Adaptive systems and methods for personalized hair treatment using multi-sensor fusion and EMR contro

Abstract

A hair treatment device is disclosed, comprising at least one electromagnetic radiation (EMR) source (UV, VL, IR) and two or more sensors (e.g., color, temperature, motion, humidity, spectroscopic) generating real-time hair characteristics and treatment condition data. A controller intelligently fuses this sensor data and employs a machine learning algorithm, trained on diverse hair profiles, to predict highly individualized optimal EMR parameters, including intensity, wavelength, and phase of individual pulses. The controller dynamically adjusts the EMR source in real-time, with continuous refinement based on predicted optimal parameters and fused sensor data in a closed-loop feedback system. This provides unprecedented precision in personalized, uniform, and damage-preventing hair treatment device. Further embodiments include nanostructured EMR-transmissive surfaces for dynamic spectral control, modular EMR systems with detachable, optimized modules, and hairbrush form factors integrating this adaptive EMR technology. A remote computing platform continuously updates the device's machine learning algorithm through cloud-based adaptive calibration, and a corresponding method for treating hair is also provided.

Description

[0001] A DAPTIVE SYSTEMS AND METHODS FOR PERSONALIZED HAIR TREATMENT USING MULTI-SENSOR FUSION AND EMR CONTROL

[0002] FIELD OF THE INVENTION

[0003] [1] The present invention pertains to the fields of cosmetics and aesthetics, and more particularly concerns methods and devices for the treatment of hair.

[0004] BACKGROUND OF THE INVENTION

[0005] [2] The invention introduces an intelligent, adaptive hair treatment system that leverages multi-sensor fusion and machine learning to achieve precise, damage-preventing control of electromagnetic radiation (EMR). Traditional hair styling tools=such as dryers, straighteners, and curlers=apply uniform heat through convection or contact, often exceeding safe temperatures and damaging hair composed of keratin and melanin. These devices rely on generalized heating with limited customization and lack real-time adaptation to individual hair characteristics, such as texture, color, or moisture.

[0006] [3] Prior art, including WO2023144810 and similar disclosures, introduced EMR-based heating and basic sensor feedback but lacked real-time adaptive control, predictive optimization, and comprehensive data integration. The present invention overcomes these limitations by enabling continuous, intelligent adjustment of EMR parameters across the UV, visible, and IR ranges.

[0007] [4] Through multi-sensor data fusion, the system constructs a real-time hair profile and employs machine learning algorithms to dynamically optimize EMR wavelength, intensity, and pulse phase. This ensures consistent, personalized, and safe hair treatment while preventing overheating or under-treatment. The invention further automates complex decision-making, eliminating the need for user expertise, and continuously improves performance through self-learning and aggregated data analysis.

[0008] SUMMERY OF THE INVENTION

[0009] [5] The present invention introduces a revolutionary hair treatment system designed to provide unprecedented precision in personalized, uniform, and damage-preventing hair treatment. This is achieved through the intelligent application of electromagnetic radiation (EMR) across ultraviolet (UV), visible light (VL), and infrared (IR) ranges, driven by advanced multi-sensor fusion and machine learning (ML) algorithms operating within a sophisticated closed-loop feedback system.

[0010] I. Core Intelligent Adaptive EMR Control Device

[0011] [6] At its foundation, the technology comprises a hair treatment device that integrates an EMR source, a comprehensive multi-sensor array, and an intelligent controller.

[0012] [7] The EMR source is configured to emit radiation in one or more wavelength ranges including UV,

[0013] VL, and IR. This source can comprise a plurality of emitters capable of generating these bands simultaneously, with the controller dynamically adjusting the relative intensity and phase of individual pulses of each simultaneously emitted wavelength range based on predicted optimal treatment parameters.

[0014] [8] The device incorporates two or more sensors, selected from a comprehensive group including color, temperature, motion, humidity, proximity, pressure, reflectivity, conductivity, vibration, infrared, and spectroscopic sensors. These sensors generate real-time data indicative of both intrinsic hair characteristics (e.g., color, density, moisture level) and dynamic treatment conditions (e.g., temperature, device movement). These sensors can be integrated into a detachable module, configured for rapid and precise field calibration or replacement to maintain the accuracy of the intelligent data fusion.

[0015] [9] The intelligent controller is the central intelligence, configured to:

[0016]

[0010] Intelligently fuse the real-time data from the multiple sensors to generate a comprehensive, dynamic hair profile. This fusion process goes beyond simple aggregation, correlating disparate inputs for a holistic understanding of the hair's state.

[0017]

[0011] Employ a machine learning algorithm, specifically a neural network architecture, trained on diverse hair profiles. This algorithm is crucial for predicting highly individualized optimal EMR parameters. This neural network is configured for real-time inference and trained using historical treatment data to optimize the prediction of individualized optimal treatment parameters.

[0018]

[0012] Predictive EMR Parameter Determination: The ML algorithm predicts optimal EMR parameters, including intensity, specific wavelength composition, and crucially, the phase of individual pulses. This prediction is tailored to the user's specific hair characteristics and dynamic treatment conditions.

[0013] Dynamic and Continuous EMR Adjustment: The controller dynamically adjusts the EMR source's output (intensity, wavelength, and pulse phase) in real-time. This adjustment is continuously refined based on the ML's predicted optimal parameters and the fused real-time sensor data, operating within a closed-loop feedback system. This continuous optimization ensures energy delivery is precisely matched to the hair's needs, with the controller configured to operate in this closed-loop feedback mode to continuously optimize energy delivery.

[0019]

[0014] Pulsed EMR with Variable Duty Cycles: The EMR source can emit pulsed radiation with dynamically variable duty cycles, adjusted by the controller based on the predicted optimal treatment parameters and fused real-time sensor data for precise and localized thermal control.

[0020]

[0015] Dynamically Phase-Controlled Modulation: The EMR emission utilizes dynamically phase- controlled modulation, determined by the ML algorithm to precisely achieve uniform thermal distribution and prevent localized overheating.

[0021]

[0016] Predictive Safety Subsystem: The device further comprises a predictive safety subsystem configured to anticipate and prevent potential hair damage by proactively deactivating or modulating the EMR source based on the ML algorithm's real-time risk assessment derived from fused sensor data.

[0022]

[0017] Monolithic Integration: The EMR source can be monolithically integrated within a photonicthermal substrate, designed for simultaneous EMR emission and highly efficient residual heat dissipation in a compact form factor.

[0023] II. Advanced Device Components and Architectures

[0024]

[0018] The technology introduces specialized components and modular designs for enhanced functionality:

[0025]

[0019] Nanostructured EMR-Transmissive Surfaces: The device incorporates at least one EMR- transmissive surface featuring a precisely engineered nanostructured coating. This coating is configured to dynamically and selectively absorb or reflect specific EMR wavelengths with high spectral resolution, thereby enhancing heating uniformity and reducing energy consumption beyond conventional pigmented or low thermal mass materials.

[0026]

[0020] The nanostructured coating can comprise metallic nanoparticles precisely tuned to specific EMR wavelength bands, with this tuning being adaptable by the controller based on the predicted optimal treatment parameters.

[0021] It may be thermochromic, dynamically altering its EMR reflectivity based on the surface temperature, providing passive, self-regulating thermal control.

[0027]

[0022] The coating can be applied to a flexible polymer substrate, enabling conformal application to non- planar surfaces or dynamic shaping during hair treatment.

[0028]

[0023] Furthermore, the nanostructured coating can provide self-cleaning and anti-oxidation properties, maintaining optical performance and durability.

[0029]

[0024] Modular EMR System: The device can feature a main housing with a plurality of detachable EMR modules. Each module is specifically optimized for a distinct hair type, color, or treatment mode, based on pre-programmed or ML-derived parameters, thereby providing a user-configurable and adaptable treatment system.

[0030]

[0025] Each detachable EMR module may include an integrated microcontroller for independent operation, allowing for localized processing and fine-tuned EMR emission control specific to that module's optimization.

[0031]

[0026] These modules can be magnetically attachable to a main housing, facilitating quick and secure interchangeability.

[0032]

[0027] The modules are automatically recognized by a central controller upon attachment, triggering the loading of corresponding machine learning models and optimal treatment parameters for the recognized module.

[0033]

[0028] Each detachable EMR module can include a unique optical filter precisely tailored for wavelength selection corresponding to the module's optimized hair type or treatment mode.

[0034] III. Hairbrush Form Factor

[0035]

[0029] The core adaptive EMR technology is specifically embodied in a hairbrush, providing precise treatment during the act of brushing: Integrated EMR and Sensors: The hairbrush comprises a handle, a bristle base with a plurality of bristles configured to engage hair, and an EMR source integrated within the bristle base. Two or more sensors are embedded within the brush, selected from the comprehensive group of sensors, and configured to generate real-time data indicative of hair characteristics and treatment conditions within the bristles' engagement area.

[0036]

[0030] Intelligent Control: A controller receives and intelligently fuses this localized sensor data, employing an ML algorithm trained on diverse hair profiles to predict highly individualized optimal EMR parameters (intensity, wavelength, and pulse phase) specifically for the hair engaged by the bristles. This provides unprecedented precision in personalized, uniform, and damagepreventing hair treatment directly through the hairbrush.

[0037]

[0031] Specialized Bristles: At least some of the bristles can be partially transparent to EMR, serving as light guides to precisely direct the dynamically adjusted EMR to individual hair strands. Bristles may also include nanostructured coatings configured for dynamically selective EMR wavelength absorption or reflection, with selectivity controlled by the controller based on predicted optimal parameters.

[0038]

[0032] Modulation by Hair Characteristics: The controller is configured to modulate EMR intensity and wavelength based on predictively determined optimal parameters for detected hair color and thickness, derived from the ML algorithm.

[0039]

[0033] Cloud Connectivity: The hairbrush can include a wireless communication module configured for cloud-based adaptive calibration and ML model updates, enabling continuous improvement of the predictive optimal treatment parameters.

[0040] IV. System-Level Integration and Methodologies

[0041]

[0034] The technology extends to a broader system and detailed methods of operation for continuous learning and optimization:

[0042]

[0035] Cloud-Based Adaptive Learning System: The device communicates wirelessly with an external computing device or cloud platform for remote monitoring, adaptive model updates, and continuous refinement of the ML algorithm based on aggregated usage data.

[0043]

[0036] A remote computing platform receives user-specific and treatment performance data from the device, analyzes it to identify patterns and correlations, and continuously updates the device’s ML algorithm to refine the prediction of highly individualized optimal EMR parameters through cloudbased adaptive calibration.

[0044]

[0037] This platform can employ federated learning to enhance data privacy and performance across a distributed network of devices.

[0045]

[0038] It provides real-time feedback to the device during operation, including dynamic adjustments based on environmental conditions or global model insights.

[0046]

[0039] The platform maintains comprehensive user profiles for personalized treatment recommendations, including historical data and hair characteristics evolution.

[0040] It can synchronize data across multiple hair treatment devices owned by the same user, ensuring consistent personalized treatment parameters and historical data.

[0047]

[0041] Method for T reating Hair :

[0048]

[0042] Detection & Fusion: The method involves detecting hair characteristics using two or more sensors and intelligently fusing this real-time data to generate a comprehensive hair profile.

[0049]

[0043] Prediction: Highly individualized optimal EMR parameters (intensity, wavelength, pulse phase) are predicted using an ML model trained on diverse hair profiles.

[0050]

[0044] Emission & Adjustment: Multi-band EMR is emitted with dynamically modulated intensity, wavelength, and pulse phase, based on the predicted optimal EMR parameters, and continuously adjusted in real time based on sensor feedback in a closed-loop system.

[0051]

[0045] Adaptive Learning: Treatment data (hair characteristics, applied EMR parameters) is stored for subsequent adaptive learning and refinement of the ML model. The ML model is updated periodically based on aggregated user data, continuously improving its predictive accuracy and adaptability.

[0052]

[0046] Moisture-Based Modulation: EMR emission can be dynamically modulated in real time according to predictively determined optimal parameters based on detected hair moisture levels.

[0053]

[0047] Proactive Safety: The method includes proactively deactivating or modulating the EMR source based on a real-time risk assessment from the ML model, anticipating and preventing excessive hair temperature before damage occurs.

[0054]

[0048] Cloud-Enhanced Learning: Treatment data is transmitted to a remote server for analysis and updating the predictive ML model, continuously improving future treatment accuracy and personalization. The remote server can employ reinforcement learning to autonomously optimize EMR control policies, generate user-specific treatment profiles, and aggregate anonymized data for model accuracy. Updated model parameters are periodically downloaded for offline operation.

[0055]

[0049] This comprehensive technology provides a holistic, intelligent, and continuously evolving solution for personalized hair treatment, moving beyond conventional methods to offer superior precision, safety, and effectiveness.

[0056]

[0050] V. Adaptive Multi-Mode Hair Treatment Device and Method Utilizing Synergistic Heat,

[0057] Light, and Airflow for Personalized and Damage-Preventing Hair Care

[0058]

[0051] The invention relates to a hair treatment device and method that utilize a synergistic combination of heat, light, and airflow to achieve efficient and safe hair treatment.

[0052] The device includes: A heating plate that applies direct heat to hair placed adjacent to it;

[0059]

[0053] A light and heat source positioned within or near the heating plate, emitting both light and heat toward the hair; and A fan that directs airflow across the heating plate and light source, conveying heated air to the hair. In operation, the heat radiated from the light source and carried by the airflow remains below approximately 180°C, while the combined effect of the heating plate, light source, and airflow produces a total heating effect exceeding 180°C. This enables effective hair treatment through convection, radiation, and conduction, while minimizing the required light intensity and reducing risks of over-illumination or eye exposure. The corresponding method involves positioning the hair near the heating plate, activating the light and heat source, directing airflow to deliver controlled heat, and combining these effects to achieve the desired temperature. The process allows personalized and controlled hair treatment, adaptable to different hair types and conditions, ensuring uniform heating and preventing damage.

[0060] BRIEF DESCRIPTION OF THE DRAWINGS

[0061]

[0054] For illustrating the invention, there are depicted in the drawings certain embodiments of the invention. However, the invention is not limited to the precise arrangements and instrumentalities of the embodiments depicted in the drawings.

[0062]

[0055] Fig. 1 illustrates a non-limiting example of a hair treatment device, in accordance with the present invention;

[0063]

[0056] Fig.2A illustrates the electromagnetic radiation absorbance in Keratin;

[0064]

[0057] Fig 2B illustrates the electromagnetic radiation absorbance in Pheomalnin;

[0065]

[0058] Fig 2C illustrates the electromagnetic radiation absorbance in Eumalnin;

[0066]

[0059] Fig.3 illustrates different color absorption / reflection in colored materials;

[0067]

[0060] Figs. 4A-4D illustrate various non-limiting embodiments of the hair treatment element of the present invention;

[0068]

[0061] Fig.5 illustrates different non-limiting embodiments for patterning EMR windows / surfaces of the present invention;

[0069]

[0062] Fig.6 illustrates non-limiting examples of implementations and combinations of the hair treatment element within hair treatment devices, in accordance with the invention;

[0070]

[0063] Figs.7A-7F illustrate various non-limiting embodiments of the hair treatment device of the present invention, including various non-limiting elements / sensors;

[0064] Fig.8 illustrates a non-limiting method for treating hair, in accordance with the present invention;

[0071] and

[0072]

[0065] Fig. 9 illustrates synergistic heat transfer mechanism combining convection, radiation, and conduction for controlled and personalized hair treatment.

[0073] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0074]

[0066] Reference is made to Fig. 1 illustrating a first non-limiting example of a hair treatment device 100, in accordance with the present invention. The hair treatment device 100 is configured for aesthetic and cosmetic treatment, such as straightening and / or curling hair. As shown, the hair treatment device 100 includes an enclosure 102 to enable holding and grasping the device in the user’s hand. Various enclosure non-limiting examples are detailed further below. In the housing, the hair treatment device 100 includes at least one hair treatment element 110 configured for applying heat to the hair to treat the hair, and at least one optional controller 140 for controlling the hair treatment device 100, including the at least one hair treatment element 110 and other optional elements, as will be detailed further below.

[0075]

[0067] The hair treatment element 110 includes a housing 112 that houses at least one electromagnetic radiation (EMR) source 120 configured and operable to generate an electromagnetic radiation in one or more wavelength ranges including at least one of the ultraviolet (UV) range, visible light (VL) range and infrared (IR) range. In some embodiments, the housing of the hair treatment element forms, coincides with or overlaps with at least a part of the enclosure of the hair treatment device.

[0076]

[0068] The hair treatment device 100 includes at least one window / surface 130 associated with the at least one hair treatment element 110 and located in the optical path of the EMR for transmitting at least a portion of the EMR, generated by the EMR source 120, to be directed towards the hair and be absorbed by the hair, thereby heating and treating the hair. In some embodiments, either the hair treatment device 100 or the hair treatment element 110 (or both), via the enclosure 102 and / or housing 112, provide(s) a gap, in the optical path, between the EMR source 120 and the window / surface 130. In some embodiments, the gap is an air gap. In some embodiments, no gap is present between the EMR source 120 and the window / surface 130, e.g. the optical path therebetween is gapless.

[0069] The present invention utilizes hair properties for absorbing electromagnetic radiation in the wavelength range of between 100 - 1000 nm. Specifically, the ultraviolet (UV) waves range from 100-400nm, the visible light (VL) waves range from 380-700nm, and the infrared (IR) waves range from 780-1000nm. According to the invention, selective irradiation of the hair with one or more of the above-mentioned wavelength ranges potentially achieves the personalized heating and treatment of the hair.

[0077]

[0070] As mentioned above, hair includes two major components, Keratin and Melanin. The latter includes Pheomelanin and Eumelanin. Reference is made to Fig. 2A showing a graph of light wavelength absorbance in keratin, Fig. 2B showing a graph of light wavelength absorbance in Pheomelanin, and Fig. 2C showing a graph of light wavelength absorbance in Eumelanin. As appreciated from the figures, Keratin and Melanin are very good UV absorbers. The very high absorption of the UV waves, translated to thermal energy, provides an efficient way of heating the hair.

[0078]

[0071] IR radiation is popularly known as “heat radiation”. Including IR radiation in the targeting electromagnetic radiation expedites the heating process of the hair.

[0079]

[0072] Visible light is absorbed best in its complementary color and reflected best in its matching color.

[0080] Reference is made to Fig. 3 which illustrates this. As shown, Red, Green and Blue (RGB) colors absorption and reflection are demonstrated. On the left side, a red material reflects the red I wave while absorbing the green (G) and blue (B) waves. In the middle, a green material reflects the green wave while absorbing the red and blue waves. And on the right, a blue material reflects the blue wave while absorbing the red and green waves. Once illuminating the hair with the entire visible light spectrum (wavelength of 380-700 nm) only the complementary light colors will be absorbed into the hair and the remaining, more matching, colors will reflect from it. Accordingly, according to the invention, hair color(s) of the specific user can be detected and irradiated with the complementary color(s), e.g. by irradiating the hair with visible light range including the complementary color(s).

[0081]

[0073] In some embodiments, the hair is illuminated with the entire spectrum between lOO-lOOOnm. The heat energy produced from this projection will sum as follows:

[0082] Energy i ,n r. _ \

[0083] , ' , , UV , IR . Complementary :

[0084] applied to “ Absorption of ; - - - . .. . .. ,

[0085] , , ■ waves ' waves * visible light waves ■

[0086] the hair . ..J

[0074] In some embodiments, when irradiating the hair with the entire spectrum (about 100-1 OOOnm), the user is provided with the ability to precisely heat the treated hair as follows: raising the intensity of the electromagnetic radiation source emitting the entire spectrum to a level that nearly reaches the required heat level by the UV and IR waves, then reaching the heating temperature goal with the suitable, complementary, visible light color that bridges the gap to get to the exact radiation heating level.

[0087]

[0075] Back to Fig. 1, in some embodiments, the at least one EMR source has a fixed EMR intensity output. In some embodiments, the at least one EMR source has a variable, controllable, EMR intensity output. In some embodiments, the at least one EMR source is configured to output EMR in a wavelength range extending over the whole spectrum of the invention, i.e. between 100- 1 OOOnm. In some embodiments, the at least one EMR source is configured to output EMR in a wavelength range extending over one or more wavelength ranges of the whole spectrum 100- 1 OOOnm. For example, the EMR source can be configured to output specific wavelength ranges corresponding to the complementary color of the hair of the user. In the latter case, the hair treatment element 110 will include more than one EMR source that together cover the whole spectrum between 100-1 OOOnm.

[0088]

[0076] In some embodiments, the hair treatment device 100 includes a controller 140 that enables either manual or automatic selective operation of the hair treatment device 100 to optimize the treatment for a specific user. The controller 140 can be configured to enable control over one or more of the following parameters of the at least one EMR source: intensity and wavelength range. In some embodiments, the controller 140 is operated manually by the user to control the intensity and / or wavelength range(s) of the at least one EMR source. In some embodiments, the controller autonomously / automatically controls the parameters of the at least one EMR source, based on an input from optional sensors mounted on the hair treatment device, as will be described further below. In some embodiments, the controller is integrated fully in the hair treatment device. In some embodiments, the controller is divided between the hair treatment device and an external device, such as a smartphone. The controller may include both hardware and software components. In one non-limiting example, the controller has a hardware component residing in the hand-held treatment device which is configured to communicate with the hair treatment element to activate / deactivate it and with optionally provided sensors, and a software component configured to receive the signals from the hardware components, analyze the signals and generate operational signals adjusting the parameters of the treatment (e.g., intensity and wavelength range) back to the hardware component that operates the hair treatment element. In some embodiments, the software is in a form of an application running on an external computing device, such as a smartphone.

[0089]

[0077] According to the invention it is safe and fast to treat the hair. In order to guard the hair and avoid burning it, the EMR source(s) can be controlled, e.g. by the controller 140, allowing to apply the required amount of energy to heat the hair to a certain required degree, depending on user’s hair color pigment, since dark hair requires less energy than bright hair. In some embodiments, the user predefines his / her hair color from a predefined color palette, thus tuning the device manually with the optimal / correct amount of energy required. In some embodiments, the device is equipped with optical sensor(s) that defines automatically the optimal energy required for a specific user’s hair color. In some embodiments, the full spectrum is projected on the hair, having only the complementary light color(s) to be absorbed in the hair and the remaining light colors reflected from the hair out.

[0090]

[0078] In another embodiment of the invention, in order to control and reach the exact required amount of heat applied, the EMR source(s) are powered and activated in pulses. The rhythm of turning the EMR source(s) on and of help control the heat and avoid the heat building up at a certain area. In this scenario, the overall heat applied will be a combination of the length of the pulse along with the light intensity emitted.

[0091]

[0079] The one or more EMR windows / surfaces 130, associated with the one or more hair treatment elements 110 serve as a medium for transmitting the EMR from the EMR source(s) towards the hair. For example, the EMR window(s) / surface(s) can be made from material(s) transparent to the whole used spectrum lOO-lOOOnm or to selective portions of the whole spectrum. For example, a plurality of window(s) / surface(s), e.g. three, can be selectively transparent to a plurality of wavelength ranges, e.g. the three UV, VL and IR ranges.

[0092]

[0080] In some embodiments, only specific selective light color(s) is / are projected on the hair in order to achieve the extra heating required. The remaining hair can be heated using conduct! on / convection heating elements / methods, optionally up to a certain level, and then bridging the gap to the right temperature using the EMR source’s ability to precisely heat the hair by direct irradiation of the hair.

[0093]

[0081] Another heat optimization presented in the invention is the use of the heat dissipated from the EMR source(s) while heating the hair. As EMR source(s) emit light energy on one side of the EMR element, the residual heat is projected from their other side. In the present invention the heat from the other end of the EMR source element (it’s back side, the one not used for its emitting abilities) is being conducted back to the hair via a metal frame attached to the back of the EMR source(s), acting as a heat sink but exceeding from the EMR source(s) perimeter outline and touching the hair treated. In this case - all the heat energy from the EMR source(s) is being fully used in its optimal way.

[0094]

[0082] Accordingly, in some embodiments, at least one of the EMR windows / surfaces 130 is configured to absorb at least a portion of the EMR. The at least one EMR window / surface may be configured to transform the absorbed EMR into heat energy and be brought to touch the hair so as to transfer heat to the hair by a convectional heating.

[0095]

[0083] In some embodiments, at least one of the EMR windows / surfaces 130 can be configured as a semitransparent window / surface colored or pigmented or doped in a dark or even black layer such that it absorbs at least a portion of the EMR and is heated such that when it is brought in contact with the hair it transfers heat energy to the hair. In some embodiments, the color / pigment is preferably in a thin layer, having a low or very low thermal mass, e.g. close to zero, such that the colored regions / area are heated and cooled quickly. The quick heating increases efficiency of the hair treatment, e.g. by minimizing the time required for achieving the required treatment, while also increasing safety because of the quick cool down.

[0096]

[0084] In some embodiments, the semi-transparent window(s) / surface(s) can be colored in whole or have a texture, pattern, or only an area colored with the dark or even black pigment, allowing some of the visible light (VL) to pass through the semi-transparent window(s) / surface(s).

[0097]

[0085] In some embodiments, different colors / doping can be used on different parts of the device to control heating degrees of the different parts or control heating in different wavelengths of EMR.

[0098]

[0086] In some embodiments, the window(s) / surface(s) 130 are made, partially or totally, from one or more materials having low or very low thermal mass, e.g. close to zero, such that they are heated quickly and cooled quickly, again to increase efficiency and safety. In some embodiments, the one or more materials include one or more of the following: Teflon, Poly ether ether ketone (PEEK), polyetherimide (e.g., ULTEM), and / or other similar materials. In some embodiments, the window(s) / surface(s) 130 can include a very thin metallic mesh, close or on the external face of it, with a low or very low thermal mass, e.g. close to zero, to enable quick heating and cooling. The metallic mesh will absorb the energy passing through the mesh, and along with the EMR absorbed in the hair will act as a heating element.

[0099]

[0087] In some embodiments, the window(s) / surface(s) 130 include one or more electrically conductive materials, e.g. thin wire(s), that are electrically insulated from the treated hair, the electrically conductive materials can be controllably heated-up by controllably passing an electrical current there through and as a result transfer heat to the treated hair. The electrically conductive materials can also be configured to have low or very low thermal mass, e.g. close to zero, such that they are heated and cooled quickly.

[0100]

[0088] Furthermore, in order to achieve the optimal heating energy, the hair treatment device can be equipped with alerting means that alert the user and correct her / his use of the device, such as timers.

[0101]

[0089] Several additional elements and peripheral components can be included to optimize the device’s operation, as will be described further below.

[0102]

[0090] Reference is now made to Figs. 4A-4D illustrating various non-limiting examples of the hair treatment element 110, in accordance with some embodiments of the invention.

[0103]

[0091] Fig. 4A is a schematic section view of a basic configuration for a hair treatment element 110A. As shown, the hair treatment element embeds a single EMR source (120A) within. The EMR source 120A can be of any type (Halogen, Xenon, Incandescent, LED or other) that is able to project light within the required wavelength spectrum. In this non-limiting example, the EMR source 120A is a united source of the full wavelength spectrum between lOO-lOOOnm, including UV, IR and VL. The EM source 120A can be controlled (e.g. activating it and its intensity) via the controller 140 acting as a dimmer-like component.

[0104]

[0092] The EMR source 120A is located inside the housing 112A of the hair treatment element 110A, whose walls can serve as reflectors for the projected EMR rays. The housing 112A allows the EMR rays to exit through its top open area. Figure 9 describes the unique selective heat mechanism enabled by the present technology, which utilizes three energy transfer mechanisms: convection, radiation, and conduction. The embodiment shown in Figure 9 demonstrates the synergistic use of all three. A schematic, not-to-scale lateral cross-section of the device is presented. A fan 91 directs air 92 towards a heating plate 93, within which a light and heat source (e.g., an incandescent lamp) 94 is located. The light source emits light 95 toward the hair 96 to be treated. The efficiency of the light source is typically less than 100%=for example, between 30% and 75% (e.g., 60%) or about 50%=so that some of the energy is converted to light and some to heat. In this invention, the heat radiated from the light source (90a) and blown by fan 91 towards the hair 96 is significantly lower than about 180°C. Simultaneously, heating plate 93 heats 90b the hair placed adjacent to it. This arrangement ensures heat transfer via convection, radiation, and conduction. Reference is now made to graph 97, which schematically illustrates the heat and light distribution. The critical temperature required for hair treatment is about 180°C. As shown in the graph, part of the heat (well below 180°C) is generated by the heating plate, while the complementary amount is generated by the light source, and together they provide a total heating effect exceeding 180°C. Thus, significantly less light is required to heat the hair, greatly reducing the risk of overillumination or hazardous exposure to high-intensity light beams. Moreover, the synergistic use of both heat and light enables the device to emit a precise amount of light radiation toward the hair, so that some hair types can be exposed to about 180°C, while others may be treated at 190°C, 200°C, etc., allowing the treatment to be personalized according to the client's specific hair type and condition.

[0105]

[0093] The following embodiments describe in detail the advanced technological implementations of the present invention, referred to herein as the current technology, which builds upon and extends the foundational concepts of WO’ 10. The embodiments disclosed below illustrate the integration of adaptive electromagnetic radiation (EMR) control, multi-sensor fusion, artificial intelligence (AI)- based predictive modeling, and cloud-based learning systems for personalized hair treatment.

[0106]

[0094] The present invention introduces an advanced hair treatment device and method that leverages sophisticated electromagnetic radiation (EMR) control and multi-sensor fusion to deliver personalized, precise, and damage-preventing hair care. This technology moves significantly beyond conventional heating methods by intelligently adapting to individual hair characteristics in real-time.

[0107]

[0095] The invention describes an advanced hair treatment device that employs electromagnetic radiation (EMR) across the ultraviolet (UV), visible light (VL), and infrared (IR) spectrum (100- 1000 nm) to achieve precise, efficient, and personalized heating of hair. The system leverages the natural absorption properties of keratin and melanin, which efficiently convert UV and IR radiation into heat.

[0096] Visible Light (VL) for Targeted Absorption: The device exploits the principle that visible light is selectively used based on the hair's color, applying the principle that hair absorbs its complementary color most effectively.

[0108]

[0097] Selective Wavelength Irradiation: The device precisely irradiates hair with specific wavelength ranges (UV, VL, IR) tailored to the unique characteristics of the user's hair.

[0109]

[0098] Complementary Color Targeting: By detecting the user’s hair color, the system emits visible light wavelengths complementary to that color, maximizing absorption and targeted heating.

[0110]

[0099] Fine-Tuned Full Spectrum Heating: The device can apply the full 100-1000 nm spectrum.

[0111] In this mode, UV and IR provide the majority of the required heat, while precisely controlled visible light fine-tunes the temperature to the desired level, ensuring optimal results without overheating.

[0112]

[0100] Intelligent Control System: A sophisticated controller orchestrates the entire process, managing the EMR source(s) and treatment parameters. This controller can operate in both manual and advanced automatic modes.

[0113]

[0101] Manual Operation: Users have the option to manually set EMR intensity and / or wavelength ranges according to their preferences.

[0114]

[0102] Autonomous Control: The controller autonomously adjusts EMR parameters based on real-time input from an array of sensors. It can be fully integrated into the device or distributed, with some functions residing on an external device such as a smartphone, communicating via a dedicated application.

[0115]

[0103] Safety and Optimization Algorithms: A key function of the controller is to ensure safe and efficient treatment. It calculates and applies the precise amount of energy required, considering the hair’s color pigment (e.g., darker hair typically requires less energy). Users can either predefine their hair color, or advanced optical sensors can automatically determine the optimal energy settings.

[0116]

[0104] Pulsed EMR Activation: To prevent localized heat buildup and ensure even treatment, the EMR source(s) can be activated in controlled pulses. The overall heat delivered is precisely managed by adjusting both the pulse duration and light intensity.

[0105] Advanced EMR Windows and Surfaces: The device incorporates specialized EMR windows and surfaces that facilitate efficient and controlled energy transfer.

[0117]

[0106] Material Composition: These surfaces are constructed from materials transparent to the desired EMR spectrum (100-1000 nm) or specific portions thereof. Multiple windows can be selectively transparent to different ranges (e.g., UV, VL, and IR).

[0118]

[0107] Convective Heat Transfer: Certain windows or surfaces are designed to absorb EMR, convert it into thermal energy, and then transfer this heat to the hair via convection, providing an additional layer of heating control.

[0119]

[0108] Semi-Transparent and Pigmented Layers: These surfaces can be semi-transparent, colored, pigmented, or doped with dark / black layers. This design allows them to absorb EMR and heat up, transferring thermal energy upon contact with the hair.

[0120]

[0109] Low Thermal Mass Materials: These components are preferably constructed from materials with low thermal mass, such as Teflon, Poly ether Ether Ketone (PEEK), or poly etherimide (e.g., ULTEM). This property enables rapid heating and cooling, significantly enhancing both treatment efficiency and safety.

[0121]

[0110] Metallic Mesh Integration: In some configurations, a thin metallic mesh with low thermal mass is integrated into the surfaces. This mesh absorbs EMR, acting as an additional heating element alongside the EMR absorbed directly by the hair.

[0122]

[0111] Electrically Conductive Elements : The windows and surfaces can also incorporate thin, electrically conductive wires, insulated from the hair. These wires can be controllably heated by electrical current, providing another means of precise heat transfer. The device manages EMR intensity, wavelength, and duration, operating in either manual or autonomous modes. In automatic operation, sensor data=including hair color and temperature=enables the controller to fine-tune output using safety and optimization algorithms.

[0123]

[0112] To ensure uniform heating and prevent damage, the device operates by balancing advanced, semi¬ specific wavelengths. Certain elements incorporate metallic components that enhance absorption and distribution. Constructed from ULTEM materials, the device achieves improved safety' and efficiency. Optional meshes and electrically conductive elements provide additional, precisely controlled pathways. Collectively, these features enable a personalized, adaptive, and safe treatment process that integrates intelligent control, multi-spectrum energy management, and realtime feedback for consistent, damage-free results.

[0124]

[0113] Patterning for EMR Control (Figure 5): The top cover of the EMR element can feature various patterns (1161-1165 in Figure 5) to precisely control the ratio of transmitted to absorbed EMR. These patterns range from fully transparent to pigmented, textured, or completely colored, allowing for fine-grained customization of energy delivery.

[0125]

[0114] Optimized Heat Management: In some embodiments, the invention includes innovative featuresto maximize heat utilization and prevent energy waste. Residual Heat Recovery: Heat naturally dissipated from the backside of the EMR source(s) is not wasted; instead, it is efficiently conducted back to the hair via a specially designed metal frame that acts as a heat sink, extending to contact the treated hair. This ensures optimal utilization of all generated thermal energy.

[0126]

[0115] Diverse Device Configurations (Figure 6): The hair treatment element can be seamlessly integrated into various device form factors. Single-Sided Application (200): An EMR element is positioned on one side, with the opposing side serving as a simple pressing surface. Reflector-Enhanced Design (210): An EMR element on one side is complemented by an EMR reflector on the opposite side. This reflector, made from materials such as highly polished metal, reflective coatings (e.g., mirror elements), or reflective colors (e.g., white), significantly enhances treatment efficiency by redirecting EMR back to the hair. Double-Sided Treatment (220): EMR elements are incorporated on both sides of the device, maximizing treatment potential and ensuring comprehensive coverage.

[0127]

[0116] A safety feature=either electronic, such as a sensor, or mechanical=is embedded to ensure that EMR projection is activated only when the device is in a closed position, effectively safeguarding the user's eyes and skin. V ersatile Application: These configurations are suitable for both clamping hair (e.g., using tong-like instruments) and applying tension through pulling actions (e.g., during combing). Comprehensive Sensor Integration (Figures 7A-7F): The device is equipped with an array of advanced sensors to enhance both operation and user safety7. Color Detection Sensors: Optical sensors accurately detect the hair's color, providing crucial data to the controller. This enables precise determination of complementary colors and subsequent adjustment of EMR intensity and wavelength for targeted treatment. These sensors can be integrated directly into the device or function externally, such as via a smartphone camera app. Temperature Sensors: These sensors continuously measure the hair's temperature, feeding data to the controller to dynamically adjust treatment parameters such as EMR. intensity, duration, and wavelength range. Safety- Critical Sensors: Proximity Sensors: Detect when the device is in proper contact with the hair, activating the EMR source only when engagement is confirmed. Pressure Sensors: Sense when the device is pressed against the hair or is in a closed, clamping state, triggering EMR activation. Movement / Speed Sensors: Monitor the device’s movement over time. If the device remains static for too long, these sensors trigger an alert to the user and can automatically reduce or deactivate EMR to prevent hair burning. They can also inform the controller to adjust EMR intensity or pulse length based on the speed of movement. Multi-Sensor Fusion: The device can integrate any combination of these sensors. For example, a combination of color detection and movement sensors can intelligently reduce EMR output if the user halts movement, proactively preventing damage.

[0128]

[0117] In some embodiments, the technology is adaptable to various hair styling tools. Straight Hairbrush (Figure 7 A): This intelligent brush features bristles, an integrated EMR element, and multiple sensors. It may also include a focusing arrangement to direct EMR precisely onto the hair. Round Hairbrush (Figure 7B): A round brush design incorporates bristles, multiple EMR elements distributed across its surface, and an array of sensors for comprehensive treatment.

[0129]

[0118] Straight Hairbrush with Textured Bristles (Figure 7C): In this embodiment, the bristles themselves are textured or patterned with dark-colored materials, enabling them to absorb EMR and contribute directly to the heating process. Straight Hairbrush with Curved Bristles (Figure 7D): This design features flat, wide, and curved (e.g., zigzag, “Z”- or

[0130]

[0131] or "S"-shaped) bristles. While allowing for normal combing, their curved form acts as a shade, preventing EMR from escaping and blinding the user. Flat Hair Straightener (Figures 7E and 7F): This device comprises two plates designed to hold and apply physical pressure to hair. EMR elements are mounted on one or both plates, complemented by integrated sensors (e.g., pressure, color, movement). In some embodiments, traditional heating elements (e.g., ceramic) may also be included alongside the EMR elements for hybrid heating.

[0132]

[0119] Method of Hair Treatment (Figure 8): The method for treating hair, according to certain embodiments, encompasses a series of intelligent steps. EMR Element Provision: A hair treatment element configured for UV, VL, and IR irradiation is provided. Hair Engagement: The hair treatment element is brought into contact with the hair to be treated. Optional Engagement Detection: Safety sensors (proximity, pressure, movement) can optionally detect and confirm engagement. EMR Activation and Selective Irradiation: The hair treatment element is activated, and hair is selectively irradiated with one or more EMR ranges (UV, VL, IR, or combinations). Optional Hair Color Detection: Sensors can optionally detect the hair's color. Complementary Color Irradiation: EMR corresponding to the complementary hair color(s) is applied. Optional Monitoring: Sensors can optionally monitor the hair's temperature and / or the treatment duration. Adaptive Treatment Adjustment: Treatment parameters are continuously or discretely determined and adjusted in real time based on sensor feedback.

[0133]

[0120] While the patent introduces advanced integrations and Al control, many components are sourced from established manufacturers. EMR sources such as UV, visible, and IR LEDs are produced by companies like Osram Opto Semiconductors, Lumileds, and Nichia, while halogen and xenon lamps are available from Philips and Ushio. Sensor technologies include color sensors from ams OSRAM, temperature sensors from Analog Devices, Texas Instruments, and Maxim Integrated, and motion or proximity sensors from STMicroelectronics and Bosch Sensortec. Humidify sensors are supplied by Sensirion and Honeywell, and miniaturized NIR spectrometers by Spectral Engines and Hamamatsu enable detailed hair analysis. Low thermal mass materials such as Teflon (DuPont), PEEK (Victrex, Solvay), and ULTEM (SABIC) ensure efficient heat management. Control systems use microcontrollers and DSPs from Microchip, STMicroelectronics, and Texas Instruments, while cloud-based Al training and data storage rely on platforms such as AWS, Microsoft Azure, and Google Cloud.

[0134] This detailed description highlights how the invention integrates advanced EMR technology, sophisticated sensing, and intelligent control into a cohesive system for superior hair treatment.

[0135] Adaptive Multi-Sensor Fusion System

[0136]

[0121] In one embodiment, the hair treatment device comprises a multi-sensor fusion system configured to collect and process data from a plurality of sensors in real time. The sensors include, but are not limited to, color, temperature, motion, humidity, proximity, pressure, reflectivity, conductivity, vibration, infrared, and spectroscopic sensors. Each sensor provides a unique data stream representing a physical or optical property of the hair or the surrounding environment.

[0122] The controller integrates these data streams using a sensor fusion algorithm that applies weighted averaging, Kalman filtering, or neural network-based data correlation to derive a unified representation of the hair’s condition. This unified data model allows the controller to determine the hair’s instantaneous moisture content, color, density, and temperature distribution.

[0137]

[0123] The fusion system is further configured to detect anomalies such as uneven heating, excessive dryness, or localized overheating and to adjust EMR emission parameters accordingly. The system continuously recalibrates itself based on historical data and environmental conditions, ensuring consistent performance across different users and hair types.

[0138] AI-Driven Predictive Control and Machine Learning Integration

[0139]

[0124] In another embodiment, the controller includes a machine learning module trained on a dataset comprising thousands of hair treatment profiles. The dataset includes variables such as hair color, thickness, humidity, treatment duration, and EMR intensity.

[0140]

[0125] The Al model employs supervised and reinforcement learning techniques to predict optimal EMR parameters for each user. During operation, the Al model receives real-time sensor data and compares it to stored patterns to determine the most effective combination of wavelength, intensity, and pulse frequency.

[0141]

[0126] The predictive control system operates in a closed-loop configuration, where the Al continuously refines its predictions based on feedback from the sensors. This enables the device to anticipate changes in hair response before they occur, preventing damage and optimizing energy efficiency. The Al module may reside locally within the device or remotely on a cloud server. In cloud-based implementations, the Al model is periodically updated through federated learning, ensuring that user data remains private while contributing to global model improvement.

[0142] Phase-Controlled Multi-Band EMR Emission

[0143]

[0127] In a further embodiment, the EMR source comprises multiple emitters configured to generate ultraviolet (UV), visible light (VL), and infrared (IR) radiation simultaneously. Each emitter is independently controllable and phase-synchronized to ensure uniform energy distribution across the hair surface.

[0144]

[0128] The phase control mechanism utilizes a digital signal processor (DSP) that modulates the timing and amplitude of each wavelength band. This synchronization minimizes interference and ensures that the combined EMR field produces consistent heating without hotspots.

[0145] The multi-band emission system can dynamically shift the phase relationship between UV, VL, and IR components to target specific hair characteristics. For example, UV and IR may be phase- aligned for rapid moisture evaporation, while VL is phase-shifted to enhance surface smoothing. Nanostructured EMR-Selective Coatings

[0146] In one embodiment, the EMR-transmissive surfaces of the device are coated with nanostructured materials designed to selectively absorb or reflect specific wavelengths. The coating may comprise metallic nanoparticles, dielectric multilayers, or photonic crystals engineered to exhibit wavelength-dependent optical properties.

[0147]

[0129] The nanostructured coating enhances energy efficiency by reflecting non-essential wavelengths and concentrating the desired spectral bands onto the hair. The coating may also exhibit thermochromic behavior, automatically adjusting its reflectivity based on temperature to prevent overheating.

[0148] In some embodiments, the coating is applied to flexible polymer substrates, allowing the EMR window to conform to the curvature of the hairbrush or straightener plates. The coating may further include self-cleaning and anti-oxidation layers to maintain optical transparency and durability over extended use.

[0149] Modular EMR Architecture

[0150]

[0130] In another embodiment, the device includes a modular EMR architecture comprising detachable EMR modules. Each module is optimized for a specific hair type or treatment mode (e.g., straightening, curling, volumizing, or conditioning).

[0151]

[0131] The modules are magnetically attachable to the main housing and include embedded microcontrollers for independent operation. Upon attachment, the main controller automatically recognizes the module type and loads the corresponding control parameters.

[0152] Each module may include a unique optical filter or nanostructured coating to tailor the emitted wavelength spectrum. This modularity allows users to easily switch between treatment modes without replacing the entire device.

[0153] Adaptive Hairbrush Implementation

[0154]

[0132] In one embodiment, the invention is implemented in the form of an intelligent hairbrush. The hairbrush includes a handle, a bristle base, and a plurality of bristles configured to engage the hair.

[0155]

[0133] The bristles are partially transparent and act as light guides, channeling EMR from embedded emitters within the bristle base to the hair strands. Some bristles are coated with nanostructured materials to selectively absorb or reflect specific wavelengths, enhancing localized heating control.

[0134] The brush integrates multiple sensors within the bristle base, including temperature, color, and motion sensors. These sensors provide real-time feedback to the controller, which adjusts EMR emission intensity and wavelength based on detected hair properties.

[0156]

[0135] The hairbrush may also include a wireless communication module that connects to a mobile application or cloud platform for calibration, data logging, and personalized treatment recommendations.

[0157] Cloud-Based Adaptive Calibration and Learning System

[0158]

[0136] In another embodiment, the device is connected to a cloud-based platform that stores user profiles, treatment histories, and performance data. The platform analyzes aggregated data from multiple users to refine the Al model and improve predictive accuracy.

[0159]

[0137] The cloud system employs federated learning, enabling distributed Al training without transmitting raw user data. Each device trains a local model on user-specific data and uploads only the model updates to the cloud, preserving privacy.

[0160]

[0138] The cloud platform provides real-time feedback to the device during operation, suggesting parameter adjustments based on environmental conditions such as humidity and temperature.

[0161]

[0139] The system also supports multi-device synchronization, allowing users to share treatment profiles across different devices (e.g., hairbrush, straightener, or curler).

[0162] Predictive Safety and Energy Optimization

[0163]

[0140] The device includes a predictive safety subsystem that monitors temperature, motion, and contact pressure to prevent overheating or misuse. The subsystem uses predictive analytics to anticipate unsafe conditions and automatically deactivate the EMR source before damage occurs.

[0141] An active energy management system dynamically adjusts EMR output based on hair reflectivity and absorption feedback, minimizing energy waste. The system ensures that only the necessary amount of energy is delivered to achieve the desired treatment outcome.

[0164] Integrated Photonic-Thermal Substrate

[0165]

[0142] In some embodiments, the EMR emitters and thermal management components are integrated into a single photonic-thermal substrate. This substrate combines optical emission and heat dissipation functionalities, reducing component count and improving thermal efficiency.

[0166]

[0143] The substrate may include microchannels for fluid cooling or embedded thermoelectric elements for active temperature regulation. The integration of photonic and thermal layers ensures consistent performance even during prolonged operation. Method of Operation

[0167]

[0144] The method of operation of the device includes the following steps: (a) Detecting hair characteristics using the multi-sensor fusion system; (b) Predicting optimal EMR parameters using the Al-based predictive model; (c) Emitting multi-band EMR with dynamically modulated intensity, wavelength, and phase; (d) Adjusting treatment parameters in real time based on sensor feedback; and (e) Storing treatment data for adaptive learning and future optimization.

[0145] The method further includes transmitting treatment data to the cloud platform for analysis and model updating. The updated model parameters are periodically downloaded to the device, enabling offline operation with the latest Al improvements.

[0168] Advantages of the Current Technology

[0169]

[0146] The embodiments described herein provide several technical advantages over prior art, including:

[0170] Real-time adaptive control of EMR emission based on multi-sensor feedback; Predictive Al algorithms that prevent overheating and optimize energy efficiency; Modular architecture allowing user customization; Nanostructured coatings for wavelength-selective energy management;

[0171]

[0147] Cloud-based learning for continuous improvement; and Integration of photonic and thermal systems for compact, efficient design. Collectively, these embodiments establish a comprehensive, intelligent, and adaptive hair treatment ecosystem that delivers personalized, safe, and efficient results across diverse hair types and environmental conditions.

[0172]

[0148] The Core Intelligent Adaptive EMR Control Device

[0173]

[0149] In one embodiment, the hair treatment device functions as a standalone intelligent system that integrates adaptive electromagnetic radiation (EMR) control with real-time sensor feedback and machine learning. The device includes an EMR source capable of emitting across ultraviolet (UV), visible light (VL), and infrared (IR) ranges. Multiple discrete emitters-such as UV LEDs, RGB LED matrices, and IR diodes-allow precise modulation of wavelength, intensity, and pulse phase to target specific hair characteristics.

[0174]

[0150] A comprehensive sensor array captures real-time data on hair and environmental conditions, including color, temperature, motion, humidity, proximity, pressure, reflectivity, and conductivity. These sensors collectively generate a detailed hair profile reflecting color, thickness, moisture, and structural integrity.

[0175]

[0151] A central controller equipped with Al acceleration hardware fuses sensor data using advanced algorithms (e.g., Kalman filtering, Bayesian inference, or deep learning) to create a unified, dynamic hair model. A machine learning module, trained on extensive datasets of hair types and treatment outcomes, predicts optimal EMR parameters-intensity, wavelength, and pulse timing- tailored to each user's hair condition.

[0176]

[0152] Operating in a closed-loop feedback system, the controller continuously refines EMR output in real time, ensuring uniform, safe, and personalized hair treatment while preventing overheating or under-treatment.

[0177]

[0153] In a primary embodiment, the hair treatment device is configured as a standalone unit that embodies the core principles of intelligent adaptive EMR control. This device comprises:

[0178]

[0154] The hair treatment device integrates an advanced electromagnetic radiation (EMR) system designed to emit across ultraviolet (UV), visible light (VL), and infrared (IR) ranges. It employs multiple discrete emitters-such as high-power UV LEDs, RGB LED matrices, and IR diodesallowing precise control of wavelength, intensity, and pulse phase. Each spectral band can be independently modulated to achieve targeted heating and treatment effects.

[0179]

[0155] A comprehensive sensor array captures real-time data on hair and environmental conditions. Core sensors include color, temperature, and motion sensors, while optional modules measure humidity, proximity, pressure, reflectivity, conductivity, and vibration. Additional infrared and spectroscopic sensors may analyze absorption and chemical composition. Together, these sensors generate a detailed, dynamic profile of the hair's condition, enabling precise feedback during treatment.

[0180]

[0156] A central intelligent controller, equipped with Al acceleration hardware, processes sensor data and orchestrates EMR output. It performs data fusion, machine learning prediction, and real-time control to ensure optimal performance.

[0181]

[0157] Using advanced algorithms such as Kalman filtering, Bayesian inference, or deep learning, the controller fuses sensor data into a unified hair profile describing color, thickness, moisture, temperature, and structural integrity.

[0182]

[0158] A machine learning model, trained on extensive datasets of hair types and treatment outcomes, predicts individualized EMR parameters-intensity, wavelength, and pulse timing-tailored to each user's hair condition.

[0183]

[0159] Operating in a closed-loop feedback system, the controller continuously refines EMR output based on live sensor input. This dynamic adjustment ensures uniform, safe, and personalized treatment, preventing overheating or under-treatment while maintaining consistent results.

[0184] Nanostructured EMR-Transmissive Surfaces

[0160] In this embodiment, the hair treatment device integrates advanced electromagnetic radiation (EMR)-transmissive surfaces designed to enhance precision, efficiency, and control of EMR delivery. The device includes at least one EMR source capable of emitting UV, visible light (VL), and infrared (IR) radiation, with adjustable intensity and wavelength.

[0185]

[0161] EMR Source: As in Embodiment 1, the device includes at least one EMR source configured to emit radiation in UV, VL, and IR ranges. This source is controllable in terms of intensity and wavelength.

[0186]

[0162] A key feature is an EMR- transmissive surface positioned between the EMR source and the hair- such as a plate, window, or bristle-coated with a nanostructured material. This coating, composed of plasmonic nanoparticles, dielectric metamaterials, or photonic crystals, enables selective absorption, reflection, and transmission of specific wavelengths.

[0187]

[0163] The coating dynamically manages EMR interaction, either passively through inherent material properties or actively via thermochromic or electro-optic effects. It selectively transmits beneficial wavelengths to the hair, absorbs others to generate gentle convective heat, and reflects unwanted radiation to prevent overheating.

[0188]

[0164] This selective control ensures uniform heating, minimizes hot and cold spots, and enhances energy efficiency by directing only the necessary wavelengths toward the hair.

[0189]

[0165] Reduced Energy Consumption: By selectively reflecting non-essential wavelengths and efficiently directing the required energy, the coating significantly reduces overall energy consumption compared to conventional methods. This goes beyond the capabilities of traditional pigmented materials or simple low thermal mass materials, which offer less precise spectral control and dynamic adaptability.

[0190]

[0166] A controller, informed by real-time sensor data such as temperature, color, and reflectivity, continuously adjusts EMR emission to maintain optimal interaction between the nanostructured surface and the hair.

[0191]

[0167] This embodimentintroduces a modular hair treatment device that offers exceptional versatility and user customization. The main housing contains the power supply, central processor, and user interface, serving as the system's core. Multiple detachable EMR modules connect seamlessly to the housing via magnetic or quick-release mechanisms. Each self-contained module features its own EMR source capable of emitting UV, visible, and infrared radiation. Modules are specifically optimized for distinct hair types, colors, or treatment modes=such as conditioning, volumizing, or straightening=based on pre-programmed or machine-learning-derived parameters. The intelligent controller automatically recognizes each attached module using identifiers such as RFID tags, electrical signatures, or optical codes. Upon recognition, it adjusts EMR parameters, including intensity, wavelength, and pulse phase, to match the module's configuration. This modular and adaptive design allows users to efficiently personalize treatments, achieving professional results with a single, reconfigurable device.

[0192]

[0168] The device features a compact main housing that contains the power supply, central processor, and user interface, serving as the system's core. Attached to the housing are multiple detachable EMR modules, each equipped with its own UV, visible, and infrared light sources. These modules connect easily via magnetic or quick-release mechanisms and are individually optimized for specific hair types, colors, or treatment modes-such as conditioning, volumizing, or straighteningbased on pre-programmed or machine-learning-derived parameters. An intelligent controller automatically identifies each module through RFID tags, electrical signatures, or optical codes and adjusts EMR parameters, including intensity, wavelength, and pulse phase, to match the module's configuration. This modular and adaptive design allows users to personalize treatments efficiently, achieving professional, safe, and consistent results with a single, reconfigurable device.

[0169] Plurality of Detachable EMR Modules: A key feature is a plurality of detachable EMR modules.

[0193] Each module is a self-contained unit that includes its own EMR source(s) capable of emitting UV, VL, and IR radiation. These modules are designed for easy attachment and detachment from the main housing (e.g., via magnetic connectors, quick-release latches, or electrical contacts).

[0194]

[0170] Optimized for Specific Conditions: Each individual EMR module is specifically optimized for a distinct hair type (e.g., a module for fine, delicate hair; another for thick, coarse hair), hair color (e.g., a module pre-calibrated for dark hair, another for blonde hair), or a particular treatment mode (e.g., a module for deep conditioning, one for volumizing, another for intense straightening, or a module for specific hair health treatments). This optimization is based on pre-programmed parameters stored within the module or, more advanced, on machine learning-derived parameters that have been pre-loaded or are accessible.

[0195]

[0171] Intelligent Controller for Module Recognition and Parameter Adjustment: The device's controller is configured to automatically recognize an attached EMR module. This recognition can occur through various means, such as RFID tags embedded in the modules, unique electrical signatures, or optical codes. Upon recognition, the controller dynamically adjusts its EMR emission parameters (intensity, wavelength, pulse phase) to align with the specific optimization of the recognized module. This seamless integration provides a highly user-configurable and adaptable treatment system, allowing users to effortlessly swap modules to match their current hair needs or desired styling outcomes without needing multiple, dedicated devices.

[0196] The Adaptive EMR Hairbrush forming

[0197]

[0172] This embodiment integrates the advanced adaptive EMR technology into the familiar and ergonomic form factor of a hairbrush, providing precise treatment during the act of brushing.

[0198]

[0173] Hairbrush Structure: The device is specifically configured as a hairbrush, comprising a handle for ergonomic grip and a bristle base from which a plurality of bristles extend.

[0199]

[0174] Bristles for Hair Engagement: The bristles are designed to effectively engage, detangle, and separate hair strands, similar to a conventional hairbrush.

[0200]

[0175] Integrated EMR Source: At least one EMR source, capable of emitting UV, VL, and IR radiation, is seamlessly integrated within the bristle base. This strategic placement ensures that EMR is delivered directly to the hair as it passes through the bristles.

[0201]

[0176] Embedded Multi-Sensors: Two or more sensors are embedded directly within the brush structure, particularly within or adjacent to the bristles. These sensors are selected from the comprehensive group (color, temperature, motion, humidity, proximity, pressure, reflectivity, conductivity, vibration, infrared, spectroscopic) and are positioned to generate real-time data indicative of hair characteristics and treatment conditions within the bristles' immediate engagement area. This provides highly localized and contextualized data.

[0202]

[0177] Intelligent Controller with Fusion and Machine Learning: A controller, integrated within the brush, receives and intelligently fuses the real-time data from the embedded sensors. It employs a machine learning algorithm, trained on diverse hair profiles, to predict highly individualized optimal EMR parameters (intensity, wavelength, and phase of individual pulses) specifically for the hair strands currently engaged by the bristles.

[0203]

[0178] Dynamic EMR Adjustment: The controller dynamically adjusts the intensity, wavelength, and phase of individual pulses of the integrated EMR source in real time. This adjustment is continuously refined based on the predicted optimal parameters and the fused real-time sensor data, operating in a closed-loop feedback system. This ensures unprecedented precision in personalized, uniform, and damage-preventing hair treatment delivered directly through the brushing action, adapting to each stroke and section of hair. The Cloud-Based Adaptive Learning System

[0204]

[0179] This embodiment describes a comprehensive system that extends the device's intelligence beyond its physical confines, leveraging cloud computing for continuous learning and optimization.

[0205]

[0180] Hair Treatment Device (as per Claim 42): The system includes a hair treatment device as described in Embodiment 1 (Claim 42), which is capable of intelligent adaptive EMR control, multi-sensor fusion, and machine learning-driven parameter prediction. This device is equipped with wireless communication capabilities (e.g., Wi-Fi, Bluetooth, cellular).

[0206]

[0181] Remote Computing Platform (Cloud Platform) : The system further comprises a remote computing platform, typically a cloud-based server infrastructure. This platform is configured to interact with the hair treatment device.

[0207]

[0182] Data Reception and Analysis: The remote platform receives user-specific data from the device.

[0208] This data includes hair characteristics (e.g., color, density, moisture level) and detailed treatment performance data (e.g., EMR parameters applied, temperature profiles achieved, duration of treatment, and potentially user-reported satisfaction). The platform analyzes this aggregated data using advanced analytics and machine learning techniques to identify patterns, correlations, and areas for improvement in the treatment algorithms.

[0209]

[0183] Continuous ML Algorithm Update and Adaptive Calibration: The primary function of the remote platform is to continuously update the device’s machine learning algorithm. This is achieved through cloud-based adaptive calibration, where the platform refines the ML model based on the aggregated data.

[0210]

[0184] Example: If the platform identifies that a particular hair type consistently responds better to a slightly different EMR pulse phase than initially predicted, the ML model is updated.

[0211]

[0185] Federated Learning: To enhance data privacy, the platform may employ federated learning, where individual devices train local models on user data, and only model updates (not raw data) are sent to the cloud for aggregation and global model improvement.

[0212]

[0186] Ongoing Optimization: This continuous learning and update cycle enables ongoing optimization of future hair treatments. The refined ML models are then pushed back to the device (e.g., via firmware updates), making the device progressively smarter, more accurate, and more effective for both individual users and the entire user base over time.

[0213] Method for AI-Driven Adaptive EMR Treatment

[0187] This embodiment describes the operational methodology underlying the intelligent hair treatment system, detailing the sequence of steps performed by the device.

[0214]

[0188] Step 1: Detecting Hair Characteristics: The method begins by detecting hair characteristics using two or more sensors (e.g., color, temperature, motion, humidity, proximity, pressure, reflectivity, conductivity, vibration, infrared, or spectroscopic sensors). These sensors continuously gather real-time data about the hair's physical and optical properties.

[0215]

[0189] Step 2: Intelligent Fusion of Real-Time Data: The real-time data from multiple sensors is then intelligently fused. This fusion process, which may utilize advanced algorithms such as Kalman filters or neural networks, generates a comprehensive hair profile that provides a holistic and dynamic understanding of the hair's current state and its response to treatment.

[0216]

[0190] Step 3: Predicting Highly Individualized Optimal EMR Parameters: A machine learning model, extensively trained on diverse hair profiles and treatment outcomes, utilizes this comprehensive hair profile to predict highly individualized optimal EMR parameters. These parameters include the precise intensity, specific wavelength composition, and exact phase of individual EMR pulses, tailored to the user's specific hair characteristics at that moment.

[0217]

[0191] Step 4: Emitting Dynamically Modulated Multi-Band EMR: Multi-band EMR (UV, VL, IR) is then emitted by the EMR source. This emission is dynamically modulated in terms of intensity, wavelength, and phase of individual pulses, all based on the predicted optimal EMR parameters.

[0218]

[0192] Step 5: Continuous Adjustment in a Closed-Loop System: The EMR emission operates dynamically, continuously adapting in real time based on sensor feedback within a closed-loop control system. The system constantly monitors the hair's response to EMR exposure, updates the hair profile, re-predicts optimal treatment parameters, and adjusts EMR output accordingly. This continuous and adaptive process ensures exceptional precision, uniformity, and safety, maintaining optimal personalization and preventing damage throughout the entire hair treatment session.

[0219] Hair Treatment Device with Hybrid Heating and Specialized EMR-Interactive Bristles

[0193] A hair treatment device comprising a handle and a bristle base;a plurality of bristles extending from the bristle base, configured to engage hair, wherein at least some of the bristles are either: textured or patterned with dark-colored materials to absorb electromagnetic radiation (EMR) and contribute directly to a heating process; or flat, wide, and curved in a zigzag, "Z", or "S"-shape to prevent EMR from escaping and blinding a user; at least one EMR source integrated within the device, configured to emit radiation in one or more wavelength ranges including ultraviolet (UV), visible light (VL), and infrared (IR); and at least one traditional heating element, such as a ceramic element, configured to apply heat to the hair. The device is configured to apply heat to the hair through a combination of EMR from the EMR source and heat from the traditional heating element, and further through EMR absorption by the specialized bristles.

[0220]

[0194] The inclusion not intended to be limiting in any way. The scope of multiple withvisiblethe invention is defined solely by the appended claims, and infrarednot by the specific examples or descriptions provided. Modifications, equivalents, and variations of the invention, as will be apparent to those skilled in the art, are intended to be included within the scope of the claims. All references, publications, and patent applications cited in this document are incorporated by reference in the entirety, using mechanisms such asbut their citation does not constitute an admission that they are prior art to the present invention.

[0221]

[0195] While embodiments of the invention have been described in detail, it will be understood by those skilled in the art that various modifications, substitutions, and changes may be made without departing from the spirit and scope of the invention as defined by the appended claims. The terminology used herein is intended to describe particular embodiments only and is not intended to limit the scope of the invention. All publications, patents, and patent applications cited herein are incorporated by reference in their entirety for all purposes to the same extent as if each individual publication, patent, or patent application were specifically and individually indicated to be incorporated by reference.

Claims

CLAIMS1. A hair treatment device comprising:at least one electromagnetic radiation (EMR) source configured to emit radiation in one or more wavelength ranges including ultraviolet (UV), visible light (VL), and infrared (IR); two or more sensors selected from a group consisting of a color sensor, a temperature sensor, a motion sensor, a humidity sensor, a proximity sensor, a pressure sensor, a reflectivity sensor, a conductivity sensor, a vibration sensor, an infrared sensor, and a spectroscopic sensor, the sensors configured to generate real-time data indicative of hair characteristics and treatment conditions; anda controller configured to receive and intelligently fuse the real-time data from the at least two sensors, and to dynamically adjust the intensity, wavelength, and phase of individual pulses of the EMR source in real time;wherein the controller employs a machine learning algorithm trained on diverse hair profiles to predict highly individualized optimal treatment parameters for a user's specific hair characteristics, and wherein the dynamic adjustment is continuously refined based on the predicted optimal parameters and the fused real-time sensor data in a closed-loop feedback system, thereby providing unprecedented precision in personalized, uniform, and damage-preventing hair treatment.

2. The device of claim 1, wherein the controller is configured to operate in a closed-loop feedback mode to continuously optimize energy delivery.

3. The device of claim 1, wherein the controller communicates wirelessly with an external computing device or cloud platform for remote monitoring, adaptive model updates, and continuous refinement of the machine learning algorithm based on aggregated usage data.

4. A hair treatment device comprising at least one EMR-transmissive surface having a precisely engineered nanostructured coating, the coating configured to dynamically and selectively absorb or reflect specific EMR wavelengths with high spectral resolution, thereby enhancing heating uniformity and reducing energy consumption beyond conventional pigmented or low thermal mass materials.

5. The device of claim 4 wherein the nanostructured coating comprises metallic nanoparticles precisely tuned to specific EMR wavelength bands, the tuning being adaptable by the controller based on the predicted optimal treatment parameters.

6. The device of claim 4 wherein the nanostructured coating further provides self-cleaning and anti-oxidation properties, maintaining optical performance and durability.

7. A hair treatment device comprising a plurality of detachable EMR modules, each module configured to emit electromagnetic radiation specifically optimized for a distinct hair type, color, or treatment mode based on pre-programmed or machine learning-derived parameters, thereby providing a user-configurable and adaptable treatment system8. The device of claim 7, wherein each detachable EMR module includes an integrated microcontroller for independent operation, allowing for localized processing and fine-tuned EMR emission control specific to that module's optimization9. A hair treatment device comprising:a handle and a bristle base;a plurality of bristles configured to engage hair;at least one electromagnetic radiation (EMR) source integrated within the bristle base and configured to emit radiation in one or more wavelength ranges including ultraviolet (UV), visible light (VL), and infrared (IR);two or more sensors embedded within the brush, selected from a group consisting of a color sensor, a temperature sensor, a motion sensor, a humidity sensor, a proximity sensor, a pressure sensor, a reflectivity sensor, a conductivity sensor, a vibration sensor, an infrared sensor, and a spectroscopic sensor, the sensors configured to generate real-time data indicative of hair characteristics and treatment conditions within the bristles' engagement area; anda controller configured to receive and intelligently fuse the real-time data from the at least two sensors, and to dynamically adjust the intensity, wavelength, and phase of individual pulses of the EMR source in real time;wherein the controller employs a machine learning algorithm trained on diverse hair profiles to predict highly individualized optimal treatment parameters for the hair engaged by the bristles, thereby providing unprecedented precision in personalized, uniform, and damagepreventing hair treatment directly through the hairbrush.

10. The hair treatment device of claim 9, wherein at least some of the bristles are partially transparent to EMR and serve as light guides, directing the dynamically adjusted EMR precisely to individual hair strands engaged by the bristles.

11. A system comprising the hair treatment device of claim 1 and a remote computing platform configured to:receive user-specific data including hair color, density, and moisture level, and treatment performance data from the device;analyze the received data to identify patterns and correlations; andcontinuously update the device’s machine learning algorithm to refine the prediction of highly individualized optimal treatment parameters through cloud-based adaptive calibration, thereby enabling ongoing optimization of future hair treatments.

12. The system of claim 11, wherein the remote computing platform employs federated learning to enhance data privacy and improve the performance of the machine learning algorithm across a distributed network of devices.

13. A method for treating hair, comprising:detecting hair characteristics using two or more sensors selected from a group consisting of a color sensor, a temperature sensor, a motion sensor, a humidity sensor, a proximity sensor, a pressure sensor, a reflectivity sensor, a conductivity sensor, a vibration sensor, an infrared sensor, and a spectroscopic sensor;intelligently fusing real-time data from the two or more sensors to generate a comprehensive hair profile;predicting highly individualized optimal electromagnetic radiation (EMR) parameters, including intensity, wavelength, and phase of individual pulses, using a machine learning model trained on diverse hair profiles;emitting multi-band EMR with dynamically modulated intensity, wavelength, and phase of individual pulses, based on the predicted optimal EMR parameters; andcontinuously adjusting the EMR emission in real time based on sensor feedback in a closed- loop system to maintain unprecedented precision in personalized, uniform, and damagepreventing hair treatment.

14. The method of claim 13, further comprising storing treatment data, including hair characteristics and applied EMR parameters, for subsequent adaptive learning and refinement of the machine learning model.

15. The method of claim 13, wherein the updated machine learning model parameters are periodically downloaded to the hair treatment device for offline operation, ensuring continued intelligent and adaptive treatment even without constant network connectivity 16. A hair treatment device wherein at least one of the following is held true:a. the device comprises:i. at least one electromagnetic radiation (EMR) source configured to emit radiation in one or more wavelength ranges including ultraviolet (UV), visible light (VL), and infrared (IR);\ii. two or more sensors selected from a group consisting of a color sensor, a temperature sensor, a motion sensor, a humidity sensor, a proximity sensor, a pressure sensor, a reflectivity sensor, a conductivity sensor, a vibration sensor, an infrared sensor, and a spectroscopic sensor; andiii.a controller configured to receive input from the at least two sensors and to dynamically adjust the intensity, wavelength, and pulse phase of the EMR source in real time; the controller employs a machine learning algorithm trained to predict optimal treatment parameters for a user ’ s specific hair characteristics, thereby providing adaptive, uniform, and safe hair treatment;b. the device comprises:i. a handle and a bristle base;ii. a plurality of bristles configured to engage hair;iii. at least one EMR source integrated within the bristle base and configured to emit radiation in one or more wavelength ranges including UV, VL, and IR; and iv. a controller configured to adjust EMR emission based on input from one or more sensors embedded within the brush; andc. the device is operative in a method comprising:i. detecting hair characteristics using a plurality of sensors;ii. predicting optimal EMR parameters using a trained machine learning model; iii. emitting multi-band EMR with dynamically modulated intensity and phase; and iv. adjusting treatment parameters in real time based on sensor feedback to maintain uniform heating and prevent hair damage.

17. A hair treatment device wherein at least one of the following is held true:a. the device comprises:i. at least one electromagnetic radiation (EMR) source configured to emit radiation in one or more wavelength ranges including ultraviolet (UV), visible light (VL), and infrared (IR); andii. two or more sensors selected from a group consisting of a color sensor, a temperature sensor, a motion sensor, a humidity sensor, a proximity sensor, a pressure sensor, a reflectivity sensor, a conductivity sensor, a vibration sensor, an infrared sensor, and a spectroscopic sensor; andb. the device comprises:i. a controller configured to receive input from the at least two sensors and to dynamically adjust the intensity, wavelength, and pulse phase of the EMR source in real time; and ii. the controller employs a machine learning algorithm trained to predict optimal treatment parameters for a user’ s specific hair characteristics, thereby providing adaptive, uniform, and safe hair treatment.

18. A hair treatment device comprising:at least one electromagnetic radiation (EMR) source configured to emit radiation in one or more wavelength ranges including ultraviolet (UV), visible light (VL), and infrared (IR); a plurality of sensors, including at least a color sensor, a temperature sensor, and a motion sensor, the sensors configured to generate real-time data indicative of hair characteristics and treatment conditions; anda controller configured to:intelligently fuse the real-time data from the plurality of sensors to generate a comprehensive hair profile;employ a machine learning algorithm, trained on diverse hair profiles, to predict highly individualized optimal EMR parameters, including intensity, wavelength, and phase of individual pulses, for a user’s specific hair characteristics; anddynamically adjust the intensity, wavelength, and phase of individual pulses of the EMR source in real time, wherein the adjustment is continuously refined based on the predicted optimal EMR parameters and the fused real-time sensor data in a closed-loop feedback system, thereby providing unprecedented precision in personalized, uniform, and damagepreventing hair treatment.

19. A hair treatment device comprising:at least one electromagnetic radiation (EMR) source configured to emit radiation in one or more wavelength ranges including ultraviolet (UV), visible light (VL), and infrared (IR); at least one EMR-transmissive surface having a precisely engineered nanostructured coating, the coating configured to dynamically and selectively absorb or reflect specific EMR wavelengths with high spectral resolution; anda controller configured to adjust EMR emission based on input from one or more sensors, wherein the nanostructured coating enhances heating uniformity and reduces energy consumption beyond conventional pigmented or low thermal mass materials.

20. A hair treatment device comprising:a main housing;a plurality of detachable EMR modules, each module configured to emit electromagnetic radiation in one or more wavelength ranges including ultraviolet (UV), visible light (VL), and infrared (IR); anda controller configured to:automatically recognize an attached EMR module; andadjust EMR emission parameters for the recognized module;wherein each detachable EMR module is specifically optimized for a distinct hair type, color, or treatment mode based on pre-programmed or machine learning-derived parameters, thereby providing a user-configurable and adaptable treatment system.

21. A hair treatment device in the form of a hairbrush, comprising:a handle and a bristle base;a plurality of bristles configured to engage hair;at least one electromagnetic radiation (EMR) source integrated within the bristle base and configured to emit radiation in one or more wavelength ranges including ultraviolet (UV), visible light (VL), and infrared (IR);two or more sensors embedded within the brush, selected from a group consisting of a color sensor, a temperature sensor, a motion sensor, a humidity sensor, a proximity sensor, a pressure sensor, a reflectivity sensor, a conductivity sensor, a vibration sensor, an infrared sensor, and a spectroscopic sensor, the sensors configured to generate real-time dataindicative of hair characteristics and treatment conditions within the bristles' engagement area; anda controller configured to receive and intelligently fuse the real-time data from the at least two sensors, and to dynamically adjust the intensity, wavelength, and phase of individual pulses of the EMR source in real time;wherein the controller employs a machine learning algorithm trained on diverse hair profiles to predict highly individualized optimal treatment parameters for the hair engaged by the bristles, thereby providing unprecedented precision in personalized, uniform, and damage-preventing hair treatment directly through the hairbrush.

22. A hair treatment system comprising:a hair treatment device according to Claim 21; anda remote computing platform configured to:receive user-specific data including hair color, density, and moisture level, and treatment performance data from the device;analyze the received data to identify patterns and correlations; andcontinuously update the device’s machine learning algorithm to refine the prediction of highly individualized optimal treatment parameters through cloud-based adaptive calibration, thereby enabling ongoing optimization of future hair treatments.

23. A method for treating hair, comprising:detecting hair characteristics using two or more sensors selected from a group consisting of a color sensor, a temperature sensor, a motion sensor, a humidity sensor, a proximity sensor, a pressure sensor, a reflectivity sensor, a conductivity sensor, a vibration sensor, an infrared sensor, and a spectroscopic sensor;intelligently fusing real-time data from the two or more sensors to generate a comprehensive hair profile;predicting highly individualized optimal electromagnetic radiation (EMR) parameters, including intensity, wavelength, and phase of individual pulses, using a machine learning model trained on diverse hair profiles;emitting multi-band EMR with dynamically modulated intensity, wavelength, and phase of individual pulses, based on the predicted optimal EMR parameters; andcontinuously adjusting the EMR emission in real time based on sensor feedback in a closed-loop system to maintain unprecedented precision in personalized, uniform, and damage-preventing hair treatment.

24. A hair treatment device comprising:a handle and a bristle base;a plurality of bristles extending from the bristle base, configured to engage hair, wherein at least some of the bristles are either: textured or patterned with dark-colored materials to absorb electromagnetic radiation (EMR) and contribute directly to a heating process; or flat, wide, and curved in a zigzag, "Z", or "S"-shape to prevent EMR from escaping and blinding a user;at least one EMR source integrated within the device, configured to emit radiation in one or more wavelength ranges including ultraviolet (UV), visible light (VL), and infrared (IR); andat least one traditional heating element, such as a ceramic element, configured to apply heat to the hair;wherein the device is configured to apply heat to the hair through a combination of EMR from the EMR source and heat from the traditional heating element, and further through EMR absorption by the specialized bristles.

25. A hair treatment device comprising:a heating plate configured to generate heat for application to hair positioned adjacent thereto; a light and heat source disposed within or proximate to the heating plate, the light and heat source being configured to emit both light and heat toward the hair;a fan arranged to direct an airflow toward the heating plate and the light and heat source, thereby conveying heated air toward the hair;wherein the heat radiated from the light and heat source and conveyed by the airflow is below about 180°C, and wherein the combined action of the heating plate, the light and heat source, and the airflow provides a total heating effect exceeding about 180°C;such that the device achieves hair treatment through a synergistic combination of convection, radiation, and conduction, while reducing the required light intensity and minimizing the risk of over-illumination or eye exposure.

26. A method for treating hair using combined heat and light, comprising: positioning hair adjacent to a heating plate; activating a light and heat source disposed within or proximate to the heating plate to emit light and heat toward the hair; directing an airflow toward the heating plate and the light and heat source to convey heated air toward the hair; controlling the temperature of the heat radiated from the light and heat source and conveyed by the airflow to remain below about 180°C; and combining the heat generated by the heating plate with the heat and light emitted by the light and heat source to achieve a total heating effect exceeding about 180°C; wherein the combined use of convection, radiation, and conduction provides a controlled and personalized hair treatment according to the hair type and condition.

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