Wearable anti-hair-loss hair growth and hair growth monitoring device and system based on low-power ultrasound

Abstract

The invention discloses a wearable anti-hair-loss hair growth monitoring device and system based on low-power ultrasound, and relates to the technical field of hair growth monitoring and treatment. Comprising an individual structure sensing and modeling module used for collecting ultrasonic monitoring data in real time and carrying out data preprocessing; evaluating the thickness of a fat layer and the thickness of a skin layer, and constructing a curvature estimation model; the sound field simulation and sound intensity prediction module is used for judging the local ultrasonic sound intensity of the hair follicle layer, performing graded ultrasonic regulation and control and calculating a sound intensity correction factor; the individualized self-adaptive regulation and control module is used for updating sound wave transmitting power, collecting temperature data in real time and evaluating local temperature rise safety; and the monitoring feedback and system self-learning module is used for carrying out scalp state analysis feedback and realizing algorithm and threshold optimization. The problem that safe and effective transmitting power cannot be uniformly preset due to the fact that the sound intensity of the same ultrasonic power in a hair follicle layer is too high or insufficient due to the fact that the scalp thickness, fat layer and bone surface curvature difference of different users is large is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of hair growth monitoring and treatment, in particular to a wearable anti-hair loss and hair growth monitoring device and system based on low-power ultrasound. BACKGROUND

[0002] Currently, under the background of the rapid development of precision medicine and personalized health care, wearable medical devices are gradually evolving from simple monitoring functions to integrated and intelligent treatment and intervention. Ultrasound technology is widely used in tissue stimulation and regenerative medicine due to its non-invasive, high tissue penetration, and controllable focusing characteristics, and it has shown high research and clinical potential in hair follicle activation and scalp microcirculation improvement. At the same time, the progress of sensor technology, miniaturized acoustic devices, low-power signal processing chips, and edge computing algorithms provides conditions for achieving high-precision acoustic measurement and real-time adaptive control in a portable and wearable form.

[0003] For example, the invention patent with the announcement number CN110037911B announced an anti-hair loss hair massager, which includes a brim (100) and a cap body (200). The inner surface of the brim (100) is provided with a first massage part (110), which presses the user's forehead meridian in a horizontal motion trajectory. The cap body (200) is shaped as a hemispherical cover, and its inner surface is provided with a filling layer (210) in which a plurality of second massage parts (220) are embedded. The second massage parts (220) are used to hit the user's vertex meridian in an arc trajectory. The first massage part (110) and the second massage part (220) of the present application simultaneously massage the forehead and the vertex, and are matched with horizontal pressing and arc-shaped light hitting respectively to massage the user's head. This can stimulate blood circulation in the head to the greatest extent, increase the supply amount, and increase the hair growth amount to achieve the effect of preventing hair loss and promoting hair growth.

[0004] For example, the invention patent with the announcement number CN106693200B announced an intelligent hair growth device and system, which belongs to the field of hair care and treatment, and particularly relates to an intelligent hair growth device, an intelligent hair growth device control method, and an intelligent hair growth system. The intelligent hair growth device includes a light emitting unit for optical irradiation of a user, wherein it further includes: a temperature and humidity sensing unit for detecting the temperature and humidity of the irradiated part of the user during use of the intelligent hair growth device; and a processing unit connected with the light emitting unit and the temperature and humidity sensing unit, for controlling the output power of the light emitting unit according to the detected temperature and / or calculating the oiliness of the irradiated part of the user according to the detected humidity. Through the management of the temperature of the irradiated part of the user, the safety of the user is ensured, the high-temperature damage to the user is avoided, and the safety hazard is eliminated.

[0005] But in the process of implementing the technical scheme of the embodiment of the application, the application finds that the above-mentioned technology at least has the following technical problems: Due to the large individual differences in the scalp thickness, fat layer and bone surface curvature of each user, the same output near-field sound intensity may be too strong or too weak in the hair follicle layer. With the same ultrasonic output power, the sound intensity is insufficient for people with thick scalps, and people with thin scalps are prone to excessive heat. Therefore, it is impossible to preset a safe and effective sound power for all people in mass production equipment.

[0006] Therefore, in view of the above problems, there is an urgent need for a wearable hair loss prevention and hair growth monitoring device and system based on low-power ultrasound. SUMMARY

[0007] Technical problems to be solved In view of the deficiencies of the prior art, the application provides a wearable hair loss prevention and hair growth monitoring device and system based on low-power ultrasound, which solves the problem that the same ultrasonic power may be too high or insufficient in the hair follicle layer due to the large differences in the scalp thickness, fat layer and bone surface curvature of different users, and it is impossible to uniformly preset a safe and effective emission power.

[0008] Technical scheme To achieve the above purpose, the application is implemented by the following technical scheme: a wearable hair loss prevention and hair growth monitoring system based on low-power ultrasound, comprising: an individual structure perception and modeling module, configured to collect ultrasonic monitoring data in real time, and to perform data preprocessing on the ultrasonic monitoring data; using the preprocessed ultrasonic monitoring data, evaluating the fat layer thickness, calculating the skin layer thickness, and constructing a curvature estimation model; a sound field simulation and sound intensity prediction module, configured to combine the preprocessed ultrasonic monitoring data, the fat layer thickness, the skin layer thickness and the curvature estimation model to determine the local ultrasonic sound intensity of the hair follicle layer, to perform graded ultrasonic regulation according to the local ultrasonic sound intensity determination result of the hair follicle layer, and to calculate a sound intensity correction factor; an individualized adaptive regulation module, configured to update the sound wave emission power according to the sound intensity correction factor, to collect temperature data in real time, to evaluate the local temperature rise safety using the temperature data, and to implement temperature rise protection measures according to the local temperature rise safety; a monitoring feedback and system self-learning module, configured to continuously monitor the ultrasonic monitoring data, the local ultrasonic sound intensity determination result of the hair follicle layer and the local temperature rise safety, and to perform scalp state analysis feedback, so as to realize algorithm and threshold optimization.

[0009] Further, the specific process of collecting and pre-processing the ultrasound monitoring data in real time is as follows: after the user wears the device and completes the fitting, the device emits and collects echo signals along the normal direction through multi-frequency ultrasound waves, records the sound wave transmission power, ultrasound frequency, beam angle, and transmission surface diameter of the transducer, and marks a unified timestamp, calculates the reflection echo time delay of the sound wave from the skin layer through the fat layer to the bone interface and back; the electrode array collects the local electrical impedance spectrum data of the scalp, uses a sliding time window to average and filter multiple collections, removes outliers, and obtains the average impedance value; the sound wave transmission power, ultrasound frequency, beam angle, transmission surface diameter of the transducer, reflection echo time delay, and average impedance value are recorded as ultrasound monitoring data, and are standardized and normalized to construct an ultrasound monitoring database to store the ultrasound monitoring data.

[0010] Further, the specific process of evaluating the fat layer thickness using the pre-processed ultrasound monitoring data is as follows: obtain the ultrasound monitoring data, average the impedance values based on a sliding time window, and calculate the average value as the impedance reference value; subtract the impedance reference value from the current average impedance value to obtain the impedance difference, multiply the impedance difference by the impedance adjustment weight factor, take the negative value as the exponential power, perform natural exponential operation to obtain the impedance suppression factor, add the impedance suppression factor to the constant one to obtain the impedance suppression term; multiply the reflection echo time delay by the normalized value of the sound velocity constant in the fat layer to obtain the two-way sound propagation length; divide the two-way sound propagation length by the impedance suppression term and multiply by one-half to obtain the fat layer thickness.

[0011] Further, the specific process of calculating the skin layer thickness and constructing the curvature estimation model is as follows: record the time delay of the sound wave propagating to the skin and coupling layer and being reflected back to the probe after the probe emits a pulse, accurately extract the skin layer reflection delay by recording the transmission time and peak value time of the received signal in real time, combining envelope extraction and peak detection algorithm, multiplying the skin layer reflection delay by the known sound velocity constant and dividing by the constant two to obtain the skin layer thickness and perform normalization processing; by controlling the beam angle and sound wave scanning path, collect the echo intensity and time difference of bone surface reflection in multiple directions, analyze the multi-dimensional signal characteristics of echo attenuation slope, waveform broadening degree, and amplitude variance, train the multi-dimensional signal characteristics using a lightweight linear regression algorithm, construct a curvature estimation model, and output the normalized bone surface local curvature; combine the skin layer thickness, fat layer thickness, and bone surface local curvature to construct an individual structure parameter set and store it in the ultrasound monitoring database.

[0012] Furthermore, combining preprocessed ultrasound monitoring data, fat layer thickness, skin layer thickness, and curvature estimation model, the specific process for determining the local ultrasound intensity in the hair follicle layer is as follows: The propagation trajectory of ultrasound in the skin layer, fat layer, and bone structure is calculated using the linear ray tracing method, and the energy concentration of the ultrasound focusing area within the hair follicle layer is assessed, considering the influence of tissue absorption and local curvature of the bone surface on the focus offset; based on the skin layer thickness and fat layer thickness, and with the center of the hair follicle layer as the target location, the focusing depth is calculated; the ultrasound frequency is obtained, and the wavelength is obtained by calculating the ratio of the known sound velocity constant to the ultrasound frequency; the transducer's emitting surface diameter is obtained, and the product of the focusing depth and wavelength is divided by twice the transducer's emitting surface diameter to obtain the total radius length; based on the total radius length, the acoustic energy focusing area is calculated using the circle area formula and then normalized; the beam angle is obtained, and the square of the cosine of the beam angle is calculated to obtain the incident angle correction factor; Simultaneously, the acoustic wave emission power, skin layer thickness, fat layer thickness, and local curvature of the bone surface are acquired. The acoustic wave emission power is divided by the acoustic energy focusing area to obtain the sound intensity per unit area. The sound intensity per unit area is multiplied by the incident angle correction factor to obtain the effective incident surface sound intensity factor. The skin layer thickness is multiplied by the skin layer correction weight factor, and the negative value is used as the exponent for natural exponential calculation to obtain the skin layer transmission factor. The fat layer thickness is multiplied by the fat layer correction weight factor, and the negative value is used as the exponent for natural exponential calculation to obtain the fat layer transmission factor. The skin layer transmission factor is multiplied by the fat layer transmission factor to obtain the tissue composite transmission factor. The square of the local curvature of the bone surface is multiplied by the bone curvature diffraction weight factor and added to a constant to obtain the bone curvature correction factor. The tissue composite transmission factor is divided by the bone curvature correction factor to obtain the curvature tissue composite attenuation term. The effective incident surface sound intensity factor is multiplied by the curvature tissue composite attenuation term to obtain the effective sound intensity value of the hair follicle layer.

[0013] Furthermore, the specific process of graded ultrasound regulation based on the local ultrasound intensity judgment results of the hair follicle layer and the calculation of the intensity correction factor is as follows: The effective intensity value of the hair follicle layer is compared with the minimum and maximum intensity thresholds. When the effective intensity value of the hair follicle layer is less than or equal to the minimum intensity threshold, it is determined to be insufficient intensity. The sound wave emission power is increased, the increase in sound wave emission power is limited, the sound energy focusing area is reduced, and the beam angle is decreased. When the effective intensity value of the hair follicle layer is greater than the minimum intensity threshold and less than or equal to the maximum intensity threshold, it is determined to be safe and effective. The current effective intensity value parameter combination of the hair follicle layer is fixed and recorded as the individual optimal intensity parameter set and stored in the ultrasound monitoring database. Regular re-enhancing... A new effective acoustic intensity value for the hair follicle layer is estimated. When the effective acoustic intensity value of the follicle layer is greater than or equal to the acoustic intensity threshold, it is determined to be excessive acoustic intensity. The sound wave emission power is reduced, the sound energy focusing area is expanded, and the beam emission angle is increased. At the same time, temperature rise protection measures are set: if the historical temperature rise rate exceeds the temperature rise protection threshold, the ultrasound output is suspended, and the user is prompted to check the quality of the coupling layer and replace the colloid. Combining the effective acoustic intensity value of the hair follicle layer, the minimum acoustic intensity threshold, and the maximum acoustic intensity threshold, half of the sum of the minimum acoustic intensity threshold and the maximum acoustic intensity threshold is set as the target acoustic intensity. The ratio of the effective acoustic intensity value of the hair follicle layer to the target acoustic intensity is calculated as the acoustic intensity correction factor. The effective acoustic intensity value of the hair follicle layer and the acoustic intensity correction factor are stored in the ultrasound monitoring database.

[0014] Furthermore, the specific process of updating the acoustic wave transmission power based on the acoustic intensity correction factor and collecting temperature data in real time to assess the safety of local temperature rise using temperature data is as follows: The acoustic intensity correction factor and the current acoustic wave transmission power are received; the acoustic intensity correction factor and the current acoustic wave transmission power are multiplied to obtain the updated transmission power value; when the acoustic intensity is determined to be insufficient or excessive, based on the updated transmission power value, the updated ultrasonic signal is emitted for germinal stimulation, and the timestamp is recorded in real time, while temperature data is collected in real time through a temperature sensor; the temperature data is normalized and stored in the ultrasonic monitoring database; based on the timestamp recording... Calculate the cumulative temperature rise time from the start of launch to the current moment; acquire the temperature data at the moment of ultrasonic signal launch and the temperature data at the current moment, and calculate the difference between the temperature data at the current moment and the temperature data at the moment of ultrasonic signal launch to obtain the temperature rise amount; based on the sliding time window, use the multi-point difference method to calculate the derivative of the temperature data with respect to time to obtain the current temperature rise rate; divide the cumulative temperature rise time by the temperature rise amount to obtain the temperature rise accumulation effect term; multiply the current temperature rise rate by the rate response weighting factor to obtain the temperature rise rate response term; add the temperature rise accumulation effect term and the temperature rise rate response term to obtain the temperature rise adjustment value.

[0015] Furthermore, the specific process for implementing temperature rise protection measures based on local temperature rise safety is as follows: The temperature rise adjustment value is calculated in real time. When the temperature rise adjustment value is less than or equal to the temperature rise warning threshold, the temperature rise is considered normal, and continuous monitoring of the temperature rise adjustment value is performed without requiring protection. When the temperature rise adjustment value is greater than the temperature rise warning threshold, the temperature rise is considered excessive, and the acoustic wave transmission power is adjusted according to the degree of excessive temperature rise. A temperature rise cooling timer window is activated. During the temperature rise cooling timer window, ultrasonic transmission is paused, active air cooling is performed, and the temperature rise adjustment value is continuously calculated until the temperature rise adjustment value is less than or equal to the temperature rise warning threshold. At this point, transmission is allowed to resume, and the acoustic wave transmission power is limited. Simultaneously, the temperature rise adjustment value and temperature rise status are stored in the ultrasonic monitoring database.

[0016] Furthermore, the process of continuously monitoring ultrasound monitoring data, judging the local ultrasound intensity of the hair follicle layer, and assessing the safety of local temperature rise, and analyzing and providing feedback on scalp status, to achieve algorithm and threshold optimization, is as follows: During the monitoring cycle, ultrasound monitoring data, skin layer thickness, fat layer thickness, local curvature of the bone surface, effective acoustic intensity value of the hair follicle layer, temperature rise adjustment value, and temperature rise status are continuously recorded. Before starting treatment, a side-mounted miniature camera is activated to take pictures of the scalp monitoring area, which are transmitted to the application backend via Bluetooth. Based on traditional image processing methods, a lightweight neural network algorithm is integrated to complete hair follicle detection, hair counting, and trend analysis, and output a hair growth analysis report. The hair growth analysis report is comprehensively analyzed to optimize and update the impedance reference value, minimum acoustic intensity threshold, maximum acoustic intensity threshold, and temperature rise warning threshold. The optimized parameters and thresholds are embedded into the initial monitoring values ​​of the next cycle to construct an individualized ultrasound emission scheme. After each monitoring cycle is completed, the effect is re-evaluated to determine whether convergence has been achieved and further adjustments are needed. An optimal treatment knowledge base is constructed for cold start recommendations for new users.

[0017] The second aspect of this invention provides a wearable anti-hair loss and hair regrowth monitoring device based on low-power ultrasound, comprising: a multi-frequency ultrasound emission and echo acquisition device for emitting low-power, multi-frequency ultrasound waves and acquiring reflected echo signals from the skin, fat layer, and bone surface, providing basic data for tissue thickness estimation, bone surface curvature analysis, and sound intensity calculation; a scalp local electrical impedance spectrum acquisition device for acquiring the average impedance values ​​of the skin and fat layers through a multi-electrode array, and performing impedance adjustment weighting factor fitting and ultrasound sound intensity correction; a temperature monitoring and safety protection device for acquiring temperature data of the target area using a high-sensitivity sensor, analyzing the temperature rise curve, determining whether the temperature rise rate exceeds the threshold, and triggering temperature rise protection measures; and a dose control and feedback execution device for real-time comparison of the calculated effective sound intensity value of the hair follicle layer with the sound intensity threshold, calculating the sound intensity correction factor, and adjusting the emission power, beam angle, and focusing area to achieve closed-loop sound intensity output.

[0018] Beneficial effects The present invention has the following beneficial effects: (1) This invention dynamically calculates the effective acoustic intensity value of the hair follicle layer by real-time calculation of the skin layer thickness, fat layer thickness and bone surface curvature of the user's scalp, combined with multi-frequency ultrasound echo and electrical impedance data. By using acoustic intensity correction factors and graded control strategies, the transmission power, beam angle and focusing area can be adjusted according to different individual differences, avoiding overdose and underdose caused by a one-size-fits-all setting, and achieving truly individualized, safe and effective ultrasound stimulation.

[0019] (2) This invention integrates multi-frequency ultrasound echo analysis with scalp local electrical impedance spectrum measurement. Through sliding time window filtering, waveform feature extraction and lightweight regression modeling, it can not only estimate the tissue layer thickness with high accuracy, but also predict the bone surface curvature and correct the sound field focusing error, thereby improving the reliability and robustness of sound intensity calculation and providing accurate input for subsequent ultrasound simulation and dose assessment.

[0020] (3) This invention, by jointly monitoring the temperature rise accumulation effect term and the temperature rise rate response term, not only focuses on the long-term temperature rise trend, but also responds quickly to instantaneous temperature rise changes. When the temperature rise adjustment value exceeds the warning threshold, power reduction, transmission suspension and air cooling measures are implemented, and safe output is dynamically restored through the cooling timing window, effectively preventing the risk of thermal damage.

[0021] (4) This invention continuously collects ultrasound monitoring data, temperature curves, and scalp images during the monitoring period, and combines hair follicle detection and hair density change trend analysis to optimize and update impedance reference values, sound intensity thresholds, and temperature rise thresholds. This forms an optimal treatment knowledge base, enabling cold start recommendations for new users and continuous evolution of individual strategies.

[0022] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0023] Figure 1 This is a block diagram of a wearable anti-hair loss and hair regrowth monitoring system based on low-power ultrasound.

[0024] Figure 2 This is a trend diagram of the effective acoustic intensity distribution in the hair follicle layer under different combinations of structural parameters.

[0025] Figure 3 This is a flowchart of a hair loss prevention and hair regrowth system based on low-power ultrasound.

[0026] Figure 4 Comparative diagram of tissue structures in animal experiments demonstrating low-power ultrasound-induced hair growth.

[0027] Figure 5 This image shows the expression results of molecular markers for hair follicle cell proliferation and differentiation under low-power ultrasound. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. As those skilled in the art will understand, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] Please see Figures 1-5 This invention provides a technical solution: a wearable anti-hair loss and hair growth monitoring device and system based on low-power ultrasound, such as... Figure 1 As shown, the system includes: an individual structure perception and modeling module, used to collect ultrasound monitoring data in real time and preprocess the ultrasound monitoring data; using the preprocessed ultrasound monitoring data, it assesses the thickness of the fat layer and calculates the thickness of the skin layer, while constructing a curvature estimation model; a sound field simulation and sound intensity prediction module, used to combine the preprocessed ultrasound monitoring data, fat layer thickness, skin layer thickness, and curvature estimation model to determine the local ultrasound sound intensity of the hair follicle layer, perform graded ultrasound control based on the local ultrasound sound intensity determination result of the hair follicle layer, and calculate the sound intensity correction factor; an individualized adaptive control module, used to update the sound wave emission power according to the sound intensity correction factor, collect temperature data in real time, use the temperature data to assess the local temperature rise safety, and implement temperature rise protection measures based on the local temperature rise safety; and a monitoring feedback and system self-learning module, used to continuously monitor ultrasound monitoring data, the local ultrasound sound intensity determination result of the hair follicle layer, and the local temperature rise safety, and perform scalp state analysis feedback to achieve algorithm and threshold optimization.

[0030] Specifically, the real-time acquisition and preprocessing of ultrasound monitoring data is as follows: After the user wears the device and ensures it fits snugly, the ultrasound transducer is in close contact with the scalp surface to reduce the impact of air gaps on ultrasound signal propagation. Multi-frequency ultrasound is emitted perpendicularly along the normal direction, and echo signals are collected. Multi-frequency ultrasound refers to the simultaneous use of different low-frequency ultrasound signals to obtain tissue information with different penetration depths and resolutions. The normal direction refers to the ultrasound beam incident perpendicularly to the scalp surface, improving the energy utilization rate of the reflected signal. The sound wave emission power, ultrasound frequency, beam angle, and transducer emission surface diameter are recorded. The sound wave emission power represents the intensity of ultrasound energy output per unit time, the ultrasound frequency determines the ultrasound beam length and penetration depth, the beam angle is the angle between the ultrasound beam and the normal direction, and the transducer emission surface diameter affects the focusing area and sound field distribution. Simultaneously, a unified timestamp is marked, and the sound wave is calculated. The time delay of the reflected echo from the skin layer through the fat layer to the bone interface is recorded. This time delay, or the time difference between the emission of an ultrasound pulse and its reflection back to the receiver at different tissue interfaces, reflects the thickness of each tissue layer. Electrical impedance spectrum data of the scalp is acquired using an electrode array. The electrical impedance spectrum refers to the electrical impedance characteristic curve of biological tissue at different frequencies, which can be used to distinguish the bioelectrical properties of different tissues such as skin and fat. Multiple acquisitions are averaged and filtered using a sliding time window to remove outliers and obtain the average impedance value. The sound wave emission power, ultrasound frequency, beam angle, transducer emission surface diameter, reflected echo time delay, and average impedance value are recorded as ultrasound monitoring data, and standardized and normalized. An ultrasound monitoring database is constructed to store the ultrasound monitoring data, providing historical and real-time data support for subsequent tissue thickness estimation, structural parameter extraction, and individualized modeling.

[0031] In this implementation scheme, comprehensive perception of scalp structural features is achieved through real-time acquisition and preprocessing of multimodal data from multi-frequency ultrasound and electrode arrays. By recording key acoustic parameters such as acoustic wave emission power, ultrasound frequency, beam angle, transducer emission surface diameter, and reflected echo time delay, and combining this with impedance spectrum data filtered through a sliding time window, the system can accurately reflect the thickness and bioelectrical properties of each tissue layer, including the skin and fat layers. It also effectively suppresses noise and occasional errors, improving data reliability. All ultrasound monitoring data are standardized and normalized before being stored in a unified database, providing high-quality historical and real-time data support for subsequent tissue thickness estimation, individual structural parameter extraction, and personalized model construction. This enhances the adaptability to differences in individual structures and the accuracy of subsequent intelligent control.

[0032] Specifically, the process of assessing fat layer thickness using preprocessed ultrasound monitoring data is as follows: Ultrasound monitoring data is acquired; average impedance values ​​are collected multiple times based on a sliding time window, and the average value is calculated as an impedance reference value; the impedance difference is obtained by subtracting the impedance reference value from the current average impedance value. This impedance difference reflects the deviation between the current measurement value and the reference state, which helps to track changes in tissue characteristics in real time; the impedance difference is multiplied by an impedance adjustment weighting factor, and the negative value is used as the exponent for natural exponential operation to obtain the impedance suppression factor. The natural exponential operation, i.e., exponential operation with base e, can enhance the detection of changes in impedance difference. The nonlinear response is analyzed by adding the impedance suppression factor to a constant to obtain the impedance suppression term; the time delay of the reflected echo is multiplied by the normalized value of the sound velocity constant in the fat layer to obtain the two-way sound propagation length; the sound velocity constant in the fat layer is a known standard medical acoustic parameter, and normalization can eliminate the absolute value difference between individuals; the two-way sound propagation length refers to the round-trip distance of the ultrasound wave from emission to arrival at the interface and back; the two-way sound propagation length is divided by the impedance suppression term and multiplied by half to obtain the fat layer thickness; multiplying by half is to restore the two-way distance to the true physical thickness of the one-way distance, and finally obtains the estimated value of the actual thickness of the fat layer.

[0033] The specific formula for the thickness of the fat layer is as follows: ; In the formula, It represents the thickness of the fat layer and is used to non-invasively estimate the true thickness of the subcutaneous fat layer in wearable devices. It combines the reflected echo time delay with the average impedance value and introduces a non-linear adjustment mechanism to more accurately adapt to individual differences and avoid errors caused by relying solely on time measurements. This represents the normalized value of the sound speed constant in the fat layer, which is a fixed constant used to convert propagation time to distance. It represents the time delay of the reflected echo, reflecting the time it takes for the sound wave to travel from the probe to the fat-bone interface, and represents the total time for the sound wave to propagate in the tissue; This indicates the current average impedance value, reflecting the conductivity of the fat layer; high fat content results in low conductivity. This represents the impedance reference value, which is compared to the baseline to determine the adjustment trend; This represents the impedance suppression factor, used to adjust the slope of the estimated thickness-response curve as a function of impedance; It represents the two-way sound propagation length, and the total distance the sound wave travels. The impedance adjustment weight factor controls the degree of nonlinear influence of impedance difference on thickness. First, the initial value of the impedance adjustment weight factor is set. Based on the reflection echo time delay and the average impedance value, the thickness of the reference fat layer is calculated. The optimal impedance adjustment weight factor is fitted by the minimum mean square error through a grid search algorithm. The value range is between 0.1 and 5.0.

[0034] In this implementation scheme, efficient, dynamic, and individualized assessment of fat layer thickness is achieved by integrating ultrasound monitoring data and electrical impedance parameters. A sliding time window is used to process the average impedance values ​​from multiple acquisitions, eliminating occasional noise. The impedance difference is then incorporated into a natural exponential function with base e, enhancing sensitivity to minute changes in tissue properties and improving nonlinear response capabilities, thereby increasing the accuracy of thickness estimation. Simultaneously, by combining the constant sound velocity in the fat layer with the reflected echo time delay, a two-way propagation length and one-way conversion method is employed to ensure the physical authenticity and standard consistency of the thickness measurement. This method not only improves the real-time performance and reliability of fat layer thickness measurement but also provides a solid data foundation for subsequent sound field simulation, individual structural parameter extraction, and precise control, enhancing adaptability under different individual and dynamic conditions.

[0035] Specifically, the process of calculating skin layer thickness and constructing a curvature estimation model is as follows: Record the time delay after the probe emits a pulse, from the sound wave propagating to the skin and coupling layer, and being reflected back to the probe. The coupling layer refers to the medium between the ultrasound probe and the skin used to conduct sound waves, such as a coupling gel or a flexible membrane, designed to reduce sound energy reflection loss at the interface. By recording the emission time and the peak time of the received signal in real time (the emission time being the moment the ultrasound pulse is emitted, and the peak time corresponding to the point of maximum ultrasound reflected signal energy), and combining envelope extraction and peak detection algorithms, the skin layer reflection wave delay is accurately extracted. The envelope extraction algorithm smooths the reflected signal and improves peak recognition accuracy, while the peak detection algorithm locks the principal maximum point of the reflected signal, thus determining the location of the tissue interface. The skin layer thickness is obtained by multiplying the skin layer reflection wave delay by a known sound velocity constant and dividing by a constant of two, and then normalized. By controlling the beam angle and the sound wave scanning path, echoes reflected from the bone surface in multiple directions are collected. Intensity and time difference, controlling the beam angle (i.e., emitting ultrasound in multiple spatial directions), and the acoustic scanning path (referring to the multi-point measurement route) are all considered. The echo characteristics of bone surface reflection reflect the three-dimensional morphology of the bone surface. Multidimensional signal features such as echo attenuation slope, waveform broadening, and amplitude variance are analyzed. The echo attenuation slope reflects the energy loss rate, the waveform broadening describes the change in the width of the echo main pulse, and the amplitude variance represents the difference in echo intensity distribution in different directions. These signal features collectively reveal bone surface curvature information. A lightweight linear regression algorithm is used to train the multidimensional signal features and construct a curvature estimation model. The lightweight linear regression algorithm is based on the linear relationship between the feature vector and bone surface curvature, balancing real-time performance and equipment resource limitations. Normalized local bone surface curvature is output. Skin layer thickness, fat layer thickness, and local bone surface curvature are combined to construct an individual structural parameter set, which is stored in the ultrasound monitoring database. This individual structural parameter set provides customized input for subsequent ultrasound propagation simulation, sound intensity estimation, and control optimization.

[0036] In this implementation scheme, high-precision assessment of skin layer thickness and local curvature of the bone surface is achieved through ultrasound pulse echo timing measurement and multi-dimensional signal feature extraction. Envelope extraction and peak detection algorithms effectively identify echoes at the skin coupling layer interface, enabling accurate extraction and normalization of skin layer thickness. Multi-angle, multi-path ultrasound scanning collects the echo intensity and signal characteristics reflected from the bone surface. A lightweight linear regression model is then used to train multiple features such as echo attenuation, broadening, and amplitude variance, yielding normalized bone surface curvature parameters. Finally, skin layer thickness, fat layer thickness, and local bone surface curvature are organically integrated to construct an individual structural parameter set. This provides a high-quality, individualized data foundation for subsequent ultrasound propagation modeling, sound intensity prediction, and control optimization, improving adaptability to complex tissue structures and individual differences, as well as the accuracy of sound intensity control.

[0037] Specifically, combining preprocessed ultrasound monitoring data, fat layer thickness, skin layer thickness, and curvature estimation models, the process for determining the local ultrasound intensity in the hair follicle layer is as follows: The linear ray tracing method is used to calculate the propagation trajectory of ultrasound in the skin, fat, and bone structures. This method, based on sound wave propagation path simulation, can estimate the path and energy changes of sound waves in each tissue layer by layer. The energy concentration of the ultrasound focusing area within the hair follicle layer is assessed; this concentration, i.e., the actual sound intensity density received in the focusing area, determines the hair follicle stimulation effect. The effects of tissue absorption and local bone surface curvature on the focal point shift are considered. Tissue absorption reflects the attenuation of sound energy during propagation due to tissue characteristics, while bone surface curvature affects the intensity of ultrasound. The refraction and focusing position of sound waves may cause the focal point to deviate from the preset target. Based on the thickness of the skin layer and fat layer, and with the center of the hair follicle layer as the target location, the focusing depth is calculated by adding the thickness of the skin layer, fat layer, and the center of the hair follicle layer. The focusing depth is the vertical distance from the ultrasound focusing area to the skin surface and is an important parameter for precise treatment. The ultrasound frequency is obtained, and the wavelength is obtained by calculating the ratio of the known sound velocity constant to the ultrasound frequency. The diameter of the transducer's emitting surface is obtained, and the product of the focusing depth and wavelength is divided by twice the diameter of the transducer's emitting surface to obtain the total radius. The total radius is used to characterize the range of sound beam extension at the target depth. Based on the total radius, the sound energy focusing is calculated using the formula for the area of ​​a circle. The focal area is normalized to eliminate the influence of area scale under different transducer and operating conditions, facilitating comparisons across individuals and devices. The beam angle is obtained, and the square of the cosine of the beam angle is calculated to obtain the incident angle correction factor. This factor reflects the correction effect of the angle between the sound beam direction and the tissue normal on energy distribution; the closer the angle is to the normal, the more concentrated the energy. Simultaneously, the sound wave emission power, skin layer thickness, fat layer thickness, and local curvature of the bone surface are obtained. The sound wave emission power is divided by the sound energy focusing area to obtain the sound intensity per unit area, which is a fundamental indicator of sound intensity distribution. Multiplying the sound intensity per unit area by the incident angle correction factor yields the effective incident surface sound intensity factor. The effective incident surface sound intensity factor is then integrated. The combined effects of power, area, and incident direction are considered to reflect the effective acoustic energy actually reaching the tissue surface. The skin layer transmission factor is obtained by multiplying the skin layer thickness by a skin layer correction weighting factor and taking the negative value as the exponent for natural exponential calculation. Based on the acoustic attenuation law, the exponential factor can enhance the influence of thickness changes on energy transmission, reflecting the degree of energy retention when ultrasound passes through the skin. Similarly, the fat layer transmission factor is obtained by multiplying the fat layer thickness by a fat layer correction weighting factor and taking the negative value as the exponent for natural exponential calculation, reflecting the fat layer's absorption and transmission capacity of acoustic energy. Finally, the tissue composite transmission factor is obtained by multiplying the skin layer transmission factor and the fat layer transmission factor, representing the total transmission efficiency when sound waves continuously pass through multiple tissue layers.The square of the local curvature of the bone surface is multiplied by the bone curvature diffraction weighting factor and added to a constant to obtain the bone curvature correction factor, which is used to simulate the scattering of focused energy by the geometric characteristics of the bone surface. The tissue composite transmission factor is divided by the bone curvature correction factor to obtain the curvature-tissue composite attenuation term, reflecting the combined effect of multi-layered tissue transmission loss and bone curvature diffraction. The effective incident surface acoustic intensity factor is multiplied by the curvature-tissue composite attenuation term to obtain the effective acoustic intensity value of the hair follicle layer, which is the actual ultrasound energy density ultimately acting on the hair follicle layer and is the core parameter for evaluating the safety and effectiveness of acoustic intensity.

[0038] The specific formula for the effective acoustic intensity value of the hair follicle layer is as follows: ; In the formula, It represents the effective sound intensity value of the hair follicle layer, which essentially ensures that the sound intensity estimation can be dynamically adjusted under the different individual differences in skin layer thickness, fat layer thickness, and local curvature anatomy of the bone surface, so as to avoid excessive and insufficient energy transfer; This represents the power of sound wave emission, determines the initial sound energy, and is the direct source of sound field intensity. The larger the value, the higher the initial sound field energy. This represents the area where sound energy is focused, which determines the degree of concentration of sound energy per unit area. The smaller the area where sound energy is focused, the higher the energy density. Indicates the beam angle. This represents the incident angle correction factor, which corrects the incident energy density. It takes into account the change in the effective area when the beam is incident at an angle, so that the sound intensity attenuates when the angle deviates from vertical, and ensures that the energy calculation is consistent with the actual effective area. This represents the effective incident surface acoustic intensity factor, the corrected incident energy density, and the effective area change considering the tilted emission. This indicates the thickness of the skin layer, which determines the distance sound waves travel in the skin and affects the amount of attenuation; The thickness of the fat layer determines the distance sound waves travel in the fat and directly affects the attenuation. This represents the tissue composite transmission factor, used to calculate the proportion of energy remaining after sound waves pass through the skin and fat. It represents the local curvature of the bone surface, reflecting the degree of geometric curvature of the bone surface. The greater the curvature, the stronger the diffraction and focal point shift. The skin layer correction weight factor is based on skin layer thickness and ultrasound frequency. It compares the emitted incident energy with the echo energy of the skin and fat layers, uses the logarithmic linear decay method, and fits the skin layer correction weight factor through least squares linear regression. The value ranges from 0.4 to 1.2. The fat layer correction weight factor is based on the fat layer thickness and ultrasound frequency. It compares the echoes of the fat layer and bone interface with the echoes of the skin layer and fat layer. The logarithmic linear attenuation method is used, and the fat layer correction weight factor is fitted by least squares linear regression. The value range is between 0.5 and 1.8. The bone curvature diffraction weighting factor is determined by fitting the dataset of local bone surface curvature and bone curvature correction factor using the nonlinear least squares method. The value ranges from 0.05 to 0.5.

[0039] The skin layer correction weighting factor was set to 0.8, the fat layer correction weighting factor to 1.3, and the bone curvature diffraction weighting factor to 0.2. With the three weighting factors being the same, different effective acoustic intensity values ​​for the hair follicle layer were calculated based on different acoustic wave emission power, acoustic energy focusing area, beam angle, skin layer thickness, fat layer thickness, and local bone surface curvature. Table 1 shows the effective acoustic intensity values ​​for the hair follicle layer.

[0040] Table 1. Effective sound intensity data for hair follicle layer

[0041] like Figure 2 The figure shows the distribution trend of effective acoustic intensity in the hair follicle layer under different combinations of structural parameters provided in the embodiments of this application. It displays the actual effective acoustic intensity values ​​received at the hair follicle layer under five different ultrasound parameters and individual structural conditions. The horizontal axis represents the sample number, and the vertical axis represents the effective acoustic intensity value of the hair follicle layer. The broken line reflects the variation range and fluctuation trend of the acoustic intensity for each sample. (Based on Table 1 and...) Figure 2 It can be seen that the sound intensity of the third group reaches its peak, the fourth group is the lowest, and the other groups are at the middle level. This shows that even if the weighting factor is fixed, different combinations of power, area, tissue thickness and bone surface curvature have a significant impact on the actual sound intensity.

[0042] In this implementation scheme, by fusing a physical model of ultrasound propagation with individual structural parameters, the propagation and energy changes of sound waves in skin, fat, and bone tissue are simulated layer by layer, comprehensively assessing the energy distribution of the focused area. Combining parameters such as frequency, focusing depth, emitter diameter, and beam angle, and after focusing area normalization, incident angle correction, layered transmission, and bone curvature diffraction processing, the actual effective acoustic intensity of the hair follicle layer is accurately calculated. This method can dynamically adapt to individual differences, improving the scientific rigor and reliability of dose assessment, and providing a solid foundation for subsequent safety assessment and closed-loop control.

[0043] Specifically, the process of graded ultrasound control based on the local ultrasound intensity assessment results of the hair follicle layer and the calculation of the intensity correction factor is as follows: The effective intensity value of the hair follicle layer is compared with the minimum and maximum intensity thresholds. The minimum and maximum intensity thresholds refer to the lower and upper limits of the intensity set to ensure hair growth safety and effectiveness, respectively, and can be dynamically set according to actual conditions. When the effective intensity value of the hair follicle layer is less than or equal to the minimum intensity threshold, it is determined to be insufficient intensity. The sound wave emission power is increased, the increase in sound wave emission power is limited, the sound energy focusing area is reduced, and the wave intensity is decreased. The smaller the beam angle, the greater the energy density as the sound energy focusing area. Reducing the beam angle improves energy directionality and helps focus energy on the target area. When the effective sound intensity value of the hair follicle layer is greater than the minimum sound intensity threshold and less than or equal to the maximum sound intensity threshold, it is considered safe and effective. The current effective sound intensity value parameter combination of the hair follicle layer is fixed and recorded as the individual's optimal sound intensity parameter set and stored in the ultrasound monitoring database to achieve individualized control and long-term efficacy tracking. The effective sound intensity value of the hair follicle layer is periodically re-estimated and triggered according to the treatment cycle to ensure real-time performance and safety. When the effective sound intensity value of the follicle layer... When the sound intensity is greater than or equal to the sound intensity threshold, it is determined to be excessive. The sound wave emission power is reduced, the sound energy focusing area is expanded, and the beam emission angle is increased. Expanding the focusing area and increasing the beam angle helps reduce the energy density per unit area, preventing local tissue overheating or damage. Simultaneously, a temperature rise protection measure is implemented: if the historical temperature rise rate exceeds the temperature rise protection threshold, ultrasound output is paused, and the user is prompted to check the coupling layer quality and replace the colloid. The temperature rise protection measure prevents the risk of tissue heat accumulation by continuously monitoring the rate of temperature change. Problems with the coupling layer, such as gel quality issues, may lead to sound energy loss and local tissue damage. This section focuses on key aspects; combining the effective acoustic intensity value of the hair follicle layer, the minimum acoustic intensity threshold, and the maximum acoustic intensity threshold, half of the sum of the minimum and maximum acoustic intensity thresholds is set as the target acoustic intensity. The target acoustic intensity is usually selected within the median of the safety range. To balance efficacy and safety, the ratio of the effective acoustic intensity value of the hair follicle layer to the target acoustic intensity is calculated as an acoustic intensity correction factor. The acoustic intensity correction factor is used to adjust subsequent emission parameters to achieve closed-loop dose control. The effective acoustic intensity value of the hair follicle layer and the acoustic intensity correction factor are stored in the ultrasound monitoring database to record key data throughout the process, facilitating effect traceability and strategy optimization.

[0044] In this implementation scheme, graded, closed-loop ultrasound dose control is achieved by comparing the effective acoustic intensity of the hair follicle layer with a dynamically set safety threshold. Based on three states—insufficient intensity, safe and effective intensity, and excessive intensity—the transmission power, focused area, and beam angle are adjusted accordingly, along with temperature rise protection measures to prevent tissue heat accumulation risks. By recording and dynamically updating the optimal acoustic intensity parameters for each individual in real time, combined with adjustments to the acoustic intensity correction factor, not only is the accuracy and response speed of dose control improved, but personalized and traceable control schemes are also provided for different users, effectively ensuring the safety and sustained efficacy of hair regrowth treatment.

[0045] Specifically, the process of updating the acoustic wave emission power based on the acoustic intensity correction factor and collecting temperature data in real time to assess the safety of local temperature rise is as follows: The acoustic intensity correction factor and the current acoustic wave emission power are received; the acoustic intensity correction factor and the current acoustic wave emission power are multiplied to obtain the updated emission power value; closed-loop control of the emission dose is achieved to ensure that the output dose always matches the individual's actual needs; when insufficient or excessive acoustic intensity is determined, the updated ultrasound signal is emitted for germinal stimulation based on the updated emission power value, and the timestamp is recorded in real time. Temperature data is collected in real time through a high-sensitivity patch that can continuously acquire tissue temperature changes on the surface or subcutaneous layer of the emission area; the temperature data is normalized and stored in the ultrasound monitoring database; based on the timestamp record, the cumulative temperature rise time from the start of emission to the current moment is calculated, reflecting the impact of continuous energy input on tissue heat accumulation; the temperature at the moment of ultrasound signal emission is obtained. The temperature rise is calculated by comparing the current temperature data with the temperature data at the time of ultrasonic signal transmission. This temperature rise reflects the immediate thermal effect caused by the ultrasonic action and is an important indicator for judging thermal safety. Based on a sliding time window, the current temperature rise rate is obtained by calculating the derivative of the temperature data with respect to time using the multi-point difference method. The sliding time window can smooth the temperature curve in real time, and the multi-point difference method calculates the rate of change by differentiating continuous data points. The temperature rise accumulation effect term is obtained by dividing the cumulative temperature rise time by the temperature rise. This term represents the cumulative energy input time required per unit temperature rise and reflects the tissue's thermal buffering capacity. The temperature rise rate response term is obtained by multiplying the current temperature rise rate by the rate response weighting factor. The temperature rise adjustment value is obtained by adding the temperature rise accumulation effect term and the temperature rise rate response term. This value comprehensively considers both thermal accumulation and temperature rise rate, and is a key reference for judging thermal safety and triggering protective measures.

[0046] The specific formula for the temperature rise adjustment value is as follows: ; In the formula, This indicates the temperature rise adjustment value, which is used to assess the local temperature rise safety of low-power ultrasound in individual use in real time, and to determine whether there is a risk of excessively rapid temperature rise and excessive heat accumulation, thereby triggering power limiting and shutdown protection mechanisms. It indicates the cumulative temperature rise time, measuring how long the heat accumulation process lasts; This indicates the amount of temperature increase; the greater the temperature increase, the higher the heat load. This represents the cumulative effect of temperature rise. The larger the cumulative effect of temperature rise, the slower the temperature rise and the smaller the temperature rise, indicating lower risk. It indicates the current rate of temperature rise and detects whether a sudden temperature increase is occurring; The rate response weighting factor determines the sensitivity to the rate of change. It is based on the historical cumulative temperature rise time, temperature rise amount and temperature rise rate, and a temperature rise warning threshold is set. The gradient sensitivity fitting method is used, and the cumulative temperature rise time, temperature rise amount and temperature rise rate when the historical temperature rise adjustment value reaches the temperature rise warning threshold are recorded. The rate response weighting factor is derived from this data, and its value ranges from 0.5 to 3.5.

[0047] In this implementation scheme, a sound intensity correction factor is introduced in real time to correct the emitted acoustic power, ensuring that the output dose dynamically adapts to individual needs. In cases of insufficient or excessive sound intensity, ultrasonic stimulation is performed based on the corrected emitted power, and the surface temperature of the emission area is continuously monitored using a high-sensitivity patch-type temperature sensor. Through normalization, timestamp synchronization, and sliding time window filtering, the entire temperature change process is accurately recorded, and the temperature rise rate is obtained using a multi-point difference method. A temperature rise adjustment value is generated by comprehensively calculating the temperature rise accumulation effect term and the temperature rise rate response term, fully reflecting the local tissue's thermal response to energy input. This method not only enhances the scientific rigor and sensitivity of temperature rise safety assessment but also provides a reliable basis for subsequent safety protection measures and individualized dose management, effectively ensuring the thermal safety and treatment precision of the hair regrowth treatment process.

[0048] Specifically, the process of implementing temperature rise protection measures based on local temperature rise safety is as follows: The temperature rise adjustment value is calculated in real time. When the temperature rise adjustment value is less than or equal to the temperature rise warning threshold, the temperature rise is considered normal, and continuous monitoring of the temperature rise adjustment value is performed without requiring protection. When the temperature rise adjustment value exceeds the temperature rise warning threshold, the temperature rise is considered excessive. The acoustic emission power is adjusted according to the degree of excessive temperature rise. Specifically, this is achieved through a combination of graded control and correction, dynamically reducing the emission power according to the degree of excessive temperature rise. This achieves safe, efficient, and individualized temperature control protection, preventing adverse reactions caused by tissue heat accumulation and ensuring the safety of equipment and users. The dynamic temperature rise cooling time window is a preset time period used to pause energy input and initiate cooling measures to ensure the tissue temperature safely drops. During the temperature rise cooling time window, ultrasonic emission is paused, and active air cooling is implemented to accelerate the diffusion and release of local heat using thermally conductive materials and hardware. The temperature rise adjustment value is continuously calculated until it is less than or equal to the temperature rise warning threshold, at which point emission is allowed to resume and the acoustic emission power is limited. Limiting the acoustic emission power aims to prevent secondary overheating. At the same time, the temperature rise adjustment value and temperature rise status are stored in the ultrasonic monitoring database, including normal temperature rise and temperature rise exceeding the standard.

[0049] This implementation plan achieves efficient safety protection against excessive local temperature rise. It can determine the temperature rise status based on the relationship between the temperature rise adjustment value and the temperature rise warning threshold. When the temperature rise exceeds the limit, it dynamically and progressively reduces the transmission power, simultaneously suspends energy input, activates the cooling timing window and active air cooling measures to accelerate local heat release. Once the temperature rise adjustment value returns to a safe range, ultrasound re-emission is only permitted under power-limited conditions, effectively preventing the risk of secondary overheating. Throughout the process, the temperature rise adjustment value and temperature rise status are continuously stored in the ultrasound monitoring database, providing complete and reliable data support for individual temperature control strategy optimization, safe equipment operation, and efficacy traceability, thereby improving the thermal safety of the equipment and the user experience.

[0050] Specifically, the process of continuously monitoring ultrasound monitoring data, judging the local ultrasound intensity of the hair follicle layer, and assessing the safety of local temperature rise, and analyzing and providing feedback on scalp status, and optimizing algorithms and thresholds, is as follows: During the monitoring period, ultrasound monitoring data, skin layer thickness, fat layer thickness, local curvature of the bone surface, effective acoustic intensity value of the hair follicle layer, temperature rise adjustment value, and temperature rise status are continuously recorded. The monitoring period is adaptively set according to the user's treatment plan, such as daily or weekly, to ensure data integrity and timeliness. Before starting treatment, a side-mounted miniature camera is activated to take pictures of the scalp monitoring area, which are transmitted to the application backend via Bluetooth. Based on traditional image processing methods, a lightweight neural network algorithm is integrated to complete hair follicle detection, hair counting, and trend analysis, outputting a hair growth analysis report. Traditional image processing methods include edge detection, region segmentation, and connected component analysis. Lightweight neural network algorithms, including MobileNet and Tiny-YOLO, can run efficiently on terminal devices. Using images of the scalp monitoring area as input, and after image preprocessing... The process involves multiple steps, including hair follicle and hair region segmentation, feature extraction and counting, and trend analysis, ultimately outputting hair follicle detection results, hair density and quantity, trend curves, and a hair regrowth effect report. A comprehensive analysis of the hair regrowth report, including key indicators such as total hair count, density, and growth rate, reflects treatment effectiveness and trends. Impedance reference values, minimum acoustic intensity thresholds, maximum acoustic intensity thresholds, and temperature rise warning thresholds are optimized and updated. The optimized parameters and thresholds are embedded into the initial monitoring values ​​for the next cycle, constructing an individualized ultrasound emission scheme to achieve personalized intelligent recommendation and closed-loop adaptive control, improving treatment accuracy and safety. After each monitoring cycle, the effect is reassessed to determine convergence and further adjustments. If the indicators remain stable over a long period and the therapeutic effect reaches the target, the parameters are considered converged; otherwise, adaptive optimization continues, building an optimal treatment knowledge base for cold start recommendations for new users. This optimal treatment knowledge base continuously accumulates historical effects, parameters, and status data to quickly generate individualized initial schemes for new users and special cases, improving adaptability.

[0051] like Figure 3The diagram shows a flowchart of a low-power ultrasound-based anti-hair loss and hair regrowth system provided in this application embodiment, illustrating the complete technical steps and intelligent closed-loop mechanism of the wearable anti-hair loss and hair regrowth monitoring system based on low-power ultrasound. First, multimodal data is collected and preprocessed to establish an individualized scalp structure model, accurately calculating skin thickness, fat layer thickness, and bone surface curvature parameters. Then, a sound field simulation prediction model is used to evaluate the effective sound intensity of the hair follicle layer, and a threshold is set to determine sound intensity safety. If the sound intensity output is unsafe, the transmission power, focusing parameters, and temperature rise protection measures are adjusted to ensure individualized and safe dosage output, and the system enters the temperature rise safety monitoring and efficacy analysis stage. Simultaneously, a temperature sensor continuously monitors tissue temperature rise, achieving multi-level active protection. Scalp images are periodically collected, and a local algorithm is used for hair follicle detection and efficacy analysis. Finally, the efficacy results and safety parameters are comprehensively considered to determine whether the current cycle has met the standards. If not, parameter adaptive optimization feedback is used to correct key algorithm parameters and thresholds, providing an optimized basis for the next cycle's treatment strategy, continuously improving individualized effects and usage safety. This closed-loop process emphasizes multimodal integration, real-time control, and self-learning optimization, comprehensively ensuring the accuracy of hair regrowth treatment and user experience.

[0052] like Figure 4 The image shows a comparative tissue structure of the low-power ultrasound-induced hair growth in an animal experiment according to an embodiment of this application. The left side of the image compares the macroscopic appearance of the skin on the backs of mice in the control and ultrasound groups, while the right side shows a comparison of HE-stained skin tissue sections. The ultrasound group shows a significantly enlarged area of ​​newly grown hair, while the control group shows sparse hair follicles, smaller dermal papillae, and significant melanin deposition. The ultrasound group shows a significantly increased number of hair follicles, enlarged dermal papillae, and reduced melanin deposition. The arrows in the HE-stained skin tissue section comparison indicate that the hair follicles are in the early stages of the anagen phase. The comparison demonstrates the changes in the structure of mouse skin, hair, and hair follicles after low-power ultrasound treatment. Compared to the control group, the ultrasound-treated group showed a significantly increased area of ​​newly grown hair, and the tissue sections showed an increased number and size of hair follicles, with reduced melanin deposition, consistent with the typical histological characteristics of hair follicles in the anagen phase. This fully demonstrates the effect of promoting hair growth and follicle activation, and visually reflects the biological effect at the tissue level.

[0053] like Figure 5The figure shows the expression results of molecular markers for hair follicle cell proliferation and differentiation under low-power ultrasound treatment according to the embodiments of this application. The figure displays the immunofluorescence staining results, showing the expression of the proliferation marker Ki67 and the differentiation-related marker LEF-1 in the hair follicle tissue. It also shows that the positive signals of Ki67 and LEF-1 were weak in the control group, while the positive signals in the ultrasound group were significantly enhanced, and the Merge channel showed co-localization of nuclear DAPI with the positive marker. This reflects that ultrasound treatment significantly upregulated the expression of Ki67 and LEF-1 in hair follicle cells, indicating active hair follicle cell proliferation and the initiation of differentiation. At the molecular level, this demonstrates the core biological mechanism by which personalized low-power ultrasound regulation promotes hair follicle cell proliferation and differentiation, thereby driving hair growth.

[0054] This implementation scheme achieves end-to-end, multi-dimensional personalized data tracking and safety monitoring. Utilizing a side-mounted miniature camera to acquire scalp images, a local analysis process integrating traditional image processing and lightweight neural network algorithms efficiently outputs objective hair regrowth analysis reports, including hair follicle detection, hair count, density, and trend changes. Based on the report data, impedance reference values, acoustic intensity thresholds, and temperature rise thresholds are optimized, and the optimization results are dynamically embedded into the initial values ​​for the next cycle, enabling intelligent emission scheme recommendations and closed-loop adaptive control tailored to individual structures. An optimal treatment knowledge base built from periodic efficacy and parameter adjustments provides users and new cases with scientific intelligent cold start and continuous optimization support, improving the objectivity of efficacy assessment, the precision of regulation, and self-learning adaptability.

[0055] The second aspect of this invention provides a wearable anti-hair loss and hair regrowth monitoring device based on low-power ultrasound, comprising: a multi-frequency ultrasound emission and echo acquisition device for emitting low-power, multi-frequency ultrasound waves and acquiring reflected echo signals from the skin, fat layer, and bone surface, providing basic data for tissue thickness estimation, bone surface curvature analysis, and sound intensity calculation; a scalp local electrical impedance spectrum acquisition device for acquiring the average impedance values ​​of the skin and fat layers through a multi-electrode array, and performing impedance adjustment weighting factor fitting and ultrasound sound intensity correction; a temperature monitoring and safety protection device for acquiring temperature data of the target area using a high-sensitivity sensor, analyzing the temperature rise curve, determining whether the temperature rise rate exceeds the threshold, and triggering temperature rise protection measures; and a dose control and feedback execution device for real-time comparison of the calculated effective sound intensity value of the hair follicle layer with the sound intensity threshold, calculating the sound intensity correction factor, and adjusting the emission power, beam angle, and focusing area to achieve closed-loop sound intensity output.

[0056] This implementation scheme integrates multiple core devices, including multi-frequency ultrasound emission and echo acquisition, scalp local electrical impedance spectrum acquisition, temperature monitoring and safety protection, and dose regulation and feedback execution, to achieve precise perception of the multi-layered scalp structure, dynamic modeling of acoustic characteristics, and closed-loop intelligent control of sound intensity. It can acquire skin, fat layer, and bone surface tissue parameters in real time and dynamically correct sound intensity output based on multi-modal data fusion, improving its adaptability to individual structural differences. Combined with temperature curve and rate analysis, it provides intelligent early warning and implements temperature control protection to ensure the safety of the treatment process. The dose regulation and feedback mechanism ensures that the sound intensity in the hair follicle layer is adjusted within a safe and effective range, promoting individualized, efficient, and sustained hair regrowth efficacy, and overall improving the device's accuracy, safety, and user experience.

[0057] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0058] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. As those skilled in the art will understand, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A wearable anti-hair loss and hair regrowth monitoring system based on low-power ultrasound, characterized in that, include: The individual structure perception and modeling module is used to collect ultrasound monitoring data in real time and perform data preprocessing on the ultrasound monitoring data; Using preprocessed ultrasound monitoring data, the thickness of the fat layer was assessed and the thickness of the skin layer was calculated, while a curvature estimation model was constructed. The sound field simulation and sound intensity prediction module is used to combine preprocessed ultrasound monitoring data, fat layer thickness, skin layer thickness and curvature estimation model to determine the local ultrasound sound intensity of the hair follicle layer, perform graded ultrasound control based on the local ultrasound sound intensity determination result of the hair follicle layer, and calculate the sound intensity correction factor. The individualized adaptive control module is used to update the sound wave emission power according to the sound intensity correction factor, and to collect temperature data in real time. The temperature data is used to assess the local temperature rise safety and to implement temperature rise protection measures based on the local temperature rise safety. The monitoring feedback and system self-learning module is used to continuously monitor ultrasound monitoring data, local ultrasound intensity judgment results of hair follicle layer and local temperature rise safety, and perform scalp condition analysis feedback to achieve algorithm and threshold optimization.

2. The wearable anti-hair loss and hair regrowth monitoring system based on low-power ultrasound according to claim 1, characterized in that, The specific process of real-time acquisition of ultrasound monitoring data and data preprocessing of ultrasound monitoring data is as follows: After the user wears the device and it fits properly, multi-frequency ultrasound is emitted perpendicularly along the normal direction and the echo signal is collected. The sound wave emission power, ultrasound frequency, beam angle and transducer emission surface diameter are recorded. At the same time, a uniform timestamp is marked, and the time delay of the reflected echo from the skin layer through the fat layer to the bone interface and back is calculated. Electrical impedance spectrum data of the scalp is collected by an electrode array. Multiple acquisitions are averaged and filtered using a sliding time window to remove outliers and obtain the average impedance value. The ultrasonic monitoring data includes acoustic wave transmission power, ultrasonic frequency, beam angle, transducer emission surface diameter, reflected echo time delay, and average impedance value. These data are then standardized and normalized to construct an ultrasonic monitoring database for storage.

3. The wearable anti-hair loss and hair regrowth monitoring system based on low-power ultrasound according to claim 1, characterized in that, The specific process of assessing fat layer thickness using preprocessed ultrasound monitoring data is as follows: Acquire ultrasound monitoring data, collect average impedance values ​​multiple times based on a sliding time window, and calculate the average value as the impedance reference value; subtract the impedance reference value from the current average impedance value to obtain the impedance difference, multiply the impedance difference by the impedance adjustment weighting factor, take the negative value as the exponent, and perform natural exponential calculation to obtain the impedance suppression factor; add the impedance suppression factor to a constant to obtain the impedance suppression term; multiply the reflected echo time delay by the normalized value of the sound velocity constant in the fat layer to obtain the two-way sound propagation length; divide the two-way sound propagation length by the impedance suppression term and multiply by half to obtain the fat layer thickness.

4. The wearable anti-hair loss and hair regrowth monitoring system based on low-power ultrasound according to claim 1, characterized in that, The specific process for calculating skin layer thickness and constructing a curvature estimation model is as follows: Record the time delay of sound waves propagating to the skin and coupling layer and being reflected back to the probe after the probe emits a pulse. By recording the transmission time and the peak time of the received signal in real time, and combining the envelope extraction and peak detection algorithms, the skin layer reflection wave delay is accurately extracted. The skin layer thickness is obtained by multiplying the skin layer reflection wave delay by the known sound speed constant and dividing by the constant two, and then normalizing the result. By controlling the beam angle and acoustic scanning path, the echo intensity and time difference of bone surface reflections in multiple directions are collected. The multidimensional signal features of echo attenuation slope, waveform broadening and amplitude variance are analyzed. The multidimensional signal features are trained using a lightweight linear regression algorithm to construct a curvature estimation model and output the normalized local curvature of the bone surface. The thickness of the skin layer, the thickness of the fat layer, and the local curvature of the bone surface are combined to construct an individual structural parameter set, which is then stored in the ultrasound monitoring database.

5. The wearable anti-hair loss and hair regrowth monitoring system based on low-power ultrasound according to claim 1, characterized in that, The specific process of determining the local ultrasound intensity of the hair follicle layer by combining pre-processed ultrasound monitoring data, fat layer thickness, skin layer thickness, and curvature estimation model is as follows: The propagation trajectory of ultrasound in the skin, fat and bone structures was calculated using the linear ray tracing method, and the energy concentration of the ultrasound focusing area in the hair follicle layer was evaluated, taking into account the effects of tissue absorption and local curvature of the bone surface on the focus shift. Based on the thickness of the skin layer and the fat layer, and with the center of the hair follicle layer as the target location, the focusing depth is calculated; the ultrasonic frequency is obtained, and the wavelength is obtained by calculating the ratio of the known sound velocity constant to the ultrasonic frequency; the diameter of the transducer's emitting surface is obtained, and the product of the focusing depth and the wavelength is divided by twice the diameter of the transducer's emitting surface to obtain the total radius length. Based on the total radius length, the sound energy focusing area is calculated using the circle area formula and then normalized. Obtain the beam angle and calculate the square of the beam angle cosine to obtain the incident angle correction factor; Simultaneously, the acoustic wave emission power, skin layer thickness, fat layer thickness, and local curvature of the bone surface are obtained; The sound intensity per unit area is obtained by dividing the sound wave emission power by the sound energy focusing area, and the effective incident surface sound intensity factor is obtained by multiplying the sound intensity per unit area by the incident angle correction factor. The skin layer transmission factor is obtained by multiplying the skin layer thickness by the skin layer correction weight factor and taking the negative value as the exponent for natural exponentiation. The fat layer transmission factor is obtained by multiplying the fat layer thickness by the fat layer correction weight factor and taking the negative value as the exponent for natural exponentiation. The tissue composite transmission factor is obtained by multiplying the skin layer transmission factor and the fat layer transmission factor. The square of the local curvature of the bone surface is multiplied by the bone curvature diffraction weighting factor and added to a constant to obtain the bone curvature correction factor. The curvature tissue composite attenuation term is obtained by dividing the tissue composite transmission factor by the bone curvature correction factor; the effective incident surface acoustic intensity factor is multiplied by the curvature tissue composite attenuation term to obtain the effective acoustic intensity value of the hair follicle layer.

6. The wearable anti-hair loss and hair regrowth monitoring system based on low-power ultrasound according to claim 1, characterized in that, The specific process of performing graded ultrasound modulation based on the local ultrasound intensity judgment results of the hair follicle layer and calculating the intensity correction factor is as follows: The effective sound intensity value of the hair follicle layer is compared with the minimum sound intensity threshold and the maximum sound intensity threshold. When the effective sound intensity value of the hair follicle layer is less than or equal to the minimum sound intensity threshold, it is determined that the sound intensity is insufficient. The sound wave transmission power is increased and the increase of the sound wave transmission power is limited, the sound energy focusing area is reduced, and the beam angle is reduced. When the effective acoustic intensity value of the hair follicle layer is greater than the minimum acoustic intensity threshold and less than or equal to the maximum acoustic intensity threshold, it is determined that the acoustic intensity is safe and effective. The current effective acoustic intensity value parameter combination of the hair follicle layer is fixed and recorded as the individual's optimal acoustic intensity parameter set and stored in the ultrasound monitoring database. The effective acoustic intensity value of the hair follicle layer is re-estimated periodically. When the effective acoustic intensity value of the capsule layer is greater than or equal to the acoustic intensity threshold, it is determined to be excessive acoustic intensity. The acoustic wave emission power is reduced, the acoustic energy focusing area is expanded, and the beam emission angle is increased. At the same time, temperature rise protection measures are set: if the historical temperature rise rate exceeds the temperature rise protection threshold, the ultrasound output is suspended, and the user is prompted to check the quality of the coupling layer and replace the colloid. Combining the effective sound intensity value of the hair follicle layer, the minimum sound intensity threshold, and the maximum sound intensity threshold, half of the sum of the minimum sound intensity threshold and the maximum sound intensity threshold is set as the target sound intensity, and the ratio of the effective sound intensity value of the hair follicle layer to the target sound intensity is calculated as the sound intensity correction factor. The effective acoustic intensity value of the hair follicle layer and the acoustic intensity correction factor are stored in the ultrasound monitoring database.

7. The wearable anti-hair loss and hair regrowth monitoring system based on low-power ultrasound according to claim 1, characterized in that, The specific process of updating the sound wave emission power according to the sound intensity correction factor, collecting temperature data in real time, and using the temperature data to assess the safety of local temperature rise is as follows: The system receives the sound intensity correction factor and the current sound wave transmission power, multiplies the sound intensity correction factor by the current sound wave transmission power to obtain the transmission power update value; when the sound intensity is determined to be insufficient or excessive, the system transmits the updated ultrasonic signal to stimulate the generation of sound waves based on the transmission power update value, records the timestamp in real time, and collects temperature data in real time through a temperature sensor; the temperature data is normalized and stored in the ultrasonic monitoring database. Based on the timestamp records, calculate the cumulative temperature rise time from the start of launch to the current moment; The temperature data at the time of ultrasonic signal transmission and the temperature data at the current time are obtained. The difference between the temperature data at the current time and the temperature data at the time of ultrasonic signal transmission is calculated to obtain the temperature rise. Based on the sliding time window, the derivative of the temperature data with respect to time is calculated using the multi-point difference method to obtain the current temperature rise rate. The temperature rise accumulation effect term is obtained by dividing the cumulative temperature rise time by the temperature rise amount; the temperature rise rate response term is obtained by multiplying the current temperature rise rate by the rate response weighting factor; and the temperature rise accumulation effect term and the temperature rise rate response term are added together to obtain the temperature rise adjustment value.

8. The wearable anti-hair loss and hair regrowth monitoring system based on low-power ultrasound according to claim 1, characterized in that, The specific process for implementing temperature rise protection measures based on local temperature rise safety is as follows: The temperature rise adjustment value is calculated in real time. When the temperature rise adjustment value is less than or equal to the temperature rise warning threshold, it is judged that the temperature rise is normal and the temperature rise adjustment value is continuously monitored without the need for protection. When the temperature rise adjustment value is greater than the temperature rise warning threshold, it is judged as excessive temperature rise. The acoustic wave transmission power is adjusted according to the degree of excessive temperature rise. The temperature rise cooling time window is activated. During the temperature rise cooling time window, the ultrasonic transmission is suspended, active air cooling is performed, and the temperature rise adjustment value is continuously calculated until the temperature rise adjustment value is less than or equal to the temperature rise warning threshold. Then, the transmission is allowed to resume and the acoustic wave transmission power is limited. At the same time, the temperature rise adjustment value and temperature rise status are stored in the ultrasonic monitoring database.

9. The wearable anti-hair loss and hair regrowth monitoring system based on low-power ultrasound according to claim 1, characterized in that, The specific process of continuously monitoring ultrasound data, judging the local ultrasound intensity of the hair follicle layer, and assessing the safety of local temperature rise, and analyzing and feeding back the scalp condition, to achieve algorithm and threshold optimization, is as follows: During the monitoring period, ultrasound monitoring data, skin layer thickness, fat layer thickness and local curvature of bone surface, effective acoustic intensity value of hair follicle layer, temperature rise regulation value and temperature rise status are continuously recorded. Before starting treatment, the side miniature camera is activated to take pictures of the scalp monitoring area and transmits them to the application backend via Bluetooth. Based on traditional image processing methods, a lightweight neural network algorithm is integrated to complete hair follicle detection, hair counting and trend analysis, and output a hair growth analysis report. Based on a comprehensive analysis of the hair growth analysis report, the impedance reference value, minimum sound intensity threshold, maximum sound intensity threshold, and temperature rise warning threshold were optimized and updated. The optimized parameters and thresholds are embedded into the initial monitoring values ​​for the next cycle to construct an individualized ultrasound emission scheme. After each monitoring cycle is completed, the effect is re-evaluated to determine whether convergence has been achieved and to make further adjustments. An optimal treatment knowledge base is then constructed for cold start recommendations for new users.

10. A wearable anti-hair loss and hair regrowth monitoring device based on low-power ultrasound, characterized in that, include: The multi-frequency ultrasound transmission and echo acquisition device is used to transmit low-power, multi-frequency ultrasound waves and acquire reflected echo signals from the skin, fat layer and bone surface, providing basic data for tissue thickness estimation, bone surface curvature analysis and sound intensity calculation. A scalp local electrical impedance spectrum acquisition device is used to obtain the average impedance values ​​of the skin and fat layers through a multi-electrode array, and to perform impedance adjustment weighting factor fitting and ultrasound intensity correction. Temperature monitoring and safety protection device is used to collect temperature data of target area using high-sensitivity sensors, analyze temperature rise curve, and determine whether the temperature rise rate exceeds the threshold, triggering temperature rise protection measures. The dose regulation and feedback actuator is used to compare the calculated effective sound intensity value of the hair follicle layer with the sound intensity threshold in real time, calculate the sound intensity correction factor, and adjust the transmission power, beam angle and focusing area to achieve closed-loop sound intensity output.

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