WO2023280017A1 - Détecteur de glycémie non invasif et méthode de détection - Google Patents

Détecteur de glycémie non invasif et méthode de détection Download PDF

Info

Publication number
WO2023280017A1
WO2023280017A1 PCT/CN2022/101907 CN2022101907W WO2023280017A1 WO 2023280017 A1 WO2023280017 A1 WO 2023280017A1 CN 2022101907 W CN2022101907 W CN 2022101907W WO 2023280017 A1 WO2023280017 A1 WO 2023280017A1
Authority
WO
WIPO (PCT)
Prior art keywords
fingertip
finger
sensor
blood glucose
temperature
Prior art date
Application number
PCT/CN2022/101907
Other languages
English (en)
Chinese (zh)
Inventor
刘炜
Original Assignee
无锡轲虎医疗科技有限责任公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 无锡轲虎医疗科技有限责任公司 filed Critical 无锡轲虎医疗科技有限责任公司
Publication of WO2023280017A1 publication Critical patent/WO2023280017A1/fr

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1455—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6813—Specially adapted to be attached to a specific body part
    • A61B5/6825—Hand
    • A61B5/6826—Finger
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation

Definitions

  • the invention relates to the improvement of non-invasive blood sugar detection technology, in particular to a non-invasive blood sugar detection instrument and detection method with multi-sensing and highly accurate data.
  • Blood glucose testing is a key link in diabetes treatment, but traditional testing requires blood sampling, and the trauma of blood sampling makes it difficult for patients to adhere to daily monitoring of blood glucose. This is also a problem that has plagued the medical profession for many years.
  • the human body is a complex living body. Physiological phenomena such as heartbeat and blood circulation will cause periodic fluctuations in blood flow volume. The time-varying characteristics of blood flow volume will cause changes in the absorbance of the human body in the near-infrared spectrum, and have a significant impact on the measurement results. Obvious impact, mainly manifested as instability in the spectral time domain.
  • the wavelength range of the photoelectric sensor is too wide
  • the wavelength receiving range of the photoelectric sensor that can be used for blood sugar detection wavelength is too wide to accurately receive the spectral information of a specific wavelength LED. It is necessary to use a filter to cut off the wavelength receiving range to make it narrower. After using the filter, the light transmission rate will be reduced. Insufficient, affect the accuracy.
  • the power of specific wavelength LEDs on the market that can be used for blood sugar detection is too small, concentrated at 1-3mw, which makes the pass rate of the light illuminated to the finger insufficient.
  • Chinese patent publication CN108593593A discloses a serial dual-infrared spectrum non-invasive blood glucose measurement device.
  • the whole device is composed of a broadband infrared light source, a measurement hole, a double filter switcher, an infrared photoelectric sensor, and a signal acquisition and processing circuit.
  • the infrared photoelectric sensor is located behind the double-filter switcher and can convert spectral energy information into corresponding voltage signals.
  • the above scheme uses a broadband infrared light source and distributes the spectral energy in the near-infrared (800nm-1100nm) or short-wave infrared (1000-1800nm) spectral range.
  • the infrared photoelectric sensor has near-infrared (800nm-1100nm) or short-wave ) spectral sensitivity.
  • the infrared photoelectric sensor is located behind the double-filter switcher, and analyzes the wavelength carrying the blood sugar level information in the form of receiving the effective wavelength after filtering out the invalid wavelength.
  • the effective wavelength carries blood glucose level information, it is still uncertain where the specific wavelengths of the effective blood glucose level information are concentrated. Usually, it is necessary to use an algorithm for conversion, combined with big data to determine the specific blood glucose level.
  • this solution is the mainstream solution for blood sugar level detection.
  • the main problem is that the wavelength range used is wide, and there are many invalid information mixed in the wavelength. It relies too much on algorithms and big data, and algorithms and big data require effective information. When there is a lot of invalid information, the accuracy of the results obtained by using algorithms and big data is still low.
  • Chinese patent application publication No. CN112022167A discloses a non-invasive blood sugar detection method based on a spectral sensor, which includes the following steps: 1) a spectral sensor is designed at the fingertip position, and an LED is designed on the other side of the fingertip position; 2) Adapt the Fabry-Perot interferometer tunable filter in the spectral sensor, and adjust the optical receiving range of the tunable filter to nm level; Spectral sensor for collection; 4): The light emitted by 1720nm LED passes through human tissue and then collected by 1550nm-1850nm spectral sensor.
  • the blood glucose level measured during the actual use of this solution is basically the same as the detection result of the invasive blood glucose level under normal circumstances.
  • a problem was also found in the actual use process, that is, when the fingertips of different fingers are sent to the non-invasive blood glucose meter for detection, the measured value has a certain deviation.
  • the measured value When the same finger is sent to the non-invasive blood glucose meter for testing, due to the different strength of the fingertips when it is inserted into the bottom and the existence of fingernails, the measured value also has a certain deviation.
  • the purpose of this application is to provide a multi-sensory and highly accurate non-invasive blood glucose detector and detection method, which can limit, classify and identify, determine the detection position and squeeze the fingertips before performing non-invasive blood glucose detection on fingers Judging by the degree, the most stable spectrum detection is performed on the finger when all the interference factors are reduced to the minimum.
  • a non-invasive blood glucose detector with multi-sensory and highly accurate data including a housing, a controller, a power module, a heat sink, a power switch, an LED light source, and a spectral sensor.
  • a finger compartment is provided, the power supply module is electrically connected to the controller and both are arranged in the casing, the LED light source is arranged at the end of the finger compartment and is located on the top surface of the finger compartment, the heat sink is connected to the spectrum sensor, and the The spectrum sensor is located at the end of the finger compartment and on the bottom surface of the finger compartment, the LED light source and the spectrum sensor are located on the same straight line, the end of the finger compartment is provided with a notch, and the edge of the notch is provided with a slope stop block, the slope block is provided with a plurality of temperature sensors side by side, the temperature sensor is electrically connected to the controller, the slope block is provided with a through hole for detecting the passage of light, and also includes fingertip pressure Detection mechanism, the
  • the detection bracket is detachably connected to the housing, and the detection bracket also abuts against the controller.
  • a guide spring is further included, the guide spring is nested on the pressure sensor, and the guide spring and the pressure sensor are inclined.
  • a guide rail groove is provided on the side wall of the finger compartment, and a guide rail is provided on the fingertip stopper, and the fingertip stopper slides and fits with the guide rail groove through the guide rail.
  • the fingertip stopper is provided with a fingertip limiting groove with a width of 5 mm to 1 cm.
  • the top of the fingertip stop is arc-shaped, and the height of the notch is greater than the height of the fingertip stop.
  • it also includes a semiconductor cooling sheet and a heat dissipation copper sheet.
  • the spectral sensor is also connected to the heat dissipation copper sheet.
  • the heating end of the semiconductor refrigeration sheet is attached to the heat dissipation sheet.
  • a multi-sensory and highly accurate non-invasive blood glucose detection method comprises the following steps:
  • the first category is the thumb
  • the second category is the index finger, middle finger and ring finger
  • the third category is the little finger
  • the pressure sensor receives the pressure signal and remains stable, it is determined that the fingertip has reached the bottom of the finger compartment and remains horizontal, and the pressure value received by the pressure sensor is a coefficient K; when the temperature received by the temperature sensor changes, it is determined that the fingertip Temperature T1, the unchanged temperature is the ambient temperature T2, the number N of changes in the temperature sensor;
  • the spectral sensor is equipped with a Fabry-Perot interferometer tunable filter, and the tunable filter can be adjusted Spectrum reception is performed after the optical receiving range of the device reaches the nm level;
  • the LED light source emits specified wavelengths of 1500 nm, 1525 nm, 1550 nm and 1575 nm.
  • the power module when the power switch is turned on, the power module also energizes the semiconductor cooling chip through the controller, and the semiconductor cooling chip directly cools down the spectral sensor through the heat dissipation copper sheet, so that the spectral sensor can emit light at a specified temperature. induction reception.
  • the inventor found the main reason after repeated tests is that the spectral detection method of the non-invasive blood glucose meter is mainly aimed at the 2-5 mm of the fingertip, which has not been blocked by bones. Therefore, when the spectrum sensor is used for collection, it is possible to collect as much wavelength as possible containing effective blood sugar information. But precisely because this part belongs to the front end of the fingertip, there is also the influence of the length of the nail.
  • the multi-sensing and highly accurate non-invasive blood glucose detection method of the present application can use the above-mentioned non-invasive blood glucose detection instrument.
  • the design of the present application adopts the design of the slope stopper, which can not only block the end of the finger to a certain extent, but also provide a tactile reminder for the finger to reach the designated position.
  • Multiple temperature sensors can detect both the temperature of the environment and the temperature of the finger, and can also judge the width of the fingertip according to the number of temperature sensors that have changed, thereby judging the category of the penetrating finger.
  • a fingertip pressure detection mechanism is set at the notch position.
  • the guide spring of the fingertip pressure detection mechanism supports the fingertip stopper and keeps it tilted.
  • the pressure sensor can further detect the extrusion variable of the finger end.
  • the height of the notch at the end of the finger compartment is higher than the height of the fingertip block.
  • the top of the fingertip block can be arc-shaped, and the gap formed in the middle can be passed by the nail to ensure that there will be no light leakage or light leakage caused by the deformation of the nail during detection. Tissue over-squeeze problem.
  • the soft material layer used for the fingertip stopper is sponge foam material inside, and the outer layer is lined with soft fabric.
  • there is a fingertip limit groove to fine-tune the level of the fingertips, prevent fingertips from shifting, and avoid excessive fingertips. Squeeze, if there is excessive extrusion, the variable of the pressure sensor can intervene and serve as a reference for blood sugar detection.
  • Figure 1 is a map of the distribution of blood vessels in the palm
  • Fig. 2 is the schematic diagram of fingertip part
  • Fig. 3 is the structural representation of the detector of the present application.
  • Fig. 4 is the internal structural schematic diagram 1 of the structural schematic diagram of the detector of the present application.
  • Fig. 5 is a partially enlarged schematic diagram of schematic diagram 1 of the present application.
  • Fig. 6 is the internal structural schematic diagram II of the structural schematic diagram of the detector of the present application.
  • FIG. 7 is a partially enlarged schematic diagram of the second schematic diagram of the present application.
  • Fig. 8 is the explosion schematic diagram of the detector of the present application.
  • FIG. 9 is a block diagram of the controller of the present application.
  • the non-invasive blood glucose meter does not necessarily remain horizontal during the use of each person, nor does it necessarily remain horizontal when the finger is inserted into the bottom of the finger compartment. It is determined that there are many variables before the measurement, and these variables are the influencing variables of the non-invasive blood glucose detection.
  • the fingertip nails of each finger vary in length according to individual habits.
  • the nail on the fingertip will contact the front end of the finger compartment, forming deformation and causing light leakage, and causing the detection part to move backward or forward.
  • the ideal position of the detection site is deviated from the position of the test light source, and the deformation of the nail will also cause changes in the tissue density of the actual detection site.
  • the fingertip does not necessarily remain horizontal. During the insertion process, the fingertip will have a certain inclination, and the test site and tissue density after the inclination will also be different from the preset value. deviation.
  • non-invasive blood glucose meters has certain resistance in the process of popularization and advancement, partly because the devices currently on the market based on near-infrared spectroscopy for the development of non-invasive blood glucose are all designed based on specific wavelength ranges or specific wavelength LEDs plus traditional photoelectric sensors. Due to the wide range of receiving wavelengths of the photoelectric sensor, if you want to obtain high-precision optical data, you need to use a filter to cut off the wavelength. However, due to the influence of the processing precision of the optical filter, the precision of the optical signal is insufficient.
  • the inventor designed a non-invasive blood glucose detector with multi-sensory and highly accurate data, and established a new fingertip non-invasive blood glucose measurement method.
  • the multi-sensory and highly accurate non-invasive blood glucose detector of the present application is shown in FIG. 8 during specific assembly.
  • the power switch 5 is installed on the upper cover 23 , and the power switch 5 is electrically connected to the controller 2 .
  • the upper cover 23 is detachably connected to the housing 1 through a buckle 24 .
  • a cooling hole 22 is provided on the side wall of the casing 1 , and a cooling fan 29 is installed on the side wall of the casing 1 through a cooling fan fixing bracket 30 and is located beside the cooling hole 22 .
  • the power module 3 is installed with the controller 2 through the fixing plate 26 , and the power module 3 is located at the bottom of the fixing plate 26 .
  • the controller 2 is located above the fixed plate 26 .
  • the fixing plate 26 and the controller 2 are assembled into a control module, it is installed on the housing 1 through the fixing bracket 25 and the height is adjustable.
  • the indicator light 21 is installed on the controller 2 and exposed on the surface of the housing 1 to indicate whether the power switch 5 is turned on.
  • the spectral sensor 7 is connected to the heat dissipation copper sheet 31 and then electrically connected to the controller 2 .
  • the finger housing 8 is clamped with the housing 1 through a rubber sealing ring 28 .
  • the semiconductor cooling sheet 32 is attached to the heat dissipation copper sheet 31 on one side and the heat dissipation sheet 4 on the other side through the heat-conducting silica gel.
  • a stainless steel heat dissipation etched net 27 is also provided on the housing 1 , and the position of the stainless steel heat dissipation etched net 27 is attached to the heat sink 4 .
  • the material of the etched stainless steel heat dissipation mesh 27 is light and thin, with a thickness of only 0.2-0.3mm, and is easy to install. Compared with the heat dissipation mesh made of plastic, it is more beautiful. At the same time, compared with plastic materials, metal materials have better thermal conductivity, which can improve heat dissipation efficiency. Due to the temperature deviation, for the spectral sensor, the detection value will drift, so the heat dissipation of the spectral sensor is extremely strict.
  • the semiconductor refrigerating sheet 32 After the power switch 5 is turned on, the semiconductor refrigerating sheet 32 is connected to electricity, and the semiconductor refrigerating sheet 32 will be refrigerated and heated while being energized. Since the heat dissipation copper sheet 31 is in contact with the spectral sensor 7, heat conduction can be realized, thereby ensuring that the ambient temperature is controllable when the spectral sensor 7 detects. Moreover, airflow is formed in the casing 1 through the heat dissipation fan 29, combined with the stainless steel heat dissipation etched mesh 27 for rapid heat dissipation, which can ensure that the detection display of the spectral sensor 7 will not occur due to the ambient temperature when the equipment works for a long time. Value drift.
  • the non-invasive blood glucose detector with multi-sensory and highly accurate data of the present application has an internal structure as shown in Figures 4 to 7.
  • the LED light source 6 is installed on the housing 1 and electrically connected to the controller 2. At the position of the top surface of the end of the bin 8, the LED light source 6 and the spectral sensor 7 are located on the same straight line.
  • a notch 9 is provided at the end of the finger bin 8 , and a slope block 10 is provided at the edge of the notch 9 .
  • the slope stopper 10 is provided with a plurality of temperature sensors 11 arranged side by side, the temperature sensors 11 are electrically connected to the controller 2, and the slope stopper 10 is provided with a through hole 12 for detecting light passing through.
  • the non-invasive blood glucose detector also includes a fingertip pressure detection mechanism 13, the fingertip pressure detection mechanism 13 includes a detection bracket 14, a fingertip stopper 15 and a pressure sensor 16, the detection bracket 14 is arranged on the housing 1, the The fingertip block 15 is connected with the detection bracket 14 through the pressure sensor 16 .
  • the pressure sensor 16 is located at the notch 9 and at the edge of the slope block 10 , and the pressure sensor 16 is also electrically connected to the controller 2 .
  • the detection bracket 14 is detachably connected to the housing 1 , and the detection bracket 14 also abuts against the controller 2 . This design can ensure that the position of the detection bracket 14 is stable without deviation.
  • a guide spring 17 is also included, and the guide spring 17 is nested on the pressure sensor 16 .
  • the guide spring 17 is designed with reference to the size and parameters of GB/T1973.3-2005 small cylindrical helical compression spring, the middle diameter of the spring is 0.8mm, and the test load is 2.16N.
  • the guide spring 17 and the pressure sensor 16 are inclined, and the specific angle can be 30 degrees.
  • the fingertip block 15 is provided with a guide rail 19 on the side wall of the finger compartment 8, and the fingertip block 15 slides through the guide rail 19 and the guide rail groove 18.
  • the inner side of the soft material layer of the fingertip stopper 15 is a sponge foam material, and the outer layer is lined with a soft fabric, which cooperates with guide rails and springs, so that when the fingers are inserted, they are not pressed by the components and have a certain damping effect.
  • the position of the fingertip is limited.
  • the fingertip stopper 15 is provided with a fingertip limiting groove 20 with a width of 5 mm to 1 cm; when the fingertip is inserted, the fingertip will automatically keep horizontal and centered according to the tactile habit, and the fingertip stopper 15 shown in the figure
  • the top is arc-shaped, and the height of the notch 9 is greater than that of the fingertip block 15, so that the nail can exceed the fingertip block 15 without being squeezed by the end of the finger bin 8.
  • the method for specifically detecting the finger includes the following steps:
  • Step 1 turn on the power switch 5, and the power module 3 powers on the LED light source 6, the spectrum sensor 7, the temperature sensor 11 and the pressure sensor 16 respectively through the controller 2;
  • Step 2 Insert your finger into the finger compartment 8 and probe into the bottom of the finger compartment 8.
  • the nail part of the fingertip will be located in the gap between the fingertip stopper 15 and the notch 9, so as to ensure that the length of the nail will not match the finger.
  • the detection part of the tip causes interference, the front end of the fingertip is limited by the fingertip limit groove 20 and the fingertip is horizontal, and the guide spring 17 provides a damping effect and limits the forward displacement of the fingertip;
  • Step 3 when the pressure sensor 16 receives the pressure signal and remains stable, it is determined that the fingertip has reached the bottom of the finger compartment 8 and remains horizontal, and the pressure value received by the pressure sensor 16 is a coefficient K; when the temperature sensor 11 receives the temperature change , thereby judging the fingertip temperature T1, the unchanged temperature is the ambient temperature T2, and the number N of changes in the temperature sensor 11;
  • Step 4 After the light of the specified wavelength is emitted by the LED light source 6, the light passes through the through hole 12 and then passes through the detection part at the front of the fingertip.
  • the spectral sensor 7 is equipped with a Fabry-Perot interferometer tunable filter, and Adjust the optical receiving range of the tunable filter to nm level and perform spectrum receiving;
  • Step 5 According to the number N of changes in the temperature sensor 11, determine whether the type of the finger belongs to the first, second or third category, combine the coefficient K, the fingertip temperature T1 and the ambient temperature T2, and combine the spectral sensor 7 to receive light
  • the converted ADC value after the signal is jointly sent to the controller 2, and the controller 2 invokes the algorithm in the built-in data storage module to calculate the blood glucose value.
  • the fingers are divided into three categories, the first category is the thumb, the second category is the index finger, middle finger and ring finger, and the third category is the little finger.
  • the LED light source 6 emits specified wavelengths of 1500nm, 1525nm, 1550nm and 1575nm.
  • step two the unique material design of the fingertip block 15 can not only ensure that when the end of the finger has a blocking effect, there will be no excessive extrusion and the movement direction will be moved by the direction of the guide rail 19 and the direction of the guide spring 17 Restricted, basically level and without deflection.
  • the power module 3 When the power switch 5 is turned on, the power module 3 also energizes the semiconductor cooling chip 32 through the controller 2 .
  • the temperature of the spectral sensor 7 is directly lowered by the semiconductor cooling sheet 32 through the heat dissipation copper sheet 31 , so that the spectral sensor 7 can sense and receive light at a specified temperature.
  • the algorithm used in this application usually contains some errors based on the spectral information measured by the spectral sensor, such as stray light, the influence of human tissue, etc., which makes the measured data have certain noise and affects the calculation accuracy of blood sugar. Therefore, before modeling It is necessary to preprocess the collected raw spectral data.
  • the preprocessing includes that the type of the finger belongs to the first type, the second type or the third type, combining coefficient K, fingertip temperature T1 and ambient temperature T2, etc., thereby reducing errors and extracting effective information in the data.
  • the calculation accuracy of the blood glucose model is improved through the above preprocessing.
  • the multi-mode spectral data is modeled using MATLAB software.
  • Two sets of near-infrared spectral data with different wavelengths are input as the independent variable matrix of the model, and the blood glucose value adopted by the household blood glucose meter is used as the dependent variable of the model, and the sample training set and test set are divided.
  • the screened spectral data are sorted according to the blood glucose values measured by the household blood glucose meter, and the training set and the test set are divided according to the ratio of 3:1 to ensure that the selected samples cover all the blood glucose values, that is, 6 sets of sample data are used as training Set, 2 sets of sample data as the test set. Then normalize the sample data.
  • Two sets of spectral data measured at different wavelengths are used as independent variables, and blood glucose values are used as dependent variables. They are normalized respectively, and the probability distribution is in the same range, so as to reduce the impact on the modeling results due to the large range of data distribution and inconsistent order of magnitude, and Improve training efficiency.
  • To set the SVM parameters it is necessary to select the best kernel function, the penalty factor coefficient (c) and the parameter coefficient (g) of the kernel function. Due to the differences in models and data, it is impossible to obtain the optimal parameters before modeling.
  • the method of cross-validation is used to obtain the best values of c and g for training and prediction. There are 6 sets of data in the experimental training set.
  • the spectral data and the true value of blood sugar of 6 groups of samples are used for training to obtain the model between the spectral data and the true value of blood sugar. Substituting the two sets of data of the test set into the model for calculation, the calculated value of the blood glucose of the two sets of data can be obtained.
  • the correlation coefficient R the root mean square error of the calibration set (RMSEC), the root mean square error of the test set (RMSEP) and the relative error E, where the correlation coefficient reflects the predicted value
  • R the root mean square error of the calibration set
  • RMSEP the root mean square error of the test set
  • E the relative error
  • the correlation coefficient of the training set is 97.29%
  • the root mean square error is 0.3558mmol/L
  • the correlation coefficient of the test set is 96.3%
  • the root mean square error is 0.3804mmol/L
  • the maximum The relative error is 13.68%
  • the average relative error is 0.069%.

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Surgery (AREA)
  • Public Health (AREA)
  • Pathology (AREA)
  • Veterinary Medicine (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • Biophysics (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Optics & Photonics (AREA)
  • Signal Processing (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Power Engineering (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physiology (AREA)
  • Psychiatry (AREA)
  • Emergency Medicine (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

Un glucomètre non invasif comprend un boîtier (1), un dispositif de commande (2), un module d'alimentation électrique (3), des ailettes de refroidissement (4), un interrupteur d'alimentation (5), une source de lumière à DEL (6) et un capteur spectral (7). Un compartiment de doigt (8) est disposé dans le boîtier (1) ; le module d'alimentation électrique (3) et le dispositif de commande (2) sont électriquement connectés l'un à l'autre et sont disposés dans le boîtier (1) ; la source de lumière à DEL (6) est disposée à l'extrémité du compartiment de doigt (8) et est située sur la surface supérieure du compartiment de doigt (8) ; les ailettes de refroidissement (4) sont reliées au capteur spectral (7) ; le capteur spectral (7) est disposé à l'extrémité du compartiment de doigt (8) et est situé sur la surface inférieure du compartiment de doigt (8) ; la source de lumière à DEL (6) et le capteur spectral (7) sont situés sur une même ligne droite. Pendant la détection non invasive de la glycémie, la limite de position, la classification et la reconnaissance, la détermination de la position de détection et la détermination du degré de pression du bout du doigt peuvent être effectuées sur le doigt avant la détection non invasive de la glycémie, et la détection spectrale la plus stable est effectuée sur le doigt lorsque tous les facteurs d'interférence sont minimisés.
PCT/CN2022/101907 2020-09-11 2022-06-28 Détecteur de glycémie non invasif et méthode de détection WO2023280017A1 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
CN202010956081.8A CN112022167A (zh) 2020-09-11 2020-09-11 一种基于光谱传感器的无创血糖检测方法
CN202110778786.X 2021-07-09
CN202110778786.XA CN113261954B (zh) 2020-09-11 2021-07-09 多元感知和高度数据精确化的无创血糖检测仪及检测方法

Publications (1)

Publication Number Publication Date
WO2023280017A1 true WO2023280017A1 (fr) 2023-01-12

Family

ID=73588949

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2022/101907 WO2023280017A1 (fr) 2020-09-11 2022-06-28 Détecteur de glycémie non invasif et méthode de détection

Country Status (2)

Country Link
CN (2) CN112022167A (fr)
WO (1) WO2023280017A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116242804A (zh) * 2023-05-09 2023-06-09 四川威斯派克科技有限公司 一种便携式近红外光谱仪

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112022167A (zh) * 2020-09-11 2020-12-04 无锡轲虎医疗科技有限责任公司 一种基于光谱传感器的无创血糖检测方法
CN113598763A (zh) * 2021-08-05 2021-11-05 重庆大学 一种基于mic-pca-narx校正算法的无创血糖检测装置及方法

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002003857A2 (fr) * 2000-07-11 2002-01-17 Lightouch Medical, Inc. Methode de modulation de tissu pour la mesure non invasive d'un analyte
CN102293654A (zh) * 2011-06-17 2011-12-28 清华大学 基于代谢热-光学方法的无创血糖检测仪
CN108593593A (zh) * 2018-04-24 2018-09-28 深圳市英谱科技有限公司 串行双红外光谱无创血糖测量装置
JP2019198363A (ja) * 2018-05-14 2019-11-21 株式会社カスタム 非侵襲性血糖測定器
CN113261954A (zh) * 2020-09-11 2021-08-17 无锡轲虎医疗科技有限责任公司 多元感知和高度数据精确化的无创血糖检测仪及检测方法

Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5362966A (en) * 1990-06-27 1994-11-08 Rosenthal Robert D Measurement of finger temperature in near-infrared quantitative measurement instrument
US7133710B2 (en) * 2002-03-08 2006-11-07 Sensys Medical, Inc. Compact apparatus for noninvasive measurement of glucose through near-infrared spectroscopy
JP2002202258A (ja) * 2000-12-28 2002-07-19 Bios Ikagaku Kenkyusho:Kk 分光光学的血糖値測定装置
WO2006086085A2 (fr) * 2004-12-28 2006-08-17 Hypermed, Inc. Imagerie hyperspectrale/multispectrale utilisee dans la determination, l'evaluation et la surveillance de la physiologie systemique ou d'un etat de choc
JP5348168B2 (ja) * 2010-12-10 2013-11-20 カシオ計算機株式会社 ネイルプリント装置
EP2869764B1 (fr) * 2012-07-06 2023-07-26 Orsense Ltd. Système et procédé de mesure de paramètres sanguins
US9717458B2 (en) * 2012-10-20 2017-08-01 Masimo Corporation Magnetic-flap optical sensor
CN104490403B (zh) * 2014-12-06 2016-08-17 深圳市贝沃德克生物技术研究院有限公司 基于光谱技术的无创血糖测量系统及其测量方法
CN109788902A (zh) * 2016-07-06 2019-05-21 开米美景公司 用于检测水肿的系统和方法
CN107334477A (zh) * 2017-05-02 2017-11-10 北京理工大学深圳研究院 一种双光谱无创血糖检测装置
CN208031213U (zh) * 2017-09-06 2018-11-02 湖北科技学院 一种近红外光谱血糖无创检测仪
CN108175418A (zh) * 2018-01-18 2018-06-19 凌中鑫 一种无创血糖测试仪
CN110327058A (zh) * 2019-07-31 2019-10-15 清华大学 一种无创血糖仪及血糖检测方法
CN111466921A (zh) * 2020-04-23 2020-07-31 中国科学院上海技术物理研究所 基于多源信息感知及融合的无创血糖检测仪与检测方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002003857A2 (fr) * 2000-07-11 2002-01-17 Lightouch Medical, Inc. Methode de modulation de tissu pour la mesure non invasive d'un analyte
CN102293654A (zh) * 2011-06-17 2011-12-28 清华大学 基于代谢热-光学方法的无创血糖检测仪
CN108593593A (zh) * 2018-04-24 2018-09-28 深圳市英谱科技有限公司 串行双红外光谱无创血糖测量装置
JP2019198363A (ja) * 2018-05-14 2019-11-21 株式会社カスタム 非侵襲性血糖測定器
CN113261954A (zh) * 2020-09-11 2021-08-17 无锡轲虎医疗科技有限责任公司 多元感知和高度数据精确化的无创血糖检测仪及检测方法

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116242804A (zh) * 2023-05-09 2023-06-09 四川威斯派克科技有限公司 一种便携式近红外光谱仪
CN116242804B (zh) * 2023-05-09 2023-08-15 四川威斯派克科技有限公司 一种便携式近红外光谱仪

Also Published As

Publication number Publication date
CN113261954A (zh) 2021-08-17
CN112022167A (zh) 2020-12-04
CN113261954B (zh) 2023-03-07

Similar Documents

Publication Publication Date Title
WO2023280017A1 (fr) Détecteur de glycémie non invasif et méthode de détection
KR101534537B1 (ko) 분석물질의 비침투식 분광 측정을 위한 장치 및 그 사용 방법
Lacerenza et al. Wearable and wireless time-domain near-infrared spectroscopy system for brain and muscle hemodynamic monitoring
CN103750829A (zh) 一种多参数生理指征检测装置
WO2002065090A3 (fr) Mesure non invasive du glucose en fonction des proprietes optiques du tissu
WO1999059464A1 (fr) Capteur optique non invasif avec regulation de temperature de tissu
US20220071520A1 (en) System for screening and diagnosis of diabetes
WO2005072599A1 (fr) Procede et appareil pour la detection non invasive du tissu d'organisme
JP5216709B2 (ja) 血糖値測定装置
WO2019184812A1 (fr) Procédé de sélection de l'intensité d'une source de lumière pour surveiller un analyte dans le sang, et dispositif associé
JP2005027821A (ja) 血糖値測定装置
US20100113899A1 (en) Alignment System for Optically Sampling a Hand
CN107303174A (zh) 一种互联网+光谱肿瘤临床医学诊断方法
RU2414854C2 (ru) Устройство для обеспечения постоянного контактного давления при отборе пробы
CN108553110A (zh) 测量人体血液成分含量的方法及其装置
CN107088055A (zh) 家用黄疸体温检测分析系统
CN114305407B (zh) 无创血糖仪
Kwok et al. Thermal imaging and analysis for breast tumor detection
CN109381197A (zh) 基于指关节多光谱影像的无创血糖检测装置及其检测方法
CN110575182A (zh) 用于检测血糖的方法及装置
CN108634964A (zh) 一种基于光谱的无创血糖仪
CN112587134A (zh) 一种无创血糖检定方法
CN108593593A (zh) 串行双红外光谱无创血糖测量装置
CN106137218B (zh) 一种非侵入红外复合吸收精测血糖变化的方法
Zhou et al. Influence of water on noninvasive hemoglobin measurement by Dynamic Spectrum

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 22836771

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE