阅读说明：本技术 一种基于物联网技术的智能骨密度检测系统 (Intelligent bone mineral density detection system based on Internet of things technology ) 是由 王林彬 潘永德 于 2020-04-30 设计创作，主要内容包括：本申请所请求保护的一种基于物联网技术的智能骨密度检测系统,分为传感层、通信层和应用层。传感层的主要由布置在被监测物体上的传感器骨骼或者是RFID标签,对监测物体实现感知。感知骨骼都附带有通信装置能够与网络层进行沟通,将监测指令或者是骨骼所附带的信息传递出去。物联网的通信层,核心是在监测骨骼上布置的节点,组成多跳型自组织网络。应用层是布置在数据中心,整理分析感知层采集到的信息,实现人机交互能够让检测人员查询信息。算法对感知到的数据分析,判断骨骼现在的健康状况,如果需要保养,能够为检测人员制定保养计划。(The intelligent bone mineral density detection system based on the technology of the Internet of things is divided into a sensing layer, a communication layer and an application layer. The sensing layer is mainly formed by a sensor skeleton or an RFID (radio frequency identification) tag arranged on a monitored object, and the monitored object is sensed. The sensing skeleton is provided with a communication device which can communicate with the network layer and transmit a monitoring instruction or information attached to the skeleton. The core of the communication layer of the Internet of things is nodes arranged on a monitoring skeleton to form a multi-hop type self-organizing network. The application layer is arranged in the data center, and information collected by the perception layer is sorted and analyzed, so that human-computer interaction is realized, and detection personnel can inquire the information. The algorithm analyzes the sensed data to determine the current health condition of the bone, and if maintenance is required, a maintenance plan can be made for the inspector.)

1. The utility model provides an intelligence bone density detecting system based on internet of things, comprises sensing layer, communication layer and application layer, its characterized in that:

the sensing layer comprises an ultrasonic sensor, a label recognizer, an instruction conversion processor and a data preprocessor and is connected with a bone node of the bone density to be detected;

the communication layer takes a communication network as a backbone network, and assists in realizing the transmission of the information of the sensing layer by taking autonomous networking and a public network as supplement;

the application layer adopts laser mode recognition to comprehensively analyze and process the information collected by the sensing layer, and helps detection personnel to make an intelligent analysis result.

2. The intelligent bone mineral density detection system based on the internet of things technology of claim 1, wherein:

the sensing layer comprises an ultrasonic sensor and an instruction conversion circuit, is connected to a bone node of the bone density to be detected, and specifically comprises:

the ultrasonic sensor consists of two ultrasonic sensing heads driven by a power supply and an instruction sensing circuit based on a CPLD, wherein the left side and the right side of a bone node of the bone density to be detected are respectively provided with an ultrasonic transmitting sensing head and an ultrasonic receiving sensing head, and the two ultrasonic transducers are ensured to be positioned on a perpendicular bisector outside the detected part of the bone node, are respectively positioned at the front ports of an excitation circuit and a receiving circuit and are respectively connected with the transmitting sensing head and the receiving sensing head;

the tag recognizer is composed of an RFID tag and a reader, a radio wave with a specific frequency is sent out by the reader, the RFID tag sends information in a chip through energy induced by a coupling coil or the RFID tag actively sends the information, the reader reads the information after decoding, the reader transmits the received information to a communication layer, and the communication layer further sends the information to an application layer to analyze and process the information as required; the instruction conversion processor obtains relevant information of a real instruction by analyzing and processing the digital instruction, and the relevant information comprises an analog instruction input port, a data conversion clock input port, a power-off mode selection, an output energy selection, a multi-state data output pin, a common-mode voltage input port, a reference voltage input port and an internal reference source output port;

the data preprocessor is used for processing the data converted by the instruction conversion processor, and specifically comprises instruction noise processing, frequency band analysis, accuracy optimization and index calculation.

3. The intelligent bone mineral density detection system based on the internet of things technology of claim 1, wherein:

the communication layer uses a communication network as a backbone network to assist in realizing the transmission of the information of the sensing layer by using an autonomous networking and a public network as a supplement, and specifically comprises the following steps:

the device comprises a power supply module, a processor, a storage module and a communication module;

the processor is responsible for controlling the control operation of all the skeleton nodes, and the skeleton motions of other modules are communicated with the processor module to complete tasks;

the storage module has the functions of temporarily storing the acquired data information, also can store data transmitted by other skeleton nodes, and determines the type of the adopted processor and the memory according to the requirement of the acquired data of the skeleton nodes;

the CPLD performs corresponding data analysis after receiving a command initiated by the processor, then performs corresponding operation, controls the power supply to rotate to a specified position if the command is a power supply control command, and then sends data to the processor to feed back the position of the sensing head to be ready; if the command is a gain adjustment command, the output voltage is changed by changing the value of the register, so that gain control is realized; if the command is a data acquisition command, firstly generating a high-voltage control pulse, then acquiring data, controlling the SRAM to store the buffered data, then reading out the data in the SRAM, synchronizing and then sending the data to the processor;

the power module is used for providing energy for the processor module and the communication module, the power module controls the processor module through the processor, and induction power supply or battery power supply is usually adopted;

the communication module is used for short-distance wireless communication with other sensor nodes and mainly used for sending acquired data and control commands issued by the processor.

4. The intelligent bone mineral density detection system based on the internet of things technology of claim 1, wherein:

the application layer adopts laser mode identification to carry out comprehensive analysis and processing to the information that the sensing layer gathered, and the help detection personnel make intelligent analysis result, specifically include:

after receiving the data of the sensing layer transmitted by the network layer, the application layer completes the contents of data receiving, warehousing, visual display and the like through background software, deeply excavates the data, and then realizes the functions of intelligent analysis, early warning, alarming and the like of the system on the monitored contents through an expert model;

the software can also be connected with other platforms to realize the sharing and interconnection among system data, and the functions realized by the application layer comprise: monitoring bone state, inquiring data, analyzing early warning, displaying visual information, identifying bone, and checking to-be-detected field state;

the method comprises the steps of monitoring the bone by using a laser mode identification mode when monitoring the bone state of an application layer, specifically, emitting laser beams by using a cross light source, dividing the laser beams emitted by the cross light source into comparison light and experimental light, transmitting the comparison light and the experimental light along different paths, combining the experimental light and the comparison light, diffracting the comparison light and the experimental light, recording light intensity information of diffraction stripes generated after the comparison light and the experimental light pass through an imaging system, calculating the phase information difference of the comparison light corresponding to the situation that the bone is not collected and the comparison light corresponding to the situation that the bone sample is placed according to the recorded light intensity information, calculating the refractive index difference of the bone sample according to the phase information difference, and obtaining various bone contents of the bone sample according to the refractive index difference;

the application layer analyzes the data of the state monitoring, the established state evaluation system is used for evaluating the monitored data, if the skeleton is in a normal state, the monitoring is continued, if the skeleton is in an abnormal detection state, the skeleton is required to be maintained, the state of the skeleton is evaluated to determine whether the skeleton is temporarily maintained or maintained for a long time, and then a maintenance plan is finally made and provided for a detector to refer to in combination with the arrangement of maintenance time.

Technical Field

The application belongs to the field of information technology detection, and particularly relates to an intelligent bone mineral density detection system based on the technology of the Internet of things.

Background

The development of the internet of things technology is regarded as a new industrial revolution, but the related technologies do not achieve a unified standard at present. Various developed countries in the world are actively developing and deploying relevant strategies to preempt the first opportunity in development. The Internet of things construction in China has been promoted to the national strategic level, and related industries enter the rapid development period.

The internet of things (the internet technologies) is a huge network formed by combining information sensing skeletons such as Radio Frequency Identification (RFID), infrared sensors, global positioning systems, laser scanners and the like with the internet, and any article is connected with the internet to perform information exchange and communication according to an agreed protocol, so that a network for intelligent identification, positioning, tracking, monitoring and management is realized, information transmission and exchange between people and articles and between articles is realized, and intelligent decision and management is finally realized. However, most of the internet of things systems used in the medical industry have no visual objects, so that the internet of things systems are not widely applied to enterprises and cannot really exert the utility and value of the internet of things; correspondingly, the domestic Internet of things detection control system cannot automatically detect, control and alarm the client condition and stays in a simple mode of video monitoring; and foreign products are not suitable for the needs of enterprises in China due to the problems of environment and cost, and particularly, a detection scheme in the form of an internet of things is lacked in the prior art for detecting the bone density, so that the real-time monitoring of the bone quality of the body among patients is facilitated.

There are many methods for detecting bone density, and the principle is different, and generally divided into a ray method and an ultrasonic method, in order to more effectively obtain bone density information of a patient, a doctor usually selects different methods for bone density detection according to different conditions of the patient. Therefore, the research of the cheap and portable bone density detection bone is very necessary and far-reaching for the prevention and treatment of osteoporosis.

Disclosure of Invention

To the problem that lacks information-based integrated detection in the above-mentioned medical bone density detection field, this application claims an intelligent bone density detecting system based on internet of things, it comprises sensing layer, communication layer and application layer, its characterized in that:

the sensing layer comprises an ultrasonic sensor, a label recognizer, an instruction conversion processor and a data preprocessor and is connected with a bone node of the bone density to be detected;

the communication layer takes a communication network as a backbone network, and assists in realizing the transmission of the information of the sensing layer by taking autonomous networking and a public network as supplement;

the application layer adopts laser mode recognition to comprehensively analyze and process the information collected by the sensing layer, and helps detection personnel to make an intelligent analysis result.

The intelligent bone mineral density detection system based on the technology of the Internet of things is divided into a sensing layer, a communication layer and an application layer. The sensing layer is mainly formed by a sensor skeleton or an RFID (radio frequency identification) tag arranged on a monitored object, and the monitored object is sensed. The sensing skeleton is provided with a communication device which can communicate with the network layer and transmit a monitoring instruction or information attached to the skeleton. The core of the communication layer of the Internet of things is nodes arranged on a monitoring skeleton to form a multi-hop type self-organizing network. The application layer is arranged in the data center, and information collected by the perception layer is sorted and analyzed, so that human-computer interaction is realized, and detection personnel can inquire the information. The algorithm analyzes the sensed data, judges the current health condition of the bone, and makes a maintenance plan for the detection personnel if maintenance is needed.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.

Fig. 1 shows a structural module diagram of an intelligent bone density detection system based on internet of things technology according to the invention.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

Referring to fig. 1, a structural module diagram of an intelligent bone density detection system based on internet of things technology according to the invention is shown;

the invention discloses an intelligent bone mineral density detection system based on the technology of the Internet of things, which consists of a sensing layer, a communication layer and an application layer, and is characterized in that:

the sensing layer comprises an ultrasonic sensor, a label recognizer, an instruction conversion processor and a data preprocessor and is connected with a bone node of the bone density to be detected;

the communication layer takes a communication network as a backbone network, and assists in realizing the transmission of the information of the sensing layer by taking autonomous networking and a public network as supplement;

the application layer adopts laser mode recognition to comprehensively analyze and process the information collected by the sensing layer, and helps detection personnel to make an intelligent analysis result.

Preferably, the sensing layer includes an ultrasonic sensor and a command conversion circuit, and is connected to a bone node of the bone density to be detected, and specifically includes:

the ultrasonic sensor consists of two ultrasonic sensing heads driven by a power supply and an instruction sensing circuit based on a CPLD, wherein the left side and the right side of a bone node of the bone density to be detected are respectively provided with an ultrasonic transmitting sensing head and an ultrasonic receiving sensing head, and the two ultrasonic transducers are ensured to be positioned on a perpendicular bisector outside the detected part of the bone node, are respectively positioned at the front ports of an excitation circuit and a receiving circuit and are respectively connected with the transmitting sensing head and the receiving sensing head;

the tag recognizer is composed of an RFID tag and a reader, a radio wave with a specific frequency is sent out by the reader, the RFID tag sends information in a chip through energy induced by a coupling coil or the RFID tag actively sends the information, the reader reads the information after decoding, the reader transmits the received information to a communication layer, and the communication layer further sends the information to an application layer to analyze and process the information as required;

the instruction conversion processor obtains relevant information of a real instruction by analyzing and processing the digital instruction, and the relevant information comprises an analog instruction input port, a data conversion clock input port, a power-off mode selection, an output energy selection, a multi-state data output pin, a common-mode voltage input port, a reference voltage input port and an internal reference source output port;

the data preprocessor is used for processing the data converted by the instruction conversion processor, and specifically comprises instruction noise processing frequency band analysis, accuracy optimization and index calculation.

In the instruction noise processing process, denoising the denoised signal by a four-point and three-time algorithm on the basis of DNR denoising; the frequency band analysis is that after the system collects ultrasonic signals, Fourier transform is needed to be carried out on the ultrasonic signals, and different simulation functions are selected for the intercepted signals subjected to noise reduction; the accuracy optimization is to adopt multiple measurement to take an average value; the index calculation is that the least square method is used for carrying out linear fitting on the ultrasonic attenuation between 0.2 MHz and 0.6MHz, and therefore the ultrasonic attenuation BUA is obtained.

The analog instruction input port of the instruction conversion processor adopts differential input, and pins IN + and IN-are respectively connected to two sides of an input instruction; when single-port input is adopted, IN + is connected with an input instruction, and IN-is connected with a COM pin. The system filters out the DC component in the command by using a differential input mode.

At the input port of the data conversion clock of the instruction conversion processor, the input clock is very important for the accuracy of the conversion result, and the stability of the clock should be ensured. The system uses the CPLD to output pulses at 100MHz, 50% duty cycle, as the sampled CLK.

The instruction conversion processor selects a power-off mode, and is set to be a power-off mode when receiving a high level and a low level, and the power-off mode is a normal mode. The system connects the pin directly to ground, allowing a straight skeletal motion in the normal mode. And selecting output energy. When the high level is connected, the output is not enabled, and when the low level is connected, the output is enabled. This pin is also controlled by the CPLD. A reference voltage input port. The input voltage determines the full scale size of the slice transition.

The chip internal reference source of the instruction conversion processor is provided with a 2.048V output port; may be connected to VCOM through a resistor as the chip reference voltage.

Preferably, the communication layer uses a communication network as a backbone network, and assists in implementing information transmission of the sensing layer by using an autonomous networking and a public network as a supplement, and specifically includes:

the device comprises a power supply module, a processor, a storage module and a communication module;

the processor is responsible for controlling the control operation of all the skeleton nodes, and the skeleton motions of other modules are communicated with the processor module to complete tasks;

the storage module has the functions of temporarily storing the acquired data information, also can store data transmitted by other skeleton nodes, and determines the type of the adopted processor and the memory according to the requirement of the acquired data of the skeleton nodes;

the CPLD performs corresponding data analysis after receiving a command initiated by the processor, then performs corresponding operation, controls the power supply to rotate to a specified position if the command is a power supply control command, and then sends data to the processor to feed back the position of the sensing head to be ready; if the command is a gain adjustment command, the output voltage is changed by changing the value of the register, so that gain control is realized; if the command is a data acquisition command, firstly generating a high-voltage control pulse, then acquiring data, controlling the SRAM to store the buffered data, then reading out the data in the SRAM, synchronizing and then sending the data to the processor;

the power module is used for providing energy for the processor module and the communication module, the power module controls the processor module through the processor, and induction power supply or battery power supply is usually adopted;

the communication module is used for short-distance wireless communication with other sensor nodes and mainly used for sending acquired data and control commands issued by the processor.

Preferably, the application layer adopts laser mode recognition to carry out comprehensive analysis processing to the information that the sensing layer gathered, helps the detection personnel to make intelligent analysis result, specifically includes:

after receiving the data of the sensing layer transmitted by the network layer, the application layer completes the contents of data receiving, warehousing, visual display and the like through background software, deeply excavates the data, and then realizes the functions of intelligent analysis, early warning, alarming and the like of the system on the monitored contents through an expert model;

the software can also be connected with other platforms to realize the sharing and interconnection among system data, and the functions realized by the application layer comprise: monitoring bone state, inquiring data, analyzing early warning, displaying visual information, identifying bone, and checking to-be-detected field state;

when the bone state is monitored, the temperature of the bone which is sensitive to the temperature is monitored by the temperature sensor arranged on the bone; a position pressure sensor is arranged on a position with important position, the pressure condition of the position is monitored in real time, and when the pressure of the position exceeds an early warning value, automatic alarm is realized; and installing a comprehensive monitoring node, monitoring the conditions of skeletal motion biological pulse, skeletal muscle content and the like, and realizing the mastering of the skeletal motion state condition.

When data is inquired, the bone information can be inquired through the computer, and the real-time state information of the monitored bone can be inquired; the historical bone data can be inquired, the historical data can be displayed in the forms of a data list, a daily curve, a monthly curve, an annual curve and the like, and excel table output is supported.

During early warning analysis, monitoring skeleton operation parameters, tracking trend changes, discovering orthopedic disease hidden dangers, sending early warning signals in time, prompting detection personnel to maintain timely, and avoiding further expansion of accidents.

When the visual information is displayed, the real-time visual display of the data is realized; bone visualization, namely embedding a two-dimensional map/a three-dimensional map/a plan view, and displaying the bone position and the sensor arrangement position in a superposition manner.

When the skeleton is identified, the RFID identification is installed on the skeleton of the distribution network site, and when a detection person approaches to the vicinity of the skeleton, the skeleton including the skeleton type, the skeletal muscle type and the skeletal part can be identified through the handheld terminal.

When the on-site state to be detected is checked, the RFID identification is scanned through the handheld terminal, the skeleton possibly suffering from orthopedic diseases is confirmed, and the mobile terminal is connected with the data center, so that the functions of checking the running state information, the motion environment information, the historical maintenance record and the skeleton orthopedic disease information of the skeleton can be realized. Uploading information of the on-site off-line test to a data center through a mobile terminal; the bone of the data center is utilized to realize the analysis and diagnosis of orthopedic diseases; after on-site maintenance is completed, the maintenance process and the test data are recorded, a maintenance report is generated and stored in the database so as to be convenient for maintenance and lookup, a sample can be provided for the data center, data are continuously enriched, and a basis is provided for more accurately judging the type of the bone orthopedic diseases in the future.

The method comprises the steps of monitoring the bone by using a laser mode identification mode when monitoring the bone state of an application layer, specifically, emitting laser beams by using a cross light source, dividing the laser beams emitted by the cross light source into comparison light and experimental light, transmitting the comparison light and the experimental light along different paths, combining the experimental light and the comparison light, diffracting the comparison light and the experimental light, recording light intensity information of diffraction stripes generated after the comparison light and the experimental light pass through an imaging system, calculating the phase information difference of the comparison light corresponding to the situation that the bone is not collected and the comparison light corresponding to the situation that the bone sample is placed according to the recorded light intensity information, calculating the refractive index difference of the bone sample according to the phase information difference, and obtaining various bone contents of the bone sample according to the refractive index difference;

the application layer analyzes the data of the state monitoring, the established state evaluation system is used for evaluating the monitored data, if the skeleton is in a normal state, the monitoring is continued, if the skeleton is in an abnormal detection state, the skeleton is required to be maintained, the state of the skeleton is evaluated to determine whether the skeleton is temporarily maintained or maintained for a long time, and then a maintenance plan is finally made and provided for a detector to refer to in combination with the arrangement of maintenance time.

The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.