Laser depilation dynamic parameter adjusting method based on skin typing recognition

Abstract

The invention discloses a laser depilation dynamic parameter adjustment method based on skin typing recognition, and relates to the technical field of laser depilation, and the method comprises the steps: constructing a three-dimensional skin model of a depilation region through multi-dimensional data cross validation; detecting local pigmentation caused by friction in each area; detecting the blood flow signal intensity of capillary vessels around the hair follicles, judging the period of the hair and generating a hair follicle activity thermodynamic diagram in real time; a three-dimensional energy focus is formed through double-beam crossing; skin curved surface data are obtained through a pressure sensor, liquid crystal molecules in a light valve are driven to be arranged, and light spots are adjusted to be in the shape attached to an unhairing area; the basal metabolic rate of the patient is measured through a noninvasive bioelectrical impedance analysis technology, and the energy density is adjusted based on the basal metabolic rate; and establishing a digital twinborn model, and integrating depilation data, skin state and hormone level information. A three-dimensional energy focus is formed through double-beam crossing, energy is accurately focused on the root of the hair follicle, and epidermis damage is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of laser hair removal, and in particular to a method for adjusting dynamic parameters of laser hair removal based on skin type recognition. Background Art

[0002] With the increasing popularity of laser hair removal technology, the market demand for personalized, precise hair removal is growing. Traditional laser hair removal devices often use fixed parameters, making it difficult to adapt to different patients' skin types, hair conditions, and physiological characteristics. This leads to inconsistent hair removal results and can even cause side effects such as skin burns and hyperpigmentation. Summary of the Invention

[0003] In order to solve the above technical problems, a method for dynamic parameter adjustment of laser hair removal based on skin type recognition is provided. This technical solution solves the problems raised in the above background technology.

[0004] In order to achieve the above objects, the technical solution adopted by the present invention is: The method for dynamic parameter adjustment of laser hair removal based on skin type recognition includes: Using a six-spectrum fusion imaging system and multi-dimensional data cross-validation, a three-dimensional skin model of the hair removal area is constructed; Correct skin color deviation, detect local pigmentation caused by friction in each area, and dynamically adjust the classification parameters of the area; By detecting the capillary blood flow signal intensity around the hair follicles, the hair cycle is determined and a real-time heat map of hair follicle activity is generated; Based on the principle of coherent light interference, a three-dimensional energy focus is formed by crossing two beams. A beam of horizontally polarized light is emitted to scan the skin surface to generate the coordinates of the hair follicle entrance. Then a vertically polarized light is emitted to penetrate the root of the hair follicle to obtain depth data. The pressure sensor acquires the skin surface data, drives the arrangement of liquid crystal molecules in the light valve, and adjusts the light spot to a shape that fits the hair removal area; Introducing a metabolic rate detection module to measure the patient's basal metabolic rate through non-invasive bioelectrical impedance analysis technology and adjust the energy density based on the basal metabolic rate; A digital twin model is established to integrate hair removal data, skin condition, and hormone level information. Through machine learning, hair follicle regeneration trends are predicted, and hair removal parameters can be adjusted and maintained in advance.

[0005] Preferably, based on the principle of coherent light interference, a three-dimensional energy focus is formed by crossing two light beams, a beam of horizontally polarized light is emitted to scan the skin surface to generate the coordinates of the hair follicle entrance, and then a vertically polarized light is emitted to penetrate the hair follicle root to obtain depth data. Specifically, the method includes: The light beam is adjusted to horizontal polarization through a polarizer and then split into two beams by a beam splitter. One beam directly illuminates the skin surface, and the other beam serves as a reference light for interference signal reception. The polarization direction of the light beam is rotated 90° by a half-wave plate to adjust it to vertical polarization. After passing through a beam splitter, it is transmitted coaxially with the horizontal light beam. The two beams intersect in the scanning area to form a three-dimensional energy focus. A two-dimensional galvanometer scanning module is configured to control the horizontal polarized light to scan the skin surface point by point, while the vertical polarized light synchronously follows the horizontal beam path and is emitted with a delayed delay. When horizontally polarized light illuminates the skin surface, the reflected light and the reference light form interference fringes on the detector. By analyzing the fringe displacement of the interference fringes, the height difference of the skin surface is calculated as twice the fringe displacement; In the surface topography, the hair follicle entrance appears as a concave structure. The center coordinates of the concave area are extracted through edge detection and marked as the hair follicle entrance position. Vertically polarized light is emitted at the entrance coordinate of the hair follicle and crosses with the horizontally polarized light under the skin, forming a local high energy density area. The energy focus excites the hair follicle root tissue to produce backscattered light; The backscattered light and the reference light form an interference signal on the detector, and its phase change is proportional to the depth of the hair follicle; The optical path difference formula is used to calculate the hair follicle depth based on the phase difference, vertical light wavelength and skin refractive index.

[0006] Preferably, the step of acquiring skin surface data through a pressure sensor, driving the arrangement of liquid crystal molecules in the light valve, and adjusting the light spot to a shape that fits the hair removal area specifically includes: Evenly attach the flexible pressure sensor array to the surface of the hair removal head, covering all areas that contact the skin. When the device is not in contact with the skin, record the initial pressure value of each sensor as a benchmark; Slowly press the hair removal head onto the skin surface, and the sensor array collects the pressure values ​​of each area in real time to form a pressure distribution map; Based on the pressure distribution map and the skin's elasticity, the height of the depressions or protrusions on the skin surface is calculated to construct a three-dimensional surface model. The surface model is smoothed to eliminate sensor noise and local outliers, and based on the skin surface model, the shape of the light spot that fits it is determined to be an ellipse or an irregular polygon; Convert the target spot shape into the arrangement instructions of liquid crystal molecules. The liquid crystal molecules are arranged vertically by default, and they are rotated to horizontal arrangement by voltage control; Based on the brightness and darkness requirements of the light spot shape, different voltage values ​​are assigned to each area, with higher voltage in bright areas and lower voltage in dark areas. Send voltage signals to the liquid crystal layer of the light valve to control the liquid crystal molecules to align according to instructions; The optical sensor captures the light spot of the hair removal area, extracts the actual contour and compares it with the target shape, and calculates the degree of overlap between the two. Determine whether there is a deviation between the actual light spot and the target shape. If so, adjust the voltage value of the corresponding area. When expanding the light spot, increase the voltage in the edge area. When shrinking the light spot, reduce the voltage in the edge area. Repeat the adjustment until the light spot completely fits the skin surface. If not, no output is made.

[0007] Compared with the prior art, the present invention has the following beneficial effects: Through multi-spectral data cross-validation, skin color deviation is corrected and local pigmentation is detected, typing parameters are dynamically adjusted, and the blood flow signal intensity is used to determine the hair cycle. A heat map of hair follicle activity is generated, and energy is concentrated during the growth phase and reduced during the regression and resting phases. This improves the efficiency of single hair removal and reduces the number of hair removals. Energy is precisely focused on the roots of the hair follicles to avoid epidermal damage. The light spot fits the skin surface to ensure even energy distribution and improve hair removal safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 This is a flow chart of the method for dynamic parameter adjustment of laser hair removal based on skin type recognition according to the present invention; Figure 2 This is a flow chart of the method for constructing a three-dimensional skin model of a hair removal area according to the present invention; Figure 3 This is a flow chart of the method for generating a hair follicle activity thermogram in real time according to the present invention; Figure 4 This is a flow chart of the method for obtaining depth data of the present invention; Figure 5 This is a flow chart of the method for adjusting the light spot to a shape that fits the hair removal area according to the present invention; Figure 6 This is a flow chart of the method for adjusting energy density based on basal metabolic rate of the present invention; Figure 7 This is a flow chart of the method for establishing a digital twin model of the present invention. DETAILED DESCRIPTION

[0009] The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are merely examples, and those skilled in the art may conceive of other obvious variations.

[0010] Reference Figure 1 As shown, the dynamic parameter adjustment method for laser hair removal based on skin type recognition includes: Using a six-spectrum fusion imaging system and multi-dimensional data cross-validation, a three-dimensional skin model of the hair removal area is constructed; Correct skin color deviation, detect local pigmentation caused by friction in each area, and dynamically adjust the classification parameters of the area; By detecting the capillary blood flow signal intensity around the hair follicles, the hair cycle is determined and a real-time heat map of hair follicle activity is generated; Based on the principle of coherent light interference, a three-dimensional energy focus is formed by crossing two beams. A beam of horizontally polarized light is emitted to scan the skin surface to generate the coordinates of the hair follicle entrance. Then a vertically polarized light is emitted to penetrate the root of the hair follicle to obtain depth data. The pressure sensor acquires the skin surface data, drives the arrangement of liquid crystal molecules in the light valve, and adjusts the light spot to a shape that fits the hair removal area; Introducing a metabolic rate detection module to measure the patient's basal metabolic rate through non-invasive bioelectrical impedance analysis technology and adjust the energy density based on the basal metabolic rate; A digital twin model is established to integrate hair removal data, skin condition, and hormone level information. Through machine learning, hair follicle regeneration trends are predicted, and hair removal parameters can be adjusted and maintained in advance.

[0011] Reference Figure 2 As shown, a six-spectrum fusion imaging system is used to construct a three-dimensional skin model of the hair removal area through multi-dimensional data cross-validation, specifically including: An industrial camera combined with digital grating projection is used to capture the deformed stripes on the skin surface, extract height information, perform visible light imaging, and generate an initial 3D contour. Using a near-infrared light source, obtaining tissue optical characteristic parameters based on diffuse reflectance imaging, simulating and inverting the distribution of dermal layer components, and performing near-infrared spectral imaging; the optical characteristic parameters include absorption coefficient and scattering coefficient; Based on the depolarization effect caused by the interaction between polarized light and the skin surface microstructure, an amplitude-divided polarization camera is used to calculate the target's polarization degree and polarization angle, map the surface roughness distribution, and perform polarized light imaging. Laser is used to excite endogenous fluorescent substances in the skin, and the fluorescent signals are captured. The principal component analysis is combined to distinguish the inflammatory area from the normal tissue and perform fluorescence imaging. The endogenous fluorescent substances in the skin include porphyrin and melanin. Using laser as the excitation source, the microscope scans the skin surface to obtain the characteristic peak intensity distribution of lipids and proteins for Raman spectroscopy imaging; Using a terahertz time-domain spectroscopy system, the dielectric constant distribution of the skin is obtained through reflective imaging, and the three-dimensional structure of the dermis is reconstructed through finite element analysis to perform terahertz wave imaging. Spatial overlap analysis was performed between the dermal fracture area detected by terahertz and the collagen degradation area shown by Raman spectroscopy to verify the consistency between structural damage and molecular changes; The correlation between skin barrier function and surface morphology after hair removal was evaluated by comparing moisture content measured by near-infrared spectroscopy with surface roughness calculated by polarized light; By combining the inflammatory areas marked by fluorescence imaging with the lipid peroxidation products detected by Raman spectroscopy, a quantitative relationship between inflammatory response and oxidative stress was established.

[0012] A near-infrared light source is used to illuminate the skin at a specific angle, and the intensity of the reflected light at different wavelengths is recorded by a detector. Based on the changes in the reflected light intensity, the skin's absorption and scattering abilities for near-infrared light are inferred, corresponding to the content of water, hemoglobin and other components in the dermis. The absorption and scattering parameters are mapped to the initial three-dimensional model to generate a heat map of the concentration distribution of water, hemoglobin and other components in the dermis.

[0013] Reference Figure 3 As shown, by detecting the capillary blood flow signal intensity around the hair follicles, the hair cycle is determined and a real-time heat map of hair follicle activity is generated. Specifically, the following steps are performed: The blood flow velocity of the microvessels around the hair follicles is measured by the principle of light scattering, and the blood flow velocity is located at a single hair follicle unit. Determine whether the blood flow velocity is higher than 15 mm / s. If so, output that the hair follicle is in the growth phase; if not, no output is made. Determine whether the blood flow velocity is less than 8 mm / s. If so, output that the hair follicle is in the resting phase; if not, output that the hair follicle is in the catagen phase; The blood flow data is converted into a color gradient map, with the growth phase hair follicles recorded in red, the catagen phase hair follicles recorded in yellow, and the resting phase hair follicles recorded in blue. The summary output is a hair follicle activity heat map.

[0014] When laser is used to irradiate the skin, the hemoglobin in the microvessels around the hair follicles absorbs specific wavelengths, such as 780nm near-infrared light. The blood flow velocity is calculated by detecting the frequency shift of the scattered light signal, namely the Doppler effect. The blood flow velocity data is mapped into color codes of red, yellow and blue, and a two-dimensional heat map is generated through spatial superposition to intuitively display the distribution of hair follicle activity.

[0015] Reference Figure 4 As shown, based on the principle of coherent light interference, a three-dimensional energy focus is formed by crossing two beams. A beam of horizontally polarized light is emitted to scan the skin surface to generate the coordinates of the hair follicle entrance. Then, a vertically polarized light is emitted to penetrate the root of the hair follicle to obtain depth data, including: The light beam is adjusted to horizontal polarization through a polarizer and then split into two beams by a beam splitter. One beam directly illuminates the skin surface, and the other beam serves as a reference light for interference signal reception. The polarization direction of the light beam is rotated 90° by a half-wave plate to adjust it to vertical polarization. After passing through a beam splitter, it is transmitted coaxially with the horizontal light beam. The two beams intersect in the scanning area to form a three-dimensional energy focus. A two-dimensional galvanometer scanning module is configured to control the horizontal polarized light to scan the skin surface point by point, while the vertical polarized light synchronously follows the horizontal beam path and is emitted with a delayed delay. When horizontally polarized light illuminates the skin surface, the reflected light and the reference light form interference fringes on the detector. By analyzing the fringe displacement of the interference fringes, the height difference of the skin surface is calculated as twice the fringe displacement; In the surface topography, the hair follicle entrance appears as a concave structure. The center coordinates of the concave area are extracted through edge detection and marked as the hair follicle entrance position. Vertically polarized light is emitted at the entrance coordinate of the hair follicle and crosses with the horizontally polarized light under the skin, forming a local high energy density area. The energy focus excites the hair follicle root tissue to produce backscattered light; The backscattered light and the reference light form an interference signal on the detector, and its phase change is proportional to the depth of the hair follicle; The optical path difference formula is used to calculate the hair follicle depth based on the phase difference, vertical light wavelength and skin refractive index.

[0016] The optical path difference formula is: , Where, is the depth of the hair follicle, is the phase difference, is the vertical light wavelength, is the skin refractive index; The liquid crystal spatial light modulator is used to dynamically adjust the shape of the light spot to fit the concave area of ​​the hair follicle entrance, thereby improving energy utilization and monitoring the backscattered light intensity in real time. If the signal at the root of the hair follicle disappears, indicating that the melanin is destroyed, the energy output in this area will be automatically terminated to reduce ineffective irradiation.

[0017] Reference Figure 5 As shown, the skin surface data is obtained through the pressure sensor, the liquid crystal molecules in the light valve are driven to arrange, and the light spot is adjusted to a shape that fits the hair removal area. Specifically, the following steps are performed: Evenly attach the flexible pressure sensor array to the surface of the hair removal head, covering all areas that contact the skin. When the device is not in contact with the skin, record the initial pressure value of each sensor as a benchmark; Slowly press the hair removal head onto the skin surface, and the sensor array collects the pressure values ​​of each area in real time to form a pressure distribution map; Based on the pressure distribution map and the skin's elasticity, the height of the depressions or protrusions on the skin surface is calculated to construct a three-dimensional surface model. The surface model is smoothed to eliminate sensor noise and local outliers, and based on the skin surface model, the shape of the light spot that fits it is determined to be an ellipse or an irregular polygon; Convert the target spot shape into the arrangement instructions of liquid crystal molecules. The liquid crystal molecules are arranged vertically by default, and they are rotated to horizontal arrangement by voltage control; Based on the brightness and darkness requirements of the light spot shape, different voltage values ​​are assigned to each area, with higher voltage in bright areas and lower voltage in dark areas. Send voltage signals to the liquid crystal layer of the light valve to control the liquid crystal molecules to align according to instructions; The optical sensor captures the light spot of the hair removal area, extracts the actual contour and compares it with the target shape, and calculates the degree of overlap between the two. Determine whether there is a deviation between the actual light spot and the target shape. If so, adjust the voltage value of the corresponding area. When expanding the light spot, increase the voltage in the edge area. When shrinking the light spot, reduce the voltage in the edge area. Repeat the adjustment until the light spot completely fits the skin surface. If not, no output is made.

[0018] Gaussian filtering is used to eliminate sensor noise, and outliers are corrected through local weighted regression to finally generate a smooth three-dimensional surface model. If the curvature radius of the model is greater than 10mm, the spot shape is a standard circle. If the curvature radius is between 5mm and 10mm, the spot shape is an ellipse. If the curvature radius is less than 5mm, the spot shape is an irregular polygon. The target shape is converted into polar coordinates or vertex coordinate sequences.

[0019] Reference Figure 6 As shown in the figure, a metabolic rate detection module is introduced to measure the patient's basal metabolic rate through non-invasive bioelectrical impedance analysis technology, and the energy density is adjusted based on the basal metabolic rate. Specifically, the following are included: Four sets of flexible conductive patches are installed on both sides of the hair removal head of the device, and the contact surface between the electrode and the skin is made of flexible conductive material; The device automatically emits weak currents of various frequencies to measure the whole body electrical impedance. The measurement is repeated three times and the average value is taken as the final data. The device estimates the target's body fat percentage based on the difference in impedance between intracellular and extracellular fluids, estimates the target's muscle mass based on the correlation between total body water content and impedance, and calculates their basal metabolic rate through a correction model; Determine whether basal energy consumption is lower than 80% of normal. If so, reduce energy intensity to avoid overstimulation. If not, do not output. Determine whether the basic energy expenditure is higher than 120% of the normal value. If so, increase the energy intensity; if not, use the standard energy intensity; When the energy intensity is reduced, the single pulse action time is extended to keep the total energy stable. When the energy intensity is increased, the electrode output power is enhanced and the hair removal interval is shortened.

[0020] Based on the characteristics that high-frequency current can more easily penetrate extracellular fluid and low-frequency current can more easily be blocked by intracellular fluid, the impedance difference at different frequencies is compared to estimate the proportion of body fat in total body weight. Combined with the correlation between whole body water content and impedance, the more water, the lower the impedance. The pre-entered age, gender, and height data are used to correct the calculation results to obtain muscle weight. Based on muscle mass, fat ratio, age, and gender, and referring to the metabolic rate database of healthy people, the system estimates the user's current basal energy consumption level. The system compares the calculation results with the average metabolic rate of people of the same age, gender, and weight to determine whether the user's metabolic rate is too low or too high.

[0021] Reference Figure 7 As shown, a digital twin model is established to integrate hair removal data, skin condition, and hormone level information. Through machine learning, the hair follicle regeneration trend is predicted, and the hair removal parameters are adjusted and maintained in advance. Specifically, The energy density, pulse width, hair removal frequency, epidermal temperature and impedance value of each hair removal are recorded by medical equipment; Regularly collect indicators of target hair follicle density, hair diameter, epidermal thickness, and inflammatory response; Obtain dynamic changes in androgen, estrogen, and metabolism-related hormones through blood tests; Newly collected hair removal data, skin conditions, and hormone levels are input into the digital twin model, which then outputs predicted values ​​for future hair follicle regeneration speed, new hair quality, and hair removal response cycle, identifying potential risks and generating early warning signals. Based on the hair follicle growth cycle model, the frequency of hair removal is increased during the predicted growth phase of the hair follicle and reduced during the resting phase of the hair follicle.

[0022] After the new data is input, the model completes the following predictions: the number of new hair follicles per unit area in the next 4 weeks, the thickness, color and growth direction of the new hair, and the effective duration of the current hair removal plan. If the prediction results show that the hair follicle regeneration rate exceeds the safety threshold or the hormone level is abnormal or the risk of skin inflammation increases, the system automatically triggers a warning signal.

[0023] Furthermore, the present solution also proposes a computer-readable storage medium on which a computer-readable program is stored. When the computer-readable program is called, the above-mentioned dynamic parameter adjustment method for laser hair removal based on skin type recognition is executed.

[0024] It is understandable that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state disk (SSD).

[0025] In summary, the advantages of the present invention are: through cross-validation of multispectral data, correcting skin color deviation and detecting local pigmentation, dynamically adjusting typing parameters, using blood flow signal intensity to judge the hair cycle, generating a hair follicle activity heat map, concentrating energy in the growth phase, reducing energy in the regression phase and resting phase, improving the efficiency of single hair removal, reducing the number of hair removal times, accurately focusing energy on the roots of hair follicles to avoid epidermal damage, and making the light spot fit the skin surface to ensure uniform energy distribution and improve hair removal safety.

[0026] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions merely illustrate the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for adjusting dynamic parameters of laser hair removal based on skin type recognition, characterized in that: include: Using a six-spectrum fusion imaging system and multi-dimensional data cross-validation, a three-dimensional skin model of the hair removal area is constructed; Correct skin color deviation, detect local pigmentation caused by friction in each area, and dynamically adjust the classification parameters of the area; By detecting the capillary blood flow signal intensity around the hair follicles, the hair cycle is determined and a real-time heat map of hair follicle activity is generated; Based on the principle of coherent light interference, a three-dimensional energy focus is formed by crossing two beams. A beam of horizontally polarized light is emitted to scan the skin surface to generate the coordinates of the hair follicle entrance. Then a vertically polarized light is emitted to penetrate the root of the hair follicle to obtain depth data. The pressure sensor acquires the skin surface data, drives the arrangement of liquid crystal molecules in the light valve, and adjusts the light spot to a shape that fits the hair removal area; Introducing a metabolic rate detection module to measure the patient's basal metabolic rate through non-invasive bioelectrical impedance analysis technology and adjust the energy density based on the basal metabolic rate; A digital twin model is established to integrate hair removal data, skin condition, and hormone level information. Through machine learning, hair follicle regeneration trends are predicted, and hair removal parameters can be adjusted and maintained in advance.

2. The method for dynamic parameter adjustment of laser hair removal based on skin type recognition according to claim 1, characterized in that: The six-spectrum fusion imaging system is used to construct a three-dimensional skin model of the hair removal area through multi-dimensional data cross-validation, specifically including: An industrial camera combined with digital grating projection is used to capture the deformed stripes on the skin surface, extract height information, perform visible light imaging, and generate an initial 3D contour. Using a near-infrared light source, obtaining tissue optical characteristic parameters based on diffuse reflectance imaging, simulating and inverting the distribution of dermal layer components, and performing near-infrared spectral imaging; the optical characteristic parameters include absorption coefficient and scattering coefficient; Based on the depolarization effect caused by the interaction between polarized light and the skin surface microstructure, an amplitude-divided polarization camera is used to calculate the target's polarization degree and polarization angle, map the surface roughness distribution, and perform polarized light imaging. Laser is used to excite endogenous fluorescent substances in the skin, and the fluorescent signals are captured. The principal component analysis is combined to distinguish the inflammatory area from the normal tissue and perform fluorescence imaging. The endogenous fluorescent substances in the skin include porphyrin and melanin. Using laser as the excitation source, the microscope scans the skin surface to obtain the characteristic peak intensity distribution of lipids and proteins for Raman spectroscopy imaging; Using a terahertz time-domain spectroscopy system, the dielectric constant distribution of the skin is obtained through reflective imaging, and the three-dimensional structure of the dermis is reconstructed through finite element analysis to perform terahertz wave imaging. Spatial overlap analysis was performed between the dermal fracture area detected by terahertz and the collagen degradation area shown by Raman spectroscopy to verify the consistency between structural damage and molecular changes; The correlation between skin barrier function and surface morphology after hair removal was evaluated by comparing moisture content measured by near-infrared spectroscopy with surface roughness calculated by polarized light; By combining the inflammatory areas marked by fluorescence imaging with the lipid peroxidation products detected by Raman spectroscopy, a quantitative relationship between inflammatory response and oxidative stress was established.

3. The method for dynamic parameter adjustment of laser hair removal based on skin type recognition according to claim 2, characterized in that: The method of detecting the blood flow signal intensity of capillaries around hair follicles to determine the hair cycle and generate a hair follicle activity heat map in real time specifically includes: The blood flow velocity of the microvessels around the hair follicles is measured by the principle of light scattering, and the blood flow velocity is located at a single hair follicle unit. Determine whether the blood flow velocity is higher than 15 mm / s. If so, output that the hair follicle is in the growth phase; if not, no output is made. Determine whether the blood flow velocity is less than 8 mm / s. If so, output that the hair follicle is in the resting phase; if not, output that the hair follicle is in the catagen phase; The blood flow data is converted into a color gradient map, with the growth phase hair follicles recorded in red, the catagen phase hair follicles recorded in yellow, and the resting phase hair follicles recorded in blue. The summary output is a hair follicle activity heat map.

4. The method for dynamic parameter adjustment of laser hair removal based on skin type recognition according to claim 3, characterized in that: Based on the principle of coherent light interference, a three-dimensional energy focus is formed by crossing two beams. A beam of horizontally polarized light is emitted to scan the skin surface to generate the coordinates of the hair follicle entrance. Then, a vertically polarized light is emitted to penetrate the hair follicle root to obtain depth data. Specifically, the following steps are performed: The light beam is adjusted to horizontal polarization through a polarizer and then split into two beams by a beam splitter. One beam directly illuminates the skin surface, and the other beam serves as a reference light for interference signal reception. The polarization direction of the light beam is rotated 90° by a half-wave plate to adjust it to vertical polarization. After passing through a beam splitter, it is transmitted coaxially with the horizontal light beam. The two beams intersect in the scanning area to form a three-dimensional energy focus. A two-dimensional galvanometer scanning module is configured to control the horizontal polarized light to scan the skin surface point by point, while the vertical polarized light synchronously follows the horizontal beam path and is emitted with a delayed delay. When horizontally polarized light illuminates the skin surface, the reflected light and the reference light form interference fringes on the detector. By analyzing the fringe displacement of the interference fringes, the height difference of the skin surface is calculated as twice the fringe displacement; In the surface topography, the hair follicle entrance appears as a concave structure. The center coordinates of the concave area are extracted through edge detection and marked as the hair follicle entrance position. Vertically polarized light is emitted at the entrance coordinate of the hair follicle and crosses with the horizontally polarized light under the skin, forming a local high energy density area. The energy focus excites the hair follicle root tissue to produce backscattered light; The backscattered light and the reference light form an interference signal on the detector, and its phase change is proportional to the depth of the hair follicle; The optical path difference formula is used to calculate the hair follicle depth based on the phase difference, vertical light wavelength and skin refractive index.

5. The method for dynamic parameter adjustment of laser hair removal based on skin type recognition according to claim 4, characterized in that: The method of obtaining skin surface data through a pressure sensor, driving the arrangement of liquid crystal molecules in the light valve, and adjusting the light spot to a shape that fits the hair removal area specifically includes: Evenly attach the flexible pressure sensor array to the surface of the hair removal head, covering all areas that contact the skin. When the device is not in contact with the skin, record the initial pressure value of each sensor as a benchmark; Slowly press the hair removal head onto the skin surface, and the sensor array collects the pressure values ​​of each area in real time to form a pressure distribution map; Based on the pressure distribution map and the skin's elasticity, the height of the depressions or protrusions on the skin surface is calculated to construct a three-dimensional surface model. The surface model is smoothed to eliminate sensor noise and local outliers, and based on the skin surface model, the shape of the light spot that fits it is determined to be an ellipse or an irregular polygon; Convert the target spot shape into the arrangement instructions of liquid crystal molecules. The liquid crystal molecules are arranged vertically by default, and they are rotated to horizontal arrangement by voltage control; Based on the brightness and darkness requirements of the light spot shape, different voltage values ​​are assigned to each area, with higher voltage in bright areas and lower voltage in dark areas. Send voltage signals to the liquid crystal layer of the light valve to control the liquid crystal molecules to align according to instructions; The optical sensor captures the light spot of the hair removal area, extracts the actual contour and compares it with the target shape, and calculates the degree of overlap between the two. Determine whether there is a deviation between the actual light spot and the target shape. If so, adjust the voltage value of the corresponding area. When expanding the light spot, increase the voltage in the edge area. When shrinking the light spot, reduce the voltage in the edge area. Repeat the adjustment until the light spot completely fits the skin surface. If not, no output is made.

6. The method for dynamic parameter adjustment of laser hair removal based on skin type recognition according to claim 5, characterized in that: The introduction of the metabolic rate detection module, measuring the patient's basal metabolic rate through non-invasive bioelectrical impedance analysis technology, and adjusting the energy density based on the basal metabolic rate specifically include: Four sets of flexible conductive patches are installed on both sides of the hair removal head of the device, and the contact surface between the electrode and the skin is made of flexible conductive material; The device automatically emits weak currents of various frequencies to measure the whole body electrical impedance. The measurement is repeated three times and the average value is taken as the final data. The device estimates the target's body fat percentage based on the difference in impedance between intracellular and extracellular fluids, estimates the target's muscle mass based on the correlation between total body water content and impedance, and calculates their basal metabolic rate through a correction model; Determine whether basal energy consumption is lower than 80% of normal. If so, reduce energy intensity to avoid overstimulation. If not, do not output. Determine whether the basic energy expenditure is higher than 120% of the normal value. If so, increase the energy intensity; if not, use the standard energy intensity; When the energy intensity is reduced, the single pulse action time is extended to keep the total energy stable. When the energy intensity is increased, the electrode output power is enhanced and the hair removal interval is shortened.

7. The method for dynamic parameter adjustment of laser hair removal based on skin type recognition according to claim 6, characterized in that: The digital twin model is established to integrate hair removal data, skin condition, and hormone level information, and to predict hair follicle regeneration trends through machine learning, so as to adjust and maintain hair removal parameters in advance. Specifically, the following are involved: The energy density, pulse width, hair removal frequency, epidermal temperature and impedance value of each hair removal are recorded by medical equipment; Regularly collect indicators of target hair follicle density, hair diameter, epidermal thickness, and inflammatory response; Obtain dynamic changes in androgen, estrogen, and metabolism-related hormones through blood tests; Newly collected hair removal data, skin conditions, and hormone levels are input into the digital twin model, which then outputs predicted values ​​for future hair follicle regeneration speed, new hair quality, and hair removal response cycle, identifying potential risks and generating early warning signals. Based on the hair follicle growth cycle model, the frequency of hair removal is increased during the predicted growth phase of the hair follicle and reduced during the resting phase of the hair follicle.

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