Intelligent orthopedic nursing bed control method based on dynamic pressure feedback

Abstract

The invention relates to the technical field of orthopedic nursing, in particular to an intelligent orthopedic nursing bed control method based on dynamic pressure feedback, and the method comprises the steps: collecting clinical information and real-time pressure information of a patient; predicting a current motion state of the patient based on the clinical information and the real-time pressure information; and adjusting the partition hardness of the partition support adjusting pad according to the current motion state. In order to solve the problem that an intelligent nursing bed in the prior art is insufficient in supporting performance for an orthopedic rehabilitation patient, rehabilitation information and real-time pressure information are collected for the patient, the current motion state of the patient is predicted by combining the rehabilitation information on the basis of current pressure distribution of the patient, then the hardness of each subarea of a mattress is dynamically adjusted, and the rehabilitation effect of the patient is improved. Safer bearing of the moving part and harder supporting compensation of the lying position of the patient are achieved, and rehabilitation actions of the patient are facilitated.

Description

Technical Field

[0001] This invention relates to the field of orthopedic nursing technology, specifically to an intelligent orthopedic nursing bed control method based on dynamic pressure feedback. Background Technology

[0002] A smart nursing bed is a new type of medical rehabilitation device that can collect patients' physiological characteristics through sensors, such as pressure distribution, heart rate, and body temperature when the patient is lying down. It may also have certain intelligent control functions, such as adjusting the height of the head and feet of the bed and adjusting the firmness of the mattress zones according to the program settings.

[0003] For example, patent application CN202510937244.0 discloses a method for optimizing the pressure distribution of a smart mattress with multiple air pumps working in tandem, relating to the field of mattress pressure optimization technology. This method includes: identifying multiple independent air chamber regions in the smart mattress and establishing pressure interference relationships between neighboring air chambers; collecting pressure data from a target user; analyzing the contact surface based on the collected pressure data to generate a user's analyzed posture; obtaining a preset spine alignment curve database; inputting the user's analyzed posture into the preset spine alignment curve database to obtain a target baseline spine alignment curve; and optimizing the pressure distribution of the multiple independent air chamber regions to control the pressure distribution. This method solves the technical problem in existing technologies where smart mattresses struggle to accurately optimize pressure distribution based on individual user characteristics and real-time posture, achieving precise optimization and control of the smart mattress pressure distribution based on individual user characteristics and real-time posture, effectively improving user sleep comfort and mattress fit.

[0004] For example, patent application CN202211173646.0 discloses a personalized, interactive, and flexible sleep posture correction system for use in large-area bedding, including a mattress. This system allows for the measurement and processing of sleep posture-related data, such as different pressure points and changes in pressure distribution during the sleep cycle. Simultaneously, the system, incorporating artificial intelligence, automatically or by the user based on their (or their) preferred response actions, adjusts one or more parameters of the bedding in response to the user's instantaneous sleep posture. In one embodiment, a sleep posture image capture module is also incorporated to capture the user's previous and instantaneous sleep postures to enhance the accuracy of posture prediction and provide the user with more information before making a response action decision.

[0005] However, in actual implementation, the inventors found that such technical solutions are usually designed for normal people. When the user is a patient who needs to perform rehabilitation activities, the traditional solution of monitoring pressure and adjusting the support distribution has the problem of insufficient support effect. Summary of the Invention

[0006] To address the aforementioned problems in existing technologies, a control method for an intelligent orthopedic nursing bed based on dynamic pressure feedback is provided.

[0007] The specific technical solution is as follows:

[0008] A control method for an intelligent orthopedic nursing bed based on dynamic pressure feedback is implemented on an orthopedic nursing bed, which includes a zoned support adjustment pad and a pressure acquisition matrix above the zoned support adjustment pad;

[0009] The intelligent orthopedic nursing bed control method includes:

[0010] Step S1: Collect clinical information and real-time stress information from the patient;

[0011] The clinical information includes the patient's fracture location and rehabilitation tips;

[0012] Step S2: Predict the patient's current motion state based on the clinical information and the real-time pressure information;

[0013] Step S3: Adjust the partition hardness of the partition support adjustment pad according to the current motion state.

[0014] On the other hand, step S1 includes:

[0015] Step S11: Collect the patient's electronic medical record, extract the document name field from the electronic medical record, and obtain the real-time pressure information based on the pressure acquisition matrix;

[0016] Step S12: Obtain diagnostic information and rehabilitation suggestions by matching the document name field;

[0017] Step S13: Generate the clinical information based on the diagnostic information and the rehabilitation recommendations.

[0018] On the other hand, the pressure acquisition matrix is ​​implemented based on a fiber optic grating sensor array.

[0019] On the other hand, the pressure acquisition matrix is ​​implemented based on a flexible pressure sensor.

[0020] On the other hand, step S2 includes:

[0021] Step S21: Collect the current time period and match it with the rehabilitation exercise period in the rehabilitation prompt information to determine whether it is in a rehabilitation period, and determine the patient's lying position according to the real-time pressure information;

[0022] If so, proceed to step S22;

[0023] If not, proceed to step S23;

[0024] Step S22: Extract the patient's active and supporting parts from the rehabilitation prompt information, map the supporting parts to the lying position, then determine the orientation of the patient's active limbs according to the relative position of the active and supporting parts, and then proceed to step S24;

[0025] Step S23: Match a standard human-shaped template according to the lying position to predict the orientation of the patient's active limbs that are not in contact with the bed, and then proceed to step S24;

[0026] Step S24: Establish the current motion state based on the lying position and the orientation of the patient's moving limbs.

[0027] On the other hand, step S22 includes:

[0028] Step S221: Obtain rehabilitation movements from the rehabilitation prompt information, and determine the active part, the supporting part, and the movement trajectory of the active part based on the rehabilitation movements;

[0029] Step S222: Scale the support part and map it to the lying position, and record the scaling ratio;

[0030] Step S223: Map the motion trajectory based on the lying position according to the scaling ratio to determine the mapped active part;

[0031] Step S224: Determine the orientation of the patient's active limb based on the relative position of the active part and the supporting part.

[0032] On the other hand, step S23 includes:

[0033] Step S231: Obtain the initial lying position, and generate a mapping ratio based on the area of ​​the initial lying position and the standard human body template;

[0034] Step S232: Transfer the standard human body template to the lying position according to the mapping ratio, and mark the orientation of the patient's active limbs.

[0035] On the other hand, step S3 includes:

[0036] Step S31: Calculate the ratio of the motion support area to the human body projection according to the lying position, and establish the motion area projection of the patient's active limb on the partitioned support adjustment pad;

[0037] Step S32: Increase the hardness of the support partition corresponding to the lying position according to the proportion of the support area, and decrease the hardness of the support partition corresponding to the projection of the active area.

[0038] On the other hand, the partitioned support adjustment pad includes multiple airbag units.

[0039] The above technical solution has the following advantages or beneficial effects:

[0040] To address the issue of insufficient support for orthopedic rehabilitation patients in existing smart nursing beds, this solution collects rehabilitation information and real-time pressure information from the patient. Based on the patient's current pressure distribution, the solution combines rehabilitation information to predict the patient's current movement status and dynamically adjusts the firmness of each zone of the mattress. This provides safer support for the moving parts and firmer support to compensate for the patient's lying position, facilitating rehabilitation movements. Attached Figure Description

[0041] Embodiments of the invention will be described more fully with reference to the accompanying drawings. However, the drawings are for illustration and explanation only and do not constitute a limitation on the scope of the invention.

[0042] Figure 1 This is an overall schematic diagram of an embodiment of the present invention;

[0043] Figure 2 This is a schematic diagram of step S1 in an embodiment of the present invention;

[0044] Figure 3 This is a schematic diagram of step S2 in an embodiment of the present invention;

[0045] Figure 4 This is a schematic diagram of step S22 in an embodiment of the present invention;

[0046] Figure 5 This is a schematic diagram of step S23 in an embodiment of the present invention;

[0047] Figure 6 This is a schematic diagram of step S3 in an embodiment of the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0050] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but this is not intended to limit the scope of the invention.

[0051] This invention includes:

[0052] A control method for an intelligent orthopedic nursing bed based on dynamic pressure feedback is implemented on an orthopedic nursing bed, which includes a zoned support adjustment pad and a pressure acquisition matrix above the zoned support adjustment pad;

[0053] like Figure 1 As shown, the control method for the intelligent orthopedic nursing bed includes:

[0054] Step S1: Collect clinical information and real-time stress information from the patient;

[0055] Clinical information includes the patient's fracture location and rehabilitation tips;

[0056] Step S2: Predict the patient's current motion state based on clinical information and real-time stress information;

[0057] Step S3: Adjust the hardness of the zone support pads according to the current motion state.

[0058] Specifically, addressing the issue of insufficient support for orthopedic rehabilitation patients in existing smart nursing beds, this solution collects rehabilitation information and real-time pressure information from the patient. Based on the patient's current pressure distribution, the solution combines rehabilitation information to predict the patient's current movement status, and then dynamically adjusts the firmness of each zone of the mattress. This achieves safer support for the moving parts and firmer support compensation for the patient's lying position, facilitating rehabilitation movements.

[0059] Specifically, the above-mentioned technical solution is mainly configured as a software implementation in the controller of the orthopedic nursing bed during implementation. It is used to analyze the pressure data collected on the orthopedic nursing bed to determine the activity pattern of the patient lying on the bed and adjust the zoned firmness of the mattress.

[0060] The orthopedic nursing bed includes at least a zoned support adjustment pad and a pressure acquisition matrix above the zoned support adjustment pad. The zoned support adjustment pad and the pressure acquisition matrix are respectively connected to the controller for data transmission and control signal reception.

[0061] The zoned support adjustment pad is a zoned support mattress composed of multiple drive units. Each drive unit can change its firmness and height to a certain extent under the control of a controller, thereby providing support for the patient. This structure can be implemented by referring to existing smart mattress technologies.

[0062] A typical design involves embedding multiple independent airbag units in a matrix within a flexible mattress. Each airbag unit has its own independent air intake and exhaust channels connected to an air pump. Under the control of the air pump, the inflation volume is changed, thereby altering the firmness at that point. When the inflation volume decreases, the airbag volume shrinks, and the surrounding flexible mattress materials, such as foam or silicone, provide support, achieving a softer support effect. When the inflation volume increases, the airbag expands to support the patient's limbs above, achieving a firmer support effect.

[0063] The pressure acquisition matrix is ​​a pressure acquisition pad integrated with polymer material above the zoned support adjustment pad. Based on a fiber optic sensor array or flexible pressure sensor, it has multiple sampling points arranged in a matrix. Pressure is collected by changing the refractive index of the fiber optic cable or the resistivity of the flexible film at that point, and the data is then aggregated in the controller. The controller pre-calibrates the positions of each acquisition point on the acquisition pad. During the acquisition process, interpolation and fitting are performed based on the data from each point to create a pressure distribution map corresponding to the complete mattress. Based on the location and magnitude of pressure on the pressure distribution map, the patient's current sitting / lying position and posture can be further determined.

[0064] Orthopedic patients refer to those who have fractures or similar conditions and require rehabilitation care. These patients are characterized by prolonged bed rest and the need to perform corresponding rehabilitation activities at set times. For the prolonged bed rest, the mattress support needs to be controlled to a certain extent, such as periodically changing the firmness of different zones to assist patients with light activities and prevent pressure sores. The rehabilitation activities require patients to perform exercises such as leg raises and arm movements in bed. These activities need to provide sufficient stability for sitting or lying positions, while optimizing the softness of the mattress in certain areas can prevent impact at the end of the activity.

[0065] Based on the above settings, during the control process, the controller first obtains clinical information from the patient and inputs fracture area and rehabilitation prompt information from the clinical information. The fracture area is used to indicate the patient's fracture type, while the rehabilitation prompt information corresponds to the time period and range of activities that the patient needs to perform rehabilitation exercises every day.

[0066] The controller then collects real-time pressure information and creates a pressure zoning map. This pressure zoning map can be used to indicate whether the patient is exhibiting fixed activities.

[0067] Based on this, the patient's current movement status is predicted using clinical information and real-time pressure information. This current movement status may correspond to the patient's ongoing rehabilitation exercises or daily activities, and corresponds to different support points and the patient's range of motion.

[0068] Based on this, the hardness of the zoned support pad is adjusted according to the current movement status. The adjustment principle is mainly to increase the hardness of the support area to improve the support for the patient's limb, while reducing the hardness of the part of the patient's limb range of motion to avoid inconvenience to the patient and additional impact when the limb falls.

[0069] In one embodiment, such as Figure 2 As shown, step S1 includes:

[0070] Step S11: Collect the patient's electronic medical record, extract the document name field from the electronic medical record, and obtain real-time pressure information based on the pressure acquisition matrix;

[0071] Step S12: Obtain diagnostic information and rehabilitation suggestions by matching the document name field;

[0072] Step S13: Generate clinical information based on diagnostic information and rehabilitation recommendations.

[0073] Specifically, in order to achieve a better extraction process of clinical information, in this embodiment, the system is first connected to the electronic medical record system to collect the patient's electronic medical record. The electronic medical record contains various documents and diagnostic suggestions, and the document name field can be extracted in advance for matching.

[0074] Based on the patient's diagnostic information and rehabilitation prescription, a corresponding thesaurus is pre-compiled, and the diagnostic information and rehabilitation suggestions are obtained by regular expression matching using the thesaurus.

[0075] The diagnostic information typically includes the patient's fracture area, while the rehabilitation recommendations specify the number of rehabilitation sessions and limb movements the patient needs to perform daily. A pre-trained natural language model is used to extract this information and remove irrelevant information to ultimately form clinical information.

[0076] Meanwhile, the controller polls each collection point to obtain pressure data, and performs interpolation fitting based on the data from each point to establish a pressure distribution map corresponding to the complete mattress as real-time pressure information.

[0077] In one embodiment, such as Figure 3 As shown, step S2 includes:

[0078] Step S21: Collect the current time period and match it with the rehabilitation exercise period in the rehabilitation prompt information to determine whether it is in the rehabilitation period, and determine the patient's lying position according to the real-time pressure information;

[0079] If so, proceed to step S22;

[0080] If not, proceed to step S23;

[0081] Step S22: Extract the patient's active and supporting parts from the rehabilitation prompt information, map the supporting parts to the lying position, then determine the orientation of the patient's active limbs according to the relative position of the active and supporting parts, and then proceed to step S24.

[0082] Step S23: Match a standard human figure template to the lying position to predict the orientation of the patient's moving limbs that are not in contact with the bed, and then proceed to step S24;

[0083] Step S24: Establish the current motion state based on the lying position and the orientation of the patient's moving limbs.

[0084] Specifically, after obtaining the patient's rehabilitation prompts and real-time stress information, a match can be made between the current time period and the rehabilitation exercise period in the rehabilitation prompts.

[0085] The rehabilitation exercise period is a time frame after the medical order has been blurred. Better redundancy is achieved by omitting the minute field or adding 30-minute blurring spaces before and after the original time frame. This time frame is then compared with the current time frame to determine whether the patient is likely engaged in rehabilitation activities.

[0086] Furthermore, by performing connected component detection based on the pressure distribution map in the real-time pressure information and retaining the area with the largest area, the patient's torso position on the bed can be determined.

[0087] Depending on the time of day, the patient may be engaged in daily activities or rehabilitation activities.

[0088] Since rehabilitation activities have relatively fixed activity patterns, relevant instructional instructions can be extracted based on rehabilitation prompts to determine the patient's activity and support points under standard rehabilitation movements, such as specific trunk positions for support and limbs moving along specific trajectories.

[0089] The supporting part is then mapped to the lying position. Subsequently, the movement trajectory can be easily predicted to determine the possible movements of the patient's limbs, and the relative position of the moving part and the supporting part is established as the orientation of the patient's moving limb.

[0090] Since daily activities do not have specific behavioral patterns, the approach adopted in this application is to match the lying position with a standard human figure template to determine the parts in contact with the mattress and the patient's active parts, thereby predicting the orientation of the patient's active limbs that are not in contact with the bed.

[0091] Finally, the current movement status is described based on the lying position and the orientation of the patient's moving limbs.

[0092] In one embodiment, such as Figure 4 As shown, step S22 includes:

[0093] Step S221: Obtain rehabilitation movements from the rehabilitation prompts, and determine the active parts, supporting parts, and movement trajectories of the active parts based on the rehabilitation movements;

[0094] Step S222: Scale the support part and map it to the lying position, and record the scaling ratio;

[0095] Step S223: Map the motion trajectory based on the lying position according to the scaling ratio to determine the mapped active parts;

[0096] Step S224: Determine the orientation of the patient's limbs based on the relative positions of the active and supporting parts.

[0097] Specifically, in order to achieve a better predictive effect on the patient's rehabilitation movements, in this embodiment, rehabilitation movements are obtained from rehabilitation prompt information. These rehabilitation movements are teaching movements compiled from standard medical rehabilitation movements. Based on the rehabilitation movements, posture estimation can be performed to determine the main active parts, supporting parts, and movement trajectories of the active parts.

[0098] Since the rehabilitation movements are based on a standard human body model, after the support points are extracted, they are mapped onto the real-time pressure distribution map according to the head-to-toe direction, and the center points are aligned and scaled so that the support points roughly coincide with the projection of the lying position. This scaling process will produce a corresponding scaling ratio.

[0099] Subsequently, using the center point as the origin, the motion trajectory is mapped based on the lying position according to the scaling ratio to determine the mapped active parts. This process is based on the transfer of the estimated posture motion. To simplify the calculation, the output of this process will be converted into a two-dimensional projection of the limb on the mattress. Finally, the orientation of the patient's active limb is established according to the relative position of the active parts and the supporting parts.

[0100] In one embodiment, such as Figure 5 As shown, step S23 includes:

[0101] Step S231: Obtain the initial lying position and generate a mapping ratio based on the area of ​​the initial lying position and the standard human body template;

[0102] Step S232: Transfer the standard human body template to the lying position according to the mapping ratio, and mark the orientation of the patient's moving limbs.

[0103] Specifically, in order to provide better support for patients during daily activities and to cushion the surrounding limbs, in this embodiment, multiple pressure distribution maps adjacent to the current time period are read and arranged in chronological order. Then, the standard deviation of the values ​​of each sampling point in the pressure distribution map at each time point is calculated. The standard deviations are then compared, and the time period with relatively consistent standard deviations is determined as the time period when the patient is lying down normally and not active. The pressure distribution map in this time period is used to extract the connected components as the initial lying position.

[0104] Subsequently, a mapping ratio is generated based on the area of ​​the initial lying position and the standard human body template, and the standard human body template is mapped onto the lying position according to the mapping ratio.

[0105] Then, the standard human body template is compared with the current lying position to determine the parts still in contact with the mattress and the limbs not in contact with the mattress. The joints of the limbs not in contact with the mattress are determined according to anatomy to determine the range of motion of the joints near the heart, thus forming the possible range of motion of the limbs and finally obtaining the orientation of the patient's limbs.

[0106] In one embodiment, such as Figure 6 As shown, step S3 includes:

[0107] Step S31: Calculate the ratio of the motion support area to the human body projection based on the lying position, and establish the projection of the patient's moving limb position on the zoned support adjustment pad.

[0108] Step S32: Increase the hardness of the support zone corresponding to the lying position according to the proportion of the support area, and decrease the hardness of the support zone corresponding to the projection of the active area.

[0109] Specifically, to achieve better firmness control, in this embodiment, the proportion of the support area relative to the body projection is first calculated based on the patient's lying position. This proportion determines the degree of pressure change in the contact area between the patient and the mattress during movement. Then, the firmness of the support zone corresponding to the lying position is increased according to this proportion. This increase is determined by pre-calibrating the pressure of the airbag unit. A common control method involves dividing the support area into multiple levels based on the proportion before and after activity, such as reducing the limb area to 40%, 50%, or 60% relative to a supine position. Different levels correspond to specific inflation volumes of the airbag unit, thereby changing the firmness.

[0110] The airbag units that require increased rigidity are determined by comparing the distribution map of the lying positions with the installation location of the airbag units.

[0111] Meanwhile, for the active limbs, the patient's active limb position is first projected onto the active area on the zoned support adjustment pad. Based on the active area projection, the airbag units that need to be reduced in stiffness are determined, and then the airbag units are directly deflated to reduce stiffness.

[0112] The above are merely preferred embodiments of the present invention and are not intended to limit the implementation methods and protection scope of the present invention. Those skilled in the art should recognize that any equivalent substitutions and obvious changes made based on the description and illustrations of the present invention should be included within the protection scope of the present invention.

Claims

1. A control method for an intelligent orthopedic nursing bed based on dynamic pressure feedback, characterized in that, Based on an orthopedic nursing bed, the orthopedic nursing bed includes a zoned support adjustment pad and a pressure acquisition matrix above the zoned support adjustment pad; The intelligent orthopedic nursing bed control method includes: Step S1: Collect clinical information and real-time stress information from the patient; The clinical information includes the patient's fracture location and rehabilitation tips; Step S2: Predict the patient's current motion state based on the clinical information and the real-time pressure information; Step S3: Adjust the partition hardness of the partition support adjustment pad according to the current motion state.

2. The smart orthopedic care bed control method of claim 1, wherein, Step S1 includes: Step S11: Collect the patient's electronic medical record, extract the document name field from the electronic medical record, and obtain the real-time pressure information based on the pressure acquisition matrix; Step S12: Obtain diagnostic information and rehabilitation suggestions by matching the document name field; Step S13: Generate the clinical information based on the diagnostic information and the rehabilitation recommendations.

3. The smart orthopedic care bed control method of claim 1, wherein, The pressure acquisition matrix is ​​implemented based on a fiber optic grating sensor array.

4. The smart orthopedic care bed control method of claim 1, wherein, The pressure acquisition matrix is ​​implemented based on a flexible pressure sensor.

5. The intelligent orthopedic care bed control method of claim 1, wherein, Step S2 includes: Step S21: Collect the current time period and match it with the rehabilitation exercise period in the rehabilitation prompt information to determine whether it is in a rehabilitation period, and determine the patient's lying position according to the real-time pressure information; If so, proceed to step S22; If not, proceed to step S23; Step S22: Extract the patient's active and supporting parts from the rehabilitation prompt information, map the supporting parts to the lying position, then determine the orientation of the patient's active limbs according to the relative position of the active and supporting parts, and then proceed to step S24; Step S23: Match a standard human-shaped template according to the lying position to predict the orientation of the patient's active limbs that are not in contact with the bed, and then proceed to step S24; Step S24: Establish the current motion state based on the lying position and the orientation of the patient's moving limbs.

6. The intelligent orthopedic care bed control method of claim 5, wherein, Step S22 includes: Step S221: Obtain rehabilitation movements from the rehabilitation prompt information, and determine the active part, the supporting part, and the movement trajectory of the active part based on the rehabilitation movements; Step S222: Scale the support part and map it to the lying position, and record the scaling ratio; Step S223: Map the motion trajectory based on the lying position according to the scaling ratio to determine the mapped active part; Step S224: Determine the orientation of the patient's active limb based on the relative position of the active part and the supporting part.

7. The smart orthopedic care bed control method of claim 5, wherein, Step S23 includes: Step S231: Obtain the initial lying position, and generate a mapping ratio based on the area of ​​the initial lying position and the standard human body template; Step S232: Transfer the standard human body template to the lying position according to the mapping ratio, and mark the orientation of the patient's active limbs.

8. The smart orthopedic care bed control method of claim 5, wherein, Step S3 includes: Step S31: Calculate the ratio of the motion support area to the human body projection according to the lying position, and establish the motion area projection of the patient's active limb on the partitioned support adjustment pad; Step S32: Increase the hardness of the support partition corresponding to the lying position according to the proportion of the support area, and decrease the hardness of the support partition corresponding to the projection of the active area.

9. The smart orthopedic care bed control method of claim 1, wherein, The partitioned support adjustment pad includes multiple airbag units.

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