Low-power laser line scanning raman imaging of the nail fold for blood lipid and blood glucose detection system and method
By using low-power laser line scanning Raman imaging technology, combined with line scanning illumination and a high-flux optical system, safe, rapid, and accurate combined detection of blood lipids and blood glucose in the nailfold region is achieved. This solves the problems of fluorescence background interference and signal attenuation in traditional Raman systems, making it suitable for non-invasive, convenient high-frequency screening and home monitoring.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHEJIANG UNIV
- Filing Date
- 2026-07-06
- Publication Date
- 2026-08-04
AI Technical Summary
Existing technologies make it difficult to perform rapid, safe, and accurate combined detection of blood lipids and blood glucose in the nailfold region at low power. Furthermore, traditional Raman systems are prone to fluorescence background interference and signal attenuation, making it difficult to effectively extract blood glucose characteristic peaks.
Low-power laser line scanning Raman imaging technology is used, combined with a line scanning illumination and high-flux optical system. The laser is precisely projected through the positioning imaging module, the scattered light is collected by the Raman signal collection module, and converted into an electrical signal by the spectral dispersion and detection module. Combined with the data processing module, blood lipid and blood glucose features are extracted.
It enables safe, rapid, and accurate semi-quantitative combined detection of blood lipids and blood glucose in the nailfold area under low power, reduces the risk of thermal damage to the skin from laser, improves the signal-to-noise ratio, and reduces measurement errors. It is suitable for non-invasive, convenient high-frequency screening and home monitoring.
Smart Images
Figure CN122498837A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of biomedical optical detection technology, specifically relating to a system and method for non-invasive, safe, and real-time detection of blood lipids and blood glucose in the nail fold (skin at the base of the nail) using low-power laser fast line scanning Raman imaging technology. Background Technology
[0002] Dyslipidemia and diabetes are major risk factors for cardiovascular disease, and the two often coexist. Routine blood lipid and glucose testing relies on venous or finger-prick blood sampling, which is invasive, requires professional personnel and consumables, and is difficult to use for high-frequency screening or home monitoring. Raman spectroscopy can provide molecular "fingerprint" information and can be used for lipid and glucose composition analysis. However, traditional point-focusing Raman systems often require high laser power densities (>50 mW / cm²) to achieve a sufficient signal-to-noise ratio. Prolonged irradiation may cause thermal effects or phototoxicity to living tissue and easily introduce strong fluorescence background. Furthermore, Raman signals attenuate significantly in areas with thicker stratum corneum (such as fingertips and forearms), making it difficult to detect lipoprotein and glucose signals in subcutaneous capillaries. The nail fold (the skin fold proximal to the nail root) has an extremely thin stratum corneum (10–20 µm) and is rich in subcutaneous capillary plexuses, making it an ideal non-invasive optical window. Current research has attempted to use nailfolds for Raman spectroscopy detection, but a method is lacking that can achieve rapid imaging, safely acquire high signal-to-noise ratio spectra at extremely low power, and simultaneously output blood lipid and blood glucose results. Furthermore, the Raman characteristic peaks of blood glucose (such as 1125 cm⁻¹) are still under development. -1 1360cm -1 The signal is weak and easily interfered with by the tissue background, making it difficult for traditional methods to extract effectively at low power. This invention solves this problem by using line scan Raman imaging and a multivariate model. Summary of the Invention
[0003] This invention aims to provide a low-power laser line-scanning Raman imaging system and method for detecting blood lipids and blood glucose in the nailfold. By employing line-scanning illumination and a high-flux optical system, the required laser power density is significantly reduced, enabling safe, rapid, and accurate semi-quantitative combined detection of blood lipids and blood glucose in the nailfold region. This invention specifically incorporates Raman spectroscopy of glucose standards as a basis for system validation, ensuring the reliability of blood glucose detection.
[0004] The technical solution for achieving the technical objective of this invention is as follows: A low-power laser line scanning Raman imaging nailfold blood lipid and blood glucose detection system includes: A low-power laser fast line scanning light source module is used to generate a linear light spot and perform fast line scanning Raman imaging of the nailfold region; The positioning imaging module is used to observe the nailfold area with visible light and guide the line spot to be precisely projected onto the area without keratinocytes; Raman signal collection module, used to collect Raman scattered light emitted by stimulated emission from nailfold tissue; The spectral dispersion and detection module is used to disperse Raman scattered light and convert it into an electrical signal; The data processing and control module is used to simultaneously extract lipid-related features and / or blood glucose-related features from Raman imaging data or spatially averaged aggregated spectra, and calculate lipid index and blood glucose concentration or relative index respectively.
[0005] The low-power laser fast line-scanning light source module has a laser wavelength of 780–920 nm, a line spot length of 3–15 mm, a line width ≤200 µm, a total output power ≤20 mW, and a power density per unit area that meets the maximum permissible laser irradiation (MPE) under fast scanning conditions. It also includes a one-dimensional scanning galvanometer to achieve rapid line spot translation. The Raman signal collection module includes a high numerical aperture (NA≥0.4) focusing lens and at least one notch filter or edge filter. The spectral dispersion and detection module employs an imaging spectrometer and a back-illuminated deep depletion layer CCD, with a spectral resolution ≤8 cm⁻¹. -1 And the spectral coverage range includes at least 800–1800 cm⁻¹ -1 and 2800–3100cm -1 .
[0006] A non-invasive method for combined detection of blood lipids and blood glucose in the nailfold based on the aforementioned system includes the following steps: a) Project a low-power laser fast line scanning spot onto the subject's nailfold area and locate it using visible light indicators, avoiding the nail plate and areas of obvious pigmentation. Start the fast scan and simultaneously acquire Raman spectral data containing spatial distribution information. b) Preprocess the acquired spectral data, including bad pixel removal, fluorescence background subtraction and water background suppression, to obtain the net Raman spectrum or the spectrum after spatial averaging. c) Extract the intensity of characteristic peaks of blood lipids from the net Raman spectrum (including 1440 cm⁻¹). -1 and 1003cm -1 ) and blood glucose characteristic peak (including 1125cm) -1 1360cm -1 Or high wavenumber region CH peak); d) Input the extracted features into the lipid calibration model and the blood glucose calibration model respectively to obtain the lipid estimates and blood glucose estimates; e) Output the joint detection results.
[0007] The method described in step b) involves subtracting the fluorescence background using polynomial fitting, adaptive iterative weighted least squares (airPLS), or wavelet transform.
[0008] The method described in step d) uses a linear regression model for blood lipid calibration, with the input being the ratio R = I. 1440 / I 1003 Or I 1660 / I 1003 The output is the concentration of total cholesterol, triglycerides, or low-density lipoprotein cholesterol.
[0009] The method described in step d) uses a multivariate regression model, which is selected from partial least squares regression (PLSR), principal component regression (PCR), or artificial neural network (ANN). The input to the model is the full spectrum after fluorescence subtraction (including at least 800–1800 cm⁻¹). -1 and / or 2800–3100cm -1 The output is the blood glucose concentration (mmol / L).
[0010] The lipid calibration model and blood glucose calibration model were obtained by regression training on the nailfold Raman spectra of at least 20 subjects and the corresponding venous lipid and fingertip blood glucose reference values.
[0011] The data processing and control module is configured as follows: The first output channel outputs lipid-related parameters, including estimated values of total cholesterol, triglycerides, or low-density lipoprotein cholesterol. The second output channel outputs an estimated blood glucose concentration or a relative blood glucose index. Furthermore, both outputs are based on the same low-power laser fast line scan Raman imaging acquisition, without the need to replace any hardware components.
[0012] The nail fold area refers to the skin without keratinocytes at the proximal nail fold at the base of the nail. Before rapid line laser scanning, the location is assisted by visible light and / or color camera images, and the subject's hand is kept fixed during the scanning process.
[0013] The total output power of the low-power laser fast line scanning light source module is ≤20mW. The laser dwell time at a single spatial point is less than 100ms through fast scanning galvanometer control, thereby effectively avoiding the heat accumulation effect. This allows the system to meet the 3R or 1 class laser safety specifications without the need for additional protective measures.
[0014] The beneficial effects of this invention are:
[0015] 1. Extremely high safety: Low-power line scanning illumination is used, with a total power of ≤20mW. Due to the rapid scanning of the galvanometer, the irradiation time of the laser at any fixed point on the skin is extremely short (<100ms). The equivalent average power density is far below the allowable limit for the skin in international laser safety standards. It is a low-risk laser application. Long-term measurement will not cause any tissue thermal damage or phototoxicity. No special protection is required and the subject will not feel anything.
[0016] 2. High signal quality: Line scanning combined with a high-throughput collection system enables the acquisition of high signal-to-noise ratio Raman spectra even at low power, clearly distinguishing characteristic peaks of lipids and glucose. The system's sensitivity for detecting lipid and glucose molecules was verified using Raman spectroscopy of standard samples. Compared to single-point measurements, spatial averaging with line scanning increases the effective photon flux by 3-5 times, significantly reducing dependence on instantaneous power.
[0017] 3. Imaging advantages: Fast line scan Raman imaging can obtain spatial distribution information of the nailfold region, reduce single-point measurement errors, and improve the representativeness of the results.
[0018] 4. Non-invasive and convenient: No blood collection, no consumables, no pain, and high subject compliance.
[0019] 5. Combined detection capability: One measurement, without the need to change hardware, simultaneously obtains two key cardiovascular metabolic indicators, blood lipids and blood glucose, which is particularly suitable for screening and follow-up of people with diabetes and dyslipidemia. Attached Figure Description
[0020] Figure 1 This is a schematic diagram of low-power laser fast line scanning Raman imaging detection in the system of the present invention, wherein L: lens; CL: cylindrical lens; DM: dichroic mirror; LPF: long-pass filter; GM: galvanometer; SL: scanning lens; TL: telescope lens; OBJ: objective lens.
[0021] Figure 2(a) shows the Raman spectrum of cholesterol standards (solid or solution).
[0022] Figure 2(b) shows the Raman spectra of glucose standard solutions of different concentrations.
[0023] Figure 3 Raman spectra of the nailfolds of three healthy subjects were measured (after fluorescence background subtraction and baseline correction). The spectra were shifted longitudinally for comparison, and lipid-related peaks (~1440 cm⁻¹) were clearly visible. -1 ) and internal reference peak (~1003cm) -1 Furthermore, blood glucose characteristic peak information can be extracted from it through a multivariate model, and inter-individual differences indicate that semi-quantitative blood lipid and blood glucose detection is feasible.
[0024] Figure 4For the Raman signal in blood from different blood glucose populations, the 1128cm mark was used to indicate the 1128cm mark. -1 Glucose characteristic peak. Detailed Implementation
[0025] The present invention will be further described below with reference to the accompanying drawings and embodiments.
[0026] Example 1: System Setup
[0027] like Figure 1 As shown, the system of the present invention includes a laser light source, a line scanning optical component, an illumination optical path, a collection optical path, a spectrometer, and a nailfold test area.
[0028] A 785nm frequency-stabilized laser diode (maximum output 30mW, set to 15mW) was used. The beam was shaped into a uniform line spot with a line length of 10mm and a line width of 100µm using a cylindrical lens and a Powell prism. A one-dimensional scanning galvanometer was then installed to achieve rapid vertical scanning of the line spot on the nail fold (scanning range 3mm, speed 10 frames / second). The total power was set to 15mW, although the line power density was 15mW / mm². 2 However, due to high-speed movement, the effective heat sink is extremely low, far below the safety limit. The light collection path uses an achromatic cemented doublet lens with NA=0.5, coupled with a 785nm notch filter (OD=6), followed by an imaging spectrometer with a focal length of 150mm (600 l / mm grating, 900nm blaze wavelength). The detector is a back-illuminated CCD (1024×256 pixels, deep depletion layer). The system integrates a color camera and visible light LEDs to display nail fold images in real time on the software interface, assisting the operator in avoiding the nail plate and aligning with the proximal nail fold. The control software is developed based on Python, integrating the airPLS baseline-cutting algorithm and the PLSR blood glucose model. The system collected spectra of cholesterol and glucose standards, as shown in Figures 2(a) and 2(b), verifying the system's ability to detect lipids and glucose.
[0029] Example 2: Blood lipid test verification
[0030] Twenty volunteers were selected, and Raman spectra of the nailfold line (integration time 10 seconds) and total cholesterol (TC) in venous blood were collected simultaneously. R = I was calculated after subtracting fluorescence from the spectra. 1440 / I 1003 A linear calibration curve was established: TC (mmol / L) = 2.1 × R + 1.5. The same individual was measured five times; the coefficient of variation (CV) was < 8%. Compared with venous blood sampling results, the root mean square error of prediction (RMSEP) was < 0.6 mmol / L, and the correlation coefficient r = 0.82. Figure 2(a) shows the Raman spectrum of the cholesterol standard as a reference. Figure 3Raman spectra (including lipid peaks) of the nail folds of three healthy individuals were presented. Compared to the traditional single-point focusing mode, the signal-to-noise ratio of the linear scanning integrated spectrum in this embodiment is improved by approximately 40%, and the tolerance for slight finger displacement is significantly increased.
[0031] Example 3: Blood Glucose Detection Verification
[0032] Ten healthy volunteers were selected to participate in the oral glucose tolerance test (OGTT). Nailfold Raman spectroscopy was measured in a fasting state (integration time 20 seconds), followed by oral administration of 75g of glucose solution. Nailfold spectroscopy was then measured every 15 minutes, and fingertip blood glucose (reference range) was collected simultaneously. A PLSR was used to analyze the full spectrum (800–1800 cm⁻¹). -1 + 2800–3100cm -1 A model was established using reference blood glucose values. To verify the system's response to glucose, the spectrum of glucose standards was pre-collected (Figure 2(b)), confirming the 1125 cm⁻¹ value. -1 1360cm -1 The positions of characteristic peaks were determined. Cross-validation results showed a root mean square error of prediction (RMSEP) of 1.1 mmol / L, a correlation coefficient r = 0.79, and Clark error grid analysis indicated that 98% of the points fell within the clinically acceptable zone A+B. No heat or discomfort was experienced by the subjects throughout the experiment. Figure 4 As shown, the analysis indicates that in the Raman fingerprint region of glucose molecules (approximately 500–1700 cm⁻¹), -1 It can be clearly observed that it is located at 1128cm. -1 The Raman characteristic peaks are attributed to the vibrations of the –COO⁻ or C–O–H groups in the glucose molecule. Analysis shows that as the blood glucose concentration of the subject increases, the full-spectrum characteristic after PLSR model weighting reaches 1128 cm⁻¹. -1 The intensity of the characteristic peaks also shows a significant increasing trend.
[0033] Example 4: Combined detection of blood lipids and blood glucose
[0034] Twenty subjects with both dyslipidemia and type 2 diabetes underwent a single-pass Raman spectroscopy acquisition using this system (integration time 25 seconds). After fluorescence subtraction, the spectra were as follows: Calculate R_lipid = I 1440 / I 1003 Substituting the values into the lipid calibration equation (Example 2), we obtain the estimated total cholesterol value.
[0035] The full spectrum was input into the blood glucose PLSR model (Example 3) to obtain the blood glucose estimate.
[0036] Compared with venous blood lipids and fingertip blood glucose: total cholesterol r=0.81, blood glucose r=0.78.
[0037] The total measurement time (including positioning and scanning) did not exceed 2 minutes, and all subjects reported no discomfort, indicating good safety. Combined test results can be output simultaneously; Figures 2(a) and 2(b) provide calibration benchmarks for blood lipid and blood glucose tests, respectively.
[0038] The embodiments described above can be further combined or replaced, and these embodiments are merely descriptions of preferred embodiments of the present invention, not limitations on the concept and scope of the present invention. Various changes and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the inventive concept are all within the protection scope of the present invention. The protection scope of the present invention is given by the appended claims and any equivalents.
Claims
1. A low-power laser line scanning Raman imaging system for detecting blood lipids and blood glucose in the nailfold, characterized in that, include: A low-power laser fast line scanning light source module is used to generate a linear light spot and perform fast line scanning Raman imaging of the nailfold region; The positioning imaging module is used to observe the nailfold area with visible light and guide the line spot to be precisely projected onto the area without keratinocytes; Raman signal collection module, used to collect Raman scattered light emitted by stimulated emission from nailfold tissue; The spectral dispersion and detection module is used to disperse Raman scattered light and convert it into an electrical signal; The data processing and control module is used to simultaneously extract lipid-related features and / or blood glucose-related features from Raman imaging data or spatially averaged aggregated spectra, and calculate lipid index and blood glucose concentration or relative index respectively.
2. The system according to claim 1, characterized in that, The low-power laser fast line-scanning light source module has a laser wavelength of 780–920 nm, a line spot length of 3–15 mm, a line width ≤200 µm, and a total output power ≤20 mW. Its power density per unit area meets the maximum allowable laser irradiation under fast scanning conditions, and it includes a one-dimensional scanning galvanometer to achieve rapid line spot translation. The Raman signal collection module includes a high numerical aperture focusing lens with NA ≥ 0.4 and at least one notch filter or edge filter. The spectral dispersion and detection module employs an imaging spectrometer and a back-illuminated deep depletion layer CCD, with a spectral resolution ≤8 cm⁻¹. -1 And the spectral coverage range includes at least 800–1800 cm⁻¹ -1 and 2800–3100cm -1 .
3. The system according to claim 1, characterized in that, The data processing and control module is configured as follows: The first output channel outputs lipid-related parameters, including estimated values of total cholesterol, triglycerides, or low-density lipoprotein cholesterol. The second output channel outputs an estimated blood glucose concentration or a relative blood glucose index. Furthermore, both outputs are based on the same low-power laser fast line scan Raman imaging acquisition, without the need to replace any hardware components.
4. The system according to claim 1, characterized in that, The total output power of the low-power laser fast line scanning light source module is ≤20mW, and the laser dwell time at a single spatial point is less than 100ms through fast scanning galvanometer control.
5. A non-invasive method for combined detection of blood lipids and blood glucose in the nailfold based on the system described in claim 1, characterized in that, Includes the following steps: a) Project a low-power laser fast line scanning spot onto the subject's nailfold area and locate it using visible light indicators, avoiding the nail plate and areas of obvious pigmentation. Start the fast scan and simultaneously acquire Raman spectral data containing spatial distribution information. b) Preprocess the acquired spectral data, including bad pixel removal, fluorescence background subtraction and water background suppression, to obtain the net Raman spectrum or the spectrum after spatial averaging. c) Extracting the 1440cm² region from the net Raman spectrum -1 and 1003cm -1 The characteristic peak intensity of blood lipids and the inclusion of 1125cm -1 1360cm -1 Or the characteristic blood glucose peak of the CH peak in the high wavenumber region; d) Input the extracted features into the lipid calibration model and the blood glucose calibration model respectively to obtain the lipid estimates and blood glucose estimates; e) Output the joint detection results.
6. The method according to claim 5, characterized in that, In step b), the method for subtracting the fluorescent background is polynomial fitting, adaptive iterative weighted least squares, or wavelet transform.
7. The method according to claim 5, characterized in that, The lipid calibration model described in step d) is a linear regression model, with the input being the ratio R = I. 1440 / I 1003 Or I 1660 / I 1003 The output is the concentration of total cholesterol, triglycerides, or low-density lipoprotein cholesterol.
8. The method according to claim 5, characterized in that, The blood glucose calibration model described in step d) is a multivariate regression model, which is selected from partial least squares regression, principal component regression or artificial neural network; the input of the model is the full spectrum after fluorescence subtraction, and the output is blood glucose concentration.
9. The method according to claim 5, characterized in that, The lipid calibration model and blood glucose calibration model were obtained by regression training on the nailfold Raman spectra of at least 20 subjects and the corresponding venous lipid and fingertip blood glucose reference values.
10. The method according to claim 5, characterized in that, The nail fold area refers to the skin without keratinocytes at the proximal nail fold at the base of the nail. Before rapid line laser scanning, the location is assisted by visible light and / or color camera images, and the subject's hand is kept fixed during the scanning process.