CN112754479A - Method and equipment for detecting blood glucose concentration - Google Patents
Method and equipment for detecting blood glucose concentration Download PDFInfo
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Abstract
The application discloses a method and equipment for detecting blood glucose concentration. The method comprises the steps of receiving a blood glucose concentration detection request comprising information of a to-be-detected object; determining a target Raman spectrum light source corresponding to the information of the object to be detected according to the object type in the information of the object to be detected and a stored Raman spectrum light source library, and triggering the target Raman spectrum light source in a Raman spectrum light source assembly to send out an optical signal; collecting light signals scattered by the skin of the external auditory canal of the object to be detected within a preset time period, and converting the collected light signals into corresponding Raman spectrum data; performing convolution characteristic analysis on the Raman spectrum data by adopting a trained real-time analysis model to obtain the blood glucose concentration of the object to be detected in a preset time period; and displaying the blood glucose concentration in a preset time period. The method improves the accuracy of blood glucose concentration detection.
Description
Technical Field
The application relates to the technical field of medical detection, biomedical detection and health monitoring, in particular to a method and equipment for detecting blood glucose concentration.
Background
Diabetes is a metabolic disorder caused by genetic and environmental factors, resulting in insulin insensitivity, insulin deficiency and impaired biological function. Due to the high morbidity of the disease, and the associated disability and mortality, the disease has become a vital health problem worldwide. According to the estimation, 1.139 million diabetics exist in China, and the current medical solution has not always developed a medicine or a method capable of curing diabetes, and the diabetics mainly realize the control of the blood sugar concentration through frequent monitoring of the blood sugar level and corresponding oral hypoglycemic medicines and insulin injection. Blood glucose concentration determination is currently the most important basis for diagnosing diabetes.
In recent years, noninvasive detection methods for blood glucose concentration are actively studied at home and abroad, and the noninvasive detection methods comprise blood substitutes, micro-osmosis, optical sensors and spectroscopy. The simplest method is to measure the glucose concentration in a blood substitute (saliva, sweat, urine), but studies have shown that the measured glucose concentration has no significant correlation with the blood glucose concentration.
Another method is to measure the correlation between the concentration of interstitial fluid and blood glucose concentration by mild skin corrosion, removing epidermal barrier and continuously pumping with negative pressure, thereby obtaining the blood glucose concentration, but the method is still a destructive detection method.
Therefore, there is a need for a non-destructive blood glucose concentration detection method for accurately detecting blood glucose concentration of a patient.
Disclosure of Invention
The embodiment of the application provides a method and equipment for detecting blood glucose concentration, which solve the problems in the prior art and improve the accuracy of blood glucose concentration detection.
In a first aspect, a method for detecting blood glucose concentration is provided, which may include:
receiving a blood glucose concentration detection request aiming at a to-be-detected object, wherein the blood glucose concentration detection request comprises information of the to-be-detected object;
determining a target Raman spectrum light source corresponding to the information of the object to be detected according to the object type in the information of the object to be detected and a stored Raman spectrum light source library, and triggering the target Raman spectrum light source in a Raman spectrum light source assembly to send out a light signal; the Raman spectrum light source component comprises Raman spectrum light sources with different wavelengths; the Raman spectrum light source library comprises corresponding relations between different object types and corresponding Raman spectrum light sources;
collecting light signals scattered by the skin of the external auditory canal of the object to be detected within a preset time period, and converting the collected light signals into corresponding Raman spectrum data;
performing Raman spectrum characteristic analysis on the Raman spectrum data by adopting a trained real-time analysis model to obtain the blood glucose concentration of the object to be detected in the preset time period; the real-time analysis model is obtained by training network parameters of the deep convolutional neural network according to Raman spectrum data at historical moments and real blood glucose concentration at corresponding moments;
and displaying the blood glucose concentration in the preset time period.
In an optional implementation, after obtaining the blood glucose concentration of the subject to be detected within the preset time period, the method further includes:
and storing the blood glucose concentration in the preset time period.
In an optional implementation, the method further comprises:
receiving a statistical analysis instruction of the blood glucose concentration of the object to be detected in a historical preset time period;
acquiring the blood glucose concentration of the object to be detected in the memory within a historical preset time period;
performing statistical analysis on the blood glucose concentration within the historical preset time period by adopting a preset statistical analysis algorithm to obtain the blood glucose concentration information of the object to be detected within the historical preset time period, wherein the blood glucose concentration information comprises the variation information of the blood glucose concentration within the historical preset time period, the maximum blood glucose concentration value and the corresponding moment, and the minimum blood glucose concentration value and the corresponding moment;
and displaying the blood glucose concentration information in the historical preset time period.
In an optional implementation, receiving a statistical analysis instruction of the blood glucose concentration of the subject to be detected in a historical preset time period includes:
periodically receiving a statistical analysis instruction of the blood glucose concentration of the object to be detected in a historical preset time period.
In an alternative implementation, converting the collected optical signals into corresponding raman spectral data comprises:
carrying out photoelectric conversion on the collected optical signals to obtain corresponding electric signals;
the electrical signals are converted to corresponding raman spectral data by an analog-to-digital converter.
In an optional implementation, the method further comprises:
sending the blood glucose concentration or the blood glucose concentration information of the object to be detected to a preset management platform;
receiving diagnosis analysis information sent by the preset management platform according to the blood glucose concentration or the blood glucose concentration information;
and displaying the diagnostic analysis information.
In a second aspect, there is provided a device for detecting blood glucose concentration, which may include: the Raman spectrum analysis system comprises a main control chip, a Raman spectrum light source assembly, a memory, a Raman spectrum signal acquisition and processing module, an analysis module and a power supply;
the main control chip is used for receiving a blood glucose concentration detection request aiming at an object to be detected, and the blood glucose concentration detection request comprises information of the object to be detected;
determining a target Raman spectrum light source corresponding to the information of the object to be detected according to the object type in the information of the object to be detected and the Raman spectrum light source library stored in the memory, and triggering the target Raman spectrum light source in the Raman spectrum light source assembly; the Raman spectrum light source library comprises corresponding relations between different object types and corresponding Raman spectrum light sources;
the Raman spectrum light source assembly is used for controlling the target Raman spectrum light source to emit light signals based on the triggering operation of the main control chip on the target Raman spectrum light source; the Raman spectrum light source component comprises Raman spectrum light sources with different wavelengths; the Raman spectrum light source library comprises corresponding relations between different object types and corresponding Raman spectrum light sources;
the Raman spectrum signal acquisition and processing module is used for acquiring the light signal scattered by the skin of the external auditory canal of the object to be detected within a preset time period and converting the acquired light signal into corresponding Raman spectrum data;
the analysis module is used for performing Raman spectrum characteristic analysis on the Raman spectrum data by adopting a trained real-time analysis model to obtain the blood glucose concentration of the object to be detected in the preset time period; the real-time analysis model is obtained by training a deep convolution neural network according to Raman spectrum data at historical moments and real blood glucose concentration at corresponding moments;
the power supply is used for supplying power to the main control chip, the Raman spectrum light source assembly, the Raman spectrum signal acquisition and processing module and the intelligent analysis module.
In an alternative implementation, the apparatus further comprises a display module;
the analysis module is further used for receiving a statistical analysis instruction of the blood glucose concentration of the object to be detected in a historical preset time period;
acquiring the blood glucose concentration of the object to be detected in the memory within a historical preset time period; the preset time period is less than the historical preset time period;
performing statistical analysis on the blood glucose concentration within the historical preset time period by adopting a preset statistical analysis algorithm to obtain blood glucose concentration information of the object to be detected within the historical preset time period, wherein the blood glucose concentration information comprises variation information of the blood glucose concentration within the historical preset time period, a maximum blood glucose concentration value and corresponding time, and a minimum blood glucose concentration value and corresponding time;
and the display module is used for displaying the blood glucose concentration information in the historical preset time period.
In an optional implementation, the analysis module is specifically configured to periodically receive a statistical analysis instruction for the blood glucose concentration of the subject to be detected within a historical preset time period.
In an optional implementation, the raman spectrum signal collecting and processing module is specifically configured to perform photoelectric conversion on a collected optical signal to obtain a corresponding electrical signal;
and converting the electrical signals into corresponding raman spectral data by an analog-to-digital converter.
In an alternative implementation, the device further comprises a communication module;
the communication module is used for sending the blood glucose concentration or the blood glucose concentration information of the object to be detected to a preset management platform;
receiving diagnosis analysis information sent by the preset management platform according to the blood glucose concentration or the blood glucose concentration information;
the display module is further used for displaying the diagnosis and analysis information.
In a third aspect, an electronic device is provided, which includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
a processor adapted to perform the method steps of any of the above first aspects when executing a program stored in the memory.
In a fourth aspect, a computer-readable storage medium is provided, having stored therein a computer program which, when executed by a processor, performs the method steps of any of the above first aspects.
The method for detecting the blood glucose concentration comprises the steps of receiving a blood glucose concentration detection request aiming at a to-be-detected object, wherein the blood glucose concentration detection request comprises information of the to-be-detected object; determining a target Raman spectrum light source corresponding to the information of the object to be detected according to the object type in the information of the object to be detected and a stored Raman spectrum light source library, and triggering the target Raman spectrum light source in a Raman spectrum light source assembly to send out an optical signal; the Raman spectrum light source component comprises Raman spectrum light sources with different wavelengths; the Raman spectrum light source library comprises corresponding relations between different object types and corresponding Raman spectrum light sources; collecting light signals scattered by the skin of the external auditory canal of the object to be detected within a preset time period, and converting the collected light signals into corresponding Raman spectrum data; performing convolution characteristic analysis on the Raman spectrum data by adopting a trained real-time analysis model to obtain the blood glucose concentration of the object to be detected in a preset time period; the real-time analysis model is obtained by training network parameters of the deep convolutional neural network according to Raman spectrum data at historical moments and real blood glucose concentration at corresponding moments; and displaying the blood glucose concentration in a preset time period. The method carries out blood sugar concentration analysis by collecting the light signals scattered by the skin of the external auditory canal with stable temperature and humidity and abundant blood vessels, thereby improving the accuracy of blood sugar concentration detection.
Drawings
Fig. 1 is a schematic structural diagram of a blood glucose concentration detecting apparatus according to an embodiment of the present invention;
FIG. 2 is a diagram of a system architecture for an application of a blood glucose concentration measuring device according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a method for detecting blood glucose concentration according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a device for detecting blood glucose concentration according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present application without any creative effort belong to the protection scope of the present application.
For convenience of understanding, terms referred to in the embodiments of the present invention are explained below:
scattering (scattering) refers to the phenomenon of light rays being emitted all around due to the inhomogeneity of the propagation medium.
Raman scattering refers to a phenomenon in which the wavelength of light changes before and after scattering, that is, a phenomenon in which the frequency of light waves changes after scattering.
Early few pilot studies found that blood glucose can directly stimulate the outer ear canal , the wax and sebaceous glands. The secretion of the external auditory canal of a healthy person does not contain glucose or has a very small content, while the content of the glucose in the subcutaneous cells and earwax of the external auditory canal of a diabetic patient can reach 0.1 microgram. Moreover, this pathological response occurs earlier than the impaired glucose tolerance and insulin resistance of the recognized early stage "recessive diabetes". This pathological change can be detected by means of raman spectroscopy. The changes of the characteristic peak position, intensity and line width of the Raman spectrum are consistent with the changes of blood sugar. And because the signal acquisition part of the wearable glucometer is an external auditory canal, the unique human anatomy structure determines that the temperature and the humidity of the part are stable, the subcutaneous tissues are few, the blood vessels are rich, and the influence of the external environment change is small, so that the part is selected to carry out noninvasive and rapid quantitative blood glucose detection and analysis by utilizing Raman spectrum, the accuracy of blood glucose concentration detection is improved, the wearable glucometer can also be used for identifying diabetes risk groups in early stage, the blood glucose control of diabetic patients, frequent blood glucose monitoring of gestational diabetes and the like, and the curative effect evaluation of antidiabetic drugs and the like, thereby providing a possible, accurate, reliable, rapid and noninvasive detection means.
The method for detecting blood glucose concentration provided by the embodiment of the present invention can be applied to the blood glucose concentration detecting apparatus shown in fig. 1, and the apparatus may include a main control chip 110, a raman spectrum light source assembly 120, a memory 130, a raman spectrum signal collecting and processing module 140, an analysis module 150, and a power supply 160. The device can be applied in a terminal.
The main control chip 110 is configured to receive a blood glucose concentration detection request of an object to be detected, and trigger the raman spectrum light source assembly based on the blood glucose concentration detection request. The main control chip may be a single chip, a processor, such as a Digital Signal Processor (DSP) processor, a Field-Programmable Gate Array (FPGA) processor, and the like.
A raman spectroscopy light source module 120 for emitting a raman spectroscopic light signal.
The raman spectrum light source assembly comprises raman spectrum light sources with different wavelengths, for example, the raman spectrum light sources comprise laser light sources with 785nm, 850nm, 980nm and 1064nm wavelengths, the raman spectrum light sources with different wavelengths can have certain selectivity according to different crowds, and can be specifically determined according to analysis and research of a large amount of clinical experiment data, and the selected wavelengths have the characteristics of high penetration rate to skin tissues of the external auditory canal, sensitivity to blood glucose concentration conversion and the like.
The raman spectrum signal collecting and processing module 140 is configured to collect an optical signal scattered at an external auditory canal of the object to be detected within a preset time period, and convert the collected optical signal into a corresponding digital signal, that is, raman spectrum data at the external auditory canal;
the raman spectrum signal collecting and processing module 140 may include an optical signal collecting module, an optical signal converting module, and an electrical signal converting module.
And the optical signal acquisition module is used for acquiring an optical signal scattered at the skin of the auditory canal, namely acquiring a Raman spectrum. The optical signal acquisition module can be an optical probe, a single-mode probe or a multi-mode probe.
The optical signal conversion module is used for converting the acquired raman spectrum signal into an electrical signal through a photoelectric conversion device such as a photodiode PD array, a photodiode InGaAs array, a photodiode array CMOS or a Charge Coupled Device (CCD) array.
And the electric signal conversion module is used for converting the electric signal into a data signal through the analog-to-digital converter.
The main control chip 110 is further configured to receive raman spectrum data obtained by the raman spectrum signal collecting and processing module, and transmit the raman spectrum data to the analysis module.
The analysis module 150 is configured to perform raman spectrum feature analysis on the raman spectrum data by using the trained real-time analysis model to obtain a blood glucose concentration of the object to be detected within a preset time period. The real-time analysis model is obtained by training the deep convolutional neural network according to the Raman spectrum data at the historical moment and the real blood glucose concentration at the corresponding moment, namely the real-time analysis model is the deep convolutional neural network containing the preset number of convolutional layers.
The memory 130 is configured to store the blood glucose concentration obtained by the analysis module and store blood glucose concentration information counted in the historical time period, where the blood glucose concentration information may include change information of the blood glucose concentration in the historical time period, a maximum blood glucose concentration value and a corresponding time, and a minimum blood glucose concentration value and a corresponding time. The Memory is a data storage device such as a Secure Digital Memory Card (SD) Card and a hard disk.
Optionally, in order to make the subject to be detected know the blood glucose concentration of the subject, the device may further include a display module 170;
and the display module 170 is configured to display the blood glucose concentration obtained by the analysis module or the blood glucose concentration information in the historical time period. Such as a display screen of a terminal, such as a mobile phone or a personal computer.
Optionally, in order to perform health management on the object to be detected, the apparatus may be combined with a health management platform to perform health management on the object to be detected, and thus, the apparatus may further include a communication module 180;
and the communication module 180 is used for sending the blood glucose concentration obtained by the analysis module or the blood glucose concentration information of the historical time period stored by the memory to the health management platform so as to realize early warning and diagnosis of the blood glucose concentration. Such as network antenna, bluetooth, etc.
And the power supply 160 is used for supplying power to the main control chip 110, the raman spectrum light source assembly 120, the memory 130, the raman spectrum signal acquisition and processing module 140, the analysis module 150, the display module 170 and the communication module 180.
The power supply is a direct current power supply, and can be an electric energy supply device which can stably supply power for a long time, such as a switching power supply, a power adapter, a lithium battery, a carbon-zinc battery, a mercury battery and the like.
It can be understood that the blood glucose concentration detection device provided by the application can be applied to a system consisting of a server and a terminal.
As shown in fig. 2, the blood glucose concentration detection device applied in a system composed of a server and a terminal may include a main control chip 110, a raman spectrum light source assembly 120, a raman spectrum signal acquisition and processing module 140, a display module 170, and a communication module 180; the server may have built in memory 130, an analysis module 150 and another communication module 180. The terminal is in communication connection with the server through the communication module.
The server can be an application server or a cloud server; the Terminal may be a User Equipment (UE) such as a Mobile phone, a smart phone, a laptop, a digital broadcast receiver, a Personal Digital Assistant (PDA), a tablet computer (PAD), a handheld device, a vehicle-mounted device, a wearable device, a computing device or other processing device connected to a wireless modem, a Mobile Station (MS), a Mobile Terminal (Mobile Terminal), etc.
The following description will be made in detail taking an example in which the blood glucose level detecting device is built in a terminal.
The preferred embodiments of the present application will be described below with reference to the accompanying drawings of the specification, it being understood that the preferred embodiments described herein are merely for illustrating and explaining the present invention and are not intended to limit the present invention, and that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
Fig. 3 is a schematic flow chart of a method for detecting blood glucose concentration according to an embodiment of the present invention. As shown in fig. 3, the method may include:
step 310, receiving a blood glucose concentration detection request for a to-be-detected object.
The blood glucose concentration detection equipment receives a blood glucose concentration detection request triggered by a to-be-detected object, wherein the blood glucose concentration detection request comprises information of the to-be-detected object, such as information of gender, age, residence and the like.
And step 320, determining a target Raman spectrum light source corresponding to the information of the object to be detected according to the object type in the information of the object to be detected and the stored Raman spectrum light source library, and triggering the target Raman spectrum light source in the Raman spectrum light source assembly to send out a light signal.
The Raman spectrum light source component comprises Raman spectrum light sources with different wavelengths, such as 785nm, 850nm, 980nm, 1064nm and the like.
Before this step is performed, in order to measure the blood glucose concentration at the external auditory canal, it is necessary to select a raman spectrum light source having characteristics such as high penetration rate to the skin tissue of the external auditory canal and sensitivity to blood glucose concentration change in blood vessels of the external auditory canal, that is, to select the wavelength of the raman spectrum light source.
The object category may be classified according to object information such as age, living area, and sex. For example, by age: the object categories may be elderly, children and adults; dividing according to living areas: in the south of the river and in africa.
Moreover, different object types have different skin thicknesses, elasticity degrees, colors and the like, so that different object types need to select a specific raman spectrum light source to ensure the detection accuracy.
Therefore, specific raman spectrum light sources corresponding to different object types can be obtained according to clinical tests, and a raman spectrum light source library is created, namely the raman spectrum light source library comprises corresponding relations between the different object types and the corresponding raman spectrum light sources.
Therefore, the object type of the object to be detected is determined according to the information of the object to be detected in the blood glucose concentration detection request; searching a Raman spectrum light source library based on the object type to obtain a target Raman spectrum light source corresponding to the object type;
and triggering a target Raman spectrum light source in the Raman spectrum light source assembly to emit a light signal so as to irradiate the external auditory canal of the object to be detected.
Step 330, collecting the light signal Raman-scattered at the skin of the external auditory canal of the object to be detected within a preset time period, and converting the collected light signal into corresponding Raman spectrum data.
Collecting scattered light signals caused by uneven blood cells at the skin of the external auditory canal of a subject to be detected in a preset time period,
carrying out photoelectric conversion on the collected optical signals to obtain corresponding electric signals;
optionally, in order to improve the detection accuracy, the electrical signal obtained by the photoelectric conversion may be amplified and filtered, and then the processed electrical signal is sent to the analog-to-digital converter, so that the electrical signal is converted into corresponding raman spectrum data by the analog-to-digital converter.
And 340, performing Raman spectrum characteristic analysis on the Raman spectrum data by adopting the trained real-time analysis model to obtain the blood glucose concentration of the object to be detected in a preset time period.
In specific implementation, the training process of the real-time analysis model comprises the following steps:
acquiring Raman spectrum data of historical moments and real blood glucose concentration of corresponding moments;
and determining the obtained Raman spectrum data at the historical moment as a Raman spectrum training sample, and determining the real blood glucose concentration at the corresponding moment as the label data of the Raman spectrum training sample.
And performing iterative training on the deep convolutional neural network based on the Raman spectrum training sample and the label data of the Raman spectrum training sample to obtain a real-time analysis model.
And further, inputting the obtained Raman spectrum data into a real-time analysis model, sequentially carrying out Raman spectrum characteristic extraction on the Raman spectrum data by a convolution layer in the real-time analysis model, acquiring the blood glucose concentration corresponding to the extracted Raman spectrum characteristic, and outputting the blood glucose concentration.
Further, the blood glucose concentration of the object to be detected in a preset time period is stored.
And 350, displaying the blood glucose concentration in the preset time period.
In some embodiments, the blood glucose concentration detection device may further receive statistical analysis instructions for blood glucose concentration of the subject to be detected within a historical preset time period, such as within the previous 3 days, within the previous 10 days, within the previous 20 days; the statistical analysis instruction may be triggered periodically or by a user at irregular times.
Based on the statistical analysis instruction, acquiring the blood glucose concentration of the object to be detected in the memory within a historical preset time period;
and carrying out statistical analysis on the blood glucose concentration in the historical preset time period by adopting a preset statistical analysis algorithm to obtain the blood glucose concentration information of the object to be detected in the historical preset time period. The blood glucose concentration information comprises change information of blood glucose concentration in a historical preset time period, a maximum blood glucose concentration value and a corresponding moment, and a minimum blood glucose concentration value and a corresponding moment;
and then, displaying the blood glucose concentration information in the historical preset time period.
In some embodiments, while displaying the blood glucose concentration related data, such as blood glucose concentration or blood glucose concentration information, the blood glucose concentration related data may be sent to a preset management platform, such as a hospital big data platform or a community health management platform, through a 5G Wireless network or a Wireless Fidelity (WiFi) network; and receiving early warning information or diagnosis and analysis information from a hospital big data platform or a community health management platform, such as diagnosis and analysis to determine whether the object to be detected has disease information such as diabetes and the like.
And displaying early warning information or diagnosis and analysis information.
The method for detecting the blood glucose concentration comprises the steps of receiving a blood glucose concentration detection request aiming at a to-be-detected object, wherein the blood glucose concentration detection request comprises information of the to-be-detected object; determining a target Raman spectrum light source corresponding to the information of the object to be detected according to the object type in the information of the object to be detected and a stored Raman spectrum light source library, and triggering the target Raman spectrum light source in a Raman spectrum light source assembly to send out an optical signal; the Raman spectrum light source component comprises Raman spectrum light sources with different wavelengths; the Raman spectrum light source library comprises corresponding relations between different object types and corresponding Raman spectrum light sources; collecting light signals scattered by the skin of the external auditory canal of the object to be detected within a preset time period, and converting the collected light signals into corresponding Raman spectrum data; performing convolution characteristic analysis on the Raman spectrum data by adopting a trained real-time analysis model to obtain the blood glucose concentration of the object to be detected in a preset time period; the real-time analysis model is obtained by training network parameters of the deep convolutional neural network according to Raman spectrum data at historical moments and real blood glucose concentration at corresponding moments; and displaying the blood glucose concentration in a preset time period. The method carries out blood sugar concentration analysis by collecting the light signals scattered by the skin of the external auditory canal with stable temperature and humidity and abundant blood vessels, thereby improving the accuracy of blood sugar concentration detection.
In accordance with the above method, an embodiment of the present invention further provides a device for detecting blood glucose concentration, as shown in fig. 4, the device for detecting blood glucose concentration includes: a receiving unit 410, a determining unit 420, an acquiring unit 430, an analyzing unit 440 and a displaying unit 450;
a receiving unit 410, configured to receive a blood glucose concentration detection request for a to-be-detected object, where the blood glucose concentration detection request includes information of the to-be-detected object;
the determining unit 420 is configured to determine, according to the object type in the object information to be detected and the stored raman spectrum light source library, a target raman spectrum light source corresponding to the object information to be detected, and trigger the target raman spectrum light source in the raman spectrum light source assembly to emit a light signal; the Raman spectrum light source component comprises Raman spectrum light sources with different wavelengths; the Raman spectrum light source library comprises corresponding relations between different object types and corresponding Raman spectrum light sources;
the acquisition unit 430 is configured to acquire an optical signal scattered by the skin of the external auditory canal of the object to be detected within a preset time period, and convert the acquired optical signal into corresponding raman spectrum data;
the analysis unit 440 is configured to perform raman spectrum feature analysis on the raman spectrum data by using a trained real-time analysis model to obtain a blood glucose concentration of the object to be detected within the preset time period; the real-time analysis model is obtained by training network parameters of the deep convolutional neural network according to Raman spectrum data at historical moments and real blood glucose concentration at corresponding moments;
and the display unit 450 is used for displaying the blood glucose concentration in the preset time period.
The functions of the functional units of the blood glucose concentration detection apparatus provided in the above embodiment of the present invention can be implemented by the above method steps, and therefore, detailed working processes and beneficial effects of the units in the blood glucose concentration detection apparatus provided in the embodiment of the present invention are not repeated herein.
An embodiment of the present invention further provides an electronic device, as shown in fig. 5, including a processor 510, a communication interface 520, a memory 530 and a communication bus 540, where the processor 510, the communication interface 520, and the memory 530 complete mutual communication through the communication bus 540.
A memory 530 for storing a computer program;
the processor 510, when executing the program stored in the memory 530, implements the following steps:
receiving a blood glucose concentration detection request aiming at a to-be-detected object, wherein the blood glucose concentration detection request comprises information of the to-be-detected object;
determining a target Raman spectrum light source corresponding to the information of the object to be detected according to the object type in the information of the object to be detected and a stored Raman spectrum light source library, and triggering the target Raman spectrum light source in a Raman spectrum light source assembly to send out a light signal; the Raman spectrum light source component comprises Raman spectrum light sources with different wavelengths; the Raman spectrum light source library comprises corresponding relations between different object types and corresponding Raman spectrum light sources;
collecting light signals scattered by the skin of the external auditory canal of the object to be detected within a preset time period, and converting the collected light signals into corresponding Raman spectrum data;
performing Raman spectrum characteristic analysis on the Raman spectrum data by adopting a trained real-time analysis model to obtain the blood glucose concentration of the object to be detected in the preset time period; the real-time analysis model is obtained by training network parameters of the deep convolutional neural network according to Raman spectrum data at historical moments and real blood glucose concentration at corresponding moments;
and displaying the blood glucose concentration in the preset time period.
In an optional implementation, after obtaining the blood glucose concentration of the subject to be detected within the preset time period, the method further includes:
and storing the blood glucose concentration in the preset time period.
In an optional implementation, the method further comprises:
receiving a statistical analysis instruction of the blood glucose concentration of the object to be detected in a historical preset time period;
acquiring the blood glucose concentration of the object to be detected in the memory within a historical preset time period;
performing statistical analysis on the blood glucose concentration within the historical preset time period by adopting a preset statistical analysis algorithm to obtain the blood glucose concentration information of the object to be detected within the historical preset time period, wherein the blood glucose concentration information comprises the variation information of the blood glucose concentration within the historical preset time period, the maximum blood glucose concentration value and the corresponding moment, and the minimum blood glucose concentration value and the corresponding moment;
and displaying the blood glucose concentration information in the historical preset time period.
In an optional implementation, receiving a statistical analysis instruction of the blood glucose concentration of the subject to be detected in a historical preset time period includes:
periodically receiving a statistical analysis instruction of the blood glucose concentration of the object to be detected in a historical preset time period.
In an alternative implementation, converting the collected optical signals into corresponding raman spectral data comprises:
carrying out photoelectric conversion on the collected optical signals to obtain corresponding electric signals;
the electrical signals are converted to corresponding raman spectral data by an analog-to-digital converter.
In an optional implementation, the method further comprises:
sending the blood glucose concentration or the blood glucose concentration information of the object to be detected to a preset management platform;
receiving diagnosis analysis information sent by the preset management platform according to the blood glucose concentration or the blood glucose concentration information;
and displaying the diagnostic analysis information.
The aforementioned communication bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the electronic equipment and other equipment.
The Memory may include a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
Since the implementation and the beneficial effects of the problem solving of each device of the electronic device in the above embodiment can be realized by referring to each step in the embodiment shown in fig. 3, detailed working processes and beneficial effects of the electronic device provided by the embodiment of the present invention are not described herein again.
In another embodiment of the present invention, there is also provided a computer-readable storage medium, having stored therein instructions, which when run on a computer, cause the computer to execute the method for detecting blood glucose concentration as described in any one of the above embodiments.
In yet another embodiment of the present invention, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform the method for detecting blood glucose concentration as described in any of the above embodiments.
As will be appreciated by one of skill in the art, the embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all changes and modifications that fall within the true scope of the embodiments of the present application.
It is apparent that those skilled in the art can make various changes and modifications to the embodiments of the present application without departing from the spirit and scope of the embodiments of the present application. Thus, if such modifications and variations of the embodiments of the present application fall within the scope of the claims of the embodiments of the present application and their equivalents, the embodiments of the present application are also intended to include such modifications and variations.
Claims (10)
1. A method for measuring blood glucose concentration, the method comprising:
receiving a blood glucose concentration detection request aiming at a to-be-detected object, wherein the blood glucose concentration detection request comprises information of the to-be-detected object;
determining a target Raman spectrum light source corresponding to the information of the object to be detected according to the object type in the information of the object to be detected and a stored Raman spectrum light source library, and triggering the target Raman spectrum light source in a Raman spectrum light source assembly to send out a light signal; the Raman spectrum light source component comprises Raman spectrum light sources with different wavelengths; the Raman spectrum light source library comprises corresponding relations between different object types and corresponding Raman spectrum light sources;
collecting light signals scattered by the skin of the external auditory canal of the object to be detected within a preset time period, and converting the collected light signals into corresponding Raman spectrum data;
performing Raman spectrum characteristic analysis on the Raman spectrum data by adopting a trained real-time analysis model to obtain the blood glucose concentration of the object to be detected in the preset time period; the real-time analysis model is obtained by training network parameters of the deep convolutional neural network according to Raman spectrum data at historical moments and real blood glucose concentration at corresponding moments;
and displaying the blood glucose concentration in the preset time period.
2. The method of claim 1, wherein after obtaining the blood glucose concentration of the subject to be tested over the preset time period, the method further comprises:
and storing the blood glucose concentration in the preset time period.
3. The method of claim 2, wherein the method further comprises:
receiving a statistical analysis instruction of the blood glucose concentration of the object to be detected in a historical preset time period;
acquiring the blood glucose concentration of the object to be detected in the memory within a historical preset time period;
performing statistical analysis on the blood glucose concentration within the historical preset time period by adopting a preset statistical analysis algorithm to obtain the blood glucose concentration information of the object to be detected within the historical preset time period, wherein the blood glucose concentration information comprises the variation information of the blood glucose concentration within the historical preset time period, the maximum blood glucose concentration value and the corresponding moment, and the minimum blood glucose concentration value and the corresponding moment;
and displaying the blood glucose concentration information in the historical preset time period.
4. The method of claim 3, wherein receiving instructions for statistical analysis of blood glucose concentration of the subject to be tested over a historical preset time period comprises:
periodically receiving a statistical analysis instruction of the blood glucose concentration of the object to be detected in a historical preset time period.
5. The method of claim 1, wherein converting the collected optical signals into corresponding raman spectral data comprises:
carrying out photoelectric conversion on the collected optical signals to obtain corresponding electric signals;
the electrical signals are converted to corresponding raman spectral data by an analog-to-digital converter.
6. The method of any one of claims 1-3, further comprising:
sending the blood glucose concentration or the blood glucose concentration information of the object to be detected to a preset management platform;
receiving diagnosis analysis information sent by the preset management platform according to the blood glucose concentration or the blood glucose concentration information;
and displaying the diagnostic analysis information.
7. A device for detecting blood glucose concentration, the device comprising: the Raman spectrum analysis system comprises a main control chip, a Raman spectrum light source assembly, a memory, a Raman spectrum signal acquisition and processing module, an analysis module and a power supply;
the main control chip is used for receiving a blood glucose concentration detection request aiming at an object to be detected, and the blood glucose concentration detection request comprises information of the object to be detected;
determining a target Raman spectrum light source corresponding to the information of the object to be detected according to the object type in the information of the object to be detected and the Raman spectrum light source library stored in the memory, and triggering the target Raman spectrum light source in the Raman spectrum light source assembly; the Raman spectrum light source library comprises corresponding relations between different object types and corresponding Raman spectrum light sources;
the Raman spectrum light source assembly is used for controlling the target Raman spectrum light source to emit light signals based on the triggering operation of the main control chip on the target Raman spectrum light source; the Raman spectrum light source component comprises Raman spectrum light sources with different wavelengths; the Raman spectrum light source library comprises corresponding relations between different object types and corresponding Raman spectrum light sources;
the Raman spectrum signal acquisition and processing module is used for acquiring the light signal scattered by the skin of the external auditory canal of the object to be detected within a preset time period and converting the acquired light signal into corresponding Raman spectrum data;
the analysis module is used for performing Raman spectrum characteristic analysis on the Raman spectrum data by adopting a trained real-time analysis model to obtain the blood glucose concentration of the object to be detected in the preset time period; the real-time analysis model is obtained by training a deep convolution neural network according to Raman spectrum data at historical moments and real blood glucose concentration at corresponding moments;
the power supply is used for supplying power to the main control chip, the Raman spectrum light source assembly, the Raman spectrum signal acquisition and processing module and the intelligent analysis module.
8. The device of claim 7, wherein the device further comprises a display module;
the analysis module is further used for receiving a statistical analysis instruction of the blood glucose concentration of the object to be detected in a historical preset time period;
acquiring the blood glucose concentration of the object to be detected in the memory within a historical preset time period; the preset time period is less than the historical preset time period;
performing statistical analysis on the blood glucose concentration within the historical preset time period by adopting a preset statistical analysis algorithm to obtain blood glucose concentration information of the object to be detected within the historical preset time period, wherein the blood glucose concentration information comprises variation information of the blood glucose concentration within the historical preset time period, a maximum blood glucose concentration value and corresponding time, and a minimum blood glucose concentration value and corresponding time;
and the display module is used for displaying the blood glucose concentration information in the historical preset time period.
9. An electronic device, characterized in that the electronic device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
a memory for storing a computer program;
a processor for implementing the method steps of any of claims 1-6 when executing a program stored on a memory.
10. A computer-readable storage medium, characterized in that a computer program is stored in the computer-readable storage medium, which computer program, when being executed by a processor, carries out the method steps of any one of claims 1 to 6.
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