method for obese patients during hospitalization, based on the intelligent turning assistance system for obese patients during hospitalization as described above. The method includes the following steps: Real-time monitoring of regional pressure in different limbs of the patient, as well as tissue oxygenation in different local tissues; Based on the regional pressure and the tissue oxygenation, risk area information for pressure ulcers is obtained, including the location and risk level of the risk area. Determine if the patient has surgical wounds; If not, a first turning strategy is generated based on the risk area information to guide patient care. The first turning strategy includes turning direction, support points, and turning frequency.

[0014] Compared with existing technologies, the beneficial effects of this application are as follows: This application quantifies the pressure distribution of various parts of the patient in real time through a split pressure sensing unit, and dynamically detects the local tissue perfusion status by combining a tissue hypoxia monitoring unit. This upgrades pressure ulcer risk assessment from nurses' subjective experience judgment to multi-dimensional physiological data-driven assessment. The system automatically identifies the location and level of high-risk areas (such as special pressure points like the sacrum, coccyx, and ankles), completely solving the problems of missed and misjudgments caused by experience differences in traditional nursing. It is especially suitable for clinical scenarios with complex postural pressure in obese patients. At the same time, based on real-time risk area information, the system automatically generates a first turning strategy including turning direction, support position, and turning frequency, and dynamically generates personalized turning strategies to ensure standardized nursing care. In addition, it adds surgical wound assessment, prioritizing the exclusion of special postoperative postoperative positional restrictions, ensuring that the generated turning strategy does not interfere with wound healing, making up for the blind spots in clinical management of obese patients with multiple comorbidities and complex nursing contraindications, avoiding surgical wound interference, and improving nursing safety. Attached Figure Description

[0015] Figure 1 A schematic diagram of the intelligent turning assistance system for obese patients during hospitalization provided in this application. Detailed Implementation

[0016] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0017] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0018] Example 1 As mentioned in the background section, in view of the problems in the prior art, this application proposes an intelligent turning assistance system for obese patients during their hospital stay, such as... Figure 1 As shown, it includes: Clinical signs acquisition module, the clinical signs acquisition module includes: A split pressure sensing unit is configured to monitor regional pressure in different limb areas of a patient. A tissue hypoxia monitoring unit, configured to monitor tissue oxygenation in different local tissues of the patient; Furthermore, the split pressure sensing unit includes a flexible distributed pressure sensing mattress, which has multiple acquisition areas. The sensor array density of each acquisition area is adjusted according to the patient's body mass index. The sensor array density of the acquisition area corresponding to the limb with high risk of pressure ulcers is greater than that of the other acquisition areas.

[0019] Furthermore, the tissue hypoxia monitoring unit includes a near-infrared spectroscopy monitoring patch group, which is attached to the limbs at high risk of pressure ulcers.

[0020] Specifically, a split-type pressure sensing pad is used, divided into 32 collection zones (8 zones in the sacral and coccygeal region, 6 zones in the scapular region, 4 zones in the heel region, etc.). Each zone is equipped with a pressure resistance sensor array (e.g., density: 25 sensors / cm² for high-risk areas of pressure ulcers in the sacral and coccygeal region). 2 9 in other areas / cm 2 The sampling frequency is 10Hz; a patch-type probe of a near-infrared spectrometer is used, attached to high-risk areas for pressure ulcers such as the sacrum, coccyx, and heel. The probe emits 650nm and 850nm near-infrared light, and the intensity of reflected light is detected. Tissue oxygenation (unit: %) is calculated by the oxyhemoglobin / deoxyhemoglobin ratio.

[0021] Specifically, the sensor array density of each acquisition area is matched with the patient's body mass index (BMI) through density adjustment rules. When the BMI range is less than 30, the sensor array density of the conventional area is 4 sensors / cm². 2 The sensor array density in high-risk areas is 9 units / cm². 2 For BMI range 30-40, the sensor array density in the typical area is 9 units / cm². 2 The sensor array density in high-risk areas is 16 units / cm². 2 For individuals with a BMI > 40, the sensor array density in the standard area is 16 units / cm². 2 The sensor array density in high-risk areas is 25 units / cm². 2 The high-risk area is the mattress area corresponding to the limbs at high risk of pressure ulcers. The limbs at high risk of pressure ulcers are determined by clinical experience, such as the sacrum, coccyx, heel, and scapula.

[0022] Nursing decision-making module, the nursing decision-making module is configured to: Based on the regional pressure and the tissue oxygenation, risk area information for pressure ulcers is obtained, including the location and risk level of the risk area. Determine if the patient has surgical wounds; If not, a first turning strategy is generated based on the risk area information to guide patient care. The first turning strategy includes turning direction, support points, and turning frequency.

[0023] Furthermore, the nursing decision module includes a risk grading unit, which is configured to obtain risk area information for pressure ulcers based on the area pressure and the tissue oxygenation. The risk classification unit is specifically configured for: The region threshold rule base is retrieved and traversed to obtain the region threshold set corresponding to the patient's body mass index. The region threshold set includes the region threshold corresponding to each collection region. The region threshold rule base includes multiple body mass index intervals and a preset region threshold set corresponding to each body mass index interval. Optionally, the regional threshold rule base includes multiple BMI intervals, each with a corresponding regional threshold set. The regional threshold set includes regional thresholds for high-risk areas corresponding to multiple high-risk limb sites for pressure ulcers. Table 1 shows the regional threshold rule base. By searching the regional threshold set that matches the patient's BMI in the regional threshold rule base, the risk of pressure ulcers in each sampling area can be identified more accurately and efficiently. The rule base is generated as follows: Because tissue perfusion pressure decreases in obese patients, the tolerance threshold decreases with increasing BMI, a fact derived from clinical experience. The actual threshold for each sampling area in the rule base can be obtained using the formula: Actual threshold = Base threshold × (1 - (BMI-25) × 0.01), where the base threshold can be obtained by referring to pressure ulcer guidelines to obtain the upper limit of healthy tissue tolerance for each site as the base threshold. For example, for a patient with a BMI of 38, the upper limit of healthy tissue tolerance in the sacrococcygeal region is 90 mmHg, then the sacrococcygeal region threshold = 90 × (1 - (38-25) × 0.01) = 70.2 mmHg.

[0024] Table 1 Regional Threshold Rule Base

[0025] If the real-time pressure on a limb is greater than the threshold of the corresponding area of ​​the collection area and continues for a first preset duration, then the limb is marked as a level 1 risk point with a risk level of level 1. Specifically, the first preset duration can be set to 120 minutes: Scientific basis: Tissue ischemia will lead to irreversible damage after 120 minutes. The pressure value is continuously monitored, and a timer is started when the threshold is exceeded. If the condition is not relieved after 120 minutes, it is marked as a level 1 risk point.

[0026] If the real-time pressure of the first-level risk point continues to rise within a second preset time period, then the first-level risk point will be upgraded to a second-level risk point. Specifically, the second preset duration can be selected as 45 minutes, and the linear regression slope of the real-time pressure > 0.1 mmHg / min (10-minute window period) is judged as showing an upward trend.

[0027] If the rate of continuous decline in tissue oxygenation at the first-level risk point / the second-level risk point is greater than or equal to the first preset rate of change, then the point is upgraded to a third-level risk point.

[0028] Specifically, the continuous decline rate is: (initial oxygenation - current oxygenation) / time interval, and the first preset change rate can be selected as 4% / min. Oxygenation is collected every 5 seconds (NIRS patch), and the decline rate within a 15-minute sliding window is calculated. When the decline rate is ≥4% / min, the risk level is upgraded to Level 3.

[0029] This implementation method establishes a dynamic three-level early warning model for the risk of pressure ulcers in obese patients, which solves the problem that traditional hospital nursing cannot quantify tissue status in real time (traditional methods mostly involve manual skin examination every 4 hours).

[0030] In a preferred embodiment, the nursing decision module includes an analysis unit configured to generate a first turning strategy to guide patient care based on the trauma information and the risk area information; The analysis unit is specifically configured for: Based on the location of the risk area, identify the pressure release target area, which is the limb area where the secondary risk point and the tertiary risk point are located; Specifically, the pressure release target area refers to a continuous anatomical region containing one or more level 2 or 3 risk points. The anatomical region includes the left limb anatomical region, the right limb anatomical region, and the sacrococcygeal anatomical region. The body surface area of ​​the left limb anatomical region is from the left shoulder to the left foot, the body surface area of ​​the right limb anatomical region is from the right shoulder to the right foot, and the body surface area of ​​the sacrococcygeal anatomical region is the spine area below L4. The pressure release target area can be obtained by directly calling the risk area information output by the risk grading unit.

[0031] The turning direction is determined based on the pressure release target area, wherein the pressure release target area includes the left limb and the right limb, and the turning direction is the opposite side of the limb corresponding to the pressure release target area; Specifically, the principle of directional decision-making is to remove the pressure release target area from contact with the bed surface. The pressure release target area includes a continuous anatomical area within the left limb anatomical region containing one or more level 2 or 3 risk points, i.e., the left limb; a continuous anatomical area within the right limb anatomical region containing one or more level 2 or 3 risk points, i.e., the right limb; and a continuous anatomical area within the sacrococcygeal region containing one or more level 2 or 3 risk points, i.e., the sacrococcygeal region. When the pressure release target area is the left limb, the turning direction is to the right to suspend the left limb and relieve pressure. When the pressure release target area is the right limb, the turning direction is to the left to suspend the right limb and relieve pressure. When the pressure release target area is the sacrococcygeal region, the turning direction is to the left or right, maintaining a 30° lateral tilt to reduce the load on the sacrum.

[0032] The supporting part is defined as the large joint protuberance on the opposite side of the limb corresponding to the pressure release target area; Specifically, considering the extreme weight of obese patients, choosing soft tissue areas (such as the abdomen) as the support point would cause a sudden drop in adipose tissue perfusion pressure, potentially leading to deep tissue necrosis. Increased shear force in skin folds could cause moisture-associated dermatitis. Therefore, the support point is the bony prominence area that bears the main weight pressure during turning (where subcutaneous fat is thin). When turning to the right, the corresponding support points are the right scapular spine and right greater trochanter of the femur; when turning to the left, the corresponding support points are the left scapular spine and left greater trochanter of the femur; and when in a 30° oblique position, the corresponding support points are the manubrium of the sternum (above the sternal angle) and the anterior superior iliac spine. Pressure-reducing devices such as silicone decompression pads or inflatable suspension pads are placed below the support points. When the real-time pressure in the original risk area drops below the threshold of the area corresponding to the sampling area, and the oxygenation increases by more than 15% within 10 minutes without any new risk points, the pressure-reducing devices at the support points are removed, and the patient returns to their original position.

[0033] Specifically, the role of the support points is to bear weight and maintain posture. When a patient turns over (e.g., from supine to right lateral), the body weight needs to be borne by the new contact points (i.e., support points). Choosing the correct support points is essential to ensure that the risk area (left side) is not compressed.

[0034] For example, a support pad is placed on the bony prominences (such as the right subscapular region or the right greater trochanter) under the right side of the body (i.e., the opposite side to the left of the risk area). These right-side support points bear the main weight of the body. Since the body is a whole, when the right side is firmly supported and bears weight, the left side of the body (risk area) will naturally "float" above the support points, detached from contact with the bed surface, achieving suspended decompression.

[0035] If the patient's limb has the aforementioned level 3 risk points, the turning frequency is set to a first preset frequency. If the patient's limb only has the aforementioned level 2 risk points, the turning frequency is set to a second preset frequency, where the second preset frequency is less than the first preset frequency.

[0036] Specifically, after this turning action is completed, in order to completely eliminate the risk of pressure ulcers, follow-up care and consolidation are required. Regular turning is also necessary. The frequency of turning can be selected. When there are level 3 risk points, the turning care should be more frequent. When there are only level 2 risk points, the turning care can be appropriately less frequent. Optionally, the first preset frequency is once every 12 hours, and the second preset frequency is once every 24 hours.

[0037] Example 2 Based on Example 1, this example considers that if a patient undergoes surgery, there will be surgical wounds on the limbs, which may affect the turning strategy. Therefore, this example proposes a scenario strategy for postoperative care of obese patients, including: The nursing decision module is also configured to: If the patient has a surgical wound, a second turning strategy is generated based on the risk area information and the trauma information corresponding to the surgical wound to guide the patient's postoperative care.

[0038] Furthermore, the nursing decision-making module includes a judgment unit, which is connected to the hospital's electronic medical record system via a medical data interface. The judgment unit is configured to: Retrieve the patient's target electronic medical record from the electronic medical record system; Determine whether the patient has surgical wounds based on the target electronic medical record; The target electronic medical record includes the patient's surgical information and incision information. The surgical information includes the surgical date and surgical type, and the incision information includes the number of incisions, the location of the incisions, and the type of incision. The trauma information is obtained from the surgical information and the incision information.

[0039] Specifically, the converted trauma information is obtained through electronic medical record fields. The trauma information includes the number of days after surgery, surgical classification code, and the anatomical coordinate system position corresponding to the wound.

[0040] In a preferred embodiment, the analysis unit is specifically configured to: A basic rollover strategy set is generated based on the risk area information. The basic rollover strategy set includes at least two candidate strategies, and the candidate strategies include candidate rollover directions and corresponding candidate support positions. Specifically, the candidate turning directions include the same fixed turning directions as described above, as well as adjustable turning angles. For example, if the patient's risk area is a level 3 risk area in the left hip, the corresponding candidate strategies include three: Candidate strategy 1 is: turning to the right at 30 degrees, with the support points being the right scapular spine and right iliac crest; Candidate strategy 2 is: turning to the right at 45 degrees, with the support points being the right scapular spine and right greater trochanter; Candidate strategy 3 is: turning to the right at 20 degrees, with the support points being the right scapular region (the support points are expanded to a region).

[0041] Retrieve the wound positioning contraindication rule library and extract the contraindicated positions associated with the trauma information. The contraindicated positions include positions that prohibit compression and positions that prohibit traction. Specifically, the wound positioning contraindication rule base includes multiple sets of trauma information (postoperative days, surgical classification code, and the anatomical coordinate system position corresponding to the wound), as well as the contraindicated positions corresponding to each set of trauma information.

[0042] For example, a patient's risk area is: Level 3 risk in the left hip. The corresponding candidate strategies include candidate strategy 1, candidate strategy 2, and candidate strategy 3. The patient's trauma information is: surgical classification code: ORTH-101 (total hip replacement), postoperative days: 3 days (inflammatory phase), incision location: right greater trochanter (coordinates X120, Y85). The wound positioning contraindication rule library is retrieved, and the contraindicated positions associated with the patient's trauma information are: prohibited compression positions include the right greater trochanter and the posterior part of the right iliac crest, based on the surgical incision location; prohibited traction positions include right hip adduction >15° and right hip external rotation >20°, based on the inflammatory phase restrictions after total hip replacement.

[0043] From the set of basic turning strategies, candidate strategies that conform to the forbidden positions are selected, and the candidate strategies are used as the second turning strategy.

[0044] For example, in candidate strategy 1, the right iliac crest, the supporting site, is a prohibited position for compression, thus candidate strategy 1 does not meet the contraindications and is therefore excluded. In candidate strategy 2, the right greater trochanter is the surgical incision site, which violates the compression rule, and the 45° turn results in 25° external rotation of the affected hip, which violates the traction rule, so candidate strategy 2 also does not meet the contraindications and is also excluded. In candidate strategy 3, the scapular region is far from the incision site, making compression safe, and the joint movement is <15° with a 20° turn, making traction safe. Candidate strategy 3 is a candidate strategy that meets the contraindications and is included as the second turning strategy in the patient's care process. This can avoid secondary damage to the surgical wound and reduce the risk of pressure sores.

[0045] In a preferred embodiment, the analysis unit is further configured to: If all candidate strategies in the basic turning strategy set violate the taboo position, then the in-situ suspension decompression strategy will be adopted as the second turning strategy.

[0046] Specifically, if none of the candidate strategies meet the contraindication for a particular posture in a given scenario, the pressure in each area is controlled according to the suspension mode parameters to execute an in-situ suspension decompression strategy. This strategy requires the use of an auxiliary device, such as a distributed pneumatic mattress or a pneumatic suspension device, which allows for independent control of airbag pressure in different areas to suspend the obese patient's limbs. For example, the pressure is: left hip risk area: 0 mmHg; right shoulder incision area: 18 mmHg; right iliac crest incision area: 18 mmHg; sacrococcygeal region: 12 mmHg. The suspension is withdrawn every 8 minutes to examine the skin, with no more than 6 cycles within 24 hours.

[0047] Example 3 Based on Example 1, this example proposes an intelligent turning assistance method for obese patients during hospitalization, implemented using the intelligent turning assistance system for obese patients during hospitalization as described in Example 1. The method includes the following steps: Real-time monitoring of regional pressure in different limbs of the patient, as well as tissue oxygenation in different local tissues; Based on the regional pressure and the tissue oxygenation, risk area information for pressure ulcers is obtained, including the location and risk level of the risk area. Determine if the patient has surgical wounds; If not, a first turning strategy is generated based on the risk area information to guide patient care. The first turning strategy includes turning direction, support points, and turning frequency.

[0048] In summary, this solution addresses the shortcomings of traditional nursing care: the neglect of BMI differences by uniform standards, the lag in visual observation (intervention only after erythema has appeared), and nurses relying on memory to avoid wounds (leading to high error rates). It proposes a scheme for dynamically adjusting BMI stratification thresholds and sensor density, a real-time pressure-hypoxia dual-modality early warning system, and a clinical strategy combining digital no-go zone coordinates with proactive avoidance of surgical wounds. This improves the sensitivity of detecting pressure ulcer risk areas, enables earlier identification of high-risk pressure ulcers, and reduces medical errors. It transforms postoperative care for obese patients from high-risk, experience-based procedures into standardized, safe processes, providing intelligent infrastructure for hospital pressure ulcer quality management.

[0049] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. The above descriptions are only preferred embodiments of this application. It should be noted that due to the limitations of written expression, while there are objectively infinite specific structures, those skilled in the art can make several improvements, modifications, or changes without departing from the principles of this invention, and can also combine the above technical features in an appropriate manner. These improvements, modifications, changes, or combinations, or the direct application of the inventive concept and technical solution to other situations without modification, should all be considered within the scope of protection of this application.

Claims

1. An intelligent turning assistance system for obese patients during hospitalization, characterized in that, include: Clinical signs acquisition module, the clinical signs acquisition module includes: A split pressure sensing unit is configured to monitor regional pressure in different limb areas of a patient. A tissue hypoxia monitoring unit, configured to monitor tissue oxygenation in different local tissues of the patient; Nursing decision-making module, the nursing decision-making module is configured to: Based on the regional pressure and the tissue oxygenation, risk area information for pressure ulcers is obtained, including the location and risk level of the risk area. Determine if the patient has surgical wounds; If not, a first turning strategy is generated based on the risk area information to guide patient care. The first turning strategy includes turning direction, support points, and turning frequency.

2. The intelligent turning assistance system for obese patients during hospitalization according to claim 1, characterized in that: The nursing decision module is also configured to: If the patient has a surgical wound, a second turning strategy is generated based on the risk area information and the trauma information corresponding to the surgical wound to guide the patient's postoperative care.

3. The intelligent turning assistance system for obese patients during hospitalization according to claim 1, characterized in that: The split pressure sensing unit includes a flexible distributed pressure sensing mattress, which has multiple acquisition areas. The sensor array density of each acquisition area is adjusted according to the patient's body mass index. The sensor array density of the acquisition area corresponding to the limb with high risk of pressure ulcers is greater than that of the other acquisition areas.

4. The intelligent turning assistance system for obese patients during hospitalization according to claim 3, characterized in that: The tissue hypoxia monitoring unit includes a near-infrared spectroscopy monitoring patch group, which is attached to the limbs at high risk of pressure ulcers.

5. The intelligent turning assistance system for obese patients during hospitalization according to claim 3, characterized in that: The nursing decision module includes a risk grading unit, which is configured to obtain risk area information for pressure ulcers based on the area pressure and the tissue oxygenation. The risk classification unit is specifically configured for: The region threshold rule base is retrieved and traversed to obtain the region threshold set corresponding to the patient's body mass index. The region threshold set includes the region threshold corresponding to each collection region. The region threshold rule base includes multiple body mass index intervals and a preset region threshold set corresponding to each body mass index interval. If the real-time pressure on a limb is greater than the threshold of the corresponding area of ​​the collection area and continues for a first preset duration, then the limb is marked as a level 1 risk point with a risk level of level 1. If the real-time pressure of the first-level risk point continues to rise within a second preset time period, then the first-level risk point will be upgraded to a second-level risk point. If the rate of continuous decline in tissue oxygenation at the first-level risk point / the second-level risk point is greater than or equal to the first preset rate of change, then the point is upgraded to a third-level risk point.

6. The intelligent turning assistance system for obese patients during hospitalization according to claim 2, characterized in that: The nursing decision-making module includes a judgment unit, which is connected to the hospital's electronic medical record system via a medical data interface. The judgment unit is configured to: Retrieve the patient's target electronic medical record from the electronic medical record system; Determine whether the patient has surgical wounds based on the target electronic medical record; The target electronic medical record includes the patient's surgical information and incision information. The surgical information includes the surgical date and surgical type, and the incision information includes the number of incisions, the location of the incisions, and the type of incision. The trauma information is obtained from the surgical information and the incision information.

7. The intelligent turning assistance system for obese patients during hospitalization according to claim 5, characterized in that: The nursing decision module includes an analysis unit configured to generate a first turning strategy to guide patient care based on the trauma information and the risk area information. The analysis unit is specifically configured for: Based on the location of the risk area, identify the pressure release target area, which is the limb area where the secondary risk point and the tertiary risk point are located; The turning direction is determined based on the pressure release target area, wherein the pressure release target area includes the left limb and the right limb, and the turning direction is the opposite side of the limb corresponding to the pressure release target area; The supporting part is defined as the large joint protuberance on the opposite side of the limb corresponding to the pressure release target area; If the patient's limb has the aforementioned level 3 risk points, the turning frequency is set to a first preset frequency. If the patient's limb only has the aforementioned level 2 risk points, the turning frequency is set to a second preset frequency, where the second preset frequency is less than the first preset frequency.

8. The intelligent turning assistance system for obese patients during hospitalization according to claim 2, characterized in that: The analysis unit is specifically configured for: A basic rollover strategy set is generated based on the risk area information. The basic rollover strategy set includes at least two candidate strategies. The candidate strategies include candidate rollover directions and corresponding candidate support positions. Retrieve the wound positioning contraindication rule library and extract the contraindicated positions associated with the trauma information. The contraindicated positions include positions that prohibit compression and positions that prohibit traction. Candidate strategies that conform to the forbidden positions are selected from the set of basic turning strategies, and the candidate strategies are used as the second turning strategy.

9. The intelligent turning assistance system for obese patients during hospitalization according to claim 8, characterized in that: The analysis unit is also configured to: If all candidate strategies in the basic turning strategy set violate the taboo position, then the in-situ suspension decompression strategy will be adopted as the second turning strategy.

10. A method for intelligent turning assistance for obese patients during hospitalization, implemented based on the intelligent turning assistance system for obese patients during hospitalization as described in any one of claims 1-9, characterized in that: The method includes the following steps: Real-time monitoring of regional pressure in different limbs of the patient, as well as tissue oxygenation in different local tissues; Based on the regional pressure and the tissue oxygenation, risk area information for pressure ulcers is obtained, including the location and risk level of the risk area. Determine if the patient has surgical wounds; If not, a first turning strategy is generated based on the risk area information to guide patient care. The first turning strategy includes turning direction, support points, and turning frequency.

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