WO2018214297A1

WO2018214297A1 - Portable device and method for non-invasive blood glucose detection

Info

Publication number: WO2018214297A1
Application number: PCT/CN2017/098189
Authority: WO
Inventors: 张贯京; 葛新科; 高伟明; 张红治; 梁昊原; 陈琦; 周亮
Original assignee: 深圳市前海安测信息技术有限公司
Priority date: 2017-05-20
Filing date: 2017-08-19
Publication date: 2018-11-29
Also published as: CN107296616A

Abstract

Provided are a portable device and method for non-invasive blood glucose detection, the method comprising the following steps: a signal processing circuit (3) controlling an infrared light source (13) to emit near infrared light to radiate at a portion to be detected of a human body; a photoelectric sensor (14) acquiring, from the portion to be detected of the human body, a pulse wave signal, and sending same to the signal processing circuit (3) for signal pre-processing (S31); acquiring the pulse wave signal from the signal processing circuit (3) (S32), and extracting a feature value of the acquired pulse wave signal (S33); using a neural prediction network to detect the feature value of the pulse wave signal, so as to obtain an original detection value of the blood glucose concentration (S34); using a neural classification network to detect the feature value of the pulse wave signal, so as to obtain a detection range of the blood glucose concentration (S35); determining whether the original detection value is within the detection range (S36); and if the original detection value is within the detection range, displaying the original detection value on a display screen (23) as a blood glucose concentration value of the human body (S37). The method can effectively reduce the disturbance on the blood glucose concentration caused by the other components of human body blood, and can improve the accuracy of the blood glucose concentration detection.

Description

Technical field

[0001] The present invention relates to the field of non-invasive blood glucose detecting technology, and in particular to a portable non-invasive blood glucose detecting device and method.

Background technique

[0002] With the development of social economy, diabetes has become one of the major diseases that endanger human health in modern society. Hyperglycemia is too high or too low to affect not only the patient's metabolism, but also some complications, such as cardiovascular disease and neuropathy, which pose a great threat to the health of patients. According to the World Health Organization report, there will be 300 million people with diabetes worldwide by 2035, and a large proportion of people with diabetes in China will also be present. In recent years, patients with diabetes have not only existed in some elderly people, but also in some young people. Diabetes is a chronic disease that is difficult to achieve with a single treatment, so people with diabetes need to know exactly what their blood sugar levels are.

[0003] However, at present, for the blood glucose detecting method, in the hospital or the patient's own home, an invasive blood glucose detecting method is adopted, that is, the patient's blood is directly taken, and the blood sugar level of the patient is detected according to an electrochemical method. This method of detection causes certain physical pain to the patient, and repeated blood draws are likely to cause infection. Further, electrochemical reaction test papers are expensive, and are also a large economic burden for diabetic patients. Non-invasive blood glucose testing can eliminate the pain of patient detection, can be frequently detected, improve the quality of life of patients

[0004] At present, there are many non-invasive blood glucose detecting methods, and infrared light-based methods for detecting glucose concentration in human blood are widely used in the research of non-invasive blood glucose detecting. However, there are many other components in the blood other than glucose, which limits the accuracy of blood glucose detection. How to improve the accuracy of blood glucose detection has become an urgent problem to be solved.

technical problem

[0005] The main object of the present invention is to provide a portable non-invasive blood glucose detecting device and method, aiming at solving the technical problem that the existing non-invasive blood glucose detecting method has low accuracy and accuracy for blood glucose detecting. Problem solution

Technical solution

[0006] In order to achieve the above object, the present invention provides a portable non-invasive blood glucose detecting device, comprising a signal collector and a non-invasive blood glucose detecting device, wherein a signal processing circuit is connected between the signal collector and the non-invasive blood glucose detecting device, wherein:

[0007] The signal collector includes an upper detecting plate, a lower detecting plate, an infrared light source, and a photoelectric sensor; the infrared light source is embedded in a lower surface of the front end of the upper detecting plate, and is configured to emit near-infrared light to be irradiated on a part to be tested; The photoelectric sensor is embedded on the front surface of the front end of the lower detecting plate, and is configured to acquire a pulse wave signal from a portion to be tested of the human body under the illumination of the near-infrared light and send a signal processing circuit to perform signal pre-processing;

[0008] The non-invasive blood glucose detecting device includes a microprocessor and a memory, wherein the memory stores a non-invasive blood glucose detecting system, wherein the non-invasive blood glucose detecting system is composed of a plurality of instructions and stored in a memory, wherein the plurality of instructions are micro The processor loads and performs the following steps:

Obtaining a pulse wave signal from the signal processing circuit, and extracting a feature value of the acquired pulse wave signal; [0010] using a predictive neural network to detect a characteristic value of the pulse wave signal to obtain an initial detection value of the blood glucose concentration; [0011] The classification neural network detects the characteristic value of the pulse wave signal to obtain a detection interval of the blood glucose concentration;

[0012] determining whether the initial detection value belongs to the detection interval;

[0013] When the initial detection value is within the detection interval, the initial detection value is displayed on the display screen as the human blood glucose concentration value.

[0014] Preferably, the signal collector further includes a support frame, the upper end of the support frame is provided with a sliding slot, one end of the upper detecting board is disposed in the sliding slot, and the lower detecting board is fixed at a lower end of the supporting frame And set parallel to the axis of the upper detection plate.

[0015] Preferably, the upper surface of the lower detecting plate is provided with a hinge mechanism, and the upper end of the hinge mechanism is provided with a return spring and is connected to the upper detecting plate through a return spring, and the lower end of the hinge mechanism is provided with a support rod and passes through The support rod is fixed to the upper surface of the lower detection plate.

[0016] Preferably, the front surface of the front end of the lower detecting plate is further provided with a detecting portion for placing a portion to be tested of the human body, and the photoelectric sensor is disposed in the detecting portion.

[0017] Preferably, the infrared light source comprises at least a plurality of the near-infrared light emitting tube 800 _n m-1500nm band, a human body part to be measured for transmitting at least a near infrared light comprises _800nm -l _500nm band signal. [0018] In addition, the present invention also provides a non-invasive blood glucose detecting method, which is applied to a portable non-invasive blood glucose detecting device, and the non-invasive blood glucose detecting method includes the steps of:

[0019] The signal processing circuit controls the infrared light source to emit near-infrared light to be irradiated on the part to be tested;

[0020] The photoelectric sensor acquires a pulse wave signal from a portion to be tested of the human body and transmits the pulse wave signal to the signal processing circuit;

[0021] the signal processing circuit performs signal pre-processing on the pulse wave signal;

[0022] The non-invasive blood glucose detecting device acquires a pulse wave signal from the signal processing circuit, and extracts a feature value of the acquired pulse wave signal;

[0023] The non-invasive blood glucose detecting device uses the predicted neural network to detect the characteristic value of the pulse wave signal to obtain an initial detected value of the blood glucose concentration;

[0024] The non-invasive blood glucose detecting device uses a classification neural network to detect a characteristic value of the pulse wave signal to obtain a detection interval of the blood glucose concentration;

[0025] The non-invasive blood glucose detecting device determines whether the initial detected value belongs to the detection interval;

[0026] If the initial detection value is within the detection interval, the non-invasive blood glucose detecting device displays the initial detection value on the display screen as the human blood glucose concentration value.

[0027] Preferably, the non-invasive blood glucose detecting method comprises the steps of: further comprising: if the initial detection value is not in the detection interval, the non-invasive blood glucose detecting device discards the initial detection value and detects the next pulse wave signal until the initial detection value Until the detection interval.

[0028] Preferably, the step of the signal processing circuit performing signal pre-processing on the pulse wave signal comprises the following steps: filtering the pulse wave signal to remove noise and DC components in the pulse wave signal, leaving a required AC component Amplifying and analog-to-digital converting the pulse wave signal to obtain a digital signal of the pulse wave signal, and transmitting the digital signal to the non-invasive blood glucose detecting device.

[0029] Preferably, the infrared light source comprises at least a plurality of near-infrared light-emitting tubes in a wavelength range of 800 _n m to 1500 nm, and is configured to emit near-infrared light including a band of 800 _n m to 1500 nm to a portion to be tested of the human body.

[0030] Preferably, the non-invasive blood glucose detecting method comprises the steps of: further comprising the steps of: the non-invasive blood glucose detecting device detects each time a plurality of pulse wave signals are collected in the preset frequency band to obtain a plurality of blood glucose detecting results; The non-invasive blood glucose detecting device calculates the average value of the same blood glucose detecting result after removing the maximum value and the minimum value from the plurality of blood sugar detecting results, and uses the average value as the final human blood sugar concentration value. Advantageous effects of the invention Beneficial effect

Compared with the prior art, the portable non-invasive blood glucose detecting device and method of the present invention uses a pulse wave signal obtained by predicting a neural network to obtain a detection interval to which a blood glucose concentration belongs, and determines a pulse wave signal obtained by the classification neural network. Obtaining whether the initial detection value of the blood glucose concentration belongs to the detection interval, and when the initial detection value is within the detection interval, the initial detection value is a blood glucose concentration value, and by determining the interval to which the initial detection value belongs, the human body can be effectively reduced. The interference of other components in the blood on blood glucose concentration improves the accuracy and accuracy of blood glucose concentration detection.

Brief description of the drawing

DRAWINGS

1 is a schematic structural view of a preferred embodiment of a portable non-invasive blood glucose detecting device of the present invention;

2 is a schematic structural view of a non-invasive blood glucose detecting device in the portable non-invasive blood glucose detecting device of the present invention;

3 is a flow chart of a preferred embodiment of the non-invasive blood glucose detecting method of the present invention;

4 is a waveform diagram of a pulse wave signal;

5 is a detailed flowchart of the feature value of the extracted pulse wave signal in step S33 of FIG. 3.

[0037] The implementation, functional features, and advantages of the present invention will be further described with reference to the accompanying drawings.

BEST MODE FOR CARRYING OUT THE INVENTION

The specific embodiments, structures, features and functions of the present invention are described in detail below with reference to the accompanying drawings and preferred embodiments. It is understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

Referring to FIG. 1, FIG. 1 is a schematic structural view of a preferred embodiment of a portable non-invasive blood glucose detecting device of the present invention. In the present embodiment, the portable non-invasive blood glucose detecting device comprises a signal collector 1 and a non-invasive blood glucose detecting device 2, wherein: the signal collecting device 1 is configured to collect and output a pulse wave signal. The non-invasive blood glucose detecting device 2 is connected to the signal collector 1 for detecting the pulse wave signal (PP G signal) output from the signal collector 1 to obtain the blood glucose concentration of the test subject.

[0040] In the present embodiment, the signal collector 1 includes a support frame 10, an upper detection plate 11, a lower detection plate 12, an infrared light source 13, and a photosensor 14. Wherein, the upper end of the support frame 10 is provided with a sliding slot 100, and the upper inspection One end of the measuring plate 11 is movably connected to the sliding slot 100, that is, the upper detecting plate 11 can be moved up and down in the sliding slot 100, so that the distance between the upper detecting plate 11 and the lower detecting plate 12 can be adjusted, and the human body of different sizes can be placed. The blood glucose test is performed at the measurement site, which improves the flexibility and applicability of the device. The lower detecting plate 12 is fixed to the lower end of the support frame 10 and disposed in parallel with the axis of the upper detecting plate 11. The upper surface of the lower detecting plate 12 is provided with a hinge mechanism 16, and both ends of the hinge mechanism 16 are provided with a return spring 17, and are connected to the upper detecting plate 11 by a return spring 17. The lower end of the hinge mechanism 16 is provided with a support rod 18 which is fixed to the upper surface of the lower detecting plate 12 by a support rod 18.

In the embodiment, the upper detecting plate 11 is located at a position directly above the hinge mechanism 16 and is provided with a screw hole 110, and the screw hole 110 is provided with an internal thread. The upper end of the hinge mechanism 16 is fixed with a screw 111. The outer surface of the screw 111 is provided with an external thread, and the screw 111 passes through the screw hole 110 and the external thread of the screw 111 matches the inner thread of the screw hole 110. Since the hinge mechanism 16 is connected to the upper detecting plate 11 through the return spring 17, the user can manually rotate the screw 111 to move the upper detecting plate 11 up and down to bring the return spring 17 up and down and compress, so that the upper detecting plate 11 can be moved along the sliding groove 100. Moving up and down, the distance between the upper detecting plate 11 and the lower detecting plate 12 can be adjusted. In this embodiment, the infrared light source 13 is embedded in the lower surface of the front end of the upper detecting plate 11, and the photoelectric sensor 14 is embedded on the front surface of the front end of the lower detecting plate 12, because the upper detecting plate 11 and the lower detecting plate 12 are arranged in parallel. Therefore, the infrared light source 13 and the photosensor 14 are disposed coaxially.

In the embodiment, the photosensor 14 is disposed in the detecting portion 15, and the detecting portion 15 is provided with a front surface of the front end of the lower detecting plate 12 for providing a blood sugar concentration detecting place, which can be used for placing the human body. a portion to be tested, such as a human finger capillary tip, an ear lobe, or a wrist, such as a human capillary-dense body tissue; the infrared light source 13 is a near-infrared light emitting tube for transmitting an optical signal including at least near-infrared light to the detecting portion 15 as In a preferred embodiment, the infrared light source 13 may include a plurality of near-infrared light-emitting tubes in the 800 _n m-1500 nm band, the peak wavelength deviation of the near-infrared light-emitting tube is ±10 nm, and the radiation power is greater than 3 mW; the photosensor 14 is configured to receive the passing detection portion 15 The subsequent optical signal is converted into an electrical signal output. In a specific embodiment, the wavelength band received by the photosensor 14 can be set such that the optical signal received by the photosensor 14 is in the near-infrared band, specifically, the photoelectric sensor. 14 The peak wavelength deviation received is ±10 nm, the photocurrent is greater than 10 uA, and the peak wavelength deviation received by photosensor 14 is less than ±10. Nm. It should be noted that, in a preferred embodiment, after the wavelength band received by the photosensor 14 is set, the infrared light source 13 may include optical signals of other wavelength bands, but needs to meet the optical signal sent by the infrared light source 13 to Less includes near-infrared light.

In a preferred embodiment, a signal processing circuit 3 can be connected between the signal collector 1 and the non-invasive blood glucose detecting device 2. Specifically, the signal processing circuit 3 is connected to the infrared light source 13 of the signal collector 1 through a control line and is connected to the photosensor 14 of the signal collector 1 and the non-invasive blood sugar detecting device 2 through a signal line. When the human body to be tested is placed in the detecting portion 15 and the power source is turned off, the signal processing circuit 3 controls the infrared light source 13 to emit and emits near-infrared light to be irradiated on the body to be tested, and the photoelectric sensor 14 is used to detect the portion from the human body. Acquire the pulse wave signal and perform signal pre-processing on the pulse wave signal. For example, the signal output from the photosensor 14 is converted, preamplified, filtered, and the like. Specifically, after filtering the pulse wave signal, the filter can be used to filter the pulse wave signal, and the noise and DC components in the pulse wave signal can be removed to leave a desired AC component; the pulse wave signal is amplified and Analog-to-digital conversion, as an example, a signal amplifier can be used to amplify the pulse wave signal, using a 12-bit analog-to-digital converter

(ADC) is sampled, and the sampling frequency can be, for example, 1 ΚΗζ to obtain a digital signal of the pulse wave signal, and the digital signal is sent to the non-invasive blood sugar detecting device 2 for subsequent processing. In a specific embodiment, the pulse wave signal may be a photoplethysmographic pulse signal or a bioimpedance signal or a pressure sensing signal. In this embodiment, the pulse wave signal collected by the photosensor 14 is a photoplethysmographic pulse signal (PPG signal). The signal processing circuit 3 can also supply power to the signal collector 1 (e.g., the infrared source 13 and the photosensor 14). Preferably, the upper surface of the upper detecting board 11 is further provided with a power switch 19, which is connected between the infrared light source 13 and the signal processing circuit 3 through a power line, and is used to activate the infrared light source 13 to emit near-infrared light. , or turn off the infrared light source 13 to stop emitting near-infrared light.

In the present embodiment, the PPG signal is acquired to select the earlobe or fingertip of the human body as a portion for extracting the PPG signal, and the earlobe or fingertip is placed on the detecting portion 15 of the signal collector 1. The blood of the fingertips and the earlobe is relatively abundant. With the periodic circulation of the heart, the photoelectric signal can be detected periodically by the photoelectric sensor. In order to obtain a stable photoplethysmographic pulse wave, the external influence factors need to be minimized or changed. For controllability, such as ambient temperature and humidity, in summary, the earlobe or fingertip is the most suitable site for extracting PPG signals. The photoelectric volume pulse wave is obtained by transmitting the human skin tissue through the near-infrared spectrum or by reflecting the human skin tissue.

[0045] Referring to FIG. 2, FIG. 2 is a schematic structural view of the non-invasive blood glucose detecting device 2. In the present embodiment, the non-invasive blood glucose detecting device 2 includes a microprocessor 21, a memory 22, and a display screen 23. The memory 21 is stored A non-invasive blood glucose detecting system 20 is stored, which is composed of a plurality of modules composed of various instructions and stored in the memory 22. The non-invasive non-invasive blood glucose detecting system 20 includes, but is not limited to, a signal acquisition module 201, an eigenvalue extraction module 202, an initial detection module 203, an interval detection module 204, and a blood glucose value output module 205. A module referred to in the present invention refers to a series of computer program instructions executable by the microprocessor 20 and capable of performing a fixed function, which are stored in the memory 21.

[0046] The microprocessor 21 may be a central processing unit (CPU), a microcontroller (MCU), a data processing chip, or an information processing unit having a data processing function. The memory 22 can be a read only memory unit ROM, an electrically erasable memory unit EEPROM, a flash memory unit FLASH or a solid state hard disk. The display screen 23 is a small-sized LCD or LED display unit that is mounted on the outer surface of the casing of the non-invasive blood glucose detecting device 2, since the measured blood sugar concentration value of the human body is displayed. This embodiment will specifically illustrate the functions of the various modules in the non-invasive blood glucose detecting system 20 in conjunction with Figs. 3, 4 and 5.

Referring to FIG. 3, there is shown a flow chart of a preferred embodiment of the non-invasive blood glucose detecting method of the present invention. In the present embodiment, based on the portable non-invasive blood glucose detecting device described above, the present invention also discloses a non-invasive blood glucose detecting method. As shown in Figs. 1 and 2, the non-invasive blood glucose detecting method includes the following steps:

[0048] Step S31, when the user turns on the power of the signal collector 1 , the signal processing circuit 3 controls the infrared light source 13 to emit near-infrared light to be irradiated on the part to be tested, and the photosensor 14 is obtained from the body to be tested. The pulse wave signal is sent to the signal processing circuit 3 for pre-processing the pulse wave signal. In the present embodiment, the infrared light source 13 may emit a plurality of near-infrared light 800 _n m-1500nm band tube, the photosensor 14 acquires the pulse wave signals from parts of the body to be measured, the signal processing circuit 3 acquires the pulse wave from the photosensor 14 Signal, and signal processing such as signal conversion, preamplification and filtering of the pulse wave signal.

[0049] Step S32, the signal acquisition module 201 acquires a pulse wave signal from the signal processing circuit 3. The so-called pulse wave signal carries the blood glucose concentration information of the sample to be tested. In this embodiment, the so-called pulse wave signal is preferably a photoplethysmographic pulse signal. The glucose formula contains multiple 0-H, CH chemical bonds, and there are absorption peaks and absorption peaks and valleys in the 800 _n m-1500 nm band. The absorption peak wavelength is the key wavelength, which is the peak wavelength of blood glucose absorption to near-infrared light, which can reflect blood sugar. For the absorption of near-infrared light, the absorption peak-to-valley wavelength is used as the reference wavelength. The photoplethysmographic pulse wave generated by the critical wavelength contains not only the absorption information of the near-infrared light by the blood glucose, but also the absorption information of the near-infrared light by other substances in the blood. Will reference wavelength and off Modeling the bond wavelengths together can effectively reduce the effects of other substances on near-infrared light absorption. In this embodiment, another important reason for selecting near-infrared light with a wavelength of less than 1500 nm is that these wavelengths are easily acquired, and some common near-infrared wavelengths, such as typical gallium arsenide diodes, can meet the demand and reduce non-invasive blood glucose. The cost of testing.

[0050] Step S33, the feature value extraction module 202 extracts the feature value of the acquired pulse wave signal. In a specific embodiment, the characteristic value of the pulse wave signal may be a magnitude in a unit period of the pulse wave signal, or may be a ratio of a main wave peak to a main wave rising day and a secondary wave main wave relative height. In a preferred embodiment, please refer to FIG. 4, which is a waveform diagram of a pulse wave signal. In one waveform period, the characteristic value is the main peak P of the pulse wave signal, the main trough A, the secondary peak T and the main peak amplitude hP of the secondary trough V, the main valley amplitude hA, the secondary peak amplitude hT, and the secondary valley. The amplitude hV, the main peak-sub-valley interval tl, the main peak-second peak interval t2, the main peak-main valley inter-turn interval t3, and the adjacent main peak inter-turn interval t4. In a specific embodiment, the feature value extraction module 202 may extract the characteristic values of the pulse wave signal by using a wavelet transform method: a main peak amplitude hP, a main valley amplitude hA, a secondary peak amplitude hT, a secondary valley amplitude hV, and a main peak. - Inter-valley interval tl, main peak-sub-peak interval t2, main peak-main valley inter-turn interval t3, and adjacent main peak inter-turn interval t4.

[0051] Step S34, the initial detection module 203 uses the predicted neural network to detect the characteristic value of the pulse wave signal to obtain an initial detection value of the blood sugar concentration. In a specific embodiment, the initial detection module 203 may perform a first detection on the acquired characteristic value of the pulse wave signal by predicting the neural network, thereby obtaining an initial detection value of the blood glucose concentration. In the specific implementation, the predictive neural network should be trained first. The training of the predicted neural network may be online or offline. In this embodiment, offline training is preferred, and the standard PPG eigenvalue training signal may be used. Training, For predictive neural networks, the input is the characteristic value of the photoplethysmographic pulse wave, and the corresponding invasively detected blood glucose concentration value (pre-acquired blood glucose sample value) is used as an output, and then the predicted neural network is trained using, for example, a MATLAB neural network.

[0052] Step S35, the interval detecting module 204 detects the characteristic value of the pulse wave signal by using the classification neural network to obtain a detection interval to which the blood glucose concentration belongs. In a specific embodiment, the interval detecting module 204 may perform second detection on the acquired pulse wave signal by using a classification neural network to obtain an interval in which the acquired pulse wave signal is located. Specifically, taking the human body as an example, the blood glucose concentration can be divided into sections [3, 4], [4, 5], [5, 6] ... [24, 25] according to a step size of 1, which will cover the human body. The blood glucose concentration range of 3 to 25 is divided into a plurality of sections. In the training of the classification neural network, the input is the characteristic value of the photoplethysmographic pulse wave, which will correspond to The blood glucose concentration values are classified. For example, the blood glucose concentration value belongs to the interval [3, 4] and is recorded as the first category, and the interval [4, 5] is recorded as the second category, and the interval [5, 6] is recorded as the third category. The analogy is used as an output until the interval [3, 25] of all blood glucose values that occur during training is included, and then the classification neural network is trained using, for example, the MATLAB neural network.

[0053] Step S36, the blood glucose level outputting module 205 compares the initial detection value with the detection interval to determine whether the initial detection value belongs to the detection interval. If the initial detection value is in the detection interval, step S37 is performed, then the initial detection value is the blood glucose concentration value carried in the pulse wave signal, and the blood glucose value output module 205 displays the initial detection value on the display screen 23 as the human blood glucose. Concentration value. If the initial detected value is not within the detection interval, step S38 is performed and then the process proceeds to step S32, i.e., the blood glucose level outputting module 205 discards the initial detected value and detects the next pulse wave signal until the initial detected value is within the detection interval. For example, if the initial detection value obtained by using the predictive neural network is 4.6, and the detection interval obtained by the classification neural network is [4, 5], the initial detection value belongs to the detection interval; otherwise, if the classification neural network is used The obtained detection interval is [5, 6], [3, 4 domain [9, 10], etc., indicating that the initial detection value does not belong to the detection interval. If the initial detection value is not within the detection interval, if the initial detection value differs greatly from the actual blood glucose concentration value, the initial detection value is discarded and the next pulse wave signal is detected.

[0054] In this embodiment, the feature values of the PPG acquisition signals are extracted and sent to the prediction neural network and the classification neural network for the first detection and the second detection, respectively. The initial detection value (blood glucose value R1) is obtained by the first detection using the predictive neural network, and the detection interval (blood glucose interval R2) is obtained by the second detection using the classification neural network. Use R1 to judge the interval to which the blood glucose level belongs. If the interval where R1 belongs to R2, then Rl is considered correct, and the detection result R1 is retained as the blood glucose concentration value of the human body; otherwise, the detection result is considered incorrect, and the detection result R1 is discarded and the next pulse is discarded. The wave signal is detected until the detection result R1 belongs to the interval belonging to R2, and will be used as the blood glucose concentration value of the human body. Such repeated detection can effectively reduce the interference of other components (such as moisture) on the blood glucose concentration, and improve the accuracy of blood glucose concentration detection. And accuracy.

As shown in FIG. 5, FIG. 5 is a detailed flowchart of extracting the characteristic values of the pulse wave signals in step S33 in FIG. Specifically, the feature value extraction module 202 extracts the feature values of the pulse wave signal by means of wavelet transform, and the following steps are as follows:

[0056] Step S331, the feature value extraction module 202 performs wavelet transform on the acquired pulse wave signal to obtain a wavelet transform sequence. Before the wavelet transform, the obtained pulse wave signal (for example, PPG signal) can be first performed. Noise processing, then the smooth wavelet transform is performed on the pure signal after denoising, and the wavelet transform sequence is obtained according to the obtained value after stationary wavelet transform.

[0057] Step S332, the feature value extraction module 202 searches the wavelet transform sequence for the modulus maxima that meets the preset threshold according to the preset threshold. After obtaining the wavelet transform sequence, a suitable preset threshold may be determined to find a modulus maxima that meets a preset threshold. In this implementation, the modulus maxima in the wavelet transform sequence includes a positive modulus maxima, a negative The modulus maxima and associated submodule maxima.

[0058] Step S333, the feature value extraction module 202 extracts the feature value of the pulse wave signal according to the modulus maximum value. In this example, as shown in FIG. 4, the characteristic values of the pulse wave signal include a main peak amplitude hP, a main valley amplitude hA, a secondary peak amplitude hT, a secondary valley amplitude hV, and according to the main peak P, the main trough A The position of the secondary peak T and the secondary trough V is obtained as an eigenvalue main peak-sub-valley interval 11, a main peak-sub-peak inter-turn interval t2, a main peak-main valley inter-turn interval t3, and an adjacent main peak inter-turn interval t4.

[0059] The portable non-invasive blood glucose detecting apparatus and method disclosed in the present embodiment obtains a blood glucose concentration by detecting a pulse wave signal obtained by using a predicted neural network to detect a pulse wave signal obtained by using a predictive neural network. Whether the initial detection value belongs to the detection interval, and when the initial detection value is within the detection interval, the initial detection value is a blood glucose concentration value, and by determining the interval to which the initial detection value belongs, the other components can effectively reduce the blood glucose. The interference caused by the concentration improves the accuracy and accuracy of blood glucose concentration detection.

[0060] Those skilled in the art may understand that all or part of the steps of the various methods in the above embodiments may be completed by a program to instruct related hardware, and the program may be stored in a computer readable storage medium, and the storage medium may include: Memory, random access memory, disk or CD, etc.

The above are only the preferred embodiments of the present invention, and are not intended to limit the scope of the invention, and the equivalent structure or equivalent process transformations made by the description of the invention and the drawings are directly or indirectly applied to other related The technical field is equally included in the scope of patent protection of the present invention.

Industrial applicability

Compared with the prior art, the portable non-invasive blood glucose detecting apparatus and method of the present invention uses a pulse wave signal obtained by predicting a neural network to obtain a detection interval to which a blood glucose concentration belongs, and determines a pulse wave signal acquired by the classification neural network. Obtaining whether the initial detection value of the blood glucose concentration belongs to the detection interval, and when the initial detection value is within the detection interval, the initial detection value is the blood glucose concentration value, and the initial detection is performed by Judging the range to which the value belongs can effectively reduce the interference of other components in the human blood on the blood glucose concentration, and improve the accuracy and accuracy of the blood glucose concentration detection.

Claims

Claim

[Claim 1] A portable non-invasive blood glucose detecting device, comprising: a signal collector and a non-invasive blood glucose detecting device, wherein a signal processing circuit is connected between the signal collector and the non-invasive blood glucose detecting device, wherein: the signal The collector includes an upper detecting plate, a lower detecting plate, an infrared light source and a photoelectric sensor; the infrared light source is embedded in a lower surface of the front end of the upper detecting plate, and is configured to emit near-infrared light to be irradiated on a part to be tested; the photoelectric sensor is embedded in The front surface of the front end of the lower detecting plate is configured to acquire a pulse wave signal from a portion to be tested of the human body irradiated by near-infrared light and send a signal processing circuit to perform signal pre-processing; the non-invasive blood glucose detecting device includes a microprocessor and a memory, The memory stores a non-invasive blood glucose detecting system, the non-invasive blood glucose detecting system is composed of a plurality of instructions and stored in a memory, the plurality of instructions being loaded by the microprocessor and performing the following steps: acquiring a pulse wave signal from the signal processing circuit, And extracting the characteristic value of the acquired pulse wave signal; The neural network detects the characteristic value of the pulse wave signal to obtain the initial detection value of the blood glucose concentration; uses the classification neural network to detect the characteristic value of the pulse wave signal to obtain the detection interval of the blood glucose concentration; determines whether the initial detection value belongs to the detection interval; when the initial detection value is Within the detection interval, the initial detection value is displayed on the display as the blood glucose concentration value of the human body.

[Claim 2] The portable non-invasive blood glucose detecting device according to claim 1, wherein the signal collector further comprises a support frame, the upper end of the support frame is provided with a sliding slot, and one end of the upper detecting plate is disposed In the sliding groove, the lower detecting plate is fixed to the lower end of the support frame and disposed in parallel with the axis of the upper detecting plate.

[Claim 3] The portable non-invasive blood glucose detecting device according to claim 2, wherein the upper surface of the lower detecting plate is provided with a hinge mechanism, and the upper end of the hinge mechanism is provided with a return spring and passes through the return spring and the upper The detecting plate is connected, and the lower end of the hinge mechanism is provided with a supporting rod and is fixed to the upper surface of the lower detecting plate by the supporting rod.

[Claim 4] The portable non-invasive blood glucose detecting device according to claim 2, wherein the front surface of the front end of the lower detecting plate is further provided with a detecting portion for placing a portion to be tested of the human body, A photosensor is disposed in the detecting portion.

[Claim 5] The portable non-invasive blood glucose detecting device according to any one of claims 1 to 4, characterized in that The infrared light source includes at least a plurality of near-infrared light-emitting tubes in a band of 800 _n m to 1500 nm, and is configured to emit near-infrared light including a band of 800 _n m to 1500 nm to a portion to be tested of a human body.

[Claim 6] A non-invasive blood glucose detecting method for use in a portable non-invasive blood glucose detecting device, characterized in that the portable non-invasive blood glucose detecting device comprises a signal collector and a non-invasive blood glucose detecting device, the signal collector and non-invasive blood glucose A signal processing circuit is connected between the detecting devices, the signal collecting device includes an infrared light source and a photoelectric sensor, wherein the non-invasive blood glucose detecting method comprises the following steps: the signal processing circuit controls the infrared light source to emit near-infrared light to be irradiated on the part to be tested; The photoelectric sensor obtains the pulse wave signal from the part to be tested of the human body and sends it to the signal processing circuit; the signal processing circuit performs signal pre-processing on the pulse wave signal; the non-invasive blood glucose detecting device acquires the pulse wave signal from the signal processing circuit, and extracts the acquired pulse wave The characteristic value of the wave signal; the non-invasive blood glucose detecting device uses the predicted neural network to detect the characteristic value of the pulse wave signal to obtain the initial detection value of the blood glucose concentration; the non-invasive blood glucose detecting device uses the classification neural network to detect the characteristic value of the pulse wave signal to obtain the blood glucose Degree detecting section; non-invasive blood glucose detection means determines whether the detected value is within the initial detection section; if the initial value is detected in the detection zone, then the initial non-invasive blood glucose value detecting means detecting a blood glucose concentration value displayed on the display screen.

[Claim 7] The non-invasive blood glucose detecting method according to claim 6, wherein the method further comprises the step of: if the initial detected value is not within the detection interval, the non-invasive blood glucose detecting device discards the initial detected value and the next one The pulse wave signal is detected until the initial detection value is within the detection interval.

The non-invasive blood glucose detecting method according to claim 6, wherein the step of performing signal pre-processing on the pulse wave signal by the signal processing circuit comprises the following steps: filtering the pulse wave signal to remove the pulse wave The noise and DC components in the signal leave the desired AC component; the pulse wave signal is amplified and analog-digital converted to obtain a digital signal of the pulse wave signal, and the digital signal is sent to the non-invasive blood glucose detecting device.

[Claim 9] The non-invasive blood glucose detecting method according to claim 6, wherein the step of extracting the characteristic value of the acquired pulse wave signal by the non-invasive blood glucose detecting device comprises the following steps: The acquired pulse wave signal is subjected to wavelet transform to obtain a wavelet transform sequence; the modulus maximum value corresponding to the preset threshold is searched in the wavelet transform sequence according to the preset threshold; and the characteristic value of the pulse wave signal is extracted according to the modulus maximum value.

The non-invasive blood glucose detecting method according to any one of claims 6 to 9, wherein the infrared light source comprises at least a plurality of near-infrared light-emitting tubes in a wavelength range of 800 _n m to 1500 nm, The human body to be tested emits near-infrared light including at least the 800 nm to 1500 nm band.