Non-invasive blood lipid detection device and detection method thereof, and smart wearable device

Abstract

The application provides a non-invasive blood lipid detection device and a detection method thereof and a smart wearable device, and relates to the technical field of non-invasive optical detection. The non-invasive blood lipid detection device comprises a carrier, a detection unit and a processing unit which are arranged on the carrier and electrically connected. The detection unit comprises a detection light source and a light signal receiver which are arranged in sequence along the length direction of a target detection position. The detection light source emits two groups of detection light with non-overlapping wavelength ranges towards the target detection position. The detection light is visible light to infrared optical radiation. The light signal receiver receives two groups of reflected light with different wavelength ranges which carry information of the target detection position. The processing unit extracts backscattering light signals in the two groups of reflected light with different wavelength ranges, retrieves pre-stored physiological information parameters, calculates blood absorption coefficients and blood scattering coefficients, and calculates and outputs corresponding blood lipid parameter information. The non-invasive blood lipid detection device can adapt to the optical characteristics of blood, the detection result is accurate, and the device is convenient and easy to operate.

Description

Technical Field

[0001] This application relates to the field of non-invasive optical detection technology, and more specifically, to a non-invasive blood lipid detection device and its detection method, and a smart wearable device. Background Technology

[0002] Currently, non-invasive optical detection technology has gradually matured and been applied to wearable devices. Various pulse oximeters and smartwatches on the market rely on transmission optical principles to achieve non-invasive real-time monitoring of pulse, blood oxygen saturation, and other parameters. In addition, in some cutting-edge fields of existing technology, wearable solutions have been proposed to achieve non-invasive estimation of blood pressure and blood sugar based on optical sensing, greatly lowering the threshold for detecting human physiological indicators and offering the advantages of home-based, continuous monitoring. However, for blood lipid indicators, the current clinical standard method is still an invasive venous blood sampling test: subjects need to fast for 5-8 hours before intermittent blood draws, and parameters such as triglycerides and lipoproteins are analyzed by biochemical instruments. The testing process is cumbersome, requires subjects to undergo multiple punctures, involves puncture pain, and cannot achieve short-term, continuous, dynamic monitoring of postprandial blood lipid fluctuations.

[0003] In existing research on non-invasive optical detection technologies, there are significant technical limitations in measuring blood lipid parameters: the traditional Beer-Lambert direct transmission method is only suitable for clear media, while blood is a highly turbid scattering medium. Furthermore, the thickness of human skin and subcutaneous tissue makes it difficult for the transmission light path to effectively extract the optical signals of lipoproteins in the blood. Rayleigh scattering and geometric scattering models also cannot match the micron-sized particles such as chylomicrons (CM) and low-density lipoproteins (VLDL) in blood.

[0004] Existing blood testing devices using backscattering detection technology cannot separate the mixed reflected light signals from subcutaneous tissue and vascular blood. Scattering noise from subcutaneous tissue can severely interfere with the calculation of lipoprotein turbidity. Conventional diffusion approximation models are only applicable to tissues where scattering is much greater than absorption. In blood, the scattering coefficient and absorption coefficient are close in value, and directly applying the original model will lead to a large error. Therefore, it can usually only measure blood turbidity separately and cannot be used to measure blood lipid parameters.

[0005] In summary, existing wearable non-invasive testing systems only cover blood oxygen, blood glucose, and blood pressure indicators. There is a lack of non-invasive blood lipid testing solutions and equipment that are compatible with smartwatches, can separate tissue noise, and are adapted to the optical properties of blood, making it difficult to meet the public's daily needs for continuous and painless blood lipid monitoring. Summary of the Invention

[0006] The purpose of this application is to provide a non-invasive blood lipid detection device and its detection method, as well as an intelligent wearable device, which can be adapted to the optical properties of blood for non-invasive blood lipid detection, with accurate detection results and convenient and easy-to-operate detection process, meeting the practical needs of daily continuous and painless blood lipid detection.

[0007] The embodiments of this application are implemented as follows: One aspect of this application provides a non-invasive blood lipid detection device, including a carrier for adhering to the skin, and a detection unit and a processing unit respectively disposed on the carrier and electrically connected to each other; the detection unit includes a detection light source and a light signal receiver arranged sequentially along the length direction of the target detection position, the detection light source emits two sets of detection light with non-overlapping wavelength ranges toward the target detection position, the detection light being visible light to infrared optical radiation, the light signal receiver receiving two sets of reflected light with different wavelength ranges carrying target detection position information, the processing unit extracting the backscattered light signal from the two sets of reflected light with different wavelength ranges respectively, retrieving pre-stored physiological information parameters to calculate the blood absorption coefficient and blood scattering coefficient, and calculating and outputting the corresponding blood lipid parameter information.

[0008] Optionally, in some feasible embodiments of this application, the detection light source includes a plurality of sub-detection light sources arranged in a preset detection area on the carrier, wherein the preset detection area can at least cover the width direction of the target detection position.

[0009] Optionally, in some feasible embodiments of this application, the preset detection area is rectangular, and the preset detection area extends across and covers the target detection position on both sides of the target detection position and exceeds the width of the target detection position.

[0010] Optionally, in some feasible embodiments of this application, the preset detection area is annular, and the annular area spans and covers both sides of the target detection position and exceeds the width of the target detection position; an imaging sensor is also provided at the center of the annular area, and the imaging sensor is electrically connected to the processing unit. The imaging sensor transmits the subcutaneous scattering image of the target detection position it captures to the processing unit, which then analyzes and processes it.

[0011] Optionally, in some feasible embodiments of this application, an operation panel is also provided on the carrier, and operation keys are provided on the operation panel to send working signals to the detection unit through the operation keys.

[0012] Optionally, in some feasible embodiments of this application, the operation panel is further provided with a display screen for displaying blood lipid parameter information calculated and output by the processing unit.

[0013] Optionally, in some feasible embodiments of this application, the carrier is further provided with an audio component, which is signal-connected to the processing unit, and the blood lipid parameter information calculated and output by the processing unit is broadcast through the audio component.

[0014] Optionally, in some feasible embodiments of this application, the processing unit further includes a memory for storing prior detection data, and the stored prior detection data can be retrieved via an operation key.

[0015] Another aspect of this application provides a detection method for a non-invasive blood lipid detection device, applicable to any of the aforementioned non-invasive blood lipid detection devices. The method includes: a detection light source emitting two sets of non-overlapping detection light in wavelength ranges toward a target detection position according to a working signal; the detection light being visible to infrared optical radiation; a processing unit receiving two sets of reflected light in different wavelength ranges carrying target detection position information received by an optical signal receiver, and extracting backscattered light signals from the two sets of reflected light; matching vascular-related parameters based on physiological information data, and substituting them into a difference analysis algorithm to obtain dual-wavelength signals of scattered light from tissues surrounding blood vessels; obtaining the dual-wavelength effective attenuation coefficient of blood in blood vessels based on a diffusion approximation algorithm, calculating the contrast difference of the dual-wavelength effective attenuation coefficient of blood to obtain the absorption coefficient and scattering coefficient of blood; inputting the absorption coefficient and scattering coefficient of blood into a database for parameter comparison, and outputting matching blood lipid parameter information.

[0016] Optionally, in some feasible embodiments of this application, obtaining the effective attenuation coefficient of blood in blood vessels based on the diffusion approximation algorithm, and calculating the contrast difference of the effective attenuation coefficient of blood in blood vessels to obtain the absorption coefficient and scattering coefficient of blood includes: obtaining the effective attenuation coefficient of blood in blood vessels based on the diffusion approximation algorithm; comparing the effective attenuation coefficient of blood in blood vessels with a preset standard parameter threshold; if it exceeds the preset standard parameter threshold, correcting the blood vessel-related parameters accordingly, and substituting them again into the difference analysis algorithm to calculate the dual-wavelength signal of scattered light from the tissue surrounding the blood vessels.

[0017] Optionally, in some feasible embodiments of this application, the non-invasive blood lipid detection device further includes an imaging sensor disposed at the center of a pre-defined annular detection area; the method further includes: the imaging sensor acquiring a subcutaneous scattering image of the target detection location; analyzing the subcutaneous scattering image to draw a vascular image of the target detection location.

[0018] Optionally, in some feasible embodiments of this application, after the imaging sensor acquires a subcutaneous scattering image of the target detection location, the method further includes: a processing unit receiving the subcutaneous scattering image and processing it based on scattering theory to obtain the target blood vessel depth and target blood vessel diameter; according to the target blood vessel depth and target blood vessel diameter, matching the target blood vessel depth ratio coefficient and target blood vessel diameter ratio coefficient based on simulation databases of blood vessel models of different sizes and depths respectively; and calculating the effective dual-wavelength attenuation coefficient of blood in the blood vessel after noise filtering based on difference operation to filter noise.

[0019] In another aspect of the embodiments of this application, a smart wearable device is provided, including any of the foregoing non-invasive blood lipid detection devices, and also including a strap structure. The non-invasive blood lipid detection device is fixedly disposed on the strap structure. After the detection unit of the non-invasive blood lipid detection device is attached to the skin at the target detection position through a carrier, it is constrained and fixed by the strap structure.

[0020] Optionally, in some feasible embodiments of this application, the detection light source of the non-invasive blood lipid detection device includes multiple sub-detection light sources arranged in a preset detection area on the carrier; after the detection unit of the non-invasive blood lipid detection device is attached to the skin at the target detection location through the carrier, the multiple sub-detection light sources independently receive working signals and can emit two sets of detection light with non-overlapping wavelength ranges according to the working signal, and the detection light is visible light to infrared optical radiation.

[0021] The beneficial effects of the embodiments of this application include: This application provides a non-invasive blood lipid detection device, including a carrier for adhering to the skin, and a detection unit and a processing unit respectively disposed on the carrier and electrically connected to each other. The detection unit includes a detection light source and a light signal receiver arranged sequentially along the length of the target detection position. The detection light source emits two sets of detection light with non-overlapping wavelength ranges towards the target detection position. The detection light is visible to infrared optical radiation. The light signal receiver receives two sets of reflected light with different wavelength ranges carrying target detection position information. The processing unit extracts the backscattered light signal from the two sets of reflected light with different wavelength ranges, retrieves pre-stored physiological information parameters to calculate the blood absorption coefficient and blood scattering coefficient, and calculates and outputs the corresponding blood lipid parameter information. By adhering the carrier to the skin at the detection position and arranging the detection light source and light signal receiver in the detection unit sequentially along the length of the target detection position, a stable detection environment is provided for the subsequent transmission and reception of detection signals, reducing light loss, improving the stability and accuracy of reflected light signal acquisition, and also improving the efficiency of photoelectric signal conversion and transmission between the detection unit and the processing unit while reducing delay and loss. The detection unit emits two sets of non-overlapping detection light wavelengths towards the target detection location. The detection light ranges from visible to infrared optical radiation. The two sets of detection light wavelengths do not overlap, and the dual wavelengths synchronously illuminate the same location, forming two independent sets of optical detection data. This effectively counteracts system interference caused by skin pigmentation, epidermal keratin, and light source power drift, reducing measurement errors. Furthermore, it can separate blood absorption and turbidity optical characteristics through dual-wavelength common-mode acquisition signals. The obtained backscattered light signal does not need to penetrate thick layers of human tissue, resulting in high light utilization. The backscattered light directly reflects the scattering degree of lipoprotein particles in the blood, which is directly related to blood lipid concentration, thus making the detection results highly sensitive to changes in blood lipids. The processing unit retrieves pre-stored physiological information parameters for calculation. It can correct stray optical signals generated by the skin and subcutaneous tissue based on the pre-stored physiological information parameters, reducing signal interference from non-blood tissues in the calculation and improving the accuracy of blood lipid parameter calculations. It also improves the consistency of measurement results across different populations and detection scenarios. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a first-view structural schematic diagram of a non-invasive blood lipid detection device provided in an embodiment of this application; Figure 2This is a schematic diagram of the structure of the detection unit in a non-invasive blood lipid detection device provided in an embodiment of this application; Figure 3 This is a first-view structural schematic diagram of another non-invasive blood lipid detection device provided in an embodiment of this application; Figure 4 This is a second-view structural schematic diagram of a non-invasive blood lipid detection device provided in an embodiment of this application; Figure 5 One of the flowcharts for a detection method of a non-invasive blood lipid detection device provided in this application embodiment; Figure 6 A second flowchart illustrating a detection method for a non-invasive blood lipid detection device provided in this application embodiment; Figure 7 The third flowchart of a detection method for a non-invasive blood lipid detection device provided in this application embodiment; Figure 8 The fourth flowchart illustrates the detection method of a non-invasive blood lipid detection device provided in this application embodiment.

[0024] Icons: 10-Carrier; 11-Detection unit; 110-Detection light source; 111-Sub-detection light source; 112-Optical signal receiver; 12-Processing unit; 13-Imaging sensor; 14-Operation panel; 15-Display screen. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, all other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0026] In the description of this application, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of this application is in use. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this application. In addition, the terms "first," "second," and "third," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] Furthermore, terms such as "horizontal" and "vertical" do not imply that components must be absolutely horizontal or suspended, but rather that they can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0028] Current wearable devices, utilizing transmissive optical technology, can perform non-invasive monitoring of biometric information such as blood oxygen and pulse, meeting people's needs for monitoring their health at home. Some cutting-edge solutions also offer non-invasive methods for estimating blood sugar and blood pressure, along with corresponding wearable monitoring devices. However, for blood lipid monitoring, it still relies solely on venous blood sampling. This process is cumbersome and involves painful punctures, especially in scenarios like tracking postprandial blood lipid changes, where repeated venous punctures further increase the discomfort and difficulty of the test.

[0029] Furthermore, transmission methods are primarily suited to clear detection media. When dealing with lipid testing, which involves penetrating difficult-to-penetrate human tissues and extracting lipoprotein signals from turbid blood, the accuracy of the data becomes extremely poor. In addition, conventional scattering models cannot match the size of chylomicrons and very low-density lipoprotein particles, leading to significant errors in the detection data.

[0030] Based on the above problems, this application provides a non-invasive blood lipid detection device, such as... Figure 1 As shown, the non-invasive blood lipid detection device includes a carrier 10 for adhering to the skin, and a detection unit 11 and a processing unit 12 respectively disposed on the carrier 10 and electrically connected to each other; the detection unit 11 includes a detection unit along the target detection position (e.g., ... Figure 1 The detection light source and the optical signal receiver are arranged sequentially along the length direction of the dashed box in the figure. The detection light source emits two sets of detection light with non-overlapping wavelength ranges towards the target detection position. The detection light is visible light to infrared optical radiation. The optical signal receiver receives two sets of reflected light with different wavelength ranges carrying the target detection position information. The processing unit 12 extracts the backscattered light signal from the two sets of reflected light with different wavelength ranges, retrieves the pre-stored physiological information parameters to calculate the blood absorption coefficient and blood scattering coefficient, and calculates and outputs the corresponding blood lipid parameter information.

[0031] The non-invasive blood lipid detection device of this application embodiment uses a carrier 10 that is attached to the skin to detect target blood vessels within the attachment location. A detection unit 11 and a processing unit 12, electrically connected to each other and mounted on the carrier 10, are used to send, receive, and process corresponding detection signals. Sending and receiving detection signals while the carrier 10 is attached to the skin minimizes light signal transmission losses, avoids interference from external stray light, and improves the stability of light signal acquisition.

[0032] The detection unit includes a detection light source and a light signal receiver arranged sequentially along the length of the target detection position. The target detection position must cover the area where the blood vessel to be tested is located. Arranging the light source along the length of the target detection position allows the light path to cover the target area of ​​the blood vessel along its direction, increasing the amount of backscattered light reflected from the blood within the vessel and thus enhancing the strength of the effective detection signal. The detection light source emits two sets of non-overlapping detection light wavelengths towards the target detection position. The light signal receiver receives the two sets of reflected light with different wavelengths carrying the target detection position information. Compared to single-point optical path acquisition, this method better avoids the impact of external errors on the detection.

[0033] The two sets of non-overlapping probe light have different blood absorption and scattering optical response characteristics. The two sets of reflected light with different wavelength ranges received serve as two independent sets of optical monitoring data, providing an independent calculation basis for separately solving the blood absorption coefficient and blood scattering coefficient.

[0034] The processing unit extracts backscattered light signals from two sets of reflected light in different wavelength ranges, retrieves pre-stored physiological information parameters to calculate the blood absorption coefficient and blood scattering coefficient, and calculates and outputs the corresponding blood lipid parameters. Backscattered light directly reflects the scattering degree of lipoprotein particles in the blood that are directly related to blood lipid concentration, making the detection results more sensitive to changes in blood lipids. The processing unit retrieves pre-stored physiological information parameters during the calculation process, correcting stray light signals generated by the skin and subcutaneous tissue. This helps to eliminate signal interference caused by non-blood tissues, improves the calculation accuracy of blood optical coefficients, and reduces correction deviations caused by human operation by retrieving corresponding pre-stored physiological information parameters according to preset relationships. This ensures accurate and matched measurement results for people with different physiological information and in different detection scenarios.

[0035] The non-invasive blood lipid detection device provided in this application includes a carrier 10 for adhering to the skin, and a detection unit 11 and a processing unit 12 respectively disposed on the carrier 10 and electrically connected to each other. The detection unit 11 includes a detection light source and a light signal receiver arranged sequentially along the length direction of the target detection position. The detection light source emits two sets of detection light with non-overlapping wavelength ranges towards the target detection position. The detection light is visible light to infrared optical radiation. The light signal receiver receives two sets of reflected light with different wavelength ranges carrying the target detection position information. The processing unit 12 extracts the backscattered light signal from the two sets of reflected light with different wavelength ranges, retrieves pre-stored physiological information parameters to calculate the blood absorption coefficient and blood scattering coefficient, and calculates and outputs the corresponding blood lipid parameter information. By adhering the carrier to the skin at the detection position and arranging the detection light source and light signal receiver in the detection unit sequentially along the length direction of the target detection position, a stable detection environment is provided for the subsequent transmission and reception of detection signals, reducing light loss and improving the stability and accuracy of reflected light signal acquisition. It also improves the efficiency of photoelectric signal conversion and transmission between the detection unit 11 and the processing unit 12 and reduces delay and loss. The detection unit 11 emits two sets of non-overlapping detection light wavelengths toward the target detection location. The two sets of detection light wavelengths do not overlap, and the dual wavelengths synchronously illuminate the same location, forming two independent sets of optical detection data. This effectively counteracts system interference caused by skin pigmentation, epidermal keratin, and light source power drift, reducing measurement errors. Furthermore, it can separate blood absorption and turbidity optical characteristics through dual-wavelength common-mode acquisition signals. The obtained backscattered light signal does not need to penetrate thick layers of human tissue, resulting in high light utilization. The backscattered light directly reflects the scattering degree of lipoprotein particles in the blood, which is directly related to blood lipid concentration, thus making the detection results highly sensitive to changes in blood lipids. The processing unit 12 retrieves pre-stored physiological information parameters for calculation. It can correct stray optical signals generated by the skin and subcutaneous tissue based on the pre-stored physiological information parameters, reducing signal interference from non-blood tissues in the calculation and improving the accuracy of blood lipid parameter calculations. It also improves the consistency of measurement results across different populations and detection scenarios.

[0036] Alternatively, in some possible implementations of this application, such as Figure 2 As shown, the detection light source includes multiple sub-detection light sources 111 arranged in a preset detection area on the carrier 10, and the preset detection area can at least cover the width direction of the target detection position.

[0037] In the non-invasive blood lipid detection device of this application embodiment, the target detection location to be covered by the detection unit 11 and processing unit 12 on the carrier 10 refers to the location of the subcutaneous blood vessel to be detected. Therefore, the length direction of the target detection location refers to the direction in which the blood vessel extends, and the width direction refers to the cross-sectional direction of the blood vessel. For example, if the non-invasive blood lipid detection device of this application embodiment is used for non-invasive detection of subcutaneous blood vessels in the wrist, the width direction refers to the width direction of the wrist, and the length direction refers to the length direction of the arm. The preset detection area means that it must at least cover the width direction of the target detection location to ensure comprehensive optical signal detection of the subcutaneous blood vessels as much as possible.

[0038] When detecting subcutaneous blood vessels at a target location, using a single light source has a limited coverage area. This is especially true for wearable devices, where inaccurate placement or varying tightness can cause the area covered by the single light source to deviate from the location of the subcutaneous blood vessels. Therefore, if... Figure 2 As shown, the detection light source in this embodiment includes a plurality of sub-detection light sources 111 arranged in a preset detection area on the carrier 10. The preset detection area covers at least the width direction of the target detection position, so that the light emission coverage of the plurality of sub-detection light sources 111 can cover the entire width range of the subcutaneous blood vessel.

[0039] Multiple sub-detection light sources 111 provide multiple independent light emission channels and incident light from multiple positions and multiple incident angles. Even if some incident light beams are blocked or their intensity is abnormally attenuated due to other external reasons, the remaining incident light can still cover the light signal, thereby enhancing the error of wear detection to a certain extent and improving the reliability of light signal acquisition.

[0040] It should be noted that, Figure 2 The diagram shows an example arrangement of multiple sub-detection light sources 111. In fact, in this embodiment, the multiple sub-detection light sources 111 can also be arranged in various other ways, such as regional arrangement, cross arrangement, overlapping arrangement, etc. The specific arrangement can be designed and set according to the installation and detection position of the non-invasive blood lipid detection device on the wearable device in this embodiment.

[0041] Optionally, in some feasible embodiments of this application, the preset detection area is rectangular, and the preset detection area extends across and covers the target detection position on both sides of the target detection position and exceeds the width of the target detection position.

[0042] Reference Figure 1As shown, the preset detection area refers to the area to be detected using the non-invasive blood lipid detection device of this application embodiment, including the target detection location, such as the subcutaneous blood vessel to be detected. Therefore, in some solutions, the preset detection area is set as a rectangle, and the width of the rectangle extends across and covers the target detection location, and extends beyond the width of the target detection location on both sides. This ensures that the detection can completely cover the cross-section of the target blood vessel, so that the received light signal covers the entire target blood vessel range. Even if the non-invasive blood lipid detection device of this application embodiment experiences some lateral or longitudinal movement during wear, the blood vessel body will still fall within the coverage area of ​​the rectangular preset detection area.

[0043] The width of the preset detection area is larger than the actual width of the blood vessel, so that part of the rectangular area spans directly above the blood vessel, while the other part covers the subcutaneous tissue surrounding the blood vessel. By collecting the signal within the rectangular area through the emitted light signals from multiple sub-detection light sources 111, the backscattered signal of the blood and the north-scattered signal of other subcutaneous tissues can be separated through differential calculation, thereby eliminating additional errors and improving the accuracy of subsequent calculations of the blood absorption coefficient and scattering coefficient.

[0044] Alternatively, in other possible implementations of this application, such as Figure 3 As shown, the preset detection area is in the shape of a ring, which spans and covers both sides of the target detection position and exceeds the width of the target detection position; an imaging sensor 13 is also set in the center of the ring, and the imaging sensor 13 is electrically connected to the processing unit 12. The imaging sensor 13 transmits the subcutaneous scattering image of the target detection position it captures to the processing unit 12, which then analyzes and processes it.

[0045] like Figure 3 As shown, the preset detection area is annular, spanning and covering the entire target detection position, and extending beyond the target detection position on both sides of its width, thus ensuring the target blood vessel ( Figure 3 The position represented by the dashed line in the middle can be completely covered within the pre-set annular detection area. Within the pre-set annular detection area, an imaging sensor 13 is also installed. The imaging sensor 13 is electrically connected to the processing unit 12. The imaging sensor 13 can acquire subcutaneous backscattered images and transmit them to the processing unit 12. Within the processing unit 12, the backscattered images are analyzed to obtain specific parameter information such as the depth, diameter, and actual direction of the subcutaneous target blood vessel. This enables automated vascular morphology mapping and provides accurate pre-parameter information input for tissue noise difference correction, thereby reducing measurement deviations caused by individual differences.

[0046] Furthermore, the subcutaneous backscattered image output by the imaging sensor 13 can provide feedback on the actual location and direction of the target blood vessel. The processing unit 12 controls the illumination of multiple sub-detection light sources based on the backscattered image, eliminates invalid optical path signals, reduces interference from invalid data on the calculation, and improves the signal-to-noise ratio.

[0047] The specific location of the imaging sensor 13 within the pre-defined detection area in the annular shape can be selected and set by those skilled in the art as needed. For example, the idle space outside the detection unit 11 and processing unit 12 in the pre-defined detection area can be fully utilized, or, under the premise of avoiding mutual interference between signals, it can be set in a layered manner to increase the imaging function without increasing the area of ​​the pre-defined detection area.

[0048] Alternatively, in some possible implementations of this application, such as Figure 4 As shown, an operation panel 14 is also provided on the carrier 10. The operation panel 14 is provided with operation keys, and the operation keys are used to send working signals to the detection unit 11.

[0049] like Figure 4 As shown, the carrier 10 is provided with an operation panel 14. The operation keys on the operation panel 14 are used to manually trigger the working signal to send the working signal to the detection unit 11. After receiving the working signal, the detection unit 11 emits dual-wavelength detection light toward the target detection position. The detection light is visible light to infrared optical radiation, that is, the detection light includes the visible light band and can also be selected in the infrared light band.

[0050] Figure 4 The diagram shows one arrangement of the operation panel 14 on the carrier 10. Since the operating signals are usually manually operated, it is sufficient to ensure that the operation panel 14 is exposed in a convenient position for operation. Specifically, it can be arranged as follows: Figure 4 The detection unit 11 can be stacked in layers, or it can be laid flat. Figure 4 The specific shape and structure of the processing unit 12 are not shown. In fact, the processing unit 12 can also be packaged together with the optical signal receiver 112.

[0051] Still as Figure 4 As shown, the detection unit 11 includes a detection light source 110 that emits dual-wavelength detection light and a light signal receiver 112 for receiving backscattered light, which are arranged sequentially along the direction of the blood vessel. When the non-invasive blood lipid detection device of this embodiment is attached to the skin according to the target detection position, the detection light source 110 emits dual-wavelength detection light according to the manual operation signal received from the operation panel 14, and the light signal receiver 112 receives the backscattered light signal and transmits it to the processing unit 12 for calculation and processing.

[0052] For example, carrier 10 can be as follows: Figure 4 In the middle, it is placed on the surface that fits the skin in a bearing manner. It can also be a flexible thin film layer, or it can be surrounded in the form of an outer frame so that the detection unit 11 and the processing unit 12 can directly fit the skin.

[0053] Alternatively, in some possible implementations of this application, such as Figure 4 As shown, the operation panel 14 is also equipped with a display screen 15, which is used to display the blood lipid parameter information calculated and output by the processing unit 12.

[0054] like Figure 4 As shown, a display screen 15 is also provided on the operation panel 14. The data or image information calculated and processed by the processing unit 12 can be transmitted to the display screen 15 for intuitive display. For example, the blood lipid value obtained after processing and calculation can be directly displayed on the display screen 15, making it convenient for users to directly read the blood lipid value information. Furthermore, different colors can be displayed on the display screen according to different blood lipid values; for example, normal blood lipid values ​​are displayed in green, high values ​​in yellow, and severely high values ​​in red.

[0055] Optionally, in some feasible embodiments of this application, an audio component is also provided on the carrier 10. Figure 4 (Not shown in the image) The audio component is connected to the processing unit 12 via a signal, and the blood lipid parameter information calculated and output by the processing unit 12 is broadcast through the audio component.

[0056] An audio component can also be set on the carrier 10. The audio component is connected to the processing unit 12 by a signal. The audio component can be preset with various broadcast information corresponding to the detection values. After the processing unit 12 calculates and outputs the blood lipid parameter information, the audio component broadcasts according to the blood lipid parameter information. For example, it can directly play and read the blood lipid parameter value. Or, after broadcasting the parameter value, it can retrieve the corresponding preset broadcast information and further output voice explanations such as normal blood lipids or high blood lipids.

[0057] Optionally, in some implementable embodiments of this application, the processing unit 12 further includes a memory ( Figure 4 (Not shown in the image), used to store previously detected data, and the stored previously detected data can be retrieved via operation keys.

[0058] The processing unit 12 also includes a memory, which allows the detection values ​​obtained from multiple tests to be stored and retained. Alternatively, multiple account information can be pre-stored in the processor so that previous detection data can be stored for different accounts. When it is necessary to retrieve the changes in blood lipid information for a single account over a period of time, the previous detection data stored in the memory can be retrieved through the operation keys, so that the user can record, analyze, and seek medical treatment.

[0059] Another aspect of this application provides a detection method for a non-invasive blood lipid detection device, applicable to any of the aforementioned non-invasive blood lipid detection devices, such as... Figure 5 As shown, the method includes: S101, the detection light source 110 emits two sets of non-overlapping detection light in the wavelength range toward the target detection position according to the working signal. The detection light is visible light to infrared optical radiation.

[0060] First, a working signal is sent to the detection light source 110, which then emits two sets of detection light with non-overlapping wavelength ranges toward the target detection position. In some embodiments, the detection light source 110 includes multiple sub-detection light sources 111, and as needed, a specific portion or all of the multiple sub-detection light sources 111 can be controlled to emit light.

[0061] For example, since the preset detection area extends beyond the width of the target blood vessel on both sides, it has a certain amount of redundancy. When the non-invasive blood lipid detection device shifts during wear, or considering the differences in individual blood vessel diameter, position, and direction, it can selectively control at least the sub-detection light source 111 above the target blood vessel to emit light after wear.

[0062] The detection light source 110 emits two sets of detection light with non-overlapping wavelength ranges. For example, the first set of detection light can be visible light with a wavelength λ1 of 660 nm, and the second set of detection light can be near-infrared light with a wavelength λ2 of 940 nm. When both sets of detection light illuminate the same target location, blood at different wavelengths exhibits a fixed scattering and absorption ratio, establishing independent measurement conditions for the two wavelengths. This provides the necessary dual-channel raw light input for subsequent separate calculations of the blood absorption coefficient and reduced scattering coefficient. Alternatively, other combinations of non-overlapping wavelength range detection light emitted by the detection light source 110 can be selected, such as two sets of non-overlapping near-infrared light. The following explanation uses visible light with λ1 of 660 nm and near-infrared light with λ2 of 940 nm as an example.

[0063] S102, the processing unit 12 receives two sets of reflected light with different wavelength ranges carrying target detection position information received by the optical signal receiver 112, and extracts the backscattered light signal from the two sets of reflected light.

[0064] The optical signal receiver 112 receives two sets of reflected light with different wavelength ranges carrying target detection location information and transmits the dual-wavelength reflected light to the processing unit 12. The processing unit 12 separates the backscattered light signal from it and removes the other transmitted light and specular reflection stray light.

[0065] Since the Beer-Lambert law only applies to clear media, and blood is a highly turbid medium containing many microparticles and cells, it cannot be calculated using the Beer-Lambert law. Furthermore, transmitted light is almost impossible to penetrate human tissue for reception on the opposite side. Therefore, the detection method in this embodiment uses reflected light, with detection light emitted from the same side illuminating the skin. The backscattered light returning from the skin surface is used, and the backscattering intensity is directly related to the concentration of lipoprotein particles in the blood. This way, only the backscattered component is extracted without requiring light to penetrate thick layers of human tissue, significantly reducing the power consumption of the light source. Moreover, the processing unit extracts the backscattered signals at 12 separate wavelengths, ensuring that the optical information in the two wavelengths is retained independently, preventing signal aliasing and guaranteeing independent calculation of the reflectance curve for each wavelength group.

[0066] If multiple sub-detector light sources 111 are used to set up the detector light source 110, the corresponding optical signal receiver 112 is also an array of photodiodes. Multiple sets of sub-detector light sources 111 and optical signal receiver 112 spacing ρ can be obtained through the multiple sub-detector light sources 111, which can construct a complete backscattered light attenuation curve, providing a curve slope basis for solving the dual-wavelength effective attenuation coefficient, and thus reducing random noise.

[0067] After steps S101 and S102, two sets of raw mixed backscattered signals at different wavelengths have been obtained. The signal acquired when irradiating the target blood vessel is denoted as R. on (ρ), which includes signals from blood and surrounding skin tissue. The signal acquired when irradiating tissue adjacent to the target blood vessel is denoted as R. off (ρ), which can be understood as the scattering signal from the skin and connective tissue. Here, ρ is the distance between the detection light source 110 and the light signal receiver 112, and the wavelengths of the two sets of non-overlapping detection lights are λ1 and λ2, respectively.

[0068] S103. Match blood vessel-related parameters based on physiological information data, and substitute them into the differential analysis algorithm to obtain the dual-wavelength signal of scattered light from the perivascular tissue.

[0069] Because the scattering coefficients of blood signals and surrounding skin tissue signals differ significantly in the collected backscattered signals (with the scattering coefficient of the surrounding skin tissue being much greater than that of blood), it is necessary to introduce two sets of backscattered light R... on (ρ) and R offIn (ρ), the proportion coefficients α and β of the blood portion.

[0070] The pre-built database contains physiological information data, including α and β values ​​that match individual physiological information such as the depth, diameter, width, and orientation of the target blood vessel. The depth and diameter of the blood vessel are the most significant factors directly influencing the values ​​of α and β. α and β can be used to establish a database matching blood vessel depth and diameter by inputting them into the simulation model. By retrieving α and β values ​​that match the blood vessel depth and diameter from the pre-built physiological information data, the α and β values ​​are more accurately matched to the user's individual data. Then, α and β are substituted into a difference analysis algorithm for calculation, which can separate the backscattered light from the skin and tissues, i.e., the dual-wavelength signal of the backscattered light from the tissues surrounding the blood vessel. After removing this part of the backscattered light, the backscattered light originating solely from the blood in the target blood vessel can be separated, denoted as R. blood (ρ).

[0071] S104. Based on the diffusion approximation algorithm, the effective attenuation coefficient of blood in the blood vessels with two wavelengths is obtained. The contrast difference of the effective attenuation coefficient of blood with two wavelengths is calculated to obtain the absorption coefficient and scattering coefficient of blood.

[0072] The blood scattered light after removing other scattered light under two sets of illumination at wavelengths λ1 and λ2, i.e., R blood (ρ1, λ1) and R blood (ρ2, λ2). Based on the distance ρ between the probe light source 110 and the optical signal receiver 112, a curve is plotted to calculate the effective attenuation coefficient of the dual wavelengths. Based on the slope of the curve, the effective attenuation coefficient of the corresponding wavelength is calculated using the diffusion approximation algorithm.

[0073] The contrast difference is calculated for two different sets of wavelengths. When the contrast between the two sets of absorption coefficients and scattering coefficients reaches the minimum value, it is recorded as the absorption coefficient and scattering coefficient of blood.

[0074] S105. Input the blood absorption coefficient and scattering coefficient into the database for parameter comparison, and output the matching blood lipid parameter information.

[0075] The system has a pre-set calibrated database containing multiple sets of optical coefficients and their corresponding data to the true values ​​of blood lipid biochemistry, such as the blood absorption coefficient and scattering coefficient corresponding to different triglyceride concentrations and lipoprotein levels.

[0076] The corrected blood absorption coefficient and scattering coefficient, calculated in the previous step, are input into the database for parameter comparison. Since the blood absorption coefficient represents the light absorption of substances such as hemoglobin, an increase in the blood absorption coefficient alone indicates changes in blood oxygen levels rather than blood lipid levels. Therefore, after calculating the results using both the blood absorption coefficient and scattering coefficient, the output is matched blood lipid parameter information that directly reflects changes in blood turbidity.

[0077] The non-invasive blood lipid detection method provided in this application uses dual-wavelength probe light to collect mixed backscattered signals from the non-invasive blood lipid detection device. A difference analysis algorithm is used to remove noise from skin tissue to obtain pure optical signals from the target blood vessels. The optical signals are optimized based on a modified diffusion model and dual-wavelength contrast difference calculation. The calculated blood absorption and scattering coefficients are then compared with a pre-set calibration database to output blood lipid parameter information. This method achieves non-invasive blood lipid detection through subcutaneous blood vessels, and the detection data removes various other noises as much as possible while making corresponding corrections to the parameters, ensuring stable and accurate measured blood lipid values.

[0078] Alternatively, in some possible implementations of this application, such as Figure 6 As shown in S104, the effective attenuation coefficient of blood in the blood vessel is obtained based on the diffusion approximation algorithm. The contrast difference of the effective attenuation coefficient of blood in the blood vessel is calculated to obtain the absorption coefficient and scattering coefficient of blood, including: S1041. The effective attenuation coefficient of blood in blood vessels is obtained based on the diffusion approximation algorithm.

[0079] S1042. Compare the effective attenuation coefficient of the blood's dual wavelengths with the preset standard parameter threshold. If it exceeds the preset standard parameter threshold, correct the vascular-related parameters accordingly, and then substitute them into the difference analysis algorithm to calculate the dual wavelength signal of the scattered light from the tissue surrounding the blood vessel.

[0080] Since the scattering coefficient and absorption coefficient of blood are close, the accuracy of the diffusion results is not good if the conventional diffusion approximation model is directly applied. Therefore, it is necessary to modify the conventional diffusion approximation model to obtain a modified diffusion coefficient model that is more suitable for blood.

[0081] First, in S1041, based on the diffusion approximation algorithm, using R obtained in the previous step... blood (ρ1, λ1) and R blood The corrected dual-wavelength effective attenuation coefficient of blood in the blood vessel is calculated using (ρ2, λ2), and denoted as μ. eff (λ1) and μ eff (λ2) eliminates the inherent model bias caused by the conventional diffusion approximation model when applied to blood media.

[0082] Then, in step S1042, a standard parameter threshold for the effective attenuation coefficient of blood with dual wavelengths is pre-stored in the database. This threshold includes an acceptable upper and lower limit. The corrected effective attenuation coefficient of blood with dual wavelengths in the blood vessel is compared with the standard parameter threshold. If the corrected effective attenuation coefficient of blood with dual wavelengths in the blood vessel falls outside the range of the standard parameter threshold, i.e., higher than the upper limit of the standard parameter threshold or lower than the lower limit of the standard parameter threshold, the calculation result is determined to be abnormal. This indicates that in step S103, due to the deviation of the proportion coefficients α and β, tissue noise could not be completely eliminated. This is characterized by the calculated effective attenuation coefficient deviating from the true physical range of the blood medium, which will lead to inaccurate blood lipid values. Therefore, the relevant parameters of the blood vessel need to be corrected accordingly. For example, the depth and diameter of the target blood vessel are adjusted within the parameter range of the database. The proportion coefficients α and β are recalculated based on the corrected blood vessel depth and diameter, and then recalculated using the difference analysis algorithm in step S103 to eliminate tissue noise again.

[0083] Alternatively, in some possible implementations of this application, such as Figure 7 As shown, the non-invasive blood lipid detection device also includes an imaging sensor 13 positioned at the center of a pre-defined annular detection area; the method further includes: S201, Imaging sensor 13 captures subcutaneous scattering images of the target detection location.

[0084] S202. Analyze the subcutaneous scattering image and draw the blood vessel image at the target detection location.

[0085] Reference Figure 3 As shown, when the preset detection area of ​​the non-invasive blood lipid detection device in this application embodiment is a ring, and an imaging sensor 13 is provided at the center of the ring, the detection method in this application embodiment further includes, before step S101, acquiring a subcutaneous scattering image of the target detection position through the imaging sensor 13.

[0086] The imaging sensor 13 is positioned at the center of a pre-defined circular detection area, which covers at least the entire cross-sectional area of ​​the target blood vessel. Therefore, the imaging sensor 13 can obviously capture an image containing the entire outline of the target blood vessel. The imaging sensor 13 acquires a reflected image formed by subcutaneous scattering, which is not a visible light image, but rather an optical image of subcutaneous scattering. The acquired optical image contains the brightness difference between the subcutaneous target blood vessel outline and the surrounding tissue. Due to blood particle scattering in the blood vessel area, there is a significant difference in image grayscale between the image and the surrounding connective tissue. For example, in this embodiment, when the imaging sensor 13 performs optical imaging, there is no need to set up an additional independent illumination element; instead, the detection light source 110 on the carrier 10 can be reused as the illumination light.

[0087] The imaging sensor 13 is electrically connected to the processing unit 12. The image captured by the imaging sensor 13, which includes the outline of the entire target blood vessel, is transmitted to the processing unit 12 for analysis and processing. The actual geometric parameters of the target blood vessel are extracted and output, including the depth and diameter of the blood vessel. Based on the information obtained from the analysis, the blood vessel image at the target detection location is drawn.

[0088] Thus, in S103, the dual-wavelength signal of scattered light from the perivascular tissue can be obtained, and the vascular parameters obtained from image analysis can be used to obtain the proportion coefficients α and β. Since the vascular parameters obtained from image analysis are more intuitive and accurate than preset values ​​or manually input individual values, the obtained proportion coefficients α and β are more accurate. Moreover, if an anomaly occurs in the threshold verification in step S1042, the image from the imaging sensor 13 can be called up or re-called for analysis and calculation to make corrections.

[0089] Optionally, such as Figure 8 As shown, in some feasible embodiments of this application, after the imaging sensor 13 acquires a subcutaneous scattering image of the target detection location in step S201, the method further includes: S2011, Processing unit 12 receives subcutaneous scattering images and, based on scattering theory, processes them to obtain the target blood vessel depth and target blood vessel diameter.

[0090] The processing unit 12 receives the original subcutaneous scattering image and processes the image based on scattering theory, including image noise reduction, grayscale normalization, and scattering blur compensation. Due to the significant difference in the scattering ability of subcutaneous blood vessels and surrounding tissues to the probe light, the image of the blood vessel region has a feature blurring and diffuse image effect. Therefore, the contour edge of the image cannot be measured intuitively. Instead, the depth and diameter of the target blood vessel are obtained by relying on scattering theory and set inversion of simulation data.

[0091] S2012. Based on the target blood vessel depth and target blood vessel diameter, the target blood vessel depth ratio coefficient and target blood vessel diameter ratio coefficient are obtained by matching simulation databases of blood vessel models of different sizes and depths.

[0092] The simulation database stores a large number of simulation samples, and these samples correspond to vessel depth, vessel diameter, corresponding spacing ρ, and proportion coefficients α and β at different wavelengths. The target vessel depth and diameter obtained from the image are matched against the target database to obtain the target vessel depth proportion coefficient and the target vessel diameter proportion coefficient. The proportion coefficients α and β are related to two sets of wavelengths and spacing ρ, thus yielding a set of coefficients that vary with spacing ρ, rather than a single constant. For example, the set of proportion coefficients corresponding to multiple spacings ρ for dual-wavelength, multiple sub-detector sources includes α(ρ, λ1), β(ρ, λ1), α(ρ, λ2), and β(ρ, λ2).

[0093] S2013. Based on the difference operation to filter noise, the effective attenuation coefficient of the blood in the blood vessel after filtering noise is calculated.

[0094] Wavelength-based difference calculations are performed to filter out scattering noise from surrounding tissues, obtaining a pure blood backscattered signal. This signal is then combined with a modified diffusion approximation model to calculate the effective dual-wavelength attenuation coefficient of the blood in the vessel after noise filtering, denoted as μ. eff (λ1) and μ eff (λ2). Thus, this method can replace the step-by-step processing method in step S103, which involves matching vascular parameters based on physiological information data and inputting them into a difference analysis algorithm to obtain the pure blood northward scattering signal, and the step S1041, which involves obtaining the effective attenuation coefficient of the blood dual wavelengths based on a diffusion approximation algorithm, thereby achieving a combined processing.

[0095] In another aspect of the embodiments of this application, a smart wearable device is provided, including any of the aforementioned non-invasive blood lipid detection devices. The smart wearable device also includes a strap structure. The non-invasive blood lipid detection device is fixedly disposed on the strap structure. After the detection unit 11 of the non-invasive blood lipid detection device is attached to the skin at the target detection position through the carrier 10, it is constrained and fixed by the strap structure.

[0096] The smart wearable device of this application embodiment includes a strap structure and a non-invasive blood lipid detection device fixed on the strap structure. The strap constrains and fixes the device to the body so that the detection unit 11 of the non-invasive blood lipid detection device can be attached to the skin surface of the target detection location via a carrier 10. For example, a wrist-worn health bracelet will be used as an example for the following description.

[0097] The band structure is worn around the wrist, and the detection unit 11 is aligned with the target detection area on the inside of the wrist. The constraint of the band structure keeps the health bracelet fixed relative to the wrist, thus ensuring stable signal transmission and reception of the detection unit 11. After being worn and fixed, the carrier 10 is flat against the skin on the inside of the wrist, with the preset detection area corresponding to the target detection location containing subcutaneous target blood vessels. The carrier 10 can be made of skin-friendly material and is set to be flexible and conform to the contour of the skin surface. This ensures that the detection unit 11 eliminates air gaps, reduces light loss and stray light interference during light signal transmission and reception, and makes the working distance of the imaging sensor stable when including the imaging sensor 13. On the other hand, it can also effectively improve comfort, especially when the smart wearable device is a health bracelet, which can meet the user's daily wear needs and be used in conjunction with other commonly used functions of the health bracelet. Thus, when using it, you only need to manually press the corresponding operation button on the operation panel 14 to transmit and receive signals and perform calculations according to the above method, and finally output blood lipid information on the display screen 15. Users do not need to hold or grip the detection probe when using it; the wearable design supports multiple measurements at home and in daily life.

[0098] The method of restraint and fixation of the strap structure is not strictly limited in this embodiment of the application, and can be adapted to the specific body position of the wearer, such as hook and loop fastener, strap, snap fastener, belt, etc.

[0099] Furthermore, the smart wearable devices in this application are not limited to the aforementioned wristband-style health bracelet. For example, they can be applied to upper arm-type wearable devices, using a wide elastic band as the band structure to fix the detection unit 11 of the non-invasive blood lipid detection device to the corresponding target blood vessel on the upper wall. They can also be combined with an upper arm blood pressure monitor to simultaneously monitor blood pressure and blood lipids. For example, a finger-type wearable monitoring device can be used, with a finger ring as the band structure to fix the detection unit 11 of the non-invasive blood lipid detection device to a position close to the fingertip. The finger has abundant superficial blood vessels under the skin and can simultaneously collect blood oxygen and heart rate information, outputting blood oxygen, heart rate, and blood lipids synchronously. As another example, an adhesive patch can be used as the band structure to be directly attached to the skin surface, corresponding the detection unit 11 of the non-invasive blood lipid detection device to the target blood vessel. The detection unit 11, processing unit 12, and battery are integrated into the adhesive patch, resulting in a thin and lightweight structure suitable for continuous postprandial blood glucose monitoring.

[0100] Optionally, in some feasible embodiments of this application, the detection light source 110 of the non-invasive blood lipid detection device includes a plurality of sub-detection light sources 111 arranged in a preset detection area on the carrier 10; after the detection unit 11 of the non-invasive blood lipid detection device is attached to the skin at the target detection position through the carrier 10, the plurality of sub-detection light sources 111 independently receive working signals and can emit two sets of detection light with non-overlapping wavelength ranges according to the working signal. The detection light is visible light to infrared optical radiation.

[0101] Reference Figure 1 and Figure 2 As shown, the detection light source 110 includes multiple sub-detection light sources 111 arranged in a preset detection area on the carrier 10. During operation, each sub-detection light source 111 can independently receive working signals. The multiple sub-detection light sources 111 are arrayed in the preset detection area, which can cover and extend beyond the width of the target blood vessel on both sides. It can also accommodate individual differences in the position and angle of subcutaneous blood vessels caused by wear-related displacement, limb rotation, etc., ensuring that at least a portion of the multiple sub-detection light sources 111 can illuminate the target blood vessel body. This avoids the problem of the detection light source 110 shifting as a whole and falling entirely on the tissue outside the blood vessel, resulting in the inability to collect effective blood backscatter signals.

[0102] The processing unit 12 implements independent switching control for each sub-detection light source 111, without needing to turn on all sub-detection light sources 111 simultaneously. It only needs to selectively select the sub-detection light sources 111 corresponding to the blood vessel projection area and the adjacent tissue area based on the actual position of the target blood vessel in the preset detection area, reducing stray light noise caused by invalid optical paths, saving energy and being highly efficient. The unactivated sub-detection light sources 111 serve as redundancy and can also provide supplementation when individual sub-detection light sources 111 are damaged or malfunction, improving operational reliability. At the same time, it also provides the electrical basis for zoned emission or time-division emission.

[0103] For example, a spatial partitioning method is used to output dual-wavelength detection light. At the same time, some sub-detection light sources 111 emit detection light of the first wavelength, while others emit detection light of the second wavelength. This allows for the simultaneous and parallel acquisition of backscattered signals of both wavelengths, shortening the total measurement time and improving detection efficiency. Sub-detection light sources 111 emitting different wavelengths can be staggered within a preset detection area, ensuring that the two wavelengths uniformly cover the target detection area and illuminate the same target blood vessel region. This guarantees the consistency of the characteristics of the measured object corresponding to the two sets of optical data, eliminating data errors caused by the slight uniqueness of the target blood vessel during sequential measurements. Combined with the blood vessel imaging recognition results, wavelength configurations can be assigned to the partitioned sub-light sources located above and beside the target blood vessel, simultaneously obtaining R under dual wavelengths. on and R off The original signal.

[0104] In time-division mode, the same sub-detector light source 111 can output detection light of two wavelengths, λ1 and λ2, in a time-division manner. This eliminates the need to integrate two sets of light-emitting chips on a single sub-detector light source 111, reducing the hardware complexity of a single sub-detector light source 111 and facilitating module miniaturization. This is beneficial for the non-invasive blood lipid detection device of this application embodiment to be used in confined spaces when adapted to small smart wearable devices such as watches and bracelets. Time-division alternating emission also avoids spectral crosstalk caused by simultaneous dual-wavelength emission. The optical signal receiver 112 collects the reflected light of the corresponding wavelength in a time-division manner, reducing mutual interference between signals of different wavelengths and improving the separation of the two sets of wavelength signals. In working scenarios with large wearing offsets and a small number of effective sub-light sources, the time-division mode can achieve multiplexing of dual-wavelength measurements for a limited number of sub-detector light sources 111. If the number of sub-detector light sources 111 is sufficient, it can also be switched to a partitioned parallel working mode to speed up the measurement and improve the mode adaptability of the smart wearable device of this application embodiment.

[0105] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A non-invasive blood lipid detection device, characterized in that, It includes a carrier for adhering to the skin, and a detection unit and a processing unit respectively disposed on the carrier and electrically connected to each other; The detection unit includes a detection light source and an optical signal receiver arranged sequentially along the length of the target detection position. The detection light source emits two sets of detection light with non-overlapping wavelength ranges toward the target detection position. The detection light is visible light to infrared optical radiation. The optical signal receiver receives two sets of reflected light with different wavelength ranges carrying target detection position information. The processing unit extracts the backscattered light signal from the two sets of reflected light with different wavelength ranges, retrieves pre-stored physiological information parameters to calculate the blood absorption coefficient and blood scattering coefficient, and calculates and outputs the corresponding blood lipid parameter information.

2. The non-invasive blood lipid detection device as described in claim 1, characterized in that, The detection light source includes multiple sub-detection light sources arranged in a preset detection area on the carrier, and the preset detection area can at least cover the width direction of the target detection position.

3. The non-invasive blood lipid detection device as described in claim 2, characterized in that, The preset detection area is rectangular, and it extends across the target detection position and beyond the width of the target detection position on both sides.

4. The non-invasive blood lipid detection device as described in claim 2, characterized in that, The preset detection area is circular, spanning and covering both sides of the target detection location and extending beyond the width of the target detection location. An imaging sensor is also provided at the center of the circular area. The imaging sensor is electrically connected to the processing unit. The imaging sensor transmits the subcutaneous scattering image of the target detection location it captures to the processing unit, where it is analyzed and processed.

5. The non-invasive blood lipid detection device as described in claim 1, characterized in that, An operation panel is also provided on the carrier, and operation keys are provided on the operation panel. Working signals are sent to the detection unit through the operation keys.

6. The non-invasive blood lipid detection device as described in claim 5, characterized in that, The operation panel is also equipped with a display screen for displaying the blood lipid parameter information calculated and output by the processing unit.

7. The non-invasive blood lipid detection device as described in claim 5, characterized in that, The carrier is also equipped with an audio component, which is signal-connected to the processing unit. The blood lipid parameter information calculated and output by the processing unit is broadcast through the audio component.

8. The non-invasive blood lipid detection device as described in claim 5, characterized in that, The processing unit also includes a memory for storing previously detected data, and the stored previously detected data can be retrieved via the operation key.

9. A detection method for a non-invasive blood lipid detection device, applied to the non-invasive blood lipid detection device as described in any one of claims 1-8, characterized in that, The method includes: The detection light source emits two sets of non-overlapping detection light in the wavelength range toward the target detection position according to the working signal. The detection light is visible light to infrared optical radiation. The processing unit receives two sets of reflected light of different wavelength ranges from the optical signal receiver, which carry the target detection location information, and extracts the backscattered light signal from the two sets of reflected light. Based on physiological information data, vascular-related parameters are matched and substituted into a differential analysis algorithm to obtain a dual-wavelength signal of scattered light from perivascular tissue. The effective attenuation coefficient of blood in blood vessels is obtained based on the diffusion approximation algorithm. The contrast difference of the effective attenuation coefficient of blood in blood vessels is calculated to obtain the absorption coefficient and scattering coefficient of blood. The blood absorption coefficient and scattering coefficient are input into the database for parameter comparison, and the corresponding blood lipid parameter information is output.

10. The detection method of the non-invasive blood lipid detection device as described in claim 9, characterized in that, The effective attenuation coefficient of blood in blood vessels is obtained based on the diffusion approximation algorithm. The contrast difference of the effective attenuation coefficient of blood in blood vessels is calculated to obtain the absorption coefficient and scattering coefficient of blood, including: The effective attenuation coefficient of blood in blood vessels with two wavelengths is obtained based on the diffusion approximation algorithm; The effective attenuation coefficient of the blood's dual wavelengths is compared with a preset standard parameter threshold. If it exceeds the preset standard parameter threshold, the vascular-related parameters are corrected accordingly, and the difference analysis algorithm is used again to calculate the dual wavelength signal of the scattered light from the tissues surrounding the blood vessels.

11. The detection method of the non-invasive blood lipid detection device as described in claim 9, characterized in that, The non-invasive blood lipid detection device also includes an imaging sensor positioned at the center of a pre-defined circular detection area; The method further includes: The imaging sensor captures subcutaneous scattering images of the target detection location; The subcutaneous scattering image is analyzed to create a vascular image at the target detection location.

12. The detection method of the non-invasive blood lipid detection device as described in claim 11, characterized in that, After the imaging sensor acquires a subcutaneous scattering image of the target detection location, the method further includes: The processing unit receives the subcutaneous scattering image and, based on scattering theory, processes it to obtain the target blood vessel depth and target blood vessel diameter; Based on the target blood vessel depth and target blood vessel diameter, the target blood vessel depth ratio coefficient and target blood vessel diameter ratio coefficient are obtained by matching simulation databases of blood vessel models of different sizes and depths. Based on the difference operation to filter noise, the effective attenuation coefficient of the blood in the blood vessels after filtering noise is calculated.

13. A smart wearable device, characterized in that, The non-invasive lipid detection device as described in any one of claims 1 to 8 further includes a band structure, wherein the non-invasive lipid detection device is fixedly disposed on the band structure, and the detection unit of the non-invasive lipid detection device is attached to the skin at the target detection location by a carrier and then constrained and fixed by the band structure.

14. The smart wearable device as described in claim 13, characterized in that, The detection light source of the non-invasive blood lipid detection device includes multiple sub-detection light sources arranged in a preset detection area on the carrier; after the detection unit of the non-invasive blood lipid detection device is attached to the skin at the target detection location through the carrier, the multiple sub-detection light sources independently receive working signals and can emit two sets of detection light with non-overlapping wavelength ranges according to the working signal. The detection light is visible light to infrared optical radiation.

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