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CN-121971807-A - Multispectral AI artificial intelligence health physiotherapy cap

CN121971807ACN 121971807 ACN121971807 ACN 121971807ACN-121971807-A

Abstract

The invention discloses a multispectral AI artificial intelligence health physiotherapy cap, which relates to the technical field of health physiotherapy equipment, and comprises a cap body, a multispectral light source module and an AI controller, wherein the AI controller is configured to respond to a target mode selected by a user, drive the light source module to execute detection treatment for a predefined number of times, and each time adopt parameter combinations with obvious differences in phototherapy parameter space; and determining the optimal phototherapy parameter combination aiming at the current user according to the model and driving the execution. According to the invention, through active detection, reverse modeling and optimization calculation, personalized accurate treatment under the extremely simple hardware condition is realized, individual physiological differences are adapted, physiotherapy effectiveness and safety are improved, and user experience and product practicability are enhanced.

Inventors

  • LIU ZIHAN
  • ZHANG HEYE

Assignees

  • 脑全康(成都)医疗器械科技有限公司

Dates

Publication Date
20260505
Application Date
20260407

Claims (10)

  1. 1. The multispectral AI artificial intelligence health physiotherapy cap is characterized by comprising a cap body, a multispectral light source module arranged in the cap body and an AI controller arranged in the multispectral light source module; The AI controller is configured to: responding to a target mode selected by a user, driving the multispectral light source module to execute a predefined number of exploratory treatments, wherein each exploratory treatment adopts a group of parameter combinations with significant differences in phototherapy parameter space; after each detection treatment, acquiring curative effect feedback information of a user for the treatment; constructing a personalized response characteristic model based on the parameter combinations of all the exploratory treatments and the corresponding curative effect feedback information; determining an optimal combination of phototherapy parameters for the current user based on the personalized response characteristics model; And driving the multispectral light source module to execute the optimal phototherapy parameter combination.
  2. 2. The multispectral AI artificial intelligence health physiotherapy cap of claim 1, wherein the method of generating a combination of parameters of the exploratory treatment comprises: Defining a phototherapy parameter space according to the adjustable parameters of the multispectral light source module; Generating a plurality of groups of candidate parameter combinations in a preset safety boundary; Calculating a difference metric between the plurality of sets of candidate parameter combinations; And screening a preset number of parameter combinations which maximize the difference from the plurality of candidate parameter combinations according to the difference measurement, and taking the preset number of parameter combinations as parameter combinations of the exploratory treatment.
  3. 3. The multi-spectral AI artificial intelligence health physiotherapy cap of claim 2, wherein the calculated difference metric comprises at least one of: Calculating cosine dissimilarity between coordinate vectors of any two groups of candidate parameter combinations; calculating a standardized Euclidean distance between coordinate vectors of any two groups of candidate parameter combinations; The coordinate vector is determined from the position of the candidate parameter combination in the phototherapy parameter space.
  4. 4. The multi-spectral AI artificial intelligence health therapy cap of claim 1, wherein the obtaining user efficacy feedback information comprises: Providing a therapeutic effect evaluation interface related to the target mode to a user after the detected treatment is finished; Receiving treatment effect evaluation input by a user on the treatment effect evaluation interface; and quantifying the treatment effect evaluation into numerical feedback information.
  5. 5. The multi-spectral AI artificial intelligence health therapy cap of claim 4, wherein the therapy effect evaluation is a binary evaluation comprising a first state value indicative of a positive therapy effect and a second state value indicative of a non-positive therapy effect.
  6. 6. The multi-spectral AI artificial intelligence health physiotherapy cap of claim 1, wherein the constructing a personalized response characteristics model comprises: defining a response characteristic vector having dimensions identical to dimensions of the phototherapy parameter space, each component representing a response weight of a user to a respective phototherapy parameter; Establishing a probability model describing a relationship between a probability that the exploratory therapy produces a specific efficacy feedback and a response characteristic vector; Solving a maximum posterior probability estimate of the response characteristic vector based on data of all the exploratory treatments; and determining the vector obtained by solving as a personalized response characteristic model.
  7. 7. The multi-spectral AI artificial intelligence health physiotherapy cap of claim 6, wherein the constructing a personalized response characteristics model further comprises: setting an independent hyper-parameter for each component of the response characteristic vector; Iteratively optimizing the hyper-parameters based on the detected treatment data; And calculating posterior distribution statistics of the response characteristic vector according to the optimized hyper-parameters.
  8. 8. The multi-spectral AI artificial intelligence health physiotherapy cap of claim 1, wherein the determining an optimal combination of phototherapy parameters comprises: representing the personalized response characteristic model as a weight vector; Constructing an optimization problem, wherein an objective function of the optimization problem comprises a correlation measure of a phototherapy parameter vector and the weight vector; solving the optimization problem under a preset constraint condition to obtain an optimal phototherapy parameter combination; Wherein the constraints include safety boundaries and comfort boundaries for each phototherapy parameter.
  9. 9. The multispectral AI artificial intelligence health therapy cap of claim 1, wherein the AI controller is further configured to: Respectively constructing independent personalized response characteristic models for a plurality of different target modes; based on the personalized response characteristic model of each target mode, generating a corresponding personalized optimal parameter combination; According to preset course logic, the personalized optimal parameter combinations of a plurality of target modes are arranged into a composite treatment program according to time sequences; the composite treatment procedure is performed.
  10. 10. The multi-spectral AI artificial intelligence health therapy cap of claim 9, wherein the course logic includes at least one of the following arrangements: executing personalized optimal parameter combination of each target mode according to a fixed sequence and a fixed duration; based on the historical curative effect feedback information of each target mode, dynamically adjusting the execution sequence and the execution duration of each target mode in the composite treatment program; The personalized optimal parameter combination of the partial target modes is selectively executed according to the real-time state or preference of the user.

Description

Multispectral AI artificial intelligence health physiotherapy cap Technical Field The invention relates to the technical field of health physiotherapy equipment, in particular to a multispectral AI artificial intelligence health physiotherapy cap. Background In modern life, the hair health problem and the sub-health problem of the mind and body are increasingly prominent, and become important factors affecting the life quality of people. Hair health problems are often manifested by alopecia, poor hair quality, scalp itching, unbalanced fat secretion and the like, the causes of which are closely related to hair follicle activity decline, scalp microcirculation unsmooth, bacterial breeding and the like, while physical and mental sub-health problems are often related to factors such as migraine, insomnia and the like, such as nerve regulation disorder, local blood circulation abnormality, physical and mental pressure accumulation and the like. In order to meet the requirements of people on convenient and efficient health care, the multispectral health physiotherapy equipment is gradually and widely applied to the intervention of the health problems by virtue of the advantages of non-invasiveness, convenience in home use and the like. The device integrates spectrum resources with different wavelengths such as red light, blue light, infrared light and the like, and utilizes the biological stimulation effect of phototherapy to respectively realize the diversified physiotherapy targets of stimulating hair follicle growth, improving scalp environment, relieving nervous tension, regulating sleep rhythm and the like. Currently, the multispectral physiotherapy equipment on the market comprises physiotherapy hat products, a plurality of preset fixed treatment programs are usually built in, each program corresponds to a group of fixed phototherapy parameter combinations, core parameters including light source wavelength, irradiation intensity, working mode, treatment duration and the like are covered, and after a user selects a corresponding mode according to own needs, the equipment mechanically executes the preset parameters to complete a standardized physiotherapy process. Part of the products are used for covering more use scenes, the number of fixed modes is tried to be increased, or a limited manual parameter adjusting function is provided, so that the application range of the products is improved. However, the conventional multispectral physiotherapy equipment has a plurality of key technical defects in practical application, and is difficult to meet personalized and accurate physiotherapy requirements of different users. First, the core control logic of the existing device is in a preset calling mode, and the design core is assumed to be that all users have consistency on the physiological responses of the same phototherapy parameter combination, but in reality, the physiological characteristics of different individuals have significant differences. In the hair care scene, the hair follicle state, scalp sensitivity and metabolism level of the user are different, in the migraine intervention scene, the pain trigger mechanism and nerve sensitivity of the user are different, and in the sleep-aiding scene, the sleep disorder type and physical and mental state of the user are also different. Such individual differences result in the possibility that the same fixation procedure may be significant for some users and even of little effect for other users, even with adverse effects such as scalp irritation and nerve discomfort caused by parameter discomfort. In addition, the manual parameter adjusting function brings higher requirements to the professional knowledge of the user, and the common user lacks knowledge of the matching relation between the phototherapy parameters and the health conditions of the user, so that the adjusting process is blindly and inefficient, the accurate physiotherapy cannot be realized, and the use safety is possibly influenced due to improper parameter setting. Finally, the existing equipment lacks an intelligent mechanism for actively exploring individual adaptive parameters of a user, cannot dynamically optimize parameter combinations according to actual physiotherapy feedback of the user, can only rely on repeated attempts of subjective experience of the user or experience guidance of medical staff, is difficult to form a closed-loop personalized physiotherapy scheme, cannot realize continuous optimization of physiotherapy effects no matter hair health care, migraine relief or insomnia improvement, and severely restricts the application value of multispectral physiotherapy technology. Disclosure of Invention Aiming at the defects in the prior art, the invention provides a multispectral AI artificial intelligence health physiotherapy cap, which solves the problems that the existing multispectral physiotherapy equipment cannot automatically adapt to individual differences and has uneven phy