Method and system for controlling output energy of intense pulsed light therapeutic apparatus

Abstract

The invention discloses an output energy control method and system for an intense pulsed light therapeutic apparatus, and particularly relates to the technical field of medical beauty equipment, and the method comprises the steps: building a tissue optical characteristic baseline through multi-wavelength detection light, and carrying out the personalized setting of initial parameters; dynamic changes of tissue optical characteristics are monitored in real time in treatment, and thermal relaxation time is adaptively adjusted based on preorder pulse energy and a temperature change rate; energy adjustment factors are calculated according to optical parameter changes, and pulse energy density, interval and waveform parameters are intelligently optimized; a pulse sequence cooperative control model is established, and multiple safety protection is realized through thermal damage probability integration and spectral feature monitoring. The technical problems that traditional equipment is unstable in energy output, depends on artificial experience and lacks real-time dynamic adjustment capacity are solved, precise and personalized energy control is achieved, and treatment safety and effectiveness are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of medical aesthetic equipment technology, and more specifically, to a method and system for controlling the output energy of an intense pulsed light therapy device. Background Technology

[0002] Intense Pulsed Light (IPL) therapy, a non-invasive medical aesthetic device, is widely used in areas such as hair removal, treatment of vascular lesions, acne treatment, and skin rejuvenation. Its treatment principle is based on selective photothermolysis; specific wavelengths of light energy are absorbed by target chromophores in the tissue (such as melanin and hemoglobin), generating a thermal effect to achieve the therapeutic goal. Currently, most IPL devices on the market use an open-loop energy control method, meaning that energy parameters are preset before treatment based on the physician's experience or the patient's basic information, lacking real-time response capabilities to dynamic changes in tissue during treatment.

[0003] Existing energy control technologies suffer from the following limitations: First, the setting of treatment parameters heavily relies on the operator's experience, making precise individualized treatment difficult. Different patients exhibit significant differences in skin type, treatment site, and tissue condition, and fixed parameter settings cannot accommodate these variations, easily leading to excessive energy causing burns or insufficient energy affecting efficacy. Second, traditional equipment lacks an effective real-time monitoring mechanism, failing to detect dynamic changes in tissue optical properties (such as absorption and scattering coefficients) during treatment. As photothermal effects accumulate, the scattering and absorption characteristics of tissues change significantly, and existing equipment cannot dynamically adjust the output energy accordingly, resulting in a mismatch between subsequent pulse energy and actual needs. Furthermore, existing safety control mechanisms are mostly based on simple temperature thresholds or fixed timing control, failing to establish an energy coupling model between pulses, making it difficult to effectively prevent thermal accumulation damage.

[0004] Although some improvements have emerged in recent years, such as temperature feedback-based control or impedance measurement-based adjustment, these methods still have significant shortcomings. Temperature feedback control typically has a lag in response and is difficult to prevent instantaneous overheating; while impedance measurement can reflect the electrical properties of tissues, it is not sensitive to changes in optical parameters. Therefore, there is an urgent need in the field for a method to control the output energy of a high-intensity pulsed light therapy device that can sense changes in tissue optical properties in real time, dynamically optimize energy output, and achieve precise and safe monitoring, in order to solve the technical problems of unstable energy output, insufficient treatment safety, and poor individual adaptability in existing technologies. Summary of the Invention

[0005] To overcome the above-mentioned deficiencies of the prior art, embodiments of the present invention provide a method and system for controlling the output energy of an intense pulsed light therapy device.

[0006] To achieve the above objectives, the present invention provides the following technical solution: The method for controlling the output energy of an intense pulsed light therapy device includes the following steps: Step 1, Baseline Measurement and Initialization: Before treatment, measure the optical properties of the tissue and establish a baseline profile. Combine this with patient information to set personalized initial treatment parameters. Step 2, Dynamic Monitoring and Modeling: During treatment, the optical properties and temperature changes of the tissue are monitored in real time, the thermal relaxation time is dynamically adjusted, and the optical parameter matrix is ​​updated. Step 3: Intelligent Energy Optimization: Calculate the energy adjustment factor based on changes in optical parameters, dynamically optimize pulse energy parameters, and customize the pulse waveform; Step 4: Collaborative Control and Safety Monitoring: Establish a pulse sequence collaborative control model to monitor the risk of thermal injury in real time and terminate treatment when the safety threshold is reached.

[0007] Specifically, in step one: tissue reflectance spectral data are collected using a multi-wavelength probe light source, and the absorption coefficient, scattering coefficient, and effective penetration depth of the tissue are calculated based on the diffusion approximation theory to form a baseline profile.

[0008] Specifically, in step one: the initial energy density and pulse width are adjusted according to the patient's skin type and treatment site using preset rules, wherein the skin type is set with an adjustment coefficient based on the Fitzpatrick classification, and the treatment site is set with a sensitivity coefficient based on the sensitivity level.

[0009] Specifically, in step two: the thermal relaxation time is dynamically calculated based on the actual output energy of the previous pulse and the real-time tissue temperature change rate, ensuring that the waiting time is automatically extended during high energy output or rapid heating.

[0010] Specifically, in step three: the energy adjustment factor is calculated based on the weighted sum of the changes in the absorption coefficient, the changes in the scattering coefficient, and the effective penetration depth, and the energy density, pulse interval, and pulse width of subsequent pulses are automatically adjusted according to the numerical range of this factor.

[0011] Specifically, in step three: the pulse waveform is dynamically selected according to the tissue optical properties. When the tissue water content increases significantly, a square wave pulse is used, and when hemoglobin absorption is dominant, a decreasing pulse is used. The pulse width and attenuation factor are customized based on the effective penetration depth and the hemoglobin absorption coefficient, respectively.

[0012] Specifically, in step four: the transfer function of the pulse sequence is established by recursive least squares method, and the optimal energy value of the next pulse is predicted and output by taking the actual energy of the previous pulse, tissue response parameters, energy adjustment factor and tissue temperature as input.

[0013] Specifically, in step four: the probability of tissue thermal damage is calculated in real time, the carbonization characteristics of the reflectance spectrum and the saturation of the treatment effect are monitored, and the treatment is automatically terminated when the probability of thermal damage exceeds the threshold, carbonization characteristics appear, or the treatment response is saturated.

[0014] The output energy control system of the intense pulsed light therapy device includes the following modules: The multispectral detection and baseline establishment module is used for pre-treatment tissue optical property measurement and personalized parameter initialization; A real-time optical property dynamic monitoring module is used for real-time monitoring of tissue optical properties and temperature changes during treatment. The intelligent energy optimization control module is used to dynamically optimize pulse energy parameters and customize pulse waveforms; Multi-pulse coordination and safety monitoring module, used for pulse sequence coordination control and treatment safety monitoring; The data management and report generation module is used for the storage, analysis, and report generation of treatment data.

[0015] The technical effects and advantages of this invention are as follows: By employing multispectral real-time monitoring and dynamic modeling technology, precise energy control during intense pulsed light (IPL) therapy is achieved. The system can establish an individualized baseline of tissue optical properties before treatment, track changes in key parameters such as absorption and scattering coefficients in real time during treatment, and dynamically optimize pulse energy, waveform, and interval parameters based on energy adjustment factors. This closed-loop control mechanism effectively overcomes the shortcomings of traditional equipment that relies on preset parameters and cannot adapt to dynamic tissue changes. It ensures that energy output always matches the actual tissue state, significantly improving the precision and adaptability of treatment and guaranteeing the stability and consistency of treatment effects.

[0016] Integrating multi-pulse collaborative control and multiple safety monitoring mechanisms, this approach significantly enhances the safety and intelligence of treatment. By establishing a pulse sequence energy coupling model and calculating the probability of thermal damage in real time, the system can proactively predict and mitigate the risk of heat accumulation. Combined with carbonization spectral identification and treatment saturation assessment, a comprehensive safety protection system is constructed. This solution not only fundamentally reduces the risk of tissue burns but also reduces reliance on operator experience through automated treatment processes. Simultaneously, it provides traceable data support for clinical treatment, achieving a balance between safety, efficiency, and intelligence. Attached Figure Description

[0017] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] like Figure 1 As shown, the steps for controlling the output energy of an intense pulsed light therapy device are as follows: Step 1: Baseline measurement and initialization. Before treatment, the tissue is irradiated with multi-wavelength probe light to collect reflectance spectral data. Based on the diffusion approximation theory, the baseline of tissue optical properties (absorption coefficient, scattering coefficient, penetration depth) is calculated and established. Combined with the patient's skin type and treatment site, safe initial treatment parameters are calculated and set through personalized formulas.

[0020] Before treatment begins, baseline measurements of the tissue's optical properties are performed. The target tissue is irradiated with a multi-wavelength LED probe light source (containing four characteristic wavelengths: 415nm, 540nm, 650nm, and 800nm) built into the treatment head, and reflectance spectral data is collected using an integrated spectrometer. Specifically, four wavelengths of low-energy probe light are emitted sequentially for 100μs, with 50μs intervals between each wavelength; the reflected light intensity corresponding to each wavelength is simultaneously collected at a sampling frequency of 10MHz; a tissue optical model is established based on the diffusion approximation theory, and the absorption coefficient of the ground-state tissue is calculated. scattering coefficient and effective penetration depth .

[0021] The parameters, along with the patient's basic information (skin type, treatment site, treatment history), are stored together as a baseline profile of tissue optical properties. Simultaneously, initial energy parameters, including pulse width, pulse interval, and energy density range, are set according to the treatment type. The initial energy parameters are calculated individually based on the patient's skin type and treatment site. Specifically, the initial energy density... Calibration is performed using the following formula: ; in, This is the standard initial energy density for this type of treatment; The adjustment factor based on Fitzpatrick skin type is 1.0-1.1 for types I-II, 0.8-0.9 for types III-IV, and 0.6-0.8 for types V-VI. The sensitivity coefficient is based on the treatment site. For the cheek and back, it is 1.0; for the limbs, it is 0.9; and for the area around the eyes, neck, and bikini area, it is 0.7-0.8.

[0022] Meanwhile, the pulse width is based on To achieve the opposite effect, the pulse width is increased by 10% by default for each skin type level increase (e.g., from type III to type IV) to ensure that energy is released more gradually over time and reduce the risk of instantaneous thermal damage.

[0023] The tissue optical model is constructed based on the diffusion approximation theory, where the reduced scattering coefficients are... With scattering coefficient The relationship is , This is the anisotropy factor, with a default value of 0.8, applicable to biological tissues. Effective penetration depth. The calculation formula is: .

[0024] Step 2: Dynamic monitoring and modeling. Low-energy probe pulses are inserted between treatment pulses to monitor tissue optical properties and temperature changes in real time. The thermal relaxation waiting time is dynamically adjusted based on the preceding pulse energy and the real-time temperature rise rate to ensure treatment safety. The dynamic optical parameter matrix is ​​updated using monitoring data, and the energy deposition of subsequent pulses is predicted through Monte Carlo simulation.

[0025] Tissue optical properties were continuously monitored during the intervals between treatment pulse firings. After each treatment pulse firing, a dynamic thermal relaxation time was allowed before a probe pulse sequence was fired. The thermal relaxation time... It is not a fixed value, but rather depends on the actual output energy of the previous treatment pulse. and the current real-time temperature change rate of the organization Dynamic adjustments are made; the calculation formula is as follows: ; in: The baseline thermal relaxation time is set to 50ms; for The actual output energy of each pulse; The rate of change of the current tissue surface temperature is calculated from the reading of the infrared temperature sensor within 10 ms after pulse emission; and These are weighting coefficients, with values ​​of 0.1 ms / J and 5.0 ms / (°C / ms), respectively. This ensures that during high energy output or rapid tissue heating, the waiting time is automatically extended to allow for sufficient heat dissipation, thereby maximizing treatment efficiency while ensuring treatment safety.

[0026] The probe pulse energy is 1% of the treatment pulse, the duration is 20 μs, and it includes the four characteristic wavelengths from step 1.

[0027] By analyzing the time-resolved characteristics of the reflectance spectrum, a dynamic change model of tissue optical properties is established. Specifically, this includes calculating the current absorption coefficient. Relative rate of change with baseline value Assess the degree of thermal denaturation of chromophores such as hemoglobin; analyze the scattering coefficient. The changing trends reflect alterations in cellular structure; based on Monte Carlo simulation, the light energy flow rate distribution is reconstructed to predict the energy deposition of subsequent treatment pulses. Real-time monitoring data is updated 20 times per second, forming a dynamic parameter matrix of tissue optical properties.

[0028] Step 3: Intelligent energy optimization. A comprehensive analysis of optical parameter variations at various characteristic wavelengths is performed, and the energy adjustment factor is calculated using a weighted formula. ;according to Based on the range of values, the energy density, interval, and pulse width of subsequent pulses are intelligently adjusted; for different dominant chromophores (such as hemoglobin and water), the waveform parameters of square waves or decreasing pulses are dynamically selected and finely customized.

[0029] Based on the dynamic tissue optical property parameters obtained in step 2, an energy output optimization model was established. First, the variation patterns of reflection intensity at each characteristic wavelength were analyzed: the reflectance change at 415nm wavelength reflects the change in melanin density, the 540nm wavelength corresponds to the absorption characteristics of oxyhemoglobin, the 650nm wavelength indicates the change in tissue water content, and the 800nm ​​wavelength reflects the scattering characteristics of deep tissues. Based on these parameters, the energy adjustment factor was calculated using the following formula. : ; in This represents the change in the absorption coefficient, specifically the difference between the current absorption coefficient and the baseline value. This is the baseline absorption coefficient, i.e., the baseline absorption coefficient measured before treatment. The change in scattering coefficient Baseline scattering coefficient, The baseline effective penetration depth is the baseline penetration depth measured before treatment. , , These are weighting coefficients, corresponding to the weights of absorption, scattering, and penetration depth, respectively, and are dynamically adjusted according to the treatment type. The initial setting of the weighting coefficients is based on the main chromophores and tissue layers of interest in the treatment target, and its preset rules are as follows: For hair removal treatments, the focus is on melanin absorption, and the treatment is designed to... =0.5, =0.3, =0.2; For vascular therapy, the focus is on hemoglobin absorption, and the setting is... =0.6, =0.2, =0.2; For skin rejuvenation / hydration treatments, the focus is on tissue scattering characteristics and moisture, set to... =0.3, =0.4, =0.3.

[0030] During the treatment process, based on real-time calculations The deviation trend of the value from the target range (0.8-1.2) is used to fine-tune the weighting coefficients. For example, if... If it remains consistently high, then reduce it appropriately. Increase the weight or The weights are adjusted to adapt to dynamic changes in the organizational state.

[0031] Then, based on the energy adjustment factor Optimize output parameters: when When the energy density is greater than 1.2, the energy density of subsequent pulses is automatically reduced by 10%-20%, while the pulse interval is extended by 15%; when the energy density is less than 0.8, the energy density of subsequent pulses is automatically reduced by 10%-20%, while the pulse interval is extended by 15%. When ≤1.2, maintain the current parameter; when When the energy density is ≤0.8, the energy density should be increased by 5%-10% and the pulse interval shortened. Simultaneously, the pulse waveform should be dynamically adjusted based on the spectral characteristics analysis results: a square wave pulse should be used when tissue water content increases significantly; a decreasing pulse should be used when hemoglobin absorption is dominant.

[0032] The specific parameters of the pulse waveform are customized based on the real-time tissue optical characteristics to achieve optimal energy distribution over time: when using a square wave pulse, its pulse width... (Unit: ms) Based on the current effective penetration depth (Unit: mm) Dynamically determined, the calculation formula is: ; Ensuring the duration of light energy injection matches the depth of light propagation within the tissue optimizes energy deposition in deep tissues. When using a decreasing pulse, its attenuation factor... Based on the absorption coefficient of hemoglobin at 540 nm (Unit: mm⁻¹) The configuration is performed using the following formula: ; Among them, attenuation factor The ratio of initial pulse energy to final pulse energy was defined. The model ensures that in areas with high hemoglobin uptake, the pulse initially acts rapidly on the target chromophore with higher energy, followed by maintaining the thermal effect with lower energy, thereby maximizing epidermal protection while achieving highly efficient treatment.

[0033] Step 4: Collaborative control and safety monitoring. Establish an energy coupling model between multiple pulses, update the transfer function online using the recursive least squares method to achieve collaborative optimization of the pulse sequence; calculate the probability of tissue thermal damage Ω in real time by integration, and simultaneously monitor spectral carbonization characteristics and treatment saturation; automatically terminate treatment when the treatment endpoint is reached or a safety threshold is triggered, and generate a treatment report containing full-process data.

[0034] Throughout the entire treatment process, coordinated control of multiple pulse sequences is implemented. An energy coupling model between pulses is established, considering the thermal accumulation and photobiological effects of preceding pulses. Specifically, the actual energy output of each pulse is recorded. and organizational response parameters ,in Let be the pulse sequence number. The transfer function of the pulse sequence is established using the recursive least squares method: ; in This represents the (i+1)th optimal energy, which is the predicted optimal energy value for the next pulse. Let i be the actual energy of the i-th time. For the first Mean change in tissue reflectance after each pulse For the first The energy adjustment factor is calculated after each pulse. For the first Tissue surface temperature after one pulse.

[0035] The specific implementation of the transfer function is a first-order linear model: ; in: For the first The actual output energy of each pulse For the first Mean change in tissue reflectance after each pulse For the first The energy adjustment factor is calculated after each pulse. For the first Tissue surface temperature after one pulse , , , , These are the model coefficients.

[0036] The model coefficients are updated online in real time using the recursive least squares method, with a forgetting factor set to 0.95 to balance the influence of historical and new data, enabling the model to quickly track the dynamic characteristics of organizational response.

[0037] Simultaneously, multiple safety monitoring measures are implemented: the probability of tissue thermal damage Ω is calculated in real time, and the output automatically stops when Ω > 0.8; the probability of tissue thermal damage Ω is calculated based on the Arrhenius biological tissue thermal damage integral model, and its expression is: ; in, It is the pre-exponential factor (frequency factor). For activation energy, This is the universal gas constant. The absolute temperature of the tissue, which is monitored in real time, is obtained by an infrared temperature sensor built into the treatment head.

[0038] Monitor for abnormal changes in the reflectance spectrum; if carbonization characteristic spectra are observed, treatment should be terminated immediately. Assess the saturation of treatment efficacy; when the tissue response change rate is <5% for three consecutive pulses, the treatment endpoint is indicated. Finally, generate a treatment report, including the energy parameters for each pulse, the trend of tissue response changes, and an assessment of treatment efficacy.

[0039] The energy output control system of the intense pulsed light therapy device consists of the following modules: The multispectral detection and baseline establishment module is responsible for acquiring tissue reflectance spectral data using multi-wavelength LED light sources and a spectrometer before treatment. It establishes a personalized baseline profile of the patient's tissue optical properties, including absorption coefficient, scattering coefficient, and effective penetration depth. Based on skin type and treatment site, it intelligently calculates initial energy parameters, providing a precise starting point for treatment.

[0040] A real-time optical property dynamic monitoring module continuously monitors the dynamic changes in tissue optical properties during treatment, including absorption coefficient, scattering coefficient, and temperature change rate. High-frequency sampling (20 times per second) and a dynamic thermal relaxation time adjustment mechanism ensure the real-time nature and security of data acquisition. The light energy flux distribution is reconstructed using the Monte Carlo method, providing real-time data support for energy optimization.

[0041] The intelligent energy optimization control module calculates the energy adjustment factor based on real-time optical characteristic data, dynamically optimizing pulse energy density, pulse interval, and pulse width. Through an adaptive adjustment mechanism of weighting coefficients, it achieves precise adaptation to different treatment types (hair removal, vascular treatment, skin rejuvenation). It intelligently selects and customizes the pulse waveform (square wave / decreasing pulse) to ensure optimal energy distribution over time.

[0042] The multi-pulse coordination and safety monitoring module establishes an energy coupling model between pulse sequences and achieves coordinated control between pulses through recursive least squares method. It calculates the probability of tissue thermal damage in real time and monitors the carbonization characteristic spectrum and treatment effect saturation. Treatment is automatically terminated when a safety risk is detected, ensuring the safety and controllability of the treatment process.

[0043] The data management and report generation module stores complete treatment process data, including energy parameters for each pulse, tissue response trends, and optical properties. Based on this data, it generates detailed treatment reports, providing assessments of treatment effectiveness and determining treatment endpoints. It also supports historical data retrospective analysis, providing data support for optimizing subsequent treatments.

[0044] The above formulas are all dimensionless calculations. Dimensionless calculations can be performed using various methods such as standardization, which will not be elaborated here. The formulas are derived from software simulations based on a large amount of collected data, and the preset parameters in the formulas can be set by those skilled in the art according to the actual situation.

[0045] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, ATA hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state ATA hard disk.

[0046] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0047] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0048] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0049] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0050] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0051] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable ATA hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0052] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for controlling the output energy of an intense pulsed light therapy device, characterized in that, Includes the following steps: Step 1, Baseline Measurement and Initialization: Before treatment, measure the optical properties of the tissue and establish a baseline profile. Combine this with patient information to set personalized initial treatment parameters. Step 2, Dynamic Monitoring and Modeling: During treatment, the optical properties and temperature changes of the tissue are monitored in real time, the thermal relaxation time is dynamically adjusted, and the optical parameter matrix is ​​updated. Step 3: Intelligent Energy Optimization: Calculate the energy adjustment factor based on changes in optical parameters, dynamically optimize pulse energy parameters, and customize the pulse waveform; Step 4: Collaborative Control and Safety Monitoring: Establish a pulse sequence collaborative control model to monitor the risk of thermal injury in real time and terminate treatment when the safety threshold is reached.

2. The method for controlling the output energy of a high-intensity pulsed light therapy device according to claim 1, characterized in that, In step one: Tissue reflectance spectral data are collected using a multi-wavelength probe light source. The absorption coefficient, scattering coefficient, and effective penetration depth of the tissue are calculated based on the diffusion approximation theory to form a baseline profile.

3. The method for controlling the output energy of a high-intensity pulsed light therapy device according to claim 1, characterized in that, In step one: The initial energy density and pulse width are adjusted according to the patient's skin type and the treatment area using preset rules. The skin type is set with an adjustment coefficient based on the Fitzpatrick classification, and the treatment area is set with a sensitivity coefficient based on the sensitivity level.

4. The method for controlling the output energy of a high-intensity pulsed light therapy device according to claim 1, characterized in that, In step two: The thermal relaxation time is dynamically calculated based on the actual output energy of the previous pulse and the real-time tissue temperature change rate, ensuring that the waiting time is automatically extended during high energy output or rapid heating.

5. The method for controlling the output energy of a high-intensity pulsed light therapy device according to claim 1, characterized in that, In step three: The energy adjustment factor is calculated based on the weighted sum of the changes in absorption coefficient, scattering coefficient, and effective penetration depth, and automatically adjusts the energy density, pulse interval, and pulse width of subsequent pulses according to the numerical range of this factor.

6. The method for controlling the output energy of a high-intensity pulsed light therapy device according to claim 5, characterized in that, In step three: The pulse waveform is dynamically selected based on the tissue's optical properties. A square wave pulse is used when the tissue water content increases significantly, and a decreasing pulse is used when hemoglobin absorption is dominant. The pulse width and attenuation factor are customized based on the effective penetration depth and the hemoglobin absorption coefficient, respectively.

7. The method for controlling the output energy of a high-intensity pulsed light therapy device according to claim 1, characterized in that, In step four: The transfer function of the pulse sequence is established by recursive least squares method. The actual energy of the previous pulse, tissue response parameters, energy adjustment factor and tissue temperature are used as inputs to predict and output the optimal energy value of the next pulse.

8. The method for controlling the output energy of a high-intensity pulsed light therapy device according to claim 7, characterized in that, In step four: The system calculates the probability of tissue thermal damage in real time, monitors the carbonization characteristics of the reflectance spectrum and the saturation of the treatment effect, and automatically terminates the treatment when the probability of thermal damage exceeds the threshold, carbonization characteristics appear, or the treatment response saturates.

9. A system applied to the method for controlling the output energy of a high-intensity pulsed light therapy device according to any one of claims 1-8, characterized in that, Includes the following modules: The multispectral detection and baseline establishment module is used for pre-treatment tissue optical property measurement and personalized parameter initialization; A real-time optical property dynamic monitoring module is used for real-time monitoring of tissue optical properties and temperature changes during treatment. The intelligent energy optimization control module is used to dynamically optimize pulse energy parameters and customize pulse waveforms; Multi-pulse coordination and safety monitoring module, used for pulse sequence coordination control and treatment safety monitoring; The data management and report generation module is used for the storage, analysis, and report generation of treatment data.

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