CN111383755B - Knee joint disease evaluation system based on Internet of things cloud server - Google Patents
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Abstract
The invention relates to a knee joint disease evaluation system based on an Internet of things cloud server. The knee joint disease evaluation system acquires knee joint movement signals, thigh movement signals and shank movement signals of a user through a knee joint data acquisition module (101) and sends the knee joint movement signals, thigh movement signals and shank movement signals to a processing module (102) for processing and judging to form knee joint damage information; displaying the knee joint movement information and the knee joint damage information on an interface through a user management terminal (104) and sending the knee joint movement information and the knee joint damage information to a cloud server (105) to form a first electronic medical record of a user; and the medical evaluation terminal (106) evaluates the knee joint state of the user according to the information in the first electronic medical record of the user to form a second electronic medical record of the user. The knee joint disease evaluation system based on the cloud server of the Internet of things can acquire knee joint movement information in a movement state at any time and any place, determine the damage degree of the knee joint and give medical advice; the user does not need to go to a hospital to carry out professional detection, and great convenience is brought to the user.
Description
Technical Field
The invention belongs to the field of medical management, and particularly relates to a knee joint disease evaluation system based on an Internet of things cloud server.
Background
The knee joint is one of the largest joints of the whole body, consists of femur, tibia and patella, is a bearing joint of a human body, and is one of the most damaged joints. Knee joint is the joint with the highest incidence of the whole body, and knee joint pain is not only related to various lesions in the joint, but also often caused by various extra-articular factors. Symptoms produced by the knee joint are often not specific. Symptoms such as pain, leg weakness, joint locking and the like can be caused by injuries of cruciate ligaments and meniscus, abnormal patellofemoral joints and joint cartilage lesions, and even can be caused by incarceration of abnormal hyperplasia synovium only. The knee joint has high morbidity and hidden development after illness, and is the first chronic disease of the world.
A conventional knee joint disease diagnosis technique is magnetic resonance imaging (Magnetic Resonance Imaging, MRI for short). Magnetic resonance imaging is one type of tomographic imaging that uses magnetic resonance phenomena to acquire electromagnetic signals from a human body and reconstruct human body information. However, MRI has many problems, such as the MRI is greatly affected by hardware of the apparatus, the film reading needs a specialist, is greatly affected by the professional level, is only suitable for static observation, is not suitable for continuous monitoring, cannot observe the change of the load state, is relatively expensive, and has potential physical damage.
In summary, the existing knee joint disease diagnosis technology has to go to the hospital for detection, has high price and more limitation, cannot track the knee joint state of people for a long time, and gives related diagnosis and treatment suggestions.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a knee joint disease evaluation system based on an Internet of things cloud server.
An embodiment of the invention provides a knee joint disease evaluation system based on an internet of things cloud server, which comprises: the knee joint data acquisition module 101, the processing module 102, the wireless communication module 103, the user management terminal 104, the cloud server 105 and the medical evaluation terminal 106; wherein,
the knee joint data acquisition module 101 is used for acquiring knee joint movement signals, thigh movement signals and shank movement signals of a user;
the processing module 102 is connected to the knee joint data acquisition module 101, and is configured to receive the knee joint motion signal, the thigh motion signal, and the shank motion signal, and process the knee joint motion signal, the thigh motion signal, and the shank motion signal to determine a knee joint damage degree, so as to form knee joint damage information;
the wireless communication module 103 is connected to the processing module 102 and is used for receiving and forwarding the knee joint movement information and the knee joint damage information;
the user management terminal 104 is communicatively connected to the wireless communication module 103, and is configured to receive the knee joint movement information and the knee joint damage information, display the knee joint movement information and the knee joint damage information on an interface, and obtain user basic information, and evaluate the knee joint damage degree of the user and remind the user based on the user basic information and the knee joint damage information;
the cloud server 105 is communicatively connected to the wireless communication module 103, and is configured to receive the knee joint movement information, the knee joint damage information, and the user basic information through the wireless communication module 103, and form a first electronic medical record of the user based on the user basic information, the knee joint movement information, and the knee joint damage information;
the medical evaluation terminal 106 is communicatively connected to the wireless communication module 103, and is configured to receive the first electronic medical record of the user through the wireless communication module 103, evaluate the knee joint state of the user according to the information in the first electronic medical record of the user, and send an evaluation result to the cloud server 105 through the wireless communication module 103 and add the evaluation result to the first electronic medical record of the user, so that the cloud server 105 forms a second electronic medical record of the user.
In one embodiment of the present invention, the user management terminal 104 is further configured to receive and display the second electronic medical record of the user through the wireless communication module 103.
In one embodiment of the present invention, the knee joint data acquisition module 101 includes: a first acquisition unit 1011, a second acquisition unit 1012, and a third acquisition unit 1013; the first acquisition unit 1011 is used for acquiring knee joint motion signals; wherein the knee joint motion signal comprises a knee joint vibration signal and a knee joint sound signal; the second acquisition unit 1012 is used for acquiring thigh movement signals; wherein the thigh motion signal comprises a thigh gesture signal; the third acquisition unit 1013 is configured to acquire a calf motion signal; wherein the calf motion signal comprises a calf attitude signal.
In one embodiment of the present invention, the first acquisition unit 1011 includes an acceleration sensor and an acoustic sensor,
the acceleration sensor is used for acquiring the knee joint vibration signal in a motion state;
the acoustic sensor is used for acquiring the knee joint sound signal under the motion state.
In one embodiment of the invention, the acceleration sensor is a micro accelerometer and the acoustic sensor is an electronic microphone.
In one embodiment of the present invention, the second acquisition unit 1012 includes a first posture sensor for acquiring the thigh posture signal in a motion state.
In one embodiment of the present invention, the third acquisition unit 1013 includes a second posture sensor for acquiring the calf posture signal in a movement state.
In one embodiment of the invention, the first and second attitude sensors are gyroscopes.
In one embodiment of the present invention, the user management terminal 104 includes a receiving unit 1041, a first display unit 1042, an alarm unit 1043, and a second display unit 1044;
the receiving unit 1041 is configured to receive the knee joint movement information, the knee joint damage information, and the second electronic medical record of the user;
the first display unit 1042 is configured to display the knee joint movement information and the knee joint damage information on an interface;
the alarm unit 1043 is configured to simply evaluate the severity of damage to the knee joint of the user based on the user basic information and the knee joint damage information and remind the user;
the second display unit 1044 is configured to display the second electronic medical record of the user on an interface.
In one embodiment of the present invention, the knee joint disease evaluation system further includes a buffer module 107 connected between the knee joint data acquisition module 101 and the processing module 102, for storing the knee joint movement signal, the thigh movement signal, and the shank movement signal.
Compared with the prior art, the knee joint disease evaluation system based on the cloud server of the Internet of things has at least the following beneficial effects:
1) The knee joint disease evaluation system based on the cloud server of the Internet of things provided by the embodiment of the invention can acquire knee joint movement information in a movement state at any time and any place, and determine the damage degree of the knee joint; the user does not need to go to a hospital to carry out professional detection, and great convenience is brought to the user;
2) According to the knee joint disease evaluation system based on the cloud server of the Internet of things, knee joint movement information and knee joint damage information are sent to the cloud server for storage, and after evaluation results are obtained through the medical evaluation terminal, the results are checked through the user management terminal, so that a user can obtain knee joint damage states and professional medical advice at any time and any place without being limited by places and without being limited by distances.
Drawings
Fig. 1 is a schematic diagram of a knee joint disease evaluation system based on an internet of things cloud server according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a knee joint data acquisition module of a knee joint disease evaluation system based on an internet of things cloud server according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a user management terminal of a knee joint disease evaluation system based on an internet of things cloud server according to an embodiment of the present invention;
fig. 4 is a schematic diagram of another knee joint disease evaluation system based on a cloud server of the internet of things provided by the embodiment of the invention.
Detailed Description
The present invention will be described in further detail with reference to specific examples, but embodiments of the present invention are not limited thereto.
Example 1
At present, a large number of users may need to be at home or even walk on the road to detect the knee joint state, and the advice of the professional medical staff is obtained, so that how to realize the function is a difficult problem. The emerging Internet of things technology provides an excellent solution to the problems. The new generation information technology of the internet of things (Internet of Things, ioT for short) connects objects with each other through the internet, and realizes information exchange among any time, any place and any object on the basis of the internet, so that human society, information space and physical space are integrated. Different devices can be communicated and information shared by utilizing the internet of things technology, and other complicated steps are omitted. And convenience is provided for adjustment and expansion of a future disease evaluation system.
Referring to fig. 1, fig. 1 is a schematic diagram of a knee joint disease evaluation system based on an internet of things cloud server according to an embodiment of the present invention. Specifically, the knee joint disease evaluation system based on the internet of things cloud server may include: the system comprises a knee joint data acquisition module 101, a processing module 102, a wireless communication module 103, a user management terminal 104, a cloud server 105 and a medical evaluation terminal 106. The processing module 102 is connected to the knee joint data acquisition module 101, the wireless communication module 103 is connected to the processing module 102, and the user management terminal 104, the cloud server 105, and the medical evaluation terminal 106 are respectively connected to the wireless communication module 103.
The knee joint data acquisition module 101 is configured to acquire a knee joint motion signal, a thigh motion signal, and a shank motion signal of a user, and send the signals to the processing module 102.
Since the knee joint motion signal generated by the damaged knee joint in the motion state is greatly different from the knee joint motion signal generated by the undamaged knee joint in the motion state, the knee joint motion signal generated by the knee joint in the motion state represents the damage degree of the knee joint.
In addition, when a human body moves, the knee joint is also in a moving state, and the combination mode of bones and the compression degree of the bones in the knee joint are different according to the different postures and the different movement speeds of the human body. It is understood that the motion states of the human body are different, the states of the knee joints are also different, and the states of the knee joints are closely related to the motion states of the lower limbs of the human body, and it is understood that the motion states of the lower limbs of the human body can be represented by thigh motion signals and shank motion signals.
Therefore, the knee joint motion signal generated by the knee joint, and the thigh motion signal and the shank motion signal corresponding to the knee joint motion signal can accurately represent the damaged state of the knee joint.
Specifically, the knee joint data acquisition module 101 may acquire a knee joint motion signal of a user, and a thigh motion signal and a shank motion signal corresponding to the knee joint motion signal, where the knee joint motion signal may include information capable of representing a motion state of a knee joint, such as a knee joint vibration signal, a knee joint sound signal, a knee joint acceleration, and the like, the thigh motion signal may include information capable of representing a motion state of a thigh, such as a posture information of a thigh, a height of the thigh from the ground, and the like, and the shank motion signal may include information capable of representing a motion state of a shank, such as a posture information of a shank, a height of the shank from the ground, and the like.
The processing module 102 is configured to receive the knee joint movement signal, the thigh movement signal, and the shank movement signal sent by the knee joint data acquisition module 101, and process the knee joint movement signal, the thigh movement signal, and the shank movement signal to determine the damage degree of the knee joint, so as to form knee joint damage information.
Specifically, the processing module 102 may process the knee motion signal, the thigh motion signal, and the shank motion signal to generate knee motion information, and determine a degree of damage to the knee joint based on the knee motion information using classification results obtained from a pre-trained model.
Wherein the knee joint movement information may include characteristic information of a knee joint movement signal and characteristic information of gesture information of the knee joint, the characteristic information of the knee joint movement signal may be generated based on the knee joint movement signal generated by the knee joint, the characteristic information of the gesture information may be generated based on the thigh movement signal and the shank movement signal, so that the processing module 102 may determine a degree of damage of the knee joint based on the knee joint movement information and form the damage information.
It should be noted that the characteristic information of the knee joint motion signal may include characteristic values of the knee joint vibration signal in the time domain and/or the frequency domain, and characteristic values of the knee joint sound signal in the time domain and/or the frequency domain.
Specifically, the characteristic value of the knee joint vibration signal may be a characteristic value of the knee joint vibration signal in a time domain and/or a frequency domain, the characteristic value of the knee joint sound signal may be a characteristic value of the knee joint sound signal in the time domain and/or the frequency domain, for example, the characteristic values of the knee joint vibration signal and the sound signal in the time domain may be root mean square, kurtosis, skewness, etc., the characteristic values of the knee joint vibration signal and the sound signal in the frequency domain may be frequency spectrum, energy spectrum, average frequency, power spectrum average value, etc., and the characteristic values of the knee joint vibration signal and the sound signal in the time-frequency domain may be wavelet packet transform coefficients, etc. Thus, the characteristic values of the knee joint vibration signal and the knee joint sound signal can intuitively represent the characteristics of the knee joint vibration signal and the knee joint sound signal from the time domain and/or the frequency domain.
Meanwhile, thigh movement signals and shank movement signals can be obtained while knee movement signals are obtained, characteristic information of gesture information can be obtained based on the thigh movement signals and the shank movement signals, and the characteristic information of the gesture information can be information which can embody the gesture of the knee joint, such as the joint angle of the knee joint, the height of the knee joint from the ground, and the like.
In general, the knee joint movement signal may include a knee joint movement signal within a preset measurement period, and accordingly, characteristic information of the posture information may be calculated based on the thigh movement signal and the shank movement signal acquired within the above-mentioned one preset measurement period.
Further, the processing module 102 may input knee joint motion information into a pre-trained model, derive classification results, and determine a degree of damage to the knee joint based on the classification results.
The pre-trained model can be a machine learning algorithm model such as a support vector machine (Support Vector Machine, SVM), a deep learning algorithm, a K-nearest neighbor algorithm, a Bayesian algorithm and the like.
In particular, the SVM model may be a radial basis function (Radial Basis Function, RBF) kernel based SVM model. Of course, other kernel functions may be selected according to the actual situation, for example, a polynomial kernel function, a laplace kernel function, a Sigmoid kernel function, and the like.
In addition, the pre-trained SVM model can be a two-class SVM model, the corresponding classification results are two classes, and the damage degree of the knee joint corresponding to the two classes of classification results is respectively undamaged and damaged; the pre-trained SVM model can also be a multi-classification VM model, the corresponding classification result can be at least five types, the damage degree of the knee joint corresponding to the classification result can be undamaged and damaged respectively, wherein the damage can be divided according to the damage degree, and at least the damage degree can be divided into primary damage, secondary damage, tertiary damage and quaternary damage.
Of course, the classification results corresponding to the multi-classification SVM model may be six or more, and in general, the damage may be subdivided, so that the finally determined damage degree of the knee joint is more accurate.
For example, when the pre-trained model is a two-class SVM model, the expected value of the classification result corresponding to the knee joint motion signal generated by the undamaged knee joint is set to be 1, and the expected value of the classification result corresponding to the knee joint motion signal generated by the damaged knee joint is set to be-1 when the original two-class SVM model is trained, then the knee joint can be determined to be undamaged when the classification result is 1, and the knee joint can be determined to be damaged when the classification result is-1.
In summary, the accuracy of the knee joint damage degree determined based on the knee joint movement information is higher than the knee joint damage degree estimated in the human body resting state.
The wireless communication module 103 is configured to receive and transmit the knee joint movement information and the knee joint damage information transmitted by the processing module 102.
The user management terminal 104 is configured to receive the knee joint movement information and the knee joint damage information forwarded by the wireless communication module 103, and display and send the knee joint movement information and the knee joint damage information on the interface.
Specifically, the user management terminal 104 receives knee joint movement information and knee joint damage information, and then displays the information on the interface according to a predetermined rule. For example, the display may be performed in chronological order, or may be performed according to the degree of knee joint damage, and information having a high degree of knee joint damage is preferentially displayed at the front end of the display page. The specific display rules can be set manually by the user.
In addition, the user management terminal 104 is further configured to obtain basic information of the user, and simply evaluate the severity of damage to the knee joint of the user and alert the user based on the basic information of the user and the damage information of the knee joint.
Specifically, the user management terminal 104 acquires basic information of the user, wherein the basic information of the user may include information of the name, address, sex, age, height, weight, and the like of the user. The injury level of the knee joint of the user is different from the injury level of the knee joint of the user to the injury of the user due to different ages, different weights and the like.
For example, a short period of low grade knee joint damage can be a serious hazard to the user as the weight increases. Thus, the severity of damage to the user's knee joint is simply assessed and alerted to the user based on the user's basic information as well as the knee joint damage information. When knee joint damage information happens accidentally, the situation can be ignored or the damage information can be marked in a display page so as to pay attention to a user; when the high-level knee joint damage information occurs or the low-level knee joint damage information occurs for a long time, the user management terminal 104 needs to send out an alarm, and notifies the user of the situation, and the user can be notified in an alarm mode such as a prompt tone, a buzzer and the like. The alarm duration can be set manually by the user, for example, the user can set as an infinite duration alarm until the user manually determines, or can set as an interval time period alarm.
The cloud server 105 is configured to receive, through the wireless communication module 103, knee joint movement information, knee joint damage information, and user basic information sent by the user management terminal 104, and form a first electronic medical record of the user based on the user basic information, the knee joint movement information, and the knee joint damage information.
Specifically, the cloud server 105 receives the knee joint movement information, the knee joint damage information, and the user basic information transmitted by the user management terminal 104 through the wireless communication module 103. The cloud server 105 allocates a storage space and a storage ID for the user according to the user basic information. After the user management terminal 104 sends the data to the cloud server 105, the cloud server 105 stores the data into a corresponding storage space according to a preset rule according to the storage ID extracted from the user basic information, so as to form a first electronic medical record of the user. The first electronic medical record of the user comprises user basic information, knee joint movement information and knee joint damage information, and the knee joint movement information and the knee joint damage information are stored according to the acquisition time sequence of the knee joint movement information.
The medical evaluation terminal 106 is configured to obtain a first electronic medical record of the user in the cloud server 105, evaluate the knee joint state of the user according to information in the first electronic medical record of the user, send an evaluation result to the cloud server 105, and add the evaluation result to the first electronic medical record of the user to form a second electronic medical record of the user.
Specifically, the medical evaluation terminal 106 obtains the first electronic medical record of the user in the cloud server 105, and evaluates the knee joint state of the user according to the user basic information, the knee joint movement information and the knee joint damage information in the first electronic medical record of the user. The knee joint movement information and the knee joint damage information in the first electronic medical record of the user are stored according to the acquisition time sequence, so that the medical evaluation terminal 106 can acquire different knee joint movement information and duration time of the knee joint damage information, evaluate the knee joint state information of the user based on the user basic information, and generate a corresponding diagnosis report and medical advice. The medical evaluation terminal 106 sends the diagnosis report and the medical advice to the cloud server 105 through the wireless communication module 103, and the cloud server 105 adds the diagnosis report and the medical advice to the first electronic medical record of the user according to the stored ID to form a second electronic medical record of the user. Further, the medical evaluation terminal 106 may send the diagnosis report and the medical advice to the cloud server 105 at regular intervals set by the user, and the medical evaluation terminal 106 may also send the diagnosis report and the medical advice to the cloud server 105 when requested by the user, where the cloud server 105 adds the diagnosis report and the medical advice to the first electronic medical record of the user to form the second electronic medical record of the user.
The cloud server 105 is further configured to store the second electronic medical record of the user, and send the second electronic medical record of the user to the user management terminal 104 through the wireless communication module 103, so that the user can check and prevent the second electronic medical record as early as possible.
In a specific embodiment, the user management terminal 104 may be a mobile terminal such as a mobile phone or a tablet.
The knee joint disease evaluation system provided by the embodiment of the invention can acquire knee joint movement information in a movement state at any time and any place, determine the damage degree of the knee joint, send the knee joint movement information and the damage information of the knee joint to a cloud server for storage, and check the result at a user management terminal after evaluating the result through a medical evaluation terminal, so that a user can acquire the damage state of the knee joint and professional medical advice at any time and any place without being limited by places and distance.
Example two
Referring to fig. 2 and fig. 3, fig. 2 is a schematic diagram of a knee joint data acquisition module of a knee joint disease evaluation system based on an internet of things cloud server according to an embodiment of the present invention; fig. 3 is a schematic diagram of a user management terminal of a knee joint disease evaluation system based on an internet of things cloud server according to an embodiment of the present invention. Based on the above embodiments, the knee joint data acquisition module 101 and the user management terminal 104 in the knee joint disease evaluation system based on the internet of things cloud server will be described in detail.
As shown in fig. 2, the knee joint data acquisition module 101 includes: a first acquisition unit 1011, a second acquisition unit 1012, and a third acquisition unit 1013. The first acquisition unit 1011 is used for acquiring knee joint motion signals; a second acquisition unit 1012 for acquiring thigh movement signals; a third acquisition unit 1013 for acquiring a calf movement signal.
Specifically, to acquire accurate signals, the first acquisition unit 1011 and the second acquisition unit 1012 may be placed on the knee at a position near the thigh to acquire knee joint movement signals and thigh movement signals, and the third acquisition unit 1013 may be placed on the calf at a position near the knee joint to acquire calf movement signals to enable the processing module 102 to generate knee joint movement information based on the above signals.
Wherein the knee joint motion signal includes a knee joint vibration signal and a knee joint sound signal. Accordingly, the first acquisition unit 1011 includes an acceleration sensor for acquiring a knee joint vibration signal in a user's motion state; the first acquisition unit 1011 further includes an acoustic sensor for acquiring knee joint sound signals in a user's motion state.
Specifically, the first acquisition unit 1011 may include an acceleration sensor capable of acquiring a knee joint vibration signal in a user's motion state, and an acoustic sensor capable of acquiring a knee joint sound signal in a user's motion state.
Since the vibration signal is generated by the movement of the knee joint, the vibration signal generated by the damaged knee joint can be distinguished from the vibration signal generated by the undamaged knee joint, and thus the vibration signal of the knee joint of the human body can be acquired using the acceleration sensor. In addition, sounds are generated between various bones and soft tissues inside the knee joint due to the movement of the knee joint, that is, sound signals of the knee joint. Thus, the acoustic sensor may be used to acquire knee joint sound signals generated by the knee joint.
In practical applications, in order to improve accuracy of the measured knee joint vibration signal, the acceleration sensors in the first acquisition unit 1011 may be plural. The acceleration sensor may be a micro accelerometer, and of course, may be other sensors having a function of measuring knee joint vibration signals. The acoustic sensor may be an electronic microphone, such as a stethoscope, or may be a piezoelectric film.
In a specific application, the thigh motion signal comprises a thigh gesture signal; the calf motion signals include calf attitude signals.
Accordingly, the second acquisition unit 1012 includes a first posture sensor for acquiring the thigh posture signal in a user movement state. The third acquisition unit 1013 includes a second posture sensor for acquiring the calf posture signal in a human body movement state.
Specifically, the thigh gesture signal may be gesture information of a thigh, and the shank gesture signal may be gesture information of a shank, so that the processing module 102 obtains information that can embody a knee joint gesture, such as an angle, an acceleration, and the like, based on the gesture information of the thigh and the gesture information of the shank.
In practical applications, the first gesture sensor and the second gesture sensor may be gyroscopes, and of course, the first gesture sensor and the second gesture sensor may be other sensors with functions of measuring gesture information.
The user management terminal 104 includes a receiving unit 1041, a first display unit 1042, an alarm unit 1043, and a second display unit 1044. The receiving unit 1041 is configured to receive the knee joint movement information and the knee joint damage information forwarded by the wireless communication module 103, and the second electronic medical record of the user sent by the cloud server 105; the first display unit 1042 is used for displaying knee joint movement information and knee joint damage information on an interface; the alarm unit 1043 is used for simply evaluating the severity of the damage of the knee joint of the user based on the basic information of the user and the damage information of the knee joint and reminding the user; the second display unit 1044 is configured to display a second electronic medical record of the user on the interface.
Specifically, the receiving unit 1041 receives the knee joint movement information and the knee joint damage information forwarded by the wireless communication module 103, and the second electronic medical record of the user sent by the cloud server 105. The first display unit 1042 displays knee joint movement information and knee joint damage information on the interface, further, the first display unit 1042 can display according to time sequence, and also can display according to the degree of knee joint damage, the information with high knee joint damage degree is preferentially displayed at the front end of the display page, and the specific display rule user can set manually. The alarm unit 1043 simply evaluates the severity of damage of the user's knee joint based on the user's basic information and knee joint damage information and alerts the user. When knee joint damage information happens accidentally, the situation can be ignored or the damage information can be marked in a display page so as to pay attention to a user; when high-level knee joint damage information occurs or low-level knee joint damage information occurs for a long time, the alarm unit 1043 gives an alarm, and notifies the user of this, and the user may be notified in an alarm manner such as a warning tone, a buzzer, or the like. The second display unit 1044 displays the second electronic medical record of the user on the interface, so that the user can check in time and prevent the second electronic medical record early.
According to the embodiment of the invention, the knee joint movement information in the movement state is accurately obtained, the knee joint damage information is formed, so that the user management terminal can display based on the knee joint movement information and the knee joint damage information, and an alarm is sent out to remind a user.
Example III
Referring to fig. 4, fig. 4 is a schematic diagram of another knee joint disease evaluation system based on a cloud server of the internet of things according to an embodiment of the present invention. On the basis of the above embodiment, the difference from the above embodiment is that the knee joint disease evaluation system based on the internet of things cloud server further includes: the buffer module 107 is connected between the knee joint data acquisition module 101 and the processing module 102. For storing knee movement signals, thigh movement signals, and calf movement signals transmitted by the knee data acquisition module 101.
Specifically, the buffer module 107 may store knee motion signals, thigh motion signals, and calf motion signals transmitted by the knee data acquisition module 101. The knee motion signal includes a knee vibration signal and a knee sound signal. The thigh motion signal includes a thigh gesture signal; the calf motion signals include calf attitude signals. The buffer module 107 stores the knee joint movement signal, the thigh movement signal and the shank movement signal, and sends the buffered data to the processing module 102 in a time-sharing and segmentation manner, so that the situation that a large amount of data is transmitted to the processing module 102 in a short time, and therefore the calculated amount of the processing module 102 cannot meet the condition that the scene is halted is avoided.
The processing module 102 receives the knee joint movement signal, the thigh movement signal and the shank movement signal sent by the buffer module 107 in a time-sharing and segmentation manner, and processes the knee joint movement signal, the thigh movement signal and the shank movement signal to judge the damage degree of the knee joint, so as to form knee joint damage information.
In practical applications, the cache module 107 may be a (Trans-Flash, TF) memory card, but may also be other devices with a memory function.
Example IV
Based on the above embodiments, the present embodiment describes in detail the working principle of the knee joint disease evaluation system based on the cloud server of the internet of things. The method comprises the following specific steps:
s401, the knee joint data acquisition module 101 acquires a knee joint motion signal, a thigh motion signal, and a shank motion signal of the user, and sends the signals to the buffer module 107 or directly to the processing module 102.
Specifically, the knee joint data acquisition module 101 may acquire a knee joint motion signal of a user, and a thigh motion signal and a shank motion signal corresponding to the knee joint motion signal, where the knee joint motion signal may include information capable of representing a motion state of a knee joint, such as a knee joint vibration signal, a knee joint sound signal, a knee joint acceleration, and the like, the thigh motion signal may include information capable of representing a motion state of a thigh, such as a posture information of a thigh, a height of the thigh from the ground, and the like, and the shank motion signal may include information capable of representing a motion state of a shank, such as a posture information of a shank, a height of the shank from the ground, and the like. The knee joint data acquisition module 101 sends the received knee joint motion signal, thigh motion signal, and calf motion signal to the caching module 107 for storage or directly to the processing module 102.
S402, the processing module 102 receives the knee joint movement signal, the thigh movement signal and the shank movement signal sent by the knee joint data acquisition module 101 or the buffer module 107, and processes the knee joint movement signal, the thigh movement signal and the shank movement signal to judge the damage degree of the knee joint, so as to form knee joint damage information.
Specifically, the processing module 102 may process the knee motion signal, the thigh motion signal, and the shank motion signal to generate knee motion information, and determine a degree of damage to the knee joint based on the knee motion information using classification results obtained from a pre-trained model.
S403, the user management terminal 104 receives the knee joint movement information and the knee joint damage information through the wireless communication module 103, displays the knee joint movement information and the knee joint damage information on an interface, and simply evaluates the severity of damage of the knee joint of the user and reminds the user based on the basic information and the knee joint damage information of the user.
Specifically, the user management terminal 104 receives knee joint movement information and knee joint damage information, and then displays the information on the interface according to a predetermined rule. The display can be performed according to time sequence, and also can be performed according to the degree grade of knee joint damage, and the information with high knee joint damage grade is preferentially displayed at the front end of the display page. The specific display rules can be set manually by the user. The user management terminal 104 acquires basic information of the user, simply evaluates the severity of damage to the knee joint of the user based on the basic information of the user and the knee joint damage information, and reminds the user. When knee joint damage information happens accidentally, the situation can be ignored or the damage information can be marked in a display page so as to pay attention to a user; when the high-level knee joint damage information occurs or the low-level knee joint damage information occurs for a long time, the user management terminal 104 needs to send out an alarm, and notifies the user of the situation, and the user can be notified in an alarm mode such as a prompt tone, a buzzer and the like. The alarm duration can be set manually by the user, for example, the user can set as an infinite duration alarm until the user manually determines, or can set as an interval time period alarm.
S404, the cloud server 105 receives the knee joint movement information, the knee joint damage information and the user basic information sent by the user management terminal 104 through the wireless communication module 103, and forms a first electronic medical record of the user based on the user basic information, the knee joint movement information and the knee joint damage information.
Specifically, the cloud server 105 receives the knee joint movement information, the knee joint damage information, and the user basic information transmitted by the user management terminal 104 through the wireless communication module 103. The cloud server 105 allocates a storage space and a storage ID for the user according to the user basic information. After the user management terminal 104 sends the data to the cloud server 105, the cloud server 105 stores the data into a corresponding storage space according to a preset rule according to the storage ID extracted from the user basic information, so as to form a first electronic medical record of the user. The first electronic medical record of the user comprises user basic information, knee joint movement information and knee joint damage information, and the knee joint movement information and the knee joint damage information are stored according to the acquisition time sequence of the knee joint movement information.
S405, the medical evaluation terminal 106 acquires a first electronic medical record of the user in the cloud server 105, and evaluates the knee joint state of the user according to the information in the first electronic medical record of the user.
Specifically, the medical evaluation terminal 106 obtains the first electronic medical record of the user in the cloud server 105, and evaluates the knee joint state of the user according to the user basic information, the knee joint movement information and the knee joint damage information in the first electronic medical record of the user. The knee joint movement information and the knee joint damage information in the first electronic medical record of the user are stored according to the acquisition time sequence, so that the medical evaluation terminal 106 can acquire different knee joint movement information and duration time of the knee joint damage information, evaluate the knee joint state information of the user based on the user basic information, and generate a corresponding diagnosis report and medical advice.
S406, the medical evaluation terminal 106 sends the diagnosis report and the medical advice to the cloud server 105 through the wireless communication module 103, and the cloud server 105 adds the diagnosis report and the medical advice to the first electronic medical record of the user according to the stored ID to form a second electronic medical record of the user.
S407, the cloud server 105 stores the second electronic medical record of the user, and sends the second electronic medical record of the user to the user management terminal 104 through the wireless communication module 103, so that the user can check and prevent the second electronic medical record as early as possible.
The above is a further detailed description of the knee joint disease evaluation system based on the cloud server of the internet of things provided by the invention in combination with a specific preferred embodiment, and it cannot be considered that the specific implementation of the invention is limited to these descriptions. It will be apparent to those skilled in the art that several simple deductions or substitutions may be made without departing from the spirit of the invention, and these should be considered to be within the scope of the invention.
Claims (9)
1. A knee joint disease continuous evaluation system based on an Internet of things cloud server is characterized by comprising: the system comprises a knee joint data acquisition module (101), a processing module (102), a wireless communication module (103), a user management terminal (104), a cloud server (105) and a medical evaluation terminal (106); wherein,
the knee joint data acquisition module (101) is used for acquiring knee joint movement signals, thigh movement signals and shank movement signals of a user; wherein the knee joint movement signals comprise knee joint vibration signals, knee joint sound signals and knee joint acceleration information which show the movement state of the knee joint; the knee joint vibration signals and knee joint sound signals are transmitted from the middle part of the patella by signals generated by bones and soft tissues in the knee joint when the knee joint stretches and bends; the thigh movement signals comprise thigh gesture information and thigh height information which represent thigh movement states; the shank movement signal comprises the posture information of the shank and the information representing the movement state of the shank, wherein the height of the shank from the ground;
the processing module (102) is connected to the knee joint data acquisition module (101) and is used for receiving the knee joint movement signal, the thigh movement signal and the shank movement signal, processing the knee joint movement signal, the thigh movement signal and the shank movement signal to judge the damage degree of the knee joint and form knee joint damage information, processing the knee joint movement signal, the thigh movement signal and the shank movement signal to generate knee joint movement information, and determining the damage degree of the knee joint based on the knee joint movement information by using a classification result obtained by a pre-trained deep learning algorithm model; wherein the knee joint movement information includes characteristic information of a knee joint movement signal and characteristic information of a posture information of a knee joint, the characteristic information of the knee joint movement signal being generated based on the knee joint movement signal, the characteristic information of the posture information being generated based on the thigh movement signal and the shank movement signal; the classification results include intact knee joints and varying degrees of impairment; different degrees of damage are represented in different levels;
the wireless communication module (103) is connected to the processing module (102) for receiving and forwarding the knee joint movement information and the knee joint damage information;
the user management terminal (104) is in communication connection with the wireless communication module (103) and is used for receiving the knee joint movement information and the knee joint damage information, displaying the knee joint movement information and the knee joint damage information on an interface, acquiring user basic information, evaluating the knee joint damage degree of a user based on the user basic information and the knee joint damage information and reminding the user;
the cloud server (105) is communicatively connected to the wireless communication module (103) and is configured to receive the knee joint movement information, the knee joint damage information and the user basic information through the wireless communication module (103), and form a first electronic medical record based on the user basic information, the knee joint movement information and the knee joint damage information;
the medical evaluation terminal (106) is in communication connection with the wireless communication module (103), and is used for receiving the first electronic medical record through the wireless communication module (103), evaluating the knee joint state of the user according to the information in the first electronic medical record of the user, sending an evaluation result to the cloud server (105) through the wireless communication module (103) and adding the evaluation result to the first electronic medical record of the user, so that the cloud server (105) forms a second electronic medical record of the user.
2. The knee joint disease evaluation continuous system of claim 1, wherein the user management terminal (104) is further configured to receive and display the user second electronic medical record via the wireless communication module (103).
3. The knee joint disease continuous assessment system according to claim 1, wherein the knee joint data acquisition module (101) comprises: a first acquisition unit (1011), a second acquisition unit (1012), and a third acquisition unit (1013);
the first acquisition unit (1011) is used for acquiring knee joint movement signals; the second acquisition unit (1012) is used for acquiring thigh movement signals; the third acquisition unit (1013) is used for acquiring a shank movement signal.
4. The knee joint disease continuous evaluation system according to claim 3, wherein the first acquisition unit (1011) includes an acceleration sensor and an acoustic sensor,
the acceleration sensor is used for acquiring the knee joint vibration signal in a motion state;
the acoustic sensor is used for acquiring the knee joint sound signal under the motion state.
5. A knee joint disease continuous assessment system according to claim 3, wherein the second acquisition unit (1012) includes a first posture sensor for acquiring the thigh posture signal in a motion state.
6. The knee joint disease continuous assessment system according to claim 5, wherein the third acquisition unit (1013) includes a second posture sensor for acquiring the calf posture signal in a motion state.
7. The continuous evaluation system for knee joint diseases of claim 6, wherein the first posture sensor and the second posture sensor are gyroscopes.
8. The knee joint disease continuous evaluation system according to claim 1, wherein the user management terminal (104) includes a receiving unit (1041), a first display unit (1042), an alarm unit (1043), and a second display unit (1044);
the receiving unit (1041) is configured to receive the knee joint movement information, the knee joint damage information, and the user second electronic medical record;
the first display unit (1042) is used for displaying the knee joint movement information and the knee joint damage information on an interface;
the alarm unit (1043) is used for evaluating the knee joint damage degree of the user based on the user basic information and the knee joint damage information and reminding the user;
the second display unit (1044) is configured to display the second electronic medical record of the user on an interface.
9. The knee joint disease continuous assessment system of claim 1, further comprising a buffer module (107) coupled between the knee joint data acquisition module (101) and the processing module (102) for storing the knee joint movement signal, the thigh movement signal, and the calf movement signal.
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| CN112201345A (en) * | 2020-10-10 | 2021-01-08 | 上海奇博自动化科技有限公司 | Method for analyzing cattle diseases based on motion sensor |
| CN112806981B (en) * | 2021-02-05 | 2022-03-25 | 北京大学口腔医学院 | Knee joint health management fitness trousers |
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