Light source control system of horizontal health cabin and control method applied by light source control system

Abstract

The invention discloses a light source control system of a horizontal health cabin and a control method applied by the light source control system, and relates to the technical field of light source control, and the system comprises a human body posture capturing module which is provided with a high-precision camera installed in the health cabin, collects a portrait image through the camera, and recognizes the human body morphological characteristics of the portrait image; the intelligent light source adjusting module comprises an LED lamp matrix capable of independently adjusting light source brightness and wavelength and is used for dynamically adjusting light source distribution and wave bands according to the control instruction; the control center receives the human body morphological characteristics, calculates an optimal light source configuration scheme and sends a control instruction to the intelligent light source adjusting module; wherein the control instruction is generated based on the human body skin color and the body contour in the human body morphological characteristics, so that the LED lamp matrix forms light coverage on the whole body of the user, and illumination of an optimized wave band is adopted for a specified part; the horizontal type health cabin has the effects of improving the light source control effect of the horizontal type health cabin and improving the user satisfaction degree.

Description

Technical Field

[0001] This application relates to the technical field of light source control, and in particular to a light source control system for a horizontal health cabin and a control method applied thereto. Background Art

[0002] Currently, phototherapy devices have been widely used in the fields of beauty and medicine, especially in skin whitening and tanning treatments. However, the light source control method of traditional health cabins is relatively single and cannot be accurately adjusted according to the human body shape, resulting in uneven lighting effects.

[0003] Most existing horizontal health cabins on the market use a fixed-mode light source irradiation, such as a single-band LED lamp array. This setting ignores individual differences and affects the treatment effect. Therefore, there are defects in the light source control effect of horizontal health cabins, resulting in poor treatment effects or whitening and tanning effects, and low user satisfaction. There is an urgent need for improvement. Summary of the Invention

[0004] In order to improve the light source control effect of the horizontal health cabin and enhance user satisfaction, this application provides a light source control system for a horizontal health cabin and a control method applied thereto.

[0005] In a first aspect, the inventive object of this application is achieved by the following technical solutions: A light source control system for a horizontal health cabin, comprising: A human body posture capture module, configured with a high-precision camera installed in the health cabin, which collects portrait images through the camera and identifies the human body shape characteristics of the portrait images; An intelligent light source adjustment module, including an LED lamp matrix that can independently adjust the light source brightness and wavelength, and is used to dynamically adjust the light source distribution and wavelength band according to a control instruction; A control center, which receives the human body shape characteristics and calculates the optimal light source configuration plan, and sends a control instruction to the intelligent light source adjustment module; Among them, the control instruction is generated based on the human skin color and body contour in the human body shape characteristics, so that the LED lamp matrix forms light coverage for the user's whole body and uses optimized wavelength band lighting for specified parts.

[0006] By adopting the above technical solution, the human body morphological features include human skin color, body contour, etc.; in actual operation, when the user lies in the horizontal health cabin, the system is automatically started, and the camera captures the user's body information. After being processed by the deep neural network, the details of the human body morphology such as the depth of the user's skin color and body curves are identified. Based on the detailed data of the human body morphological features, the control center adjusts the brightness and wavelength of each lamp in the LED lamp matrix to ensure that the light source evenly covers the whole body of the user, and uses an optimized wavelength band for the specified parts (such as the face, arms) to achieve the best whitening or tanning effect. Thus, this application improves the light source control effect of the horizontal health cabin and enhances user satisfaction.

[0007] In a preferred example of this application: The control center further includes: Obtain the timing parameter set of multiple groups of phototherapy parameters in the health cabin, where the phototherapy parameters include pulsed light intensity value, multi-spectral combination mode, and pulsed frequency gradient; Create dynamic phototherapy time blocks according to the beauty effect time windows of each phototherapy parameter in the timing parameter set; Based on the dynamic phototherapy time blocks, intelligently arrange multiple groups of phototherapy parameters to generate a multi-channel beauty light waveform set; Optimize the multi-channel beauty light waveform set based on the human body morphological features to obtain the best light source configuration plan.

[0008] By adopting the above technical solution, the dynamic matching of the beauty light waveform and the user's biological clock is realized, which is beneficial to eliminating the energy waste caused by the static phototherapy parameters in the traditional way, and solving the problems of local overexposure or underexposure caused by the uniform irradiation of the LED matrix.

[0009] In the second aspect, the invention object of this application is realized by adopting the following technical solution: A light source control method for a light source control system applied to a horizontal health cabin, including: Collect the portrait image of the user through a high-precision camera installed inside the health cabin; Based on the portrait image, identify and extract the human body morphological features of the user, where the human body morphological features include human skin color and body contour; transmit the extracted human body morphological features to the control center, and the control center calculates the best light source configuration plan adapted to the user; generate corresponding control instructions according to the best light source configuration plan and send them to the intelligent light source adjustment module; The intelligent light source adjustment module responds to the control instructions and dynamically adjusts the brightness and wavelength of each light source unit in the LED lamp matrix to achieve light coverage of the whole body of the user, and performs enhanced processing on the illumination of the specified parts of the user with an optimized wavelength band; Among them, the LED lamp matrix can be independently controlled in zones.

[0010] By adopting the above technical solution, establishing a dynamic mapping relationship between human body morphological features and light intensity adjustment is beneficial to reducing the uneven energy distribution caused by uniform illumination and realizing the intelligent switching between full-cabin light coverage and local enhanced illumination.

[0011] In a preferred example of the present application: after generating the multi-channel beauty light waveform set, it further includes: Obtaining the ambient light parameters and user physiological characteristic data in the health cabin; Evaluating the lighting comfort according to the ambient light parameters and user physiological characteristic data to obtain the analysis result of the light environment quality; according to the analysis result of the light environment quality, segmenting the lighting time period in the health cabin, and performing directional parameter optimization analysis on the local time period with unqualified light environment to obtain the corresponding time period adjustment parameters; Adjusting the light intensity adjustment intensity of the local time period according to the time period adjustment parameters, generating and sending the light control instruction of the local time period to the intelligent light source adjustment module according to the adjusted adjustment parameters, so that the intelligent light source adjustment module adjusts the light intensity adjustment process of the local time period according to the light control instruction.

[0012] By adopting the above technical solution, the entire light therapy cycle is divided into several time periods, and the local time periods with unqualified light environment are identified; the directional parameter analysis can be performed on the identified abnormal time periods to determine the key factors affecting comfort; the corresponding time period adjustment parameters can also be generated based on the analysis result to adjust the light intensity adjustment intensity; the light control instruction of the local time period can be generated according to the adjustment parameters and sent to the light source module to realize the precise intervention of the light intensity adjustment process of the local time period.

[0013] In a preferred example of the present application: evaluating the lighting comfort according to the ambient light parameters and user physiological characteristic data to obtain the analysis result of the light environment quality, specifically including: Calculating the correlation with the melatonin secretion level in the user physiological characteristic data according to the color temperature value and illuminance value in the ambient light parameters; quantifying the circadian rhythm matching degree of each time node according to the correlation; Analyzing the phase deviation value between the current light environment and the human body biological clock according to the circadian rhythm matching degree; Estimating the comfort deviation index of the overall light environment according to the phase deviation value, and evaluating the light environment quality according to the deviation index to obtain the analysis result of the light environment quality.

[0014] By adopting the above technical solution, combining with the user's physiological rhythm data, the matching degree between the light environment and the user's biological clock at different time nodes is quantified; based on the matching degree data, the phase shift situation between the current light environment and the user's ideal biological clock is analyzed; by synthesizing various indicators, the overall comfort deviation index of the current light environment is estimated; according to the deviation index, the analysis result of the light environment quality is output, which serves as the data support for subsequent adjustment decisions. The present application can scientifically evaluate the lighting comfort of users under non-invasive conditions.

[0015] In a preferred example of the present application: The method further includes: Obtain the brightness gradient difference between adjacent light intensity adjustment periods, and obtain the light intensity adjustment amplitude difference and spectral shift amount corresponding to the light intensity attenuation parameter according to the brightness gradient difference; Construct a light intensity adjustment curve corresponding to the brightness gradient difference according to the light intensity adjustment amplitude difference and spectral shift amount; Analyze the comfort attenuation trend of the light environment according to the light intensity adjustment curve to obtain the fatigue attenuation value of the current light intensity adjustment; when the actual light intensity in the monitoring cabin reaches the fatigue attenuation value, output dynamic compensation parameters to the intelligent light source adjustment module.

[0016] By adopting the above technical solution, introducing the brightness gradient difference analysis mechanism of the light intensity adjustment period, and constructing a light intensity adjustment curve by combining the light intensity attenuation parameter and the spectral shift amount, the change trend of the comfort of the light environment in the cabin can be dynamically identified, and the problems of possible visual fatigue or decreased light adaptation of users can be predicted in advance; further, when it is detected that the actual light intensity reaches the fatigue attenuation value, dynamic compensation parameters are automatically output to the intelligent light source adjustment module, so as to realize the adaptive adjustment of the light source output.

[0017] In a preferred example of the present application: According to the analysis result of the light environment quality, the lighting period in the health cabin is segmented, and the directional parameter optimization analysis is carried out on the local period where the light environment does not meet the standard, and the corresponding sub-period adjustment parameters are obtained, including: Obtain the light intensity adjustment quality difference between adjacent time periods according to the analysis result of the light environment quality; According to the quality difference, divide the lighting period in the cabin into time windows to generate continuous light intensity adjustment periods with the same quality level; mark the low-quality periods where the light environment comfort is lower than the preset threshold, and perform light intensity fluctuation analysis on the marked periods to obtain the light intensity adjustment entropy value and spectral dispersion degree of the low-quality periods; Calculate the dynamic adjustment intensity coefficient and frequency band compensation parameter of the low-quality period according to the light intensity adjustment entropy value and spectral dispersion degree, and obtain the sub-period adjustment parameter of the low-quality period.

[0018] By adopting the above technical solution, the quality difference of light intensity adjustment in adjacent time periods is analyzed, and the time window of the in-cabin lighting period is divided according to the quality level, realizing the refined management of the time dimension of the phototherapy process; at the same time, abnormal marking is carried out for the low-quality time periods where the light environment comfort level is lower than the preset threshold, and further analysis is made on its light intensity adjustment entropy value and spectral dispersion degree, so as to accurately identify the key factors affecting the lighting quality.

[0019] In a preferred example of the present application: the light intensity adjustment intensity of the local time period is adjusted according to the time-period adjustment parameter, and a light control instruction for the local time period is generated and sent to the intelligent light source adjustment module according to the adjusted adjustment parameter, specifically including: According to the time-period adjustment parameter, obtain the light intensity adjustment intensity and spectral distribution parameter of the current light intensity adjustment frequency band, and analyze the light intensity adjustment efficiency of the current light environment; Calculate the dynamic deviation value between the time-period adjustment parameter and the real-time light intensity adjustment efficiency, and adjust the light intensity adjustment intensity of the local time period according to the deviation value; Obtain the real-time physiological characteristic data of the user in the health cabin, and conduct hierarchical analysis on the adjustment effects of each adjustment frequency band on the physiological characteristic response curve to obtain the spectral compensation sequence; According to the light intensity adjustment intensity and the spectral compensation sequence, reconstruct the parameters of the original light intensity adjustment process of the local time period, and generate a light control instruction including a dynamic compensation coefficient.

[0020] By adopting the above technical solution, the intensity and spectral distribution parameters of the current light intensity adjustment frequency band are obtained according to the time-period adjustment parameter, and deviation analysis is carried out in combination with the real-time light intensity adjustment efficiency, ensuring that the adjustment instruction of the local time period has high real-time responsiveness and adaptability. The system further introduces the real-time physiological characteristic data of the user, conducts hierarchical analysis on the performance of each adjustment frequency band on the physiological response curve, and generates a spectral compensation sequence, so that the light source adjustment not only meets the physical parameter requirements, but also better fits the current physiological state of the user.

[0021] In the third aspect, the invention object of the present application is realized by adopting the following technical solution: A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above light source control method of a light source control system applied to a horizontal health cabin are realized.

[0022] In summary, the present application includes at least one of the following beneficial technical effects: 1. An intelligent light source control system with personalized recognition and adaptive adjustment capabilities is constructed to achieve precise perception of user individual differences. The control center generates corresponding control instructions based on the extracted human body shape characteristics, driving a light source matrix composed of LED lamp units that can independently adjust brightness and wavelength, dynamically adjusting the light source distribution and spectral band to ensure uniform and continuous light coverage of the user's whole body. At the same time, the system supports directional irradiation of optimized bands on specified parts (such as the face, shoulders, neck, joints, etc.) to improve the pertinence and effectiveness of light therapy. 2. By reconstructing parameters to generate light control instructions containing dynamic compensation coefficients, the leap from static control to dynamic feedback light source control is achieved, improving the accuracy and personalization level of light source adjustment. Brief Description of the Drawings

[0023] Figure 1 is a framework diagram of a light source control system for a horizontal health cabin in an embodiment of the present application; Figure 2 is a flowchart of a light source control method for a light source control system applied to a horizontal health cabin in an embodiment of the present application; Figure 3 is another flowchart in a light source control method for a light source control system applied to a horizontal health cabin in an embodiment of the present application. Detailed Description of the Embodiment

[0024] The following further elaborates on the present application in conjunction with the accompanying drawings.

[0025] In one embodiment, as Figure 1 shown, the present application discloses a light source control system for a horizontal health cabin. The light source control system of the horizontal health cabin includes a human body posture capture module, an intelligent light source adjustment module, and a control center. The human body posture capture module is configured with high-precision cameras installed in the health cabin. Four wide-angle cameras are installed on the top of the health cabin to cover the whole body area of the user. The installation height is 2.2 meters from the bottom of the cabin, and the depression angle is 15°. Infrared fill lights are configured to ensure clear human portraits can still be captured in low-light environments. The human body shape characteristics are recognized by collecting human portrait images through the cameras. The human body shape characteristics include skin color (RGB value range), body contour (joint point positions), and posture (lying angle).

[0026] The intelligent light source adjustment module includes an LED lamp matrix that can independently adjust the light source brightness and wavelength, and is used to dynamically adjust the light source distribution and band according to control instructions. The correspondence between skin color RGB values and the optimal color temperature is established (for example, cold white light is suitable for light skin color, and warm yellow light is suitable for dark skin color). The genetic algorithm is used to solve the light intensity distribution that covers the whole body and strengthens the key areas. The calculation formula of the objective function is: where Coveragei refers to the illumination uniformity score (0 - 1) of the i-th area; Comfort i is the subjective score (0 - 10 points) of the user's lighting comfort in the i-th area; Energy is the total energy consumption of the light source control system; λ is the energy consumption penalty coefficient (0 < λ ≤ 1).

[0027] The control center receives the human body morphological characteristics and calculates the optimal light source configuration plan, and sends control instructions to the intelligent light source adjustment module; Instruction generation includes converting the optimized light field parameters into LED control signals: Color temperature adjustment is achieved through the RGBW mixing ratio (e.g., warm light = 10% red + 20% green + 70% blue). Band selection refers to enabling a specific LED channel (e.g., activating the 630nm channel).

[0028] The optimal light source configuration plan is based on a dynamic light field model of human skin color and posture, including color temperature (2700K - 6500K), illumination gradient, and band combination; The control instruction is a binary control signal sent to the LED driver through the MQTT protocol. Among them, the control instruction is generated based on the human skin color and body contour in the human body morphological characteristics, enabling the LED lamp matrix to form light coverage of the user's whole body, and using optimized band illumination for the specified part, and the specified part is a specific part of the human body; For example, red light (630nm) is emitted for the joint part (such as the knee) to promote blood circulation, and blue light (470nm) is emitted for the shoulder and neck part to relieve muscle tension.

[0029] The control center also includes: Obtain the time series parameter set of multiple groups of phototherapy parameters in the health cabin, and the phototherapy parameters include pulsed light intensity value, multi-spectral combination mode, and pulsed frequency gradient; Among them, the pulsed light intensity value (unit: mW / cm 2 ) refers to the light energy density per unit area. For example: The freckle removal mode requires 300 mW / cm 2 , and the moisturizing mode requires 150 mW / cm 2 . The multi-spectral combination mode refers to the combination ratio of lights with different wavelengths (such as red light 630nm: blue light 470nm = 7:3); The pulsed frequency gradient refers to the gradient curve of the pulse width modulation (PWM) frequency. The time series parameter set refers to the sequence of phototherapy parameters recorded along the time axis.

[0030] Create dynamic phototherapy time blocks according to the beauty effect time windows of each phototherapy parameter in the time series parameter set; The beauty effect time window refers to the optimal action duration of different phototherapy parameters on the skin (such as red light needs to last for 30 minutes, and blue light needs 15 minutes). The dynamic phototherapy time block first defines a time window parameter mapping table, including phototherapy modes (such as freckle removal, moisturizing), action time windows, and optimal frequency gradients (Hz). The greedy algorithm is used for partitioning: Prioritize allocating the parameters of the longest action time window, and fill the remaining time with short time window parameters.

[0031] Based on the dynamic phototherapy time blocks, multiple groups of phototherapy parameters are intelligently arranged to generate a multi-channel beauty light waveform set; the multi-channel beauty light waveform set includes the intensity-time curve combinations of different spectral channels (such as red, blue, and infrared), and a light waveform sequence that meets the time block constraints is generated through a genetic optimization algorithm; the arrangement is carried out based on the preset arrangement rule constraint conditions, where the preset arrangement constraint conditions include that red light and blue light cannot be turned on simultaneously (to avoid photochemical reactions) and the pulse frequency gradient needs to have a smooth transition (slope ≤ 5Hz / s), and the arrangement objective function is to maximize the phototherapy effect score (such as the collagen generation rate); the dynamic time blocks divide the total treatment cycle into several sub-periods according to time windows, and each sub-period corresponds to a specific parameter combination.

[0032] Optimize the multi-channel beauty light waveform set based on the human body morphological characteristics to obtain the best light source configuration plan; specifically, first adjust the importance of phototherapy parameters according to characteristics such as skin color and contour in the human body morphological characteristics. For example: for users with dark skin, reduce the proportion of blue light, where the skin color weight calculates the skin chroma value through the HSV color space in the portrait image (H ∈ [0, 30] in the HSV color space is dark skin, and the weight coefficient is 0.7); the contour weight refers to calculating the body posture according to the joint point distance (such as increasing the infrared light intensity for users with hunchback to relieve muscle tension); then set the rules for dynamic parameter adjustment: for example, if it is detected that the spinal angle of the user deviates from the normal physiological curvature by more than a preset threshold (such as greater than 5°), it is determined that there is a tendency of hunchback, and accordingly, the infrared light output intensity is increased by no less than 30% of the current infrared light intensity to enhance the thermotherapy effect on the muscle tissues of the shoulder, neck, and back.

[0033] In one embodiment, as Figure 2 shown, a light source control method for a light source control system of a horizontal health cabin is provided. This light source control method for a light source control system of a horizontal health cabin is applied to the above-mentioned light source control system of a horizontal health cabin, and specifically includes the following steps: S1: Collect the portrait image of the user through a high-precision camera installed inside the health cabin.

[0034] In this embodiment, the portrait image includes the color / infrared image of the user's whole body or key torso area. When the image is collected, the exposure time is automatically adjusted through the ISP algorithm; the portrait image is subjected to multi-spectral fusion: the RGB channel captures the visible light image (for skin color analysis); the IR channel captures the thermal image (for contour extraction).

[0035] S2: Identify and extract the human body morphological characteristics of the user based on the portrait image. The human body morphological characteristics include the human skin color and body contour.

[0036] In this embodiment, a lightweight human key point detection model (such as HRNet-w32) is deployed, with an input size of 512×512, and the coordinates of 17 joint points are output; adjacent joint points (such as shoulders, hips, knees) are connected to generate a polygon mask, and morphological dilation (radius 3px) is used to fill the occluded area to obtain the human body pose contour information. The extraction of skin color features is obtained by calculating the average HSV value and color difference of the skin area; the extraction of contour features includes joint point spacing (such as shoulder width, leg length) and spinal curvature (by fitting the curvature of the spinal curve).

[0037] S3: Transmit the extracted human body morphological features to the control center, and the control center calculates the optimal light source configuration scheme suitable for the user.

[0038] In this embodiment, the corresponding relationship between predefined skin color parameters (H / S / V) and phototherapy parameters (color temperature, intensity) is defined, and an illumination distribution optimization function (such as coverage uniformity score) based on the user's contour is predefined to calculate the optimal light source configuration scheme suitable for the current user.

[0039] S4: Generate corresponding control instructions according to the optimal light source configuration scheme and send them to the intelligent light source adjustment module.

[0040] Specifically, convert the phototherapy parameters into hardware control instructions for the LED beads of the LED lamp matrix.

[0041] S5: The intelligent light source adjustment module responds to the control instructions, dynamically adjusts the brightness and wavelength of each light source unit in the LED lamp matrix to achieve light coverage of the user's whole body, and enhances the illumination of the user's specified part with an optimized wavelength band; among them, the LED lamp matrix can be independently controlled in zones.

[0042] In this embodiment, the LED lamp matrix can be controlled in zones. For example, the matrix is divided into 8 independent regions (such as the head, shoulders and neck, torso, limbs); the PCA9685 PWM controller is used to connect the LED lamp matrix, and the brightness of 16 channels is adjusted through the I 2 C interface, with a resolution of 12 bits (0.08% accuracy), and the lamp beads of the LED lamp matrix are RGBW four-color LED mixed light, and the currents of the R / G / B / W channels can be independently controlled through a discrete drive circuit (20mA~200mA).

[0043] In one embodiment, as Figure 3 shown, after generating the multi-channel beauty light waveform set, a light source control method for a light source control system of a horizontal health cabin further includes: S10: Obtain the ambient light parameters and user physiological characteristic data in the health cabin.

[0044] In this embodiment, the ambient light parameters include color temperature value (K), illuminance value (lux), and spectral distribution; the color temperature value is the temperature characterization of the light source color (such as warm yellow light 2700K, cold white light 6500K); the illuminance value (lux) is the luminous flux per unit area (such as the target illuminance in the health cabin is 300 lux); the spectral distribution is the energy ratio of light of each wavelength (such as the ratio of red light at 630nm is 30%). The user's physiological characteristic data includes melatonin secretion level and heart rate variability. Wear a flexible wristband-type biosensor (such as Empatica E4) to synchronously monitor heart rate variability (HRV), skin conductance (EDA), and core body temperature.

[0045] Specifically, the melatonin secretion level is detected by a wristband sensor for the melatonin concentration in the blood (pg / mL); the heart rate variability (HRV) is an index reflecting the activity of the autonomic nervous system (ms).

[0046] S20: Evaluate the lighting comfort according to the ambient light parameters and the user's physiological characteristic data to obtain the analysis result of the light environment quality.

[0047] In this embodiment, step S20 includes: S201: Calculate the correlation with the melatonin secretion level in the user's physiological characteristic data according to the color temperature value and the illuminance value in the ambient light parameters.

[0048] In this embodiment, a spectral sensor is used to collect the color temperature value (Tc) and the illuminance value (E) in real time; the melatonin data is obtained by detecting the melatonin concentration (M) through venous blood samples or wearable devices (such as AliveCor KardiaBand).

[0049] Specifically, a linear regression model for analyzing the correlation is supervised: M = α×Tc + β×E + γ, where α, β, and γ are regression weight coefficients obtained through training with historical data.

[0050] S202: Quantify the circadian rhythm matching degree at each time node according to the correlation.

[0051] In this embodiment, the circadian rhythm matching degree is the synchronization degree of the light cycle with the human biological clock (24-hour rhythm) (represented by 0 to 1, 1 being completely synchronized); the time node is a discrete time point in minutes.

[0052] Specifically, a heart rate variability (HRV) signal is obtained through a wristband sensor, and the ratio of low-frequency (LF, 0.04–0.15 Hz) to high-frequency (HF, 0.15–0.4 Hz) power (LF / HF) is calculated; the circadian rhythm component of the HRV signal is extracted using Fourier transform, and the peak time is calculated. The matching degree calculation formula is: matching degree = 1 - (absolute value of the difference between the peak time of the light cycle and the peak time of the biological clock) / 12.

[0053] S203: Analyze the phase deviation value between the current light environment and the human biological clock according to the circadian rhythm matching degree.

[0054] In this embodiment, the phase deviation value is the absolute value of the phase difference between the light cycle and the biological clock (unit: hour); the light environment phase refers to the peak time of the light cycle measured by a spectral sensor (such as 10:00 am). If the peak time of the light cycle is greater than the peak time of the biological clock, it is determined to be phase-advanced, and vice versa.

[0055] S204: Estimate the comfort deviation index of the overall light environment according to the phase deviation value, and evaluate the light environment quality according to the deviation index to obtain the light environment quality analysis result.

[0056] In this embodiment, the comfort deviation index (CDI) quantifies the gap between the current light environment and the ideal comfort state (0–1, 0 being the best). The weight coefficients refer to α (color temperature weight), β (illuminance weight), γ1 (phase deviation weight), which are calibrated through machine learning.

[0057] Specifically, the calculation formula for the comfort deviation index is:

[0058] S30: According to the light environment quality analysis result, segment the lighting period in the health cabin, and perform directional parameter optimization analysis on the local periods where the light environment does not meet the standard to obtain the corresponding segmented adjustment parameters.

[0059] In this embodiment, the health cabin lighting period is divided into continuous short periods to obtain continuous time windows; the K-means algorithm is used to cluster the CDI sequence, and the windows with the same continuous quality level are merged. The determination of the quality level is to divide the period into excellent (CDI ≤ 0.2), good (0.2 < CDI ≤ 0.5), and poor (CDI > 0.5) according to the CDI value.

[0060] Specifically, step S30 includes: S301: According to the light environment quality analysis result, obtain the difference in light intensity adjustment quality between adjacent time periods.

[0061] Specifically, the poor quality of light intensity adjustment refers to the change amplitude of the light environment quality (such as the CDI value) within adjacent lighting periods (which can be determined by the CDI difference between adjacent time windows), reflecting the stability of the lighting strategy.

[0062] S302: Divide the lighting periods in the cabin into time windows according to the quality difference, and generate continuous light intensity adjustment periods with the same quality level.

[0063] In this embodiment, all time windows are traversed, and the quality levels of each lighting period are marked according to the CDI threshold. For example, for window 3, CDI = 0.6 → poor); S303: Mark the low-quality periods where the light environment comfort level is lower than the preset threshold, and perform light intensity fluctuation analysis on the marked periods to obtain the light intensity adjustment entropy value and spectral dispersion of the low-quality periods.

[0064] S304: Calculate the dynamic adjustment intensity coefficient and frequency band compensation parameter of the low-quality period according to the light intensity adjustment entropy value and spectral dispersion, and obtain the sub-period adjustment parameters of the low-quality period.

[0065] Specifically, the low-quality period refers to the period when CDI > preset threshold (such as 0.5), which needs to be optimized keyly; the light intensity adjustment entropy value is an index for measuring the disorder degree of light intensity fluctuation (calculated using the Shannon entropy formula); the spectral dispersion refers to the uniformity of the spectral distribution (standard deviation). The dynamic adjustment intensity coefficient is a real-time adjustment factor for correcting light intensity attenuation (% / min); the frequency band compensation parameter is the adjustment weight for a specific spectral band (such as the blue light proportion ±10%).

[0066] Specifically, the calculation formula for the light intensity adjustment entropy value H is: where, p i is the value of the light intensity probability density function (obtained through histogram statistics). If the light intensity is always constant (single-peak histogram), H is approximately equal to 0, indicating no fluctuation. If the light intensity varies randomly within a wide range (multi-peak histogram), H approaches the maximum value; n is the total number of intervals in the light intensity range, and i1 is the interval index.

[0067] The calculation formula for the spectral dispersion D is: where, λ i2 is the intensity value of light of each wavelength (for example, the light intensity of wavelengths such as 400nm, 450nm, 500nm, etc.); is the average wavelength; the larger the D value, the more dispersed the spectral distribution; i2 is the wavelength point index, and N is the total number of wavelength points in the spectrum.

[0068] The compensation adjustment coefficient K intensity of the dynamic intensity coefficient is calculated as: where, CDI targrt is the deviation index of the ideal comfort level; CDIcurrent is the current comfort deviation index; Δt is the adjustment time window; η is the device efficiency.

[0069] The calculation formula for the frequency band compensation parameter Δf is: where ω1 and ω2 are weight coefficients; HRV LF / HF is the heart rate variability ratio.

[0070] Specifically, in a medical scenario, calculating the CDI can help patients improve their mood: Test scenario: The following are the night light therapy parameters for User C (a patient with depression who needs stable lighting to improve mood): Current ambient light parameters of the health cabin: color temperature 4000K, illuminance 300 lux, phase 22:00; Physiological data: HRV LF / HF = 2.8, biological clock peak time 23:00; Segmentation result of the segmented adjustment parameters: The time period from 22:00 to 23:30 is marked as the "low-quality time period", CDI = 0.6; Optimization parameters: The color temperature is reduced to 3000K, the blue light proportion is reduced to 5%, and the red light is increased to 70%.

[0071] Optimization effect: The CDI is reduced to 0.3, and the user's sleep onset time is shortened by 40 minutes.

[0072] S40: Adjust the light intensity adjustment strength of the local time period according to the segmented adjustment parameters, generate and send a light control command for the local time period to the intelligent light source adjustment module according to the adjusted adjustment parameters, so that the intelligent light source adjustment module adjusts the light intensity adjustment process of the local time period according to the light control command.

[0073] In this embodiment, step S40 includes: S401: According to the segmented adjustment parameters, obtain the light intensity adjustment strength and spectral distribution parameters of the current light intensity adjustment frequency band, and analyze the light intensity adjustment efficiency of the current light environment.

[0074] In this embodiment, the light intensity adjustment frequency band refers to the wavelength interval that can be independently adjusted in the light source matrix (such as red light at 630 nm and blue light at 470 nm); the light intensity adjustment strength refers to the brightness adjustment percentage of the light sources in each frequency band; the spectral distribution parameter refers to the distribution ratio of the light intensities of each wavelength (such as 60% red light proportion, 30% blue light proportion, and 10% other wavelengths).

[0075] Specifically, the calculation formula for the light intensity adjustment efficiency is: where i′ is the frequency band index; N′ is the total number of frequency bands; δ i′ is the frequency band weight (such as the red light weight of 0.6); is the target light intensity; is the actual light intensity.

[0076] S402: Calculate the dynamic deviation value between the segmented adjustment parameter and the real-time light intensity adjustment efficiency, and adjust the light intensity adjustment strength of the local time period according to the deviation value.

[0077] In this embodiment, the dynamic deviation value refers to the difference between the segmented adjustment parameter and the real-time light intensity adjustment efficiency (such as the difference between the segmented target CDI and the actual time period CDI); a PID controller is used to calculate the correction amount of the adjustment strength.

[0078] Specifically, the calculation formula of the PID controller is: where, ΔI is the correction amount; ΔE is the dynamic deviation value; K p , K i , K d are the proportional, integral and differential coefficients.

[0079] S403: Obtain the real-time physiological characteristic data of the user in the health cabin, perform hierarchical analysis on the adjustment effects of each adjustment frequency band on the physiological characteristic response curve, and obtain the spectral compensation sequence.

[0080] In this embodiment, the physiological response curve refers to the curve of the user's physiological indicators (such as melatonin concentration, HRV) changing with the light parameters, and the user's physiological data (heart rate, skin conductance, core body temperature) is collected in real time through a wearable device (such as Biostrap). The spectral compensation sequence is a compensation scheme for the frequency bands with insufficient physiological response (such as increasing the proportion of blue light to inhibit melatonin).

[0081] Specifically, a machine learning model of random forest is used to predict the influence of light of different frequency bands on physiological indicators. For example, when the input is 80% red light intensity and 30% blue light intensity, the predicted value of melatonin concentration is 2.5 pg / mL.

[0082] A spectral rule library based on spectral compensation is preset in advance: if the melatonin concentration is lower than the threshold (such as 2.0 pg / mL), increase the proportion of blue light (+10%); if HRV LF / HF > 3.0, increase the proportion of red light (+5%), and the generated compensation sequence is {"blue": +15%, "red": +0%}.

[0083] S404: According to the light intensity adjustment strength and the spectral compensation sequence, perform parameter reconstruction on the original light intensity adjustment process of the local time period, and generate a light control instruction including a dynamic compensation coefficient.

[0084] In this embodiment, the dynamic compensation coefficient is an adjustment weight that is adjusted in real time according to the dynamic deviation value and the physiological response (such as the blue light compensation coefficient 1.1); the light control instruction is a control instruction (in JSON format) that includes the intensity, wavelength, and duration of the target frequency band.

[0085] Specifically, the final compensation coefficient is I final = I adjusted ×(1 + ΔI) × C comp wherein, I adjusted is the light intensity value preliminarily adjusted by the segmented adjustment parameters; C comp is the spectral compensation coefficient (different spectral compensation coefficients can be set corresponding to different colors of the spectrum, such as the blue light compensation coefficient 1.1). The light control instruction is sent to the intelligent light source module through the CAN bus or the MQTT protocol, and the priority is higher than the basic mode.

[0086] It should be understood that the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0087] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: S1: Collect the portrait image of the user through a high-precision camera installed inside the health cabin; S2: Identify and extract the human body morphological features of the user based on the portrait image. The human body morphological features include human skin color and body contour; S3: Transmit the extracted human body morphological features to the control center, and the control center calculates the optimal light source configuration plan adapted to the user; S4: Generate a corresponding control instruction according to the optimal light source configuration plan and send it to the intelligent light source adjustment module; S5: The intelligent light source adjustment module responds to the control instruction, dynamically adjusts the brightness and wavelength of each light source unit in the LED lamp matrix to achieve light coverage of the user's whole body, and performs enhanced processing on the user's specified part with optimized band light; wherein, the LED lamp matrix can be independently controlled in zones.

[0088] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0089] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0090] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A light source control system for a horizontal health cabin, characterized in that, Comprising: A human body posture capture module, configured with a high-precision camera installed in the health cabin, collecting portrait images through the camera and identifying the human body morphological features of the portrait images; An intelligent light source adjustment module, including an LED lamp matrix capable of independently adjusting the light source brightness and wavelength, for dynamically adjusting the light source distribution and wavelength band according to control instructions; A control center, receiving the human body morphological features and calculating the optimal light source configuration scheme, and sending control instructions to the intelligent light source adjustment module; Wherein, the control instructions are generated based on the human skin color and body contour in the human body morphological features, enabling the LED lamp matrix to form light coverage for the user's whole body and adopting optimized wavelength band illumination for specified parts.

2. The light source control system of a horizontal health cabin according to claim 1, characterized in that The control center further includes: Obtaining a time series parameter set of multiple groups of phototherapy parameters in the health cabin, where the phototherapy parameters include pulsed light intensity values, multi-spectral combination modes, and pulsed frequency gradients; Creating dynamic phototherapy time blocks according to the beauty effect time windows of each phototherapy parameter in the time series parameter set; Based on the dynamic phototherapy time blocks, intelligently arranging multiple groups of phototherapy parameters to generate a multi-channel beauty light waveform set; Optimizing the multi-channel beauty light waveform set based on the human body morphological features to obtain the optimal light source configuration scheme.

3. A light source control method for a light source control system applied to a horizontal health cabin, characterized in that, Comprising: Collecting the user's portrait images through a high-precision camera installed inside the health cabin; Identifying and extracting the user's human body morphological features based on the portrait images, where the human body morphological features include human skin color and body contour; Transmitting the extracted human body morphological features to the control center, and the control center calculates the optimal light source configuration scheme adapted to the user; Generating corresponding control instructions according to the optimal light source configuration scheme and sending them to the intelligent light source adjustment module; The intelligent light source adjustment module responds to the control instructions, dynamically adjusting the brightness and wavelength of each light source unit in the LED lamp matrix to achieve light coverage for the user's whole body, and performing enhanced processing on the user's specified parts with optimized wavelength band illumination; Wherein, the LED lamp matrix can be independently controlled in zones.

4. The light source control method of a light source control system applied to a horizontal health cabin according to claim 3, characterized in that, After generating the multi-channel beauty light waveform set, it further includes: Obtaining the ambient light parameters and the user's physiological characteristic data in the health cabin; Evaluating the lighting comfort according to the ambient light parameters and the user's physiological characteristic data to obtain the light environment quality analysis result; According to the light environment quality analysis result, performing segmented processing on the lighting time period in the health cabin, and performing directional parameter optimization analysis on the local time periods with unqualified light environment to obtain the corresponding segmented adjustment parameters; Adjusting the light intensity adjustment intensity of the local time periods according to the segmented adjustment parameters, generating and sending the light control instructions for the local time periods to the intelligent light source adjustment module according to the adjusted adjustment parameters, so that the intelligent light source adjustment module adjusts the light intensity adjustment process of the local time periods according to the light control instructions.

5. The light source control method of a light source control system applied to a horizontal health cabin according to claim 4, characterized in that, The evaluating the lighting comfort according to the ambient light parameters and the user's physiological characteristic data to obtain the light environment quality analysis result specifically includes: Calculating the correlation with the melatonin secretion level in the user's physiological characteristic data according to the color temperature value and illuminance value in the ambient light parameters; Quantify the circadian rhythm matching degree of each time node according to the relevance; Analyze the phase deviation value between the current light environment and the human body biological clock according to the circadian rhythm matching degree; Estimate the comfort deviation index of the overall light environment according to the phase deviation value, and evaluate the light environment quality according to the deviation index to obtain the light environment quality analysis result.

6. The light source control method of a light source control system applied to a horizontal health cabin according to claim 4, characterized in that, The method further includes: Obtain the brightness gradient difference between adjacent light intensity adjustment periods, and obtain the light intensity adjustment amplitude difference and spectral offset corresponding to the light intensity attenuation parameter according to the brightness gradient difference; Construct a light intensity adjustment curve corresponding to the brightness gradient difference according to the light intensity adjustment amplitude difference and the spectral offset; Analyze the comfort attenuation trend of the light environment according to the light intensity adjustment curve to obtain the fatigue attenuation value of the current light intensity adjustment; When the actual light intensity in the monitoring cabin reaches the fatigue attenuation value, output dynamic compensation parameters to the intelligent light source adjustment module.

7. The light source control method of a light source control system applied to a horizontal health cabin according to claim 4, characterized in that, The step of segmenting the lighting period in the health cabin according to the light environment quality analysis result and performing directional parameter optimization analysis on the local period with unqualified light environment to obtain the corresponding segmented adjustment parameters includes: Obtain the light intensity adjustment quality difference between adjacent time periods according to the light environment quality analysis result; Divide the lighting period in the cabin into time windows according to the quality difference to generate continuous light intensity adjustment periods with the same quality level; Mark the low-quality periods with the comfort of the light environment lower than the preset threshold as abnormal, and perform light intensity fluctuation analysis on the marked periods to obtain the light intensity adjustment entropy value and spectral dispersion of the low-quality periods; Calculate the dynamic adjustment intensity coefficient and frequency band compensation parameter of the low-quality period according to the light intensity adjustment entropy value and the spectral dispersion to obtain the segmented adjustment parameter of the low-quality period.

8. The light source control method of a light source control system applied to a horizontal health cabin according to claim 7, characterized in that, The step of adjusting the light intensity adjustment intensity of the local period according to the segmented adjustment parameter, generating and sending a light control instruction for the local period to the intelligent light source adjustment module specifically includes: Obtain the light intensity adjustment intensity and spectral distribution parameter of the current light intensity adjustment frequency band according to the segmented adjustment parameter, and analyze the light intensity adjustment efficiency of the current light environment; Calculate the dynamic deviation value between the segmented adjustment parameter and the real-time light intensity adjustment efficiency, and adjust the light intensity adjustment intensity of the local period according to the deviation value; Obtain the real-time physiological characteristic data of the user in the health cabin, and perform hierarchical analysis on the adjustment effects of each adjustment frequency band on the physiological characteristic response curve to obtain a spectral compensation sequence; Reconstruct the parameters of the original light intensity adjustment process of the local period according to the light intensity adjustment intensity and the spectral compensation sequence to generate a light control instruction including a dynamic compensation coefficient.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the light source control method of a light source control system applied to a horizontal health cabin according to any one of claims 3 to 8.

Images