WO2020187240A1 - 一种无创伤智能血糖测量仪 - Google Patents

一种无创伤智能血糖测量仪 Download PDF

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Publication number
WO2020187240A1
WO2020187240A1 PCT/CN2020/079934 CN2020079934W WO2020187240A1 WO 2020187240 A1 WO2020187240 A1 WO 2020187240A1 CN 2020079934 W CN2020079934 W CN 2020079934W WO 2020187240 A1 WO2020187240 A1 WO 2020187240A1
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Prior art keywords
infrared
blood glucose
finger
glucose meter
infrared light
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PCT/CN2020/079934
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English (en)
French (fr)
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邓庆平
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邓庆平
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Priority to CN202080032405.7A priority Critical patent/CN113811243A/zh
Priority to EP20739552.6A priority patent/EP3747363A4/en
Priority to US16/964,003 priority patent/US20220079477A1/en
Publication of WO2020187240A1 publication Critical patent/WO2020187240A1/zh

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    • 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
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0075—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0077—Devices for viewing the surface of the body, e.g. camera, magnifying lens
    • 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
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G06T7/0014—Biomedical image inspection using an image reference approach
    • G06T7/0016—Biomedical image inspection using an image reference approach involving temporal comparison
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10048—Infrared image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30101—Blood vessel; Artery; Vein; Vascular

Definitions

  • the invention relates to a blood glucose measuring instrument, in particular to a non-invasive intelligent blood glucose measuring instrument.
  • non-invasive blood glucose meters There are also some so-called “non-invasive” blood glucose meters. Although it does not require users to collect blood to detect blood sugar by traditional methods, in the initial stage of using the blood glucose meters, users still need to collect blood through traditional methods to establish their own blood sugar. The corresponding model of the indicator value. This is not a true "non-invasive" blood glucose meter.
  • a non-invasive intelligent blood glucose measuring instrument which includes a near-infrared image acquisition device and a processor, wherein
  • the near-infrared picture acquisition device is used to collect near-infrared pictures of the human body
  • the processor is used for the processing, comparison and result calibration of the near-infrared photos, and then outputs the user's blood glucose measurement result.
  • the non-invasive intelligent blood glucose meter further includes an input and output device for the user to manipulate and display information.
  • the non-invasive intelligent blood glucose meter further includes an external device and an interface for communicating with the external device, and the external device communicates with other components of the non-invasive intelligent blood glucose meter in a wired and/or wireless manner .
  • the near-infrared picture acquisition device is a finger near-infrared picture acquisition device for collecting near-infrared pictures of a user's finger.
  • the near-infrared image acquisition device includes a near-infrared camera, a near-infrared light source component and a limb fixing device.
  • the finger near-infrared picture acquisition device includes a near-infrared camera, a near-infrared light source component and a finger fixing device.
  • the near-infrared light source component includes one or more sets of near-infrared lamps emitting near-infrared light of different wavelengths.
  • the near-infrared light source component includes three sets of near-infrared lamps emitting near-infrared light of different wavelengths.
  • the near-infrared picture acquisition device sequentially collects three sets of near-infrared pictures with different wavelengths.
  • the wavelength selection range of the near-infrared light emitted by the near-infrared light source component is 700-1800 nm.
  • the first wavelength selection range of the near-infrared light emitted by the near-infrared light source component is between 700-800 nm
  • the second wavelength selection range is between 800-900 nm
  • the third wavelength selection range is between 900-1000 nm. between.
  • the first wavelength selection range of the near-infrared light emitted by the near-infrared light source component is between 750-800 nm
  • the second wavelength selection range is between 850-900 nm
  • the third wavelength selection range is between 950-1000 nm. between.
  • the near-infrared camera is arranged on one side of the finger fixing device, and the near-infrared light source component is arranged on the other side of the finger fixing device.
  • the near-infrared camera is arranged below the finger fixing device, and the near-infrared light source component is arranged above the finger fixing device.
  • the near-infrared camera and the finger fixing device are separated by transparent glass.
  • the finger fixing device includes a U-shaped groove.
  • a switch is provided at a position corresponding to the fingertip of the U-shaped groove for starting the collection of near-infrared images of the finger.
  • the switch is a touch sensitive switch.
  • the bottom of the U-shaped groove is hollow.
  • the processor includes an image processing module and a comparison and calibration module.
  • the processor further includes a data management module.
  • the image processing module processes the collected near-infrared images and transmits them to the comparison and calibration module for comparison and calibration.
  • the image processing includes associating the collected near-infrared image with the near-infrared wavelength at the time of shooting.
  • the comparison and calibration module is obtained by using artificial intelligence machine learning algorithms and a large amount of training data to train on a computer with powerful computing capabilities.
  • the artificial intelligence machine learning algorithm is a deep learning algorithm.
  • the computer with powerful computing capability is a GPU computer.
  • the training data includes the finger near-infrared light map of the collected person and the corresponding blood glucose index, and the wavelength of the near-infrared light corresponding to the finger near-infrared light map used in the training data is the same as that of the finger near-infrared image collection.
  • the wavelength of the near-infrared light used in the device is the same.
  • the comparison and calibration module is configured to be able to operate normally without a network.
  • the data management module is used to manage the user's information and analyze the historical data of the blood glucose level measured by the user.
  • the non-invasive intelligent blood glucose measuring instrument of the present invention can collect the near-infrared picture of the finger and send it to the comparison and calibration module, thereby obtaining the user's blood glucose indicators directly and in real time, without blood samples or blood stains, and no trauma, For users, there is no tingling, no risk of infection and cross-infection.
  • the use of the non-invasive intelligent blood glucose meter of the present invention does not need to produce consumables, does not produce disposable products or hazardous waste, the number of times the user can use is not limited, and the use cost will not increase, thereby reducing the finances of diabetic patients. Stress improves their quality of life and can also be a reminder to help potential diabetic people avoid becoming "forever" diabetic.
  • the non-invasive intelligent blood glucose meter of the present invention is convenient to carry and simple to operate. It can be used anytime and anywhere, whether at home, in an office or even other public places, which greatly facilitates users.
  • the non-invasive intelligent blood glucose meter of the present invention can record the historical results of users, help doctors analyze, research and formulate treatment methods.
  • One instrument can also be used by multiple people or the whole family without causing mutual infection and data results. Confusion, these have also greatly improved the user experience and quality of life.
  • Figure 1a schematically shows a functional framework diagram of an atraumatic intelligent blood glucose meter according to an embodiment of the present invention
  • Figure 1b schematically shows the structure of the non-invasive intelligent blood glucose meter in Figure 1a;
  • Fig. 2 schematically shows a flow chart of the use of the non-invasive intelligent blood glucose meter in an embodiment of the present invention.
  • the non-invasive intelligent blood glucose meter 100 includes: a processor 1, an input and output device 2, a finger near-infrared image acquisition device 3, and an external device 4.
  • the finger near-infrared picture acquisition device 3 collects near-infrared pictures of the user's fingers (pictures taken by a near-infrared camera under near-infrared light), and then these pictures are transmitted to the processor 1 for processing, and the comparison is completed in the processor 1. After calibration, output the result.
  • the result can be displayed in the input and output device 2 integrated into the non-invasive smart blood glucose meter 100, or can be transmitted to an external external device 4.
  • the input/output device 2 and the external device 4 may not be included. In this embodiment, they are described together for the purpose of detail, but this does not mean that these components are necessary.
  • the finger near-infrared image acquisition device 3 includes a near-infrared camera 31, a near-infrared light source component 32 and a finger fixing device 33.
  • the near-infrared camera 31 is used to take a near-infrared picture of the finger
  • the near-infrared light source component 32 is used to emit near-infrared light to the user's finger so that the near-infrared camera 31 takes a picture.
  • the near-infrared light source component 32 emits three different wavelengths of near-infrared light accordingly, and the near-infrared camera 31 sequentially takes three near-infrared pictures with different wavelengths.
  • near-infrared light is preferably used in this embodiment, it is also possible to use light of other frequency bands on the spectrum in other embodiments, and these alternative solutions should not be excluded from the scope of the present invention. It should also be understood that although it is preferred to collect photos of three different wavelengths of near-infrared light in this embodiment, in other embodiments, one, two, or four, five or more different wavelengths of photos are also used. Yes, these alternatives should not be excluded from the scope of the present invention.
  • the near infrared light source component 32 is located above the finger fixing device 33, and the near infrared camera 31 is located below the finger fixing device 33.
  • a layer of transparent glass is separated between the finger fixing device 33 and the near infrared camera 31.
  • the transparent glass plays a dust-proof effect on the near-infrared camera 31; the near-infrared camera 31 can photograph the finger through the glass.
  • the "up" and “down” in this embodiment only indicate the relative positions of the components.
  • the near-infrared light source component 32 can also be located on the left side of the finger fixing device 33, and near The infrared camera 31 is located on the right side of the finger fixing device 33.
  • the position of one side and the other side is preferably a position directly opposite, but in some implementation forms, it may deviate from the position directly opposite to a certain extent.
  • the near-infrared light source component 32 can illuminate the user’s finger, and the near-infrared camera 31 takes a picture of the near-infrared light passing through the finger, these solutions should not be excluded from the present invention. Out of scope.
  • the finger holding device 33 is a "U-shaped" groove with a hollow bottom.
  • the top of the "U-shape" (the position corresponding to the fingertip) is provided with a capacitive sensor touch switch, and its sensor touch function is triggered by a capacitive sensor chip circuit installed there.
  • the finger fixing device 33 may not be U-shaped, but may have other suitable shapes; its bottom is not necessarily hollow, as long as the near-infrared camera 31 can capture the near-infrared light passing through The photo behind the finger is fine; the inductive touch switch does not have to be set at the top of the U shape, and other suitable positions are also possible.
  • inductive touch switch in this embodiment is capacitive, other forms of inductive touch switches are also possible; and, even other forms of switches, such as mechanical switches, light-sensitive switches, or voice-activated switches, are all available. It works. None of these alternatives should be excluded from the scope of the present invention.
  • the near-infrared light source component 32 includes three groups of near-infrared lamps, wherein each group includes one or more near-infrared lamps, preferably each group includes 8-12 near-infrared lamps. Each group of near-infrared lights can emit near-infrared light of that group of wavelengths when it is turned on. When the near-infrared camera 31 starts the shooting process, each group of wavelength near-infrared lamps is turned on in turn, and the near-infrared picture of the finger at the wavelength is taken accordingly.
  • the near-infrared light source component 32 turns on the near-infrared light of the first wavelength
  • the near-infrared camera 31 takes a picture of the near-infrared light of the finger at the first wavelength
  • the near-infrared light source component 32 turns on the near-infrared light of the second wavelength
  • the near-infrared camera 31 takes a photo of near-infrared light of the finger at the second wavelength
  • the near-infrared light source component 32 turns on the near-infrared light of the third wavelength
  • the near-infrared camera 31 takes a photo of the near-infrared light of the finger at the third wavelength.
  • the entire photographing process takes less than 1 second.
  • the user can remove the finger from the finger fixing device 33 by himself.
  • the aforementioned light-emitting and photographing processes can be completed automatically once started, while in other embodiments, the process can also be controlled by the user, for example, through the aforementioned switch or another switch. Take control.
  • the user may be prompted by light or sound, for example, by the input/output device 2 or the external device 4 of the non-invasive smart blood glucose meter 100; Of course, you can also set a reminder light or horn to remind you. None of these alternatives should be excluded from the scope of the present invention.
  • the three different wavelengths of the near-infrared light source component 32 are all between 700-1800 nm.
  • the first wavelength is set between 700-800nm
  • the second wavelength is set between 800-900nm
  • the third wavelength is set between 900-1000nm.
  • the first wavelength is set between 750-800 nm
  • the second wavelength is set between 850-900 nm
  • the third wavelength is set between 950-1000 nm.
  • the processor 1 is preferably a CPU processor, which includes an image processing module 11, a comparison and calibration module 12, and a data management module 13.
  • the image processing module 11 processes the near-infrared image collected in the finger near-infrared image acquisition device 3 and transmits it to the comparison and calibration module 12 for comparison and calibration, and the result of the comparison and calibration module 12 is output to the data management module 13, where The data is analyzed and output to the input/output device 2 or the external device 4 to the user.
  • the collected near-infrared images are associated with the near-infrared wavelengths at the time of shooting, and the comparison and calibration module 12 will compare and calibrate the images based on specific wavelength information.
  • the comparison and calibration module 12 reflects the corresponding blood glucose index through three near-infrared images with different wavelengths, and obtains the final blood glucose index through comparison and calibration.
  • the program for controlling the finger near-infrared image acquisition device 3 to take pictures can also be integrated into the image processing module 11.
  • the functions of the image processing module 11 can also be integrated into the comparison and calibration module 12, or directly integrated into the finger near-infrared image acquisition device 3.
  • the comparison and calibration module 12 is obtained by using artificial intelligence machine learning algorithms, such as deep learning algorithm training, and the processed near-infrared image is sent to the comparison and calibration module 12 to obtain the corresponding user Blood sugar level.
  • the comparison and calibration module 12 is based on a large amount of raw data specially collected and accurately arranged and matched as basic training data, and then it is obtained by applying deep learning algorithm training on a computer with powerful computing capability, such as a GPU computer.
  • the raw data includes the near-infrared light image of the person's finger and the corresponding blood glucose index.
  • the wavelength of the near-infrared light corresponding to the finger near-infrared light map used in the training data is the same as the wavelength of the near-infrared light used in the finger near-infrared image collection device 3.
  • the near-infrared image of the finger in the training data is also collected using three different wavelengths between 700 and 1800 nm.
  • three different wavelengths between 700-800 nm, 800-900 nm, and 900-1000 nm are used for collection.
  • More preferably, three different wavelengths between 750-800nm, 850-900nm, and 950-1000nm are used for collection.
  • the corresponding blood glucose index values of the collected training data are distributed between 3.6 and 22.0 with a span of 0.1.
  • For each blood glucose value at least 40 pictures are collected at each wavelength.
  • other numerical range distributions and spans, and the number of collected photos can all be adjusted. None of these alternatives should be excluded from the scope of the present invention.
  • the trained model (engine) is embedded in the comparison and calibration module 12, and the user's blood glucose level can be directly calculated after sending the user's near-infrared picture.
  • the trained model also ensures that the blood glucose meter of the present invention can work without a network, that is, all measurement, calculation, and storage tasks can be done locally in the blood glucose meter without the intervention of the cloud (such as cloud storage). , Cloud computing, etc.); Of course, the blood glucose meter of the present invention does not exclude cooperation with cloud devices.
  • the data management module 13 is used to manage the relevant information of the user and perform relevant analysis on the historical data of the blood glucose level measured by the user.
  • the data management module 13 may include a user information registration sub-module for registering basic user information.
  • the basic information includes user name, age, gender, home address, and other additional instructions.
  • multiple users can be registered through the user information registration submodule.
  • the data management module 13 may also include a historical data analysis sub-module, through which a historical database of blood glucose measurement can be established for each user, and can be output to the input and output device 2 and / Or feedback to the user on the external device 4.
  • specific health care suggestions can be given for the user's current measurement data and historical data changes, and these suggestions can also be output to the input and output device 2 and/or the external device 4 for feedback to the user.
  • the data management module 13 may not be included. In this embodiment, they are described together for the purpose of detail, but this does not mean that these modules are necessary.
  • the input and output device 2 is a touch screen, and it, the processor 1 and the finger near-infrared image acquisition device 3 are all installed on the main body of the non-invasive intelligent blood glucose meter 100.
  • the input and output device 2 is used for inputting, editing and presenting each user's personal information and its blood glucose measurement status, historical data, analysis results and nursing advice.
  • the input and output device 2 can directly output the result according to the user's setting, or output the result in combination with historical data and/or care advice. If there is no measurement result, the input/output device 2 can give a prompt for the user to measure again.
  • the input and output device 2 may be, for example, a capacitive or resistive touch screen. In other embodiments, it may also be a traditional form of non-touch screen plus physical buttons, or an input and output form using voice. None of these alternatives should be excluded from the scope of the present invention.
  • the external device 4 can be the user's own mobile phone, Pad computer or PC computer. In a preferred embodiment, it communicates with the processor 1 in a wired or wireless manner, and a corresponding interface or communication module is set on the non-invasive intelligent blood glucose meter 100 to communicate with it; if necessary, the corresponding APP program or API program.
  • Wireless methods include, for example, WiFi, Bluetooth, Zigbee, etc., and also include, for example, 3G, 4G, and 5G.
  • the external device 4 can also be a component produced and sold together with other components of the non-invasive smart blood glucose meter 100, but is independent of the main body of the non-invasive smart blood glucose meter 100.
  • the input and output device 2 can also be regarded as a kind of External device.
  • the input/output device 2 and the external device 4 are not mutually exclusive, and they can be used simultaneously. These alternatives should not be excluded from the scope of the present invention.
  • FIG. 2 schematically shows a flow chart of the use of the non-invasive intelligent blood glucose meter in an embodiment of the present invention.
  • the user first places the finger on the finger fixing device 33 of the finger near-infrared image acquisition device 3, triggers the switch to start collecting the finger’s near-infrared image, and the collected image is transmitted to the CPU processor 1 for processing. After processing, the near-infrared image spectrum is compared and calibrated to obtain the user's blood glucose level. If the user's blood glucose level cannot be obtained after processing by the CPU processor 1, the user is asked to place his finger again for collection and analysis. After obtaining the user's blood glucose level, the user can also select a time period to query the historical data of the blood glucose level and its analysis results during this period.
  • the present invention is explained by taking the example of collecting and analyzing near-infrared pictures of fingers, the present invention is not limited to only being performed based on the user's fingers. Other suitable methods, such as taking and analyzing pictures of palms or other limbs of the human body, are also possible. These alternatives should not be excluded from the scope of the present invention.

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Abstract

一种无创伤智能血糖测量仪(100)，包括近红外图片采集装置(3)和处理器(1)，其中，近红外图片采集装置(3)用于采集人体近红外照片，而处理器(1)用于近红外照片的处理、比对和校准然后输出使用者的血糖测量结果。使用时仅需将拍摄人体特定部位的近红外图片并送入处理器(1)即可获得血糖值。使用简便，可多人共享，没有耗材或污染，是真正的"无创伤"血糖测量仪。

Description

一种无创伤智能血糖测量仪 技术领域
本发明涉及一种血糖测量仪，具体来说，涉及一种无创伤智能血糖测量仪。
背景技术
众所周知，在世界范围内有数十亿的糖尿病人和潜在的糖尿病人。糖尿病已成为影响人们生命健康和生活质量的非常严重问题。糖尿病患者需要时常预防疾病的慢性和急性并发症，所以，糖尿病患者每天需要测量血糖多次。进一步，由于糖尿病病理的特殊性(血糖超过一个指标值后成为糖尿病人从此再也不可逆转)，所以，即使是潜在的糖尿病人也需要经常测量自己的血糖值以防自己成为“永远”的糖尿病人。目前，通常使用的血糖测量仪需要通过手指刺穿获取每次测试的血液，这引起疼痛和不便，下次测试还需要一个新的测试条，或者可以频繁/连续监视血糖指标的仪器目前确实存在，但是他们需要每两周左右做一次皮下植入，在植入时给使用者造成创伤或疼痛感，这些方法的使用者使用体验差，且因为有耗材而产生财务压力。
现在也有一些所谓的“无创伤”血糖仪，虽然它不需使用者用传统方法采血来检测血糖，但是在使用该血糖仪的初期，仍然需要使用者通过传统方法采血来建立使用者自己的血糖指标值的对应模型。这并不是真正的“无创伤”血糖仪。
因此，需要提供一种真正无创伤的血糖测量仪。
发明内容
根据本发明的一个主要方面，提供一种无创伤智能血糖测量仪，其包括近红外图片采集装置和处理器，其中
所述近红外图片采集装置用于采集人体在近红外照片，
所述处理器用于所述近红外照片的处理、比对和结果校准，然后输出使用者的血糖测量结果。
优选地，所述无创伤智能血糖测量仪还包括输入输出装置，用于使用者操控及显示信息。
优选地，所述无创伤智能血糖测量仪还包括外接装置以及与所述外接装置通信的接口，所述外接装置通过有线和/或无线的方式与所述无创伤智能血糖测量仪的其他部件通信。
优选地，所述近红外图片采集装置是手指近红外图片采集装置，用于采集使用者手指的近红外照片。
优选地，所述近红外图片采集装置包括近红外摄像头、近红外光源部件和肢体固定装置。
优选地，所述手指近红外图片采集装置包括近红外摄像头、近红外光源部件和手指固定装置。
优选地，所述近红外光源部件包括一组或多组发射不同波长的近红外光的近红外灯。
优选地，所述近红外光源部件包括三组发射不同波长的近红外光的近红外灯。
优选地，所述近红外图片采集装置依次采集三组不同波长的近红外照片。
优选地，所述近红外光源部件发射的近红外光的波长选择范围为700-1800nm。
优选地，所述近红外光源部件发射的近红外光的第一波长选择范围在700-800nm之间，第二波长选择范围在800-900nm之间，而第三波长选择范围在900-1000nm之间。
优选地，所述近红外光源部件发射的近红外光的第一波长选择范围在750-800nm之间，第二波长选择范围在850-900nm之间，而第三波长选择范围在950-1000nm之间。
优选地，所述近红外摄像头设置在所述手指固定装置的一侧，而所述近红外光源部件设置在所述手指固定装置的另一侧。
优选地，所述近红外摄像头设置在所述手指固定装置的下方，而所述近红外光源部件设置在所述手指固定装置的上方。
优选地，所述近红外摄像头与所述手指固定装置之间用透明玻璃隔开。
优选地，所述手指固定装置包括U形凹槽。
优选地，所述U形凹槽的与指尖对应的位置设置有开关，用于启动手指近红外图片的采集。
优选地，所述开关是触摸感应开关。
优选地，所述U形凹槽的底部是中空的。
优选地，所述处理器包括图片处理模块和比对校准模块。
优选地，所述处理器还包括数据管理模块。
优选地，所述图片处理模块将采集到的近红外图片进行处理后传送到所述比对校准模块进行比对校准。
优选地，所述图片处理包括将采集到的近红外图片与拍摄时的近红外波长进行关联。
优选地，所述比对校准模块是应用人工智能机器学习算法和大量的训练数据在计算能力强大的计算机上训练取得的。
优选地，所述人工智能机器学习算法是深度学习算法。
优选地，所述计算能力强大的计算机是GPU计算机。
优选地，所述训练的数据中包括被采集者的手指近红外光图及对应的血糖指标，而训练数据使用的手指近红外光图对应的近红外光的波长与所述手指近红外图片采集装置中所使用的近红外光的波长是一样的。
优选地，所述比对校准模块设置成能够在无网络的情况下正常运行。
优选地，所述数据管理模块用于管理使用者的信息，并对使用者测量的血糖值的历史数据进行分析。
本发明的无创伤智能血糖测量仪能够采集手指近红外图片并将其送入到比对与校准模块，从而直接、实时地获得使用者的血糖指标，无需血样或血渍，不需产生创伤，对使用者来说没有刺痛，也没有感染及交叉感染风险。而且，使用本发明的无创伤智能血糖测量仪也不需产生耗材，不产生一次性用品或危险废物，使用者的使用次数不受限制，使用费用也不会因此增加，减少了糖尿病人的财务压力从而提高他们的生活质量，并且也可以提醒帮助潜在的糖尿病人避免自己成为“永远”的糖尿病人。另外，本发明的无创伤智能血糖测量仪携带方便，操作简单，无论在家里还是在办公室甚至其他公共场所，都可以随时随地使用，极大地方便了使用者。再有，本发明的无创伤智能血糖测量仪可以记录使用者的历史结果，帮助医生分析研究与制定治疗方法，一台仪器还可多人或者全家使用，也不会产生相互感染和数据结果的混淆，这些也都极大地提升了使用者体验与生活质量。
附图说明
通过结合附图进行阅读，将会更好地了解以上概述以及以下详细描述。为了便于说明，附图中示出本公开的某些实施例。但是，应当理解，本发明并不局限于所示的准确布置和工具。结合到本说明书中并且构成其部分的附图示出按照本发明的***和设备的实现，并且连同本描述一起用来说明按照本发明的优点和原理。
图1a示意性地显示了根据本发明的一个实施例中的无创伤智能血糖测量仪的功能框架图；
图1b示意性地显示了图1a中的无创伤智能血糖测量仪的结构；
图2示意性地显示了根据本发明的一个实施例中的无创伤智能血糖测量仪的使用流程图。
具体实施方式
在详细说明本发明的至少一个实施例之前，要理解，本发明并不局限于它在以下描述中提出或者在附图中示出的构造的细节以及组件的布置的应用。提供附图和书面描述，以指导本领域的技术人员进行和使用对其寻求专利保护的本发明。本发明适用于其他实施例并且能够按照各种方式来实施和执行。本领域的技术人员将会理解，为了清楚起见和便于了解，并非示出一商业实施例的所有特征。本领域的技术人员还将会理解，结合本发明的方面的实际商业实施例的开发将要求许多实现特定判定来取得开发人员的商业实施例的最终目标。虽然这些工作会是复杂和费时的，但是这些工作是获益于本公开的领域的技术人员例行任务。
另外，要理解，本文所采用的用语和术语是为了便于描述，而不应当被视作限制。例如，单数术语、例如“一”、“一个”的使用不是意在限 制项的数量。另外，非限制性地诸如“顶部”、“底部”、“左”、“右”、“上”、“下”、“向下”、“向上”、“侧”之类的关系术语的使用为了清楚起见而具体参照附图用于本描述中，而不是意在限制本发明或者所附权利要求书的范围。此外，应当理解，本发明的特征的任一个可单独地或者与其他特征结合使用。通过阅读附图和详细描述，本领域的技术人员将会清楚地知道本发明的其他***、方法、特征和优点。预计所有这类其他***、方法、特征和优点都包含在本描述之内，包含在本发明的范围之内，并且受到所附权利要求书保护。
现在将参照附图来详细描述本发明的实现。
请参阅图1a，在本发明的一个实施例中，无创伤智能血糖测量仪100包括：处理器1、输入输出装置2、手指近红外图片采集装置3和外接装置4。其中，手指近红外图片采集装置3采集使用者手指的近红外照片(近红外照相机在近红外光下拍摄的照片)，然后这些图片被传输到处理器1中处理，在处理器1中完成比对和校准后，输出结果。结果可以显示在集成到无创伤智能血糖测量仪100的输入输出装置2中，也可以传输到外接的外接装置4中。
需要知道，在本发明的其它实施例中，可以不包括输入输出装置2和外接装置4。在本实施例中出于详尽的目的而将它们一起说明，但这并不意味着这些部件是必需的。
如图1a所示，手指近红外图片采集装置3包括近红外摄像头31、近红外光源部件32和手指固定装置33。近红外摄像头31用于拍摄手指的近红外图片，而近红外光源部件32用于向使用者的手指发出近红外光以便近红外摄像头31拍照。当使用者把手指正确地放在手指固定装置33上时，近红外光源部件32依此发出三种不同波长的近红外光，而近红外摄像头31则依次拍照三张不同波长的近红外图片。应当理解， 虽然在本实施例中优选采用的是近红外光，在其他实施例中采用光谱上其他频段的光也是可以的，这些备选方案不应排除在本发明的范围之外。还应当理解，虽然本实施例中优选采集三种不同波长的近红外光下的照片，在其他实施例中采用一种、两种、或四种、五种甚至更多的不同波长的照片也是可以的，这些备选方案也不应排除在本发明的范围之外。
参见图1b，近红外光源部件32位于手指固定装置33的上方，而近红外摄像头31位于手指固定装置33的下方。手指固定装置33与近红外摄像头31之间隔着一层透明玻璃。透明玻璃对近红外摄像头31起到防尘作用；近红外摄像头31可以透过玻璃拍摄到手指。再次强调，本实施例中的“上”、“下”只是表明部件之间的相对位置，在其他实施例中，也可以例如使近红外光源部件32位于手指固定装置33的左侧，而近红外摄像头31位于手指固定装置33的右侧。当然，这种一侧和另一侧的位置，优选是正对面的位置，但在一些实施形式中也可以是偏离正对面的位置一定范围。本领域普技术人员应当明白，只要近红外光源部件32能够照射到使用者的手指，而使近红外摄像头31拍摄到近红外光穿过手指后的照片，这些方案就不应排除在本发明的范围之外。
手指固定装置33是一个“U形”的凹槽，其底部是空的。“U形”的顶端(与指尖对应的位置)设置有电容式的感应触摸开关，其感应触摸功能是由一块安装在那里的电容感应芯片电路触发。需要明白，在其他实施例中，手指固定装置33也可以不是U形的，是其他合适的形状；其底部也并不一定是中空的，只要能使近红外摄像头31拍摄到近红外光穿过手指后的照片即可；感应触摸开关也不一定要设置在U形的顶端，其他合适的位置也都是可以的。还需要明白，虽然在本实施例中感应触摸开关是电容式的，但其他形式的感应触摸开关也是可以的；并且， 即使是其他形式的开关，例如机械开关、光敏开关或是声控开关也都是可行的。这些备选方案都不应该排除在本发明的范围之外。
当手指顶端碰到该顶端的开关时，就会开启拍摄近红外图片的过程。近红外光源部件32包括三组近红外灯，其中每组都包括一只或多只近红外灯，优选的是每组包括8-12只近红外灯。每组近红外灯开启时可以发出该组波长的近红外光。当近红外摄像头31开始拍摄过程时，依次开启各组波长近红外灯，并依此拍摄该波长下的手指近红外图片。具体来说，近红外光源部件32会打开第一波长的近红外光，近红外摄像头31拍摄第一波长下的手指近红外光照片，然后近红外光源部件32打开第二波长的近红外光，近红外摄像头31拍摄第二波长下的手指近红外光照片，再然后近红外光源部件32会打开第三波长的近红外光，近红外摄像头31拍摄第三波长下的手指近红外光照片。在优选的实施例中，整个拍照过程连1秒钟都不到。拍照结束后，使用者可以自行将手指从手指固定装置33上移开。需要明白，在一些实施例中，前述发光和拍照的过程一经启动就可以是自动完成的，而在另一些实施例中，该过程也可以由使用者控制，例如通过前述开关或者另设的开关进行控制。还需要明白，在一些实施例中，拍照结束后，可以用光或声的方式向使用者发出提示，例如，在无创伤智能血糖测量仪100的输入输出装置2或者外接装置4上发出提示；当然，也可以设置提示灯或者喇叭来进行提示。这些备选方案都不应该排除在本发明的范围之外。
近红外光源部件32的三个不同的波长都在700～1800nm之间。在优选的实施例中，第一波长设置在700-800nm之间，第二波长设置在800-900nm之间，而第三波长设置在900-1000nm之间。在更优选的实施例中，第一波长设置在750-800nm之间，第二波长设置在850-900nm之间，而第三波长设置在950-1000nm之间。
如图1a所示，处理器1优选的是一个CPU处理器，其中包括图片处理模块11、比对校准模块12和数据管理模块13。图片处理模块11将手指近红外图片采集装置3中采集到的近红外图片进行处理后传送到比对校准模块12进行比对校准，而比对校准模块12的结果输出到数据管理模块13，在其中将数据分析后输出到输入输出装置2或者外接装置4上给使用者。
在图片处理模块11中，将采集到的近红外图片与拍摄时的近红外波长进行关联，在比对校准模块12将基于具体的波长信息对图片进行比对校准。在优选的实施例中，比对校准模块12通过三张不同波长的近红外图片反映对应的血糖指标，并经比对校准得出最终血糖指标。在一些实施例中，可以把控制手指近红外图片采集装置3拍照的程序也集成到图片处理模块11中。当然，也可以把图片处理模块11的功能集成到比对校准模块12中，或是直接集成到手指近红外图片采集装置3上。
在优选的实施例中，比对校准模块12是利用人工智能机器学习算法、例如深度学习算法训练取得的，将处理后的近红外图片送入比对校准模块12即可获得相对应的使用者的血糖值。具体来说，比对校准模块12是基于专门采集的大量原始数据并经准确整理匹配后作为基础训练数据，然后在计算能力强大的计算机、例如GPU计算机上应用深度学习算法训练得到。原始数据中包括被采集者的手指近红外光图及对应的血糖指标。训练数据使用的手指近红外光图对应的近红外光的波长与手指近红外图片采集装置3中所使用的近红外光的波长是一样的。例如，训练数据中的手指近红外图片也利用700～1800nm之间的三个不同的波长来采集。优选地，利用在700-800nm之间、800-900nm之间以及900-1000nm之间的三个不同的波长来采集。更优选地，利用在750-800nm之间、850-900nm之间以及950-1000nm之间的三个不同的波 长来采集。
在优选的实施例中，采集的训练数据的对应血糖指标值分布在3.6～22.0之间，跨度为0.1，针对每个血糖值，在每个波长下采集至少40张图片。当然，应当明白，其他的数值范围分布和跨度，以及采集照片的数量都是可以调整的。这些备选方案都不应该排除在本发明的范围之外。
在优选的实施例中，训练好之后的模型(引擎)被嵌入到比对校准模块12中，在送入使用者的近红外图片之后，就可以直接算出使用者的血糖值。这就无需使用者用传统方法采血来检测血糖，也无需使用者像使用其他并非纯粹的“无创伤”血糖仪一样，在初始阶段用传统方法采血建立使用者自己本人的血糖指标值的对应模型。同时，训练好的模型也保证了本发明的血糖仪能够在无网络的情况下工作，即所有的测量、计算、存储工作都可以在血糖仪本地完成，而不需要云端的介入(例如云存储、云计算等)；当然，本发明的血糖仪并不排斥与云端装置的合作。
数据管理模块13用于管理使用者的相关信息，并对使用者测量的血糖值的历史数据进行相关分析。在数据管理模块13中，可以包括使用者信息注册子模块，用于登记使用者的基本信息，这些基本信息包括使用者姓名、年龄、性别、家庭地址以及其它附加说明。优选的情况下，通过使用者信息注册子模块可以注册多个使用者。在数据管理模块13中，还可以包括历史数据分析子模块，通过该子模块，可以针对每个使用者建立其血糖值测量的历史数据库，并可以以适当的图表形式输出到输入输出装置2和/或外接装置4上反馈给使用者。同时针对使用者的当前测量数据以及历史数据的变化还可以给出针对性的健康护理建议，这些建议也可以输出到输入输出装置2和/或外接装置4上反馈给使用者。
应当明白，在本发明的其它实施例中，可以不包括数据管理模块13的部分或全部。在本实施例中出于详尽的目的而将它们一起说明，但这并不意味着这些模块是必需的。
如图1b所示，输入输出装置2是一块触摸屏，它和处理器1以及手指近红外图片采集装置3都安装在无创伤智能血糖测量仪100的主体上。输入输出装置2用于输入编辑和呈现每位使用者的个人信息及其测量血糖的情况、历史数据、分析结果及护理建议。在有测量结果时，输入输出装置2可以根据使用者的设置直接输出结果，或结合历史数据和/或护理建议一起输出。如果没有测量结果，输入输出装置2可以给出提示让使用者再次测量。应当明白，输入输出装置2可以是例如电容式或电阻式的触摸屏，在其他实施例中，也可以是非触摸屏加上物理按钮的传统形式，或者是利用语音的输入输出形式。这些备选方案都不应该排除在本发明的范围之外。
外接装置4可以是使用者自己的手机、Pad电脑或PC电脑。在优选的实施例中，它通过有线或无线的方式与处理器1通信，在无创伤智能血糖测量仪100上会设置相应的接口或通信模块与之通信；如有必要，还会使用对应的APP程序或者API程序。无线的方式包括例如WiFi、蓝牙、Zigbee等，也包括例如3G、4G、5G等。当然，外接装置4也可以是和无创伤智能血糖测量仪100的其他部件一起生产和销售的部件，只是独立于无创伤智能血糖测量仪100的主体。本领域普通技术人员应当明白，如果把前述的输入输出装置2也设置在无创伤智能血糖测量仪100的主体之外，则从某种意义上来说，输入输出装置2也可以被看作一种外接装置。本领域普通技术人员还应当明白，输入输出装置2和外接装置4并不是互斥的，它们可以同时使用。这些备选方案也不应该排除在本发明的范围之外。
参见图2，其中示意性地显示了根据本发明的一个实施例中的无创伤智能血糖测量仪的使用流程图。如图所示，使用者首先将手指放置在手指近红外图片采集装置3的手指固定装置33上，触发开关开始采集手指近红外图片，采集好的图片被传送至CPU处理器1，在其中进行处理后进行近红外图片光谱的比对与校准，得到使用者的血糖值。如果CPU处理器1处理后得不到使用者的血糖值，则请使用者再次放置手指进行采集和分析。得到使用者的血糖值后，使用者还可以选择时间段查询这段时间内的血糖值的历史数据及其分析结果。
需要明白，虽然在上述实施例中，以采集和分析手指近红外图片的例子来阐释本发明，但本发明并不仅仅局限于只能根据使用者手指来进行。其他合适的方式，例如拍摄采集和分析手掌或人体其他肢段的图片也是可以行的。这些备选方案不应该排除在本发明的范围之外。
另外，本领域普通技术人员应当明白，由于软硬件(包括固件)结合的多样性，一种软件功能并不必然只由一个硬件实施，多种软件功能既可以集成在一个硬件中实现，也可以分散在多个硬件中实现。如非特别说明，硬件的分离或集成并不对软件的功能构成限制。特别地，由于云存储和云计算技术的发展，有些功能既可以在本地实现，也可以在“云”上实现，或者兼而有之。如非特别说明，这些替代方案都不应该排除在本发明的范围之外。
本领域的技术人员将会理解，可对上述实施例进行变更，而不背离其广义的发明概述。因此要理解，本文所公开的本发明并不局限于所公开的具体实施例，而是意在涵盖如所附权利要求书所限定的本发明的精神和范围之内的所有变体。另外，即使是按照本发明中所公开的实施例来解读所附权利要求书所限定的本发明的精神和范围，除非申请人做出特别说明，否则不应当适用捐献原则对本发明的本发明的精神和范围进 行取舍。

Claims (15)

  1. 一种无创伤智能血糖测量仪，其包括近红外图片采集装置和处理器，其中，
    所述近红外图片采集装置用于采集人体近红外照片，而
    所述处理器用于所述近红外照片的处理、比对和结果校准，然后输出使用者的血糖测量结果。
  2. 根据权利要求1所述的无创伤智能血糖测量仪，其特征在于，还包括输入输出装置，用于使用者操控及显示信息。
  3. 根据权利要求1所述的无创伤智能血糖测量仪，其特征在于，还包括外接装置以及与所述外接装置通信的接口，所述外接装置通过有线和/或无线的方式与所述无创伤智能血糖测量仪的其他部件通信。
  4. 根据权利要求1所述的无创伤智能血糖测量仪，其特征在于，所述近红外图片采集装置是手指近红外图片采集装置，用于采集使用者手指近红外照片。
  5. 根据权利要求4所述的无创伤智能血糖测量仪，其特征在于，所述手指近红外图片采集装置包括近红外摄像头、近红外光源部件和手指固定装置。
  6. 根据权利要求5所述的无创伤智能血糖测量仪，其特征在于，所述近红外光源部件包括一组或多组发射不同波长的近红外光的近红外灯。
  7. 根据权利要求5所述的无创伤智能血糖测量仪，其特征在于，所述近红外光源部件包括三组发射不同波长的近红外光的近红外灯。
  8. 根据权利要求7所述的无创伤智能血糖测量仪，其特征在于，所述近红外图片采集装置依次采集三组不同波长的近红外照片。
  9. 根据权利要求5所述的无创伤智能血糖测量仪，其特征在于，所述近红外光源部件发射的近红外光的波长选择范围为700-1800nm。
  10. 根据权利要求5所述的无创伤智能血糖测量仪，其特征在于，所述近红外摄像头设置在所述手指固定装置的一侧，而所述近红外光源部件设置在所述手指固定装置的另一侧。
  11. 根据权利要求5所述的无创伤智能血糖测量仪，其特征在于，所述近红外摄像头与所述手指固定装置之间用透明玻璃隔开。
  12. 根据权利要求5所述的无创伤智能血糖测量仪，其特征在于，所述手指固定装置包括U形凹槽；并且
    所述U形凹槽的与指尖对应的位置设置有开关，用于启动手指近红外图片的采集。
  13. 根据权利要求1所述的无创伤智能血糖测量仪，其特征在于，所述处理器包括图片处理模块和比对校准模块，其中
    所述图片处理模块将采集到的近红外图片进行处理后传送到所述比对校准模块进行比对校准；
    所述图片处理包括将采集到的近红外图片与拍摄时的近红外波长进行关联。
  14. 根据权利要求13所述的无创伤智能血糖测量仪，其特征在于，所述比对校准模块是应用人工智能机器学习算法和大量的训练数据在计算能力强大的计算机上训练取得的；
    所述训练数据中包括被采集者的手指近红外光图及对应的血糖指标，而训练数据使用的手指近红外光图对应的近红外光的波长与所述手指近红外图片采集装置中所使用的近红外光的波长是一样的。
  15. 根据权利要求14所述的无创伤智能血糖测量仪，其特征在于，所述比对校准模块设置成能够在无网络的情况下正常运行。
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Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109965886A (zh) * 2019-03-21 2019-07-05 邓庆平 一种无创伤智能血糖测量仪
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110082711A1 (en) * 2009-10-06 2011-04-07 Masimo Laboratories, Inc. Personal digital assistant or organizer for monitoring glucose levels
CN106037760A (zh) * 2016-06-30 2016-10-26 武汉市明安创科科技有限公司 一种无创血糖仪的连续血糖监测***
CN107361776A (zh) * 2017-05-20 2017-11-21 深圳市前海安测信息技术有限公司 无创血糖检测***及方法
CN107689040A (zh) * 2017-07-18 2018-02-13 深圳市科迈爱康科技有限公司 血糖检测的移动终端
CN108024745A (zh) * 2015-09-25 2018-05-11 桑米纳公司 生物传感器监测和跟踪带的***和方法
CN109965886A (zh) * 2019-03-21 2019-07-05 邓庆平 一种无创伤智能血糖测量仪

Family Cites Families (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5424545A (en) * 1992-07-15 1995-06-13 Myron J. Block Non-invasive non-spectrophotometric infrared measurement of blood analyte concentrations
CN100342825C (zh) * 2005-11-28 2007-10-17 何宗彦 无创快速血糖检测方法及其检测仪
US8203704B2 (en) * 2008-08-04 2012-06-19 Cercacor Laboratories, Inc. Multi-stream sensor for noninvasive measurement of blood constituents
CN101548892B (zh) * 2009-04-29 2010-12-29 天津市先石光学技术有限公司 植入式在体连续血糖监测装置
GB0915775D0 (en) * 2009-09-09 2009-10-07 Univ Gent Implantable sensor
CN104739421A (zh) * 2015-04-09 2015-07-01 深圳市一体太赫兹科技有限公司 血糖检测方法和装置
CN105718925A (zh) * 2016-04-14 2016-06-29 苏州优化智能科技有限公司 基于近红外和面部微表情的真人活体身份验证终端设备
CN106308814A (zh) * 2016-08-09 2017-01-11 上海润寿智能科技有限公司 基于近红外光谱分析的血糖无创检测仪及其实现方法
CN206775560U (zh) * 2017-05-25 2017-12-19 云狐科技(沈阳)有限公司 一种具有多项人体生理参数检测功能的手机
CN107505268A (zh) * 2017-08-04 2017-12-22 中国科学院半导体研究所 血糖检测方法及***
US10687739B2 (en) * 2017-09-05 2020-06-23 Cnoga Medical Ltd. Method and apparatus for non-invasive glucose measurement
CN107360279A (zh) * 2017-09-05 2017-11-17 陈银芳 一种带血糖测量功能的移动终端
CN208551781U (zh) * 2017-11-09 2019-03-01 广州迪克医疗器械有限公司 基于智能手机的生理数据监测***
CN108175416A (zh) * 2018-01-09 2018-06-19 电子科技大学 一种多传感器血糖检测数据融合装置及方法
CN109381197A (zh) * 2018-09-06 2019-02-26 北京大学 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
CN214761095U (zh) * 2020-07-17 2021-11-19 苏州优化医疗科技有限公司 一种无创伤智能血糖测量仪

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110082711A1 (en) * 2009-10-06 2011-04-07 Masimo Laboratories, Inc. Personal digital assistant or organizer for monitoring glucose levels
CN108024745A (zh) * 2015-09-25 2018-05-11 桑米纳公司 生物传感器监测和跟踪带的***和方法
CN106037760A (zh) * 2016-06-30 2016-10-26 武汉市明安创科科技有限公司 一种无创血糖仪的连续血糖监测***
CN107361776A (zh) * 2017-05-20 2017-11-21 深圳市前海安测信息技术有限公司 无创血糖检测***及方法
CN107689040A (zh) * 2017-07-18 2018-02-13 深圳市科迈爱康科技有限公司 血糖检测的移动终端
CN109965886A (zh) * 2019-03-21 2019-07-05 邓庆平 一种无创伤智能血糖测量仪

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP3747363A4 *

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