SUMMERY OF THE UTILITY MODEL
The embodiment of the disclosure provides an analgesia system based on wearable equipment. The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
In some optional embodiments, a wearable device-based analgesia system comprises:
the wearable intelligent equipment is used for receiving an analgesia instruction of a user and sending the analgesia instruction to the electronic injection pump;
the electronic drug injection pump is used for performing analgesic administration according to the received analgesic instruction;
wherein, wearable smart machine and electron injection pump pass through wireless communication device and link to each other.
Further, a wearable smart device, comprising:
the health acquisition module is used for acquiring physiological information of a user and sending the physiological information to the cloud server and the doctor end APP;
the human-computer interaction module is used for receiving an analgesia instruction and a pain evaluation result of a user and sending the pain evaluation result to the cloud server;
the core processing module is used for sending out first voice prompt information when an analgesia instruction is not received in a preset time length, sending out second voice prompt information when the number of times of the analgesia instruction received in the preset time length exceeds a preset threshold value, and sending out third voice prompt information when the physiological information is abnormal.
And the wireless communication module is used for being in communication connection with the electronic injection pump, the cloud server and the medical end APP.
Further, still include:
and the cloud server is connected with the wearable intelligent device and used for receiving the physiological information and the pain evaluation result and sending the pain grade of the user to the APP at the doctor end.
Further, the cloud server is also used for sending the pre-operation education content to the wearable intelligent device.
Further, still include:
doctor end APP links to each other with high in the clouds server for receive user's painful grade, and send the analgesia scheme that the doctor formulated to electron injection pump and wearable smart machine.
Further, the doctor end APP is also used for receiving the user physiological information, the first prompt information, the second prompt information and the third prompt information sent by the wearable intelligent device.
Further, a health collection module comprising:
the heart rate unit is used for acquiring the heart rate of the user;
the body temperature unit is used for collecting the body temperature of a user;
the blood oxygen unit is used for acquiring the blood oxygen of a user;
and the blood pressure unit is used for collecting the blood pressure of the user.
Further, the human-computer interaction module comprises:
a voice recognition unit for recognizing voice information of a user;
a display unit for displaying pain investigation information and analgesia scheme information;
an input unit for inputting a pain evaluation result.
Further, a wireless communication module comprising:
one or more of a Bluetooth unit, a 4G unit, a 5G unit, a WiFi unit, a Lora Internet of things unit and a ZigBee unit.
Further, the wearable smart device includes a smart band.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
the disclosed embodiment provides an analgesia system based on wearable equipment, includes: the wearable intelligent equipment is used for receiving an analgesia instruction of a user and sending the analgesia instruction to the electronic injection pump; the electronic drug injection pump is used for performing analgesic administration according to the received analgesic instruction; wherein, wearable smart machine and electron injection pump pass through wireless communication device and link to each other. The wearable intelligent device is made of the PCA operation control, the user can utilize the wearable intelligent device to automatically control pain, man-machine interaction can be achieved, operation is intelligent and convenient, and experience of the user is greatly improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention as claimed.
Detailed Description
So that the manner in which the features and elements of the disclosed embodiments can be understood in detail, a more particular description of the disclosed embodiments, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. In the following description of the technology, for purposes of explanation, numerous details are set forth in order to provide a thorough understanding of the disclosed embodiments. However, one or more embodiments may be practiced without these details. In other instances, well-known structures and devices may be shown in simplified form in order to simplify the drawing.
The PCA in the prior art is only a simple operation control, only a starting signal can be triggered by pressing to start the pump end to infuse analgesic drugs, the function is single, automatic control analgesia cannot be actively reminded under the condition that automatic control analgesia is not known, and prompt information cannot be sent when the pressing times are too many. The PCA provided by the embodiment of the disclosure is a wearable intelligent device, and by means of the built-in core processing module, the voice module, the communication module and the like, when the automatic control analgesia is not performed for a long time, the PCA can be operated when pain is reminded by voice to perform the automatic control analgesia, when the analgesia frequency is too many in a preset time, the analgesia frequency is reminded to be too many, and the automatic control analgesia can be continuously performed after a period of time, so that the function of man-machine interaction is realized. The physiological information and the pain assessment result of the user can be collected for a long time, the physiological information and the pain assessment result are stored in the cloud server, the cloud server establishes the relation between the physiological information and the pain degree through a machine learning method, the pain level can be assessed through the physiological information, the physiological information and the pain degree can be sent to the doctor end APP, the doctor can refer to and adjust the pain relieving scheme, the pain relieving education can be conducted before pain relieving through the cloud server and the mobile phone APP, and after pain relieving, postoperative visit is conducted with the doctor in an auxiliary mode. The user can conveniently communicate with a doctor, and the experience degree of the user is greatly improved.
A wearable device-based analgesic system provided by the embodiments of the present application will be described in detail below with reference to fig. 1 to 5.
Referring to fig. 1, the wearable device-based analgesia system comprises:
the wearable intelligent equipment is used for receiving an analgesia instruction of a user and sending the analgesia instruction to the electronic injection pump;
specifically, wearable smart machine includes healthy collection module, a physiological information for gathering user, wherein, healthy collection module includes the rhythm of the heart unit, a rhythm of the heart information for gathering user, including the body temperature unit, a body temperature information for gathering user, including the blood oxygen unit, a blood oxygen information for gathering user, still include the blood pressure unit, a blood pressure information for gathering user, and with above-mentioned rhythm of the heart information, body temperature information, blood oxygen information and blood pressure information send for core processing module, and with above-mentioned rhythm of the heart information through wireless communication device, body temperature information, blood oxygen information and blood pressure information send for cloud server and doctor end APP.
Optionally, the wearable smart device further includes a photoelectric sensor, a geomagnetic sensor, an acceleration sensor, and a gyroscope, and the health acquisition module may acquire physiological information of the user through the sensors. For example, a specific calculation formula can be obtained by acquiring a pulse wave waveform of a wrist part through a photoelectric sensor, analyzing characteristic parameters such as a rising slope and a wave band time of the pulse wave, estimating a blood pressure value, detecting a heart rate of a user through an optical heart rate sensor, detecting a body temperature of the user through a temperature sensor, detecting action information of the user through an acceleration sensor and a geomagnetic sensor, and detecting blood oxygen content of the user through a blood oxygen saturation sensor.
Optionally, send above-mentioned rhythm of the heart information, body temperature information, blood oxygen information and blood pressure information for user side cell-phone APP, the user's of being convenient for real-time query vital sign information oneself, in a possible implementation, the user can wear wearable smart machine for a long time to with cell-phone APP wireless communication connection, look over the vital sign information of oneself in real time.
Specifically, the wearable smart device comprises a human-computer interaction module for receiving analgesia instructions and pain assessment results of a user.
In one possible implementation mode, the voice information of the user is acquired through a built-in microphone, and the voice of the user is recognized through a voice recognition chip. For example, the user sends voice information of 'please perform analgesia', and the wearable intelligent device receives and recognizes the analgesia instruction of the user, so that self-control drug administration is realized.
Optionally, the analgesia system further comprises a key identification unit for identifying key information of a user, and the user can trigger an analgesia instruction by pressing an analgesia key on the bracelet to realize self-control drug delivery.
The pain management system further comprises a display unit for displaying pain investigation information and analgesia scheme information. In one possible implementation, the wearable smart device displays pain investigation information through the display unit, for example, to investigate which of no pain, mild pain, moderate pain, and severe pain the user feels at the time. And the analgesia scheme formulated by the doctor can be displayed, so that the user can conveniently obtain the analgesia scheme in real time.
The pain management device further comprises an input unit for inputting a pain evaluation result, and when the user sees the pain investigation information displayed by the display unit, the pain evaluation result can be input in a key or touch form.
Alternatively, the pain assessment (VAS score) may be automatically performed on the user by voice question answering or online form filling, thereby obtaining the pain level of the user.
Specifically, the wearable smart device further includes a core processing module, and fig. 2 is a schematic structural diagram of a core processing module according to an exemplary embodiment, and as shown in fig. 2, the core processing module includes a health acquisition module interface circuit, a charging circuit, a lithium battery, a network communication interface circuit, a bluetooth communication interface circuit, a voice chip, a micro motor, an LED lamp, and a microprocessor.
Further, the microprocessor may record the number of times of self-control analgesia performed by the user, for example, a microprocessor of the model STM32F427VE may be adopted, the microprocessor has a timer, may record the use duration of the user, and when the analgesia instruction of the user is not received within a preset duration, sends out a first voice prompt message for reminding the user of pain and performing self-control analgesia. Wherein, the preset duration can be set by the user.
In some exemplary scenes, the preset time is 2 hours, the analgesia instruction of the user is not received within 2 hours, the microprocessor sends out first voice prompt information that the intelligent bracelet can be operated to perform automatic control analgesia when the user is painful, and the user is reminded that automatic control analgesia can be performed when the user is painful.
When the number of times of receiving the pain instruction of the user within the preset time exceeds the preset number threshold, sending out second voice prompt information for reminding the user that the threshold is reached, if the analgesia is required to be continued, contacting a doctor, or waiting for a preset interval and then performing self-control analgesia.
In some exemplary scenarios, the preset time period is 5 hours, the threshold of the number of times of operation within 5 hours is set to 4, and when the number of times of self-controlled analgesia performed by the user within 5 hours exceeds 4, a second voice prompt message of "reaching the analgesia threshold, asking the doctor to contact if the analgesia is required to be continued, or performing self-controlled analgesia later" is sent to remind the user that the analgesia threshold has been reached.
Through the arrangement, when the user does not perform automatic control analgesia for a long time, the voice reminds the user to operate the PCA when the user feels pain, the automatic control analgesia is performed, when the number of analgesia times in the preset time of the user is too many, the user is reminded that the number of analgesia times is too many, the automatic control analgesia can be continuously performed after a period of time, the function of human-computer interaction is realized, and the experience degree of the user is greatly improved.
The microprocessor can receive the heart rate information, the blood oxygen information, the body temperature information and the blood pressure information of the user sent by the health acquisition module, compares the heart rate information, the blood oxygen information, the body temperature information and the blood pressure information with a normal vital sign range, and sends out third voice prompt information when the vital sign information of the user is abnormal, so that the abnormal vital signs of the user and family members can be reminded. For example, when the physiological information of the user is abnormal, an alarm message of "physiological information abnormality" is issued.
Optionally, when the vital sign information of the user is abnormal, the third voice prompt information is sent to the doctor-end computer for reminding the doctor that the vital sign of the user is abnormal.
Optionally, the core processing module further includes a prompt alarm unit for sending voice prompt information and alarm information, and when the analgesia instruction of the user is not received within the preset time, the first voice prompt information of "pain can be generated to operate the smart band and perform self-control analgesia" is sent, so as to remind the user of performing self-control analgesia when the user is painful. When the number of times of receiving the pain instruction of the user in the preset time exceeds the preset number threshold, sending out a second voice prompt message of 'reaching the analgesia threshold, asking the doctor to contact if the analgesia is needed to be continued, or automatically controlling the analgesia later', and reminding the user that the analgesia threshold is reached. And when the vital sign information of the user is abnormal, sending out third voice prompt information of abnormal vital sign.
Optionally, when the vital signs of the user are abnormal, the warning unit is prompted to flash an LED indicator light, and a buzzer gives an alarm to remind the user that the vital signs are abnormal.
Optionally, when the vital signs of the user are abnormal, the wearable smart device vibrates to prompt the user that the vital signs are abnormal.
Specifically, the wearable intelligent device further comprises a wireless communication module, optionally, a Bluetooth module of HC-05 type is available, the Bluetooth module of the type is a master-slave integrated serial port module, the default of leaving the factory is a slave, the slave can be switched into a host through an AT instruction, the input voltage is 3.2-6V, the wearable intelligent device can be connected with singlechips of various types, and the effective communication distance in an open environment can reach 10 m.
Alternatively, a WiFi module of MT7601U model may be used, the frequency range of the model is 2.4GHz, the data rate is 150Mbps, the operating voltage is 3.3V, and the outdoor communication distance can reach 100 meters. Data transmission rates are fast but power consumption is large.
Optionally, a ZM516x series ZigBee module can be used, the module of the model is operated by a pure serial port, the design is simple, the sleep power consumption is as low as 100nA, and the ZigBee module is suitable for occasions with low speed and low power consumption.
Optionally, the wireless communication module further includes one or more of a 4G unit, a 5G unit, and a Lora internet of things technology.
In a possible implementation, wearable smart machine links to each other with the electron injection pump through wireless communication module, give the electron injection pump with the instruction of easing pain, the electron injection pump is according to the instruction of easing pain that received and is dosed, wearable smart machine passes through wireless communication module and links to each other with high in the clouds server, with physiological information and painful aassessment result send for the high in the clouds server, also can receive the teaching content before the art that the high in the clouds server sent and come, the user can be before the operation, through wearable smart machine accept the education of easing pain before the art. Wearable smart machine still can link to each other with doctor end APP through wireless communication module, and supplementary doctor carries out the postoperative visit to and give doctor end APP with user's physiological information, first prompt information, second prompt information and third prompt information transmission, the doctor of being convenient for knows user's the condition in real time.
Specifically, wearable smart machine still includes power module, can select for use the lithium cell to supply power for wearable smart machine.
The analgesia system based on the wearable device provided by the embodiment of the disclosure further comprises a cloud server for receiving physiological information and pain evaluation results of a user.
The cloud server can store the user physiological information and the pain assessment result sent by the wearable intelligent device, machine learning is carried out based on a large amount of stored physiological information and the pain assessment result, a pain grade prediction model is built, the physiological information of the user is input into the prediction model, the pain grade of the user can be obtained, the obtained pain grade is sent to the APP at the doctor end by the cloud server, and the analgesia scheme can be adjusted by the doctor in real time. Through this high in the clouds server, can be based on the painful grade of user's physiological information aassessment user, provide reference data for the doctor formulates analgesia scheme.
In one possible implementation, the cloud server uses an analytic hierarchy process to build the prediction model, and fig. 4 is a schematic diagram of building the prediction model.
First, a sample of pain assessment results is divided into a plurality of pain levels, in one possible implementation, level 1, level 2, and level 3, and physiological information is divided into a plurality of physiological characteristics, including blood pressure, temperature, blood oxygen, and heart rate. And then, establishing a hierarchical analysis model, wherein a target layer is a pain grade evaluation result, a criterion layer is physiological characteristics such as blood pressure, temperature, heart rate and blood oxygen, and a decision layer is a pain grade such as grade 1, grade 2 and grade 3.
The parameter setting of the model comprises that the initial learning rate is set to be 0.1 and is gradually reduced along with the training; the down sampling of 0.5 is used, so that the training speed is higher; the maximum depth of the tree is 8; the number of trees is 100; according to the established hierarchical model, the weight of each physiological feature in the criterion layer to the target layer is obtained, the weight vector of each pain grade in the decision layer to the target layer is calculated according to the weight, and the pain grade evaluation result of the target layer is obtained according to the weight vector.
Optionally, deep learning can be performed through a neural network, since in this task, the number of the physiological features is 4, and the data features are one-dimensional, the neural network does not need to be too complex, and the depth does not need to be too deep, a fully-connected neural network is adopted here, the neural network has 5 layers in total, including one input layer, one output layer, and three hidden layers, a specific connection mode is as shown in fig. 5, in parameter setting, each hidden layer adopts a ReLu activation function, the nonlinearity of the network is increased, the initial value of the weight is set to be random initialization, the learning rate is set to be 0.01, and is reduced as the number of cycles increases, the optimizer selects a random gradient descent method SGD, and the loss function selects a cross entropy loss function.
The neural network has good fitting to the nonlinear corresponding relation, can avoid the over-fitting condition, has high precision, inputs the samples divided into a plurality of pain grades into the multi-classification neural network for training, and can judge the pain grade of new physiological information data according to the obtained prediction model.
The analgesia system based on wearable equipment that this disclosed embodiment provided still includes the electron injection pump for analgesia is dosed according to the analgesia instruction of receiving, and the electron injection pump can be connected with wearable smart machine, receives user's analgesia instruction, can also be connected with doctor end APP, receives the analgesia scheme that the doctor made.
Further, wearable device-based analgesia system still includes: doctor end APP, link to each other with the high in the clouds server, a painful grade for receiving the user, the doctor is according to received painful grade, the adjustment analgesia scheme, positive to improving analgesia effect, in addition, doctor end APP still links to each other with the electron injection pump, an electron injection pump is sent to the analgesia scheme for formulating the doctor, link to each other with wearable smart machine, a wearable smart machine is sent to the analgesia scheme, and a user's physiological information who sends to receive wearable smart machine, first prompt information, second prompt information and third prompt information, be convenient for the doctor masters user's physiological information and analgesia information.
Optionally, the wearable smart device in the embodiments of the present disclosure may be a smart band, through which the user detects physiological information in real time and sends an analgesic instruction.
FIG. 3 is a diagram illustrating a human-machine interaction, according to an example embodiment. As shown in fig. 3, the user realizes the automatic control through wearable smart machine and doses, wearable smart machine accessible WIFI, 4G, one or more in the 5G, Lora internet of things links to each other with user side cell-phone APP and medical care end cell-phone APP, when the user does not carry out the automatic control in predetermineeing long time and doses, the information propelling movement that does not carry out the automatic control analgesia to user side cell-phone APP and medical care end cell-phone APP for a long time with the user, user side cell-phone APP accessible pronunciation remind the user to carry out the automatic control analgesia, user accessible cell-phone APP knows the doctor, convey medical care end APP with the service conditions of automatic control analgesia, medical care personnel can fix a position out user's position according to cell-phone APP fast, also can realize the doctor. When the user reaches the preset threshold value at the number of times of carrying out the automatic control analgesia in predetermineeing long time, the information propelling movement that will reach the analgesia threshold value reaches user side cell-phone APP and medical care end cell-phone APP, user side cell-phone APP accessible pronunciation remind the user to reach the analgesia threshold value, if the user still needs the analgesia to administrate, accessible cell-phone APP is one to know medical personnel, realize the doctor and suffer from the disease and communicate, medical care end cell-phone APP also can receive the information that the user reaches the analgesia threshold value, and fix a position out the user position fast through cell-phone APP, look over user. The user can also learn analgesic knowledge through the mobile phone APP. Through the system, doctor-patient communication is greatly facilitated, and user experience is improved.
When the user does not perform automatic control analgesia for a long time, the analgesia system based on the wearable device provided by the embodiment of the disclosure can operate the PCA by voice to remind the user of pain, performs automatic control analgesia, reminds the user of excessive analgesia when the analgesia frequency is excessive within the preset time of the user, and can continue to perform automatic control analgesia after a period of time, thereby realizing the function of human-computer interaction. The physiological information and the pain assessment result of the user can be collected for a long time, the physiological information and the pain assessment result are stored in the cloud server, the cloud server establishes the relation between the physiological information and the pain degree through a machine learning method, the pain level can be assessed through the physiological information, the physiological information and the pain degree can be sent to the doctor end APP, the doctor can refer to and adjust the pain relieving scheme, the pain relieving education can be conducted on the user through the cloud server and the mobile phone APP before pain relieving, and after pain relieving, the user and the doctor are assisted to conduct postoperative visit. The communication between the user and the doctor is facilitated, and the experience degree of the user is greatly improved.
The above description is only for the preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.