CN117257571B - Electric medical bed intelligent control system based on artificial intelligence - Google Patents
Electric medical bed intelligent control system based on artificial intelligence Download PDFInfo
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- A61G7/015—Beds specially adapted for nursing; Devices for lifting patients or disabled persons having adjustable mattress frame divided into different adjustable sections, e.g. for Gatch position
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- A61G2203/00—General characteristics of devices
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Abstract
The invention discloses an electric medical bed intelligent control system based on artificial intelligence, which comprises a man-machine interaction module, an executing mechanism, a data acquisition module, a data processing module, an evaluation module, an expert control module, a driving module and an energy supply module. According to the technical scheme, based on the principle of an expert control system, an evaluation model is built according to the acquired stress data and the calculation result of the angular acceleration value of the back plate of the medical bed through the evaluation module, comfort level of a patient in the use process is evaluated, a quantitative evaluation result of comfort level is obtained, the comfort level evaluation result of the patient in the use process is analyzed through the expert control module, a control strategy is generated according to the analysis result, intelligent control of the medical bed in the process of completing at least one action of leg bending, back lifting and turning can be achieved, running stability of an executing mechanism is improved, and comfort performance of the patient in the use process is improved.
Description
Technical Field
The invention relates to the field of electric medical beds, in particular to an intelligent control system of an electric medical bed based on artificial intelligence.
Background
The electric medical bed is not only suitable for medical units as an I CU nursing bed, but also as a home nursing bed for nursing homes and nursing homes.
At present, the control system of the existing electric medical bed in the market is low in intelligent degree, can only meet basic nursing functions, is simple in function, and in the control process, when the medical bed bends legs or lifts back and the like, the running stability of an actuating mechanism is poor, so that the comfort of the medical bed is poor, the use effect is poor, and the rehabilitation of a patient is not facilitated.
Disclosure of Invention
The invention mainly aims to provide an electric medical bed intelligent control system based on artificial intelligence, which can effectively solve the problems in the background technology.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
An electric medical bed intelligent control system based on artificial intelligence comprises a man-machine interaction module, an execution mechanism, a data acquisition module, a data processing module, an evaluation module, an expert control module, a driving module and an energy supply module;
The man-machine interaction module is used for giving control instructions to the medical bed by a patient or medical staff in at least one mode of touching, voice, appointed behaviors or actions;
the data acquisition module is used for acquiring operation data of the back plate of the medical bed and stress data of feet, legs, buttocks and back areas of a patient in the operation process of the electric medical bed, wherein the operation data comprise corner values of the back plate of the medical bed;
The data processing module constructs an electric medical bed parameterized motion model according to the acquired operation data, and calculates the maximum value of the angular acceleration value of the back plate of the medical bed at the moment t according to the constructed motion model, wherein the motion model has the expression:
σi＝f(θi,li,t)
Wherein i=1, 2,3, n; sigma i is the angular acceleration value of the ith section of the medical bed backboard at the time t, theta i is the angular value of the ith section of the medical bed backboard at the time t, and l i is the length value of the ith section of the medical bed backboard;
The evaluation module builds an evaluation model according to the acquired stress data and the calculation result of the angular acceleration value of the back plate of the medical bed, evaluates the comfort level of a patient in the use process, and acquires a quantitative evaluation result of the comfort level, wherein the expression of the evaluation model is as follows:
S (t) is a comfort value at time t in the use process of a patient; sigma i max is the maximum value of the angular acceleration value of the back plate of the medical bed in a fixed time interval; Δfmax is the maximum value of the amount of change in the force value in the foot, leg, hip and back regions of the patient over a fixed time interval; alpha and beta are weight coefficients; max [ F jt-Fjt' ] is the maximum value in F jt-Fjt', and F jt is the stress value of any region of the foot, leg, hip and back of the patient at time t; f jt' is the stress value of the corresponding region in the foot, leg, hip and back of the patient at a fixed time interval from time t;
The expert control module analyzes the comfort evaluation result in the use process of the patient and generates a control strategy according to the analysis result;
responding to a control strategy generated by an expert control module, and generating a control instruction signal by the driving module;
Responding to the control instruction signal generated by the driving module, the executing mechanism drives the back plate of the medical bed to act, so that the medical bed is promoted to complete at least one action content of leg bending, back lifting and turning;
the energy supply module is used for providing electric power resources for all power utilization units in the system.
Further, the analysis of the comfort level evaluation result includes the following steps:
Step one, acquiring a comfort level S (t) at a moment t in the use process of a patient, and creating a sample set by utilizing the value of the comfort level S (t), wherein m is the total number of the comfort level values;
Step two, acquiring the mean value and the standard deviation in the sample set, and standardizing the data by using the mean value and the standard deviation, wherein the standardized formula is as follows In the formula, z is a standard parameter, sigma is the variance of sample data, and mu is the mean value of the sample data;
Step three, after the standardization is completed, utilizing the standard parameters Adjusting the numerical interval to be between 0 and 1, and classifying the comfort level value by using the function value of f (k), wherein the classification mechanism is as follows:
when f (k) min is less than or equal to f (k) < f (k) 1, classifying the comfort value into a first class;
When f (k) 1≤f(k)＜f(k)2, the classification of the comfort value is secondary;
When f (k) 2≤f(k)＜f(k)3, the classification of the comfort value is three-level;
similarly, when f (k) t is less than or equal to f (k) < f (k) max, the class of comfort values is t;
Wherein f (k) min, f (k) max are the minimum and maximum values of the function value of f (k), respectively, f (k) 1、f(k)2、、、f(k)t is the intermediate value of f (k), and f (k) min < f (k) 1＜f(k)2＜、、、＜f(k)t < f (k) max, t is a positive integer.
Further, the generation principle of the control strategy is as follows:
When the classification result of f (k) function values f (k) q of the comfort level standard parameters is a first level, generating a control strategy for keeping the motion speed of the actuating mechanism, wherein f (k) q is an intermediate value of f (k), and f (k) min < f (k) q < f (k) max;
and when the classification result of the f (k) function value f (k) q of the comfort level standard parameter is not one level, generating a control strategy for reducing the movement speed of the actuating mechanism.
Further, the data acquisition module comprises at least one group of angle sensors and at least four groups of pressure sensors.
Further, the pressure sensors are respectively arranged at the positions corresponding to the back plate of the medical bed and the foot, leg, hip and back areas of the patient.
Further, the system includes a memory module, a processor, and a computer program stored on the memory module and executable on the processor.
Further, the control flow of the system is as follows:
Step 1), a patient or medical staff issues a control instruction to a medical bed through a man-machine interaction module in at least one mode of touch, voice, appointed behavior or action, and a driving module drives an executing mechanism to execute the control instruction in response to the control instruction issued by the man-machine interaction module;
Step 2), the data acquisition module acquires operation data of a back plate of the medical bed and stress data of feet, legs, buttocks and back areas of a patient in the operation process of the electric medical bed in real time;
Step 3), the data processing module constructs an electric medical bed parameterized motion model according to the acquired operation data, and calculates the maximum value of the angular acceleration value of the back plate of the medical bed at the moment t according to the constructed motion model;
step 4), an evaluation module builds an evaluation model according to the acquired stress data and the calculation result of the angular acceleration value of the back plate of the medical bed, evaluates the comfort level of the patient in the use process and acquires a quantized evaluation result of the comfort level;
Step 5), the expert control module analyzes the comfort evaluation result in the use process of the patient and generates a control strategy according to the analysis result;
Step 6), responding to the control strategy generated by the expert control module, and generating a control instruction signal by the driving module;
and 7) responding to the control instruction signal generated by the driving module, and driving the back plate of the medical bed to act by the executing mechanism to promote the medical bed to complete at least one action content including leg bending, back lifting and turning.
Compared with the prior art, the invention has the following beneficial effects:
(1) According to the technical scheme, based on the principle of an expert control system, an evaluation model is built according to the acquired stress data and the calculation result of the angular acceleration value of the back plate of the medical bed through the evaluation module, comfort level of a patient in the use process is evaluated, a quantitative evaluation result of comfort level is obtained, the comfort level evaluation result of the patient in the use process is analyzed through the expert control module, a control strategy is generated according to the analysis result, intelligent control of the medical bed in the process of completing at least one action of leg bending, back lifting and turning can be achieved, running stability of an executing mechanism is improved, and comfort performance of the patient in the use process is improved.
Drawings
FIG. 1 is a schematic diagram of the overall structure of an intelligent control system of an electric medical bed based on artificial intelligence;
FIG. 2 is a control flow diagram of an intelligent control system for an electric medical bed based on artificial intelligence in accordance with the present invention;
FIG. 3 is a schematic diagram of the operational mode of an intelligent control system for an electric medical bed based on artificial intelligence of the invention.
In the figure: l 1、l2、l3 are all back plates of the medical bed.
Detailed Description
The present invention will be further described with reference to the following detailed description, wherein the drawings are for illustrative purposes only and are presented as schematic drawings, rather than physical drawings, and are not to be construed as limiting the invention, and wherein certain components of the drawings are omitted, enlarged or reduced in order to better illustrate the detailed description of the present invention, and are not representative of the actual product dimensions.
Example 1
As shown in fig. 1-3, an electric medical bed intelligent control system based on artificial intelligence comprises a man-machine interaction module, an executing mechanism, a data acquisition module, a data processing module, an evaluation module, an expert control module, a driving module and an energy supply module.
The control flow of the system is as follows:
Step 1), a patient or medical staff issues a control instruction to a medical bed through a man-machine interaction module in at least one mode of touch, voice, appointed behavior or action, and a driving module drives an executing mechanism to execute the control instruction in response to the control instruction issued by the man-machine interaction module;
Step 2), the data acquisition module acquires operation data of a back plate of the medical bed and stress data of feet, legs, buttocks and back areas of a patient in the operation process of the electric medical bed in real time;
Step 3), the data processing module constructs an electric medical bed parameterized motion model according to the acquired operation data, and calculates the maximum value of the angular acceleration value of the back plate of the medical bed at the moment t according to the constructed motion model;
step 4), an evaluation module builds an evaluation model according to the acquired stress data and the calculation result of the angular acceleration value of the back plate of the medical bed, evaluates the comfort level of the patient in the use process and acquires a quantized evaluation result of the comfort level;
Step 5), the expert control module analyzes the comfort evaluation result in the use process of the patient and generates a control strategy according to the analysis result;
Step 6), responding to the control strategy generated by the expert control module, and generating a control instruction signal by the driving module;
and 7) responding to the control instruction signal generated by the driving module, and driving the back plate of the medical bed to act by the executing mechanism to promote the medical bed to complete at least one action content including leg bending, back lifting and turning.
Taking the back lifting action of the medical bed as an example to describe the scheme of the invention, as shown in fig. 3, when the medical bed performs the back lifting action, the l 1 back plate of the medical bed rotates clockwise around a point o 1 under the drive of an executing mechanism, the l 2 back plate and the l 3 back plate keep original states, namely, in the actual movement process, the upper body of a patient rotates by taking a hip joint as a rotation center, the legs and feet of the patient do not change, in the movement process, the feet, the legs, the buttocks and the back area of the patient are in real-time contact with the back plate l 1、l2、l 3 of the medical bed, the operation data of the back plate of the medical bed and the stress data of the feet, the legs, the buttocks and the back area of the patient in the operation process of the electric medical bed are acquired in real time through a data acquisition module, an electric medical bed parameterization movement model is constructed through a data processing module, and the maximum value of the angular acceleration value of the back plate of the medical bed at the moment t is calculated according to the constructed movement model, wherein the expression of the movement model is as follows:
σi＝f(θi,li,t)
according to the analysis result of the motion process, when the back lifting motion process is carried out at any time, the angular acceleration value sigma i of the l 1 back plate of the medical bed is a function of the rotation angle theta i, the back plate length and the time, namely, the rotation angle theta i, the back plate length and the time corresponding to the angular acceleration value sigma i at the time t are determined, the angular acceleration value sigma i can reflect the running stability of the l 1 back plate, when the value of sigma i is about 0, the rotation speed of the l 1 back plate is about constant, when the rotation speed of the l 1 back plate is about constant, the variation of the body pressure value between the patient and the back plate of the medical bed is about stable, an evaluation model is constructed according to the acquired stress data and the calculation result of the angular acceleration value of the back plate of the medical bed through the evaluation module, and the comfort degree of the patient in the use process is evaluated, wherein the evaluation model is expressed as follows:
S (t) in the model is a comfort value at t time in the use process of a patient; sigma i max is the maximum value of the angular acceleration value of the back plate of the medical bed in a fixed time interval; Δfmax is the maximum value of the amount of change in the force value in the foot, leg, hip and back regions of the patient over a fixed time interval; alpha and beta are weight coefficients; max [ F jt-Fjt' ] is the maximum value in F jt-Fjt', F jt is the stress value of any region of the foot, leg, hip and back of the patient at time t, and the main contact positions of the patient and the medical bed are the four parts in the process of using the medical bed, so that the change of the stress values between the foot, leg, hip and back and the backboard is taken as a parameter for measuring comfort level, and when the change of the body pressure value between the patient and the medical bed backboard is stable, the change of the pressure value felt by the body of the patient is stable; f jt' is the stress value of the corresponding region in the foot, leg, hip and back of the patient at a fixed time interval from time t; after the quantized evaluation result of the comfort level is obtained through the evaluation model, classifying the quantized value of the evaluation result, wherein the method comprises the following specific steps:
Step one, acquiring a comfort level S (t) at a moment t in the use process of a patient, and creating a sample set by utilizing the value of the comfort level S (t), wherein m is the total number of the comfort level values;
Step two, acquiring the mean value and the standard deviation in the sample set, and standardizing the data by using the mean value and the standard deviation, wherein the standardized formula is as follows In the formula, z is a standard parameter, sigma is the variance of sample data, and mu is the mean value of the sample data;
Step three, after the standardization is completed, utilizing the standard parameters Adjusting the numerical interval to be between 0 and 1, and classifying the comfort level value by using the function value of f (k), wherein the classification mechanism is as follows:
when f (k) min is less than or equal to f (k) < f (k) 1, classifying the comfort value into a first class;
When f (k) 1≤f(k)＜f(k)2, the classification of the comfort value is secondary;
When f (k) 2≤f(k)＜f(k)3, the classification of the comfort value is three-level;
similarly, when f (k) t is less than or equal to f (k) < f (k) max, the class of comfort values is t;
Wherein f (k) min, f (k) max are respectively the minimum value and the maximum value of the function value of f (k), f (k) 1、f(k)2、、、f(k)t is respectively the intermediate value of f (k), f (k) min < f (k) 1＜f(k)2＜、、、＜f(k)t < f (k) max, t is a positive integer, according to the evaluation model, when the rotation speed of the i 1 backboard tends to be uniform, the value of sigma i tends to be 0, the variation of the body pressure value between the patient and the medical bed backboard tends to be stable, at this time, S (t) tends to be the minimum value, namely, during the back lifting action of the medical bed, the l 1 backboard gradually turns to a designated angle value from a horizontal position at a uniform stable state, and a control strategy is generated by analyzing the comfort evaluation result during the use of the patient, wherein the generation principle of the control strategy is as follows:
When the classification result of f (k) function values f (k) q of the comfort level standard parameters is one level, at the moment, when the rotation speed of the l 1 back plate tends to be uniform, the value of sigma i tends to be 0, and during the period, the motion of the l 1 back plate is stable, so that a control strategy for keeping the motion speed of an executing mechanism is generated, wherein f (k) q is an intermediate value of f (k), and f (k) min < f (k) q < f (k) max;
When the classification result of f (k) function value f (k) q of the standard parameter of the comfort level is not the first level, at this time, the rotation speed of the l 1 back plate is in a continuously changing state, in this time period, the movement of the l 1 back plate is unstable, and along with the higher level of the classification result, the change of the rotation speed of the l 1 back plate is larger, through analyzing the actual movement process, the process may be in a process of changing and accelerating rotation in which the rotation angular acceleration of the l 1 back plate is continuously increased, so that a control strategy for reducing the movement speed of the executing mechanism is generated, a control command signal is generated by the driving module in response to the control strategy generated by the expert control module, and the executing mechanism drives the back plate of the medical bed to act in response to the control command signal generated by the driving module, so that the medical bed is promoted to complete the back lifting action content.
In summary, the technical scheme provided by the invention is based on the expert control system principle, an evaluation model is constructed through an evaluation module according to the acquired stress data and the calculation result of the angular acceleration value of the back plate of the medical bed, the comfort degree of a patient in the use process is evaluated, the quantitative evaluation result of the comfort degree is obtained, the comfort degree evaluation result of the patient in the use process is analyzed through the expert control module, and a control strategy is generated according to the analysis result, so that the intelligent control of the medical bed in the process of completing at least one action of leg bending, back lifting and turning can be realized, the running stability of an executing mechanism is improved, and the comfort performance of the patient in the use process is improved.
The foregoing has shown and described the basic principles and main features of the present invention and the advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. An electric medical bed intelligent control system based on artificial intelligence, its characterized in that: the system comprises a man-machine interaction module, an executing mechanism, a data acquisition module, a data processing module, an evaluation module, an expert control module, a driving module and an energy supply module;
The man-machine interaction module is used for giving control instructions to the medical bed by a patient or medical staff in at least one mode of touching, voice, appointed behaviors or actions;
the data acquisition module is used for acquiring operation data of the back plate of the medical bed and stress data of feet, legs, buttocks and back areas of a patient in the operation process of the electric medical bed, wherein the operation data comprise corner values of the back plate of the medical bed;
The data processing module constructs an electric medical bed parameterized motion model according to the acquired operation data, and calculates the maximum value of the angular acceleration value of the back plate of the medical bed at the moment t according to the constructed motion model, wherein the motion model has the expression:
σi＝f(θi,li,t)
Wherein i=1, 2,3, n; sigma i is the angular acceleration value of the ith section of the medical bed backboard at the time t, theta i is the angular value of the ith section of the medical bed backboard at the time t, and l i is the length value of the ith section of the medical bed backboard;
The evaluation module builds an evaluation model according to the acquired stress data and the calculation result of the angular acceleration value of the back plate of the medical bed, evaluates the comfort level of a patient in the use process, and acquires a quantitative evaluation result of the comfort level, wherein the expression of the evaluation model is as follows:
S (t) is a comfort value at time t in the use process of a patient; sigma i max is the maximum value of the angular acceleration value of the back plate of the medical bed in a fixed time interval; Δfmax is the maximum value of the amount of change in the force value in the foot, leg, hip and back regions of the patient over a fixed time interval; alpha and beta are weight coefficients; max [ F jt-Fjt' ] is the maximum value in F jt-Fjt', and F jt is the stress value of any region of the foot, leg, hip and back of the patient at time t; f jt' is the stress value of the corresponding region in the foot, leg, hip and back of the patient at a fixed time interval from time t;
The expert control module analyzes the comfort evaluation result in the use process of the patient and generates a control strategy according to the analysis result;
responding to a control strategy generated by an expert control module, and generating a control instruction signal by the driving module;
Responding to the control instruction signal generated by the driving module, the executing mechanism drives the back plate of the medical bed to act, so that the medical bed is promoted to complete at least one action content of leg bending, back lifting and turning;
the energy supply module is used for providing electric power resources for all power utilization units in the system.
2. The intelligent control system of an artificial intelligence based electric medical bed according to claim 1, wherein: the analysis of the comfort assessment result comprises the following steps:
Step one, acquiring a comfort level S (t) at a moment t in the use process of a patient, and creating a sample set by utilizing the value of the comfort level S (t), wherein m is the total number of the comfort level values;
Step two, acquiring the mean value and the standard deviation in the sample set, and standardizing the data by using the mean value and the standard deviation, wherein the standardized formula is as follows In the formula, z is a standard parameter, sigma is the variance of sample data, and mu is the mean value of the sample data;
Step three, after the standardization is completed, utilizing the standard parameters Adjusting the numerical interval to be between 0 and 1, and classifying the comfort level value by using the function value of f (k), wherein the classification mechanism is as follows:
when f (k) min is less than or equal to f (k) < f (k) 1, classifying the comfort value into a first class;
When f (k) 1≤f(k)＜f(k)2, the classification of the comfort value is secondary;
When f (k) 2≤f(k)＜f(k)3, the classification of the comfort value is three-level;
similarly, when f (k) t is less than or equal to f (k) < f (k) max, the class of comfort values is t;
Wherein f (k) min, f (k) max are the minimum and maximum values of the function value of f (k), respectively, f (k) 1、f(k)2、、、f(k)t is the intermediate value of f (k), and f (k) min < f (k) 1＜f(k)2＜、、、＜f(k)t < f (k) max, t is a positive integer.
3. The intelligent control system of an artificial intelligence based electric medical bed according to claim 2, wherein: the generation principle of the control strategy is as follows:
When the classification result of f (k) function values f (k) q of the comfort level standard parameters is a first level, generating a control strategy for keeping the motion speed of the actuating mechanism, wherein f (k) q is an intermediate value of f (k), and f (k) min < f (k) q < f (k) max;
and when the classification result of the f (k) function value f (k) q of the comfort level standard parameter is not one level, generating a control strategy for reducing the movement speed of the actuating mechanism.
4. The intelligent control system of an artificial intelligence based electric medical bed according to claim 1, wherein: the data acquisition module comprises at least one group of angle sensors and at least four groups of pressure sensors.
5. The intelligent control system for an electric medical bed based on artificial intelligence according to claim 4, wherein: the pressure sensors are respectively arranged at the positions corresponding to the back plate of the medical bed and the foot, leg, hip and back areas of the patient.
6. The intelligent control system of an artificial intelligence based electric medical bed according to claim 1, wherein: the system includes a memory module, a processor, and a computer program stored on the memory module and executable on the processor.
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