Hygiene product personalized recommendation method and system based on usage state monitoring

Abstract

The application relates to the field of daily necessities, and discloses a sanitary product personalized recommendation method and system based on use state monitoring. The method comprises the following steps: acquiring multi-dimensional physiological data generated by a user during use of a sanitary product; acquiring contact pressure data between the sanitary product and the skin of the user according to skin temperature data, skin humidity data and a pre-established temperature and humidity-pressure mapping library, and determining the activity intensity level of the user according to the acceleration vector module value; matching configuration parameters of the sanitary product from a sanitary product attribute library according to the skin temperature data, the skin humidity data and the contact pressure data; adjusting the configuration parameters according to the activity intensity level; dividing a physiological period stage according to menstrual flow data, and generating a sanitary product recommendation scheme set according to the physiological period stage and the adjusted configuration parameters. The scheme can realize accurate and personalized recommendation of the sanitary product according to the real-time physiological state and use environment of the user.

Description

Technical Field

[0001] This application relates to the field of daily necessities technology, and in particular to a method and system for personalized recommendation of hygiene products based on usage status monitoring. Background Technology

[0002] Feminine hygiene products are daily necessities that directly impact the physical comfort and quality of life of hundreds of millions of users. Therefore, recommending suitable hygiene products to different users is crucial.

[0003] However, current recommendation methods rely primarily on users' static basic information and historical purchase records, making it difficult to accurately capture the real-time interaction between each user's body and the product during actual use. Users' experiences with hygiene products vary greatly depending on their menstrual cycle and activity level; these differences essentially determine the threshold between comfort and discomfort. Existing recommendation systems cannot capture these dynamic details, resulting in recommended products often failing to match users' actual experiences, leading to instances of purchased but abandoned products and repeated trial and error.

[0004] In summary, existing hygiene product recommendation methods are insufficient to combine users' real-time physiological state and usage environment to achieve accurate personalized recommendations. Summary of the Invention

[0005] This application provides a method and system for personalized recommendation of hygiene products based on usage status monitoring, which can achieve accurate personalized recommendations of hygiene products according to the user's real-time physiological status and the dynamic changes in the usage environment.

[0006] According to one aspect of this application, a method for personalized recommendation of hygiene products based on usage status monitoring is provided, comprising:

[0007] Acquire multidimensional physiological data generated by users during the use of hygiene products; wherein, the multidimensional physiological data includes: acceleration vector magnitude, skin temperature data, skin humidity data, and menstrual flow data;

[0008] Based on the skin temperature data, the skin humidity data, and the pre-established temperature-humidity-pressure mapping library, the contact pressure data between the hygiene product and the user's skin is obtained, and the user's activity intensity level is determined based on the acceleration vector magnitude.

[0009] Based on the skin temperature data, the skin humidity data, and the contact pressure data, the configuration parameters of the hygiene products are matched from the hygiene product attribute library; wherein, the configuration parameters include breathability parameters, moisture absorption capacity parameters, and pressure cushioning design parameters;

[0010] The configuration parameters are adjusted according to the activity intensity level;

[0011] The menstrual period is divided into stages based on the menstrual flow data, and a set of recommended hygiene products is generated based on the menstrual period stages and the adjusted configuration parameters.

[0012] Optionally, acquiring the multidimensional physiological data generated by the user during the use of hygiene products includes:

[0013] The skin temperature data and skin humidity data are collected through a sensor array in the skin contact area of ​​the sanitary product.

[0014] The acceleration vector magnitude is acquired using a triaxial accelerometer in the non-skin contact area of ​​the sanitary product.

[0015] The menstrual flow data is obtained through a fluid sensor in the core absorption area of ​​the sanitary product.

[0016] Optionally, the method for pre-establishing the temperature, humidity, and pressure mapping library is as follows:

[0017] When the tester uses the sanitary product, the pressure parameters of the sanitary product in contact with the tester's skin are obtained, and the temperature and humidity parameters corresponding to the skin contact area are recorded simultaneously.

[0018] The temperature, humidity and pressure parameters are mapped using a support vector machine model to obtain the temperature-humidity-pressure mapping library.

[0019] Optionally, before obtaining the contact pressure data between the sanitary product and the user's skin based on the skin temperature data, the skin humidity data, and a pre-established temperature-humidity-pressure mapping library, the method further includes: obtaining ambient temperature data and ambient humidity data during the use of the sanitary product; obtaining the contact pressure data between the sanitary product and the user's skin based on the skin temperature data, the skin humidity data, and the pre-established temperature-humidity-pressure mapping library includes:

[0020] The skin temperature data is compensated based on the ambient temperature data, and the skin humidity data is compensated based on the ambient humidity data;

[0021] The compensated skin temperature data and compensated skin humidity data are used as inputs to the temperature-humidity-pressure mapping library, and the contact pressure data is output.

[0022] Optionally, matching the configuration parameters of the hygiene product from the hygiene product attribute library based on the skin temperature data, the skin humidity data, and the contact pressure data includes:

[0023] Based on the skin temperature data and the skin humidity data, the breathability requirement level of the hygiene product is obtained;

[0024] Based on the skin humidity data, the moisture absorption requirement level of the hygiene product is obtained;

[0025] Based on the contact pressure data, the pressure cushioning strength level of the sanitary product is obtained;

[0026] Based on the breathability requirement level, the moisture absorption requirement level, and the pressure cushioning requirement level, the breathability parameter, the moisture absorption capacity parameter, and the pressure cushioning design parameter of the hygiene product are obtained from the hygiene product attribute library.

[0027] Optionally, the activity intensity level includes low activity intensity, medium activity intensity, and high activity intensity; adjusting the configuration parameters according to the activity intensity level includes:

[0028] When the activity intensity level is the low activity intensity, the air permeability parameter and the moisture absorption capacity parameter are kept unchanged, and the pressure buffer design parameter is reduced.

[0029] When the activity intensity level is medium activity intensity, the air permeability parameter and the moisture absorption capacity parameter remain unchanged, and the pressure buffer design parameter is increased;

[0030] When the activity intensity level is the high activity intensity, increase the air permeability parameter, the moisture absorption capacity parameter, and the pressure buffer design parameter.

[0031] Optionally, generating a set of recommended hygiene products based on the menstrual cycle stage and the adjusted configuration parameters includes:

[0032] Select recommended products suitable for each of the aforementioned menstrual phases from the candidate hygiene products;

[0033] For each of the aforementioned physiological stages, the corresponding weights for air permeability parameters, moisture absorption capacity parameters, and pressure buffer design parameters are configured respectively;

[0034] Based on the weights of the air permeability parameter, the moisture absorption capacity parameter, and the pressure buffer design parameter, calculate the comprehensive suitability score for each of the recommended products.

[0035] The recommended hygiene products are generated based on the comprehensive fit score.

[0036] Optionally, generating the hygiene product recommendation scheme based on the comprehensive fit score includes:

[0037] The comprehensive fit scores of the recommended products under each menstrual cycle stage are sorted in descending order, and the recommended product with the highest score is selected as the target recommended product for that menstrual cycle stage.

[0038] Integrate all the recommended products corresponding to the aforementioned menstrual cycle stages to form a hygiene product recommendation scheme that covers different user traffic stages.

[0039] Optionally, after dividing the menstrual period into stages based on the menstrual flow data and generating a set of recommended hygiene products based on the menstrual period stages and the adjusted configuration parameters, the method further includes:

[0040] Obtain user feedback data after using the hygiene product recommendation scheme, and update the hygiene product recommendation scheme based on the feedback data.

[0041] According to another aspect of this application, a personalized recommendation system for hygiene products based on usage status monitoring is provided, comprising:

[0042] The data acquisition module is used to acquire multidimensional physiological data generated by the user during the use of hygiene products; wherein, the multidimensional physiological data includes: acceleration vector magnitude, skin temperature data, skin humidity data, and menstrual flow data;

[0043] The contact pressure analysis module is used to obtain the contact pressure data between the hygiene product and the user's skin based on the skin temperature data, the skin humidity data and the pre-established temperature-humidity-pressure mapping library, and to determine the user's activity intensity level based on the acceleration vector magnitude.

[0044] The parameter matching module is used to match the configuration parameters of the hygiene products from the hygiene product attribute library based on the skin temperature data, the skin humidity data, and the contact pressure data; wherein the configuration parameters include breathability parameters, moisture absorption capacity parameters, and pressure cushioning design parameters; and to adjust the configuration parameters according to the activity intensity level;

[0045] The hierarchical recommendation decision module is used to divide the menstrual period into stages based on the menstrual flow data, and generate a set of recommended hygiene products based on the menstrual period stages and the adjusted configuration parameters.

[0046] The technical solution of this application derives contact pressure and activity intensity levels from the user's multidimensional physiological data, matches and optimizes the configuration parameters of sanitary products accordingly, and finally generates a personalized set of sanitary product recommendations by combining menstrual flow data to classify menstrual cycle stages. Specifically, matching sanitary product configuration parameters with skin temperature and humidity data and contact pressure data reduces subjective judgment by the user and improves the scientific rigor of the recommendations; dynamically adjusting configuration parameters based on activity intensity levels adapts to the user's comfort and reliability needs in different usage scenarios; and the resulting set of sanitary product recommendations comprehensively covers the differentiated needs of each stage of the menstrual cycle. In summary, this application can achieve accurate and personalized recommendations of sanitary products based on the user's real-time physiological state and usage environment.

[0047] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 A flowchart illustrating a personalized recommendation method for hygiene products based on usage status monitoring, provided for embodiments of this application;

[0050] Figure 2 A flowchart of another personalized recommendation method for hygiene products based on usage status monitoring provided in this application embodiment;

[0051] Figure 3 A flowchart of another personalized recommendation method for hygiene products based on usage status monitoring provided in this application embodiment;

[0052] Figure 4 This is a schematic diagram of the structure of a personalized recommendation system for hygiene products based on usage status monitoring, provided in an embodiment of this application. Detailed Implementation

[0053] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0054] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0055] Figure 1 This is a flowchart illustrating a personalized hygiene product recommendation method based on usage status monitoring, provided as an embodiment of this application. This embodiment is applicable to recommending suitable hygiene products to users, and the method can be executed by a personalized hygiene product recommendation system based on usage status monitoring. Figure 1 As shown, the method includes:

[0056] S110. Obtain multidimensional physiological data generated by users during the use of hygiene products.

[0057] Specifically, multidimensional physiological data refers to multiple bodily indicators collected during the use of hygiene products. This multidimensional physiological data can be collected through smart sensors. These include: acceleration vector magnitude, skin temperature data, skin moisture data, and menstrual flow data.

[0058] Furthermore, the acceleration vector magnitude refers to a quantitative physical parameter characterizing the user's limb activity state. The acceleration vector magnitude can be obtained by collecting acceleration components along the X, Y, and Z axes from a triaxial accelerometer and then calculating it using a vector synthesis algorithm. Skin temperature data refers to the temperature of the skin surface in contact with the sanitary product. Skin humidity data refers to the humidity of the skin surface in contact with the sanitary product. Menstrual flow data refers to the menstrual flow during each time period of the user's menstrual cycle.

[0059] Optionally, skin temperature and skin humidity data can be collected through a sensor array in the skin contact area of ​​the sanitary product; acceleration vector magnitude can be collected through a triaxial accelerometer in the non-skin contact area of ​​the sanitary product; and menstrual flow data can be obtained through a fluid sensor in the core absorption area of ​​the sanitary product.

[0060] For example, a high-density flexible sensor array is embedded in the skin-contact area of ​​the sanitary product. This array includes 64 temperature sensors and 36 humidity sensors, with a spatial resolution of approximately 8mm × 8mm, continuously collecting skin temperature and humidity data from the user's physiological contact area at a base sampling rate of 10Hz. In the non-skin-contact area of ​​the sanitary product, such as the outer layer of the adhesive backing or the outer non-woven fabric at the end of the wings, a miniature triaxial accelerometer is embedded. The sampling rate of this triaxial accelerometer is synchronized with the sensor array, allowing real-time acquisition of acceleration data along the X, Y, and Z axes. An internal algorithm is then used to calculate the acceleration vector magnitude to determine the user's activity intensity. In the core absorbent area of ​​the sanitary product, between the superabsorbent polymer layer and the lint-free paper corresponding to the physiological excretion location, a grid-distributed flexible fluid sensor is embedded. This fluid sensor, based on capacitive detection, has 16 detection nodes with a 12mm spacing between adjacent nodes. By monitoring changes in capacitance between different nodes, the fluid permeation volume and cumulative permeation volume per unit time can be calculated, thereby obtaining menstrual flow data. All data collected by the sensors can be transmitted to a mobile app via a low-power Bluetooth module integrated into the edge of the hygiene product.

[0061] In this embodiment, multidimensional physiological data covers key indicators that affect user comfort with sanitary products. Specifically, the acceleration vector magnitude reflects the user's motion state; skin temperature and skin humidity data reflect the local environment of the area in contact with the sanitary product; and menstrual flow data reflects the characteristics of each stage of the menstrual cycle. Therefore, real-time collection of multidimensional physiological data when users use sanitary products can provide a reliable data foundation for recommending suitable sanitary products to users.

[0062] S120. Based on skin temperature data, skin humidity data, and a pre-established temperature-humidity-pressure mapping library, obtain contact pressure data between the hygiene product and the user's skin, and determine the user's activity intensity level based on the acceleration vector magnitude.

[0063] Specifically, the temperature-humidity-pressure mapping library refers to a pre-built database. It contains reference data on the contact pressure between skin and hygiene products under specific temperature and humidity conditions. Contact pressure data refers to the pressure value generated when a hygiene product comes into contact with a user's skin. Contact pressure can affect user comfort. User activity intensity levels are categorized based on the magnitude of the acceleration vector. For example, user activity levels can include three levels: light activity, moderate activity, and heavy activity.

[0064] For example, the temperature and humidity changes in the area where hygiene products contact the skin can be recorded in advance through experiments under different pressures. For instance, increased pressure can lead to a decrease in the rate of humidity diffusion. Then, a temperature-humidity-pressure mapping library can be established using algorithms such as machine learning. Alternatively, a segmented threshold method can be used to obtain the user's activity intensity level. Specifically, a three-level threshold range for the acceleration vector magnitude can be preset: 0-1.5g corresponds to low-intensity activity, 1.5-3g corresponds to medium-intensity activity, and anything exceeding 3g is considered high-intensity activity.

[0065] In this embodiment, raw multidimensional physiological data is transformed into quantifiable contact pressure and activity intensity levels, providing accurate input for subsequent parameter matching. The contact pressure is measured indirectly, eliminating the need for bulky force sensors, effectively controlling product costs while maintaining the lightweight and portable form factor of the hygiene product. The user's activity intensity classification based on acceleration vector magnitude accurately identifies whether the user is primarily sedentary or physically active, significantly improving the adaptability and matching accuracy of subsequent product recommendations generated based on usage scenarios.

[0066] S130. Based on skin temperature data, skin humidity data, and contact pressure data, match the configuration parameters of the hygiene products from the hygiene product attribute library. These configuration parameters include breathability parameters, moisture absorption capacity parameters, and pressure cushioning design parameters.

[0067] Specifically, the hygiene product attribute database is a pre-built structured database that stores the relationship between the core configuration parameters of different types of hygiene products and their adaptation to human physiological states. The database contains multiple sets of key configuration parameters for hygiene products, such as absorbent core specifications of different thicknesses, surface non-woven fabric materials with different breathability rates, adhesive parameters with different adhesive strengths, and product patterns of different lengths / widths. It also associates these configuration parameters with the optimal physiological state ranges they correspond to, such as "low humidity + medium body temperature" adapting to highly breathable surface materials, and "high-intensity activity" adapting to materials with high absorbency. Breathability parameters characterize the material's air permeability; high breathability improves comfort and reduces stuffiness. Moisture absorption capacity parameters characterize the material's ability to absorb and retain moisture. Moisture absorption capacity directly affects the dryness and comfort of hygiene products. Pressure cushioning design parameters reflect the design characteristics of hygiene products that effectively distribute pressure when in contact with the skin. Pressure cushioning helps reduce discomfort during use.

[0068] In this embodiment of the application, the optimal combination of performance parameters of hygiene products is selected based on the current physiological state, which can transform subjective comfort requirements into objective parameters and avoid relying on user experience for product recommendations.

[0069] S140. Adjust the configuration parameters according to the activity intensity level.

[0070] In this embodiment, the configuration parameters are dynamically adjusted based on the user's activity level, accurately matching the core needs of users in different usage scenarios and avoiding discomfort caused by homogenized parameter settings. For example, for users who are primarily engaged in light activities and spend most of their time indoors, breathability parameters can be enhanced; for users who are primarily engaged in heavy activities and spend most of their time outdoors, pressure cushioning and moisture absorption speed parameters can be optimized, making the user experience of hygiene products more closely aligned with the user's actual usage. Simultaneously, this adjustment method allows for more targeted personalized recommendation sequences, improving the adaptability and rationality of the recommendation results.

[0071] S150. Divide menstrual period into stages based on menstrual flow data, and generate a set of recommended hygiene products based on the menstrual period stages and the adjusted configuration parameters.

[0072] Specifically, the menstrual cycle refers to the different flow stages within a woman's menstrual cycle, typically divided into three phases: early menstruation, mid-cycle, and late menstruation. Early menstruation usually occurs on day 1 of the menstrual cycle, with light menstrual flow. Mid-cycle typically occurs from day 2 to day 4, with menstrual flow gradually increasing to its peak. Late menstruation typically occurs from day 5 to day 6, during which menstrual flow begins to decrease. A set of recommended hygiene products refers to a personalized product recommendation scheme generated based on the user's menstrual cycle stage and corresponding adjustment parameters. This set of recommended hygiene products provides users with suitable hygiene product options tailored to their needs at different stages of their menstrual cycle.

[0073] In this embodiment of the application, menstrual flow data is combined with the time dimension to dynamically identify the user's menstrual cycle stage and generate a set of personalized hygiene product recommendations for each stage, which can meet the differentiated needs of users at different stages of the menstrual cycle.

[0074] The technical solution of this application embodiment derives contact pressure and activity intensity levels from the user's multidimensional physiological data, matches and optimizes the configuration parameters of sanitary products accordingly, and finally generates a personalized set of sanitary product recommendations by combining menstrual flow stages. Specifically, matching sanitary product configuration parameters with skin temperature and humidity data and contact pressure data reduces subjective user judgment and improves the scientific rigor of the recommendations; dynamically adjusting configuration parameters based on activity intensity levels adapts to the user's comfort and reliability needs in different usage scenarios; and the resulting set of sanitary product recommendations comprehensively covers the differentiated needs of each stage of the menstrual cycle. In summary, this application embodiment can achieve accurate and personalized recommendations of sanitary products based on the user's real-time physiological state and usage environment.

[0075] Based on the above embodiments, an optional method for pre-establishing a temperature-humidity-pressure mapping library is as follows: When a test subject uses sanitary products, the pressure parameters of the area in contact between the sanitary products and the test subject's skin are obtained, and the temperature and humidity parameters corresponding to the skin contact area are recorded simultaneously. A support vector machine model is used to establish the mapping relationship between the temperature, humidity, and pressure parameters to obtain the temperature-humidity-pressure mapping library.

[0076] For example, in a laboratory environment, several typical hygiene product samples and several test subjects with different body types and skin types are first selected. Pressure sensors and temperature / humidity sensor arrays are placed on the skin contact surface of each sample. Then, the test subjects wear the sensor-equipped samples and simulate three scenarios: sitting, walking, and running. The temperature, humidity, and pressure data collected by the sensors are continuously recorded, forming a raw dataset. The data in the raw dataset is preprocessed to obtain standardized data. The standardized data is then divided into training and testing sets in a 7:3 ratio. A support vector machine (SVM) model is used, with temperature and humidity as inputs and pressure as the output, and a radial basis function kernel function is configured. The penalty factor C = 1.0 and the kernel function parameter σ = 0.1 are set. After optimizing the parameters through a grid search, the SVM model is iteratively trained on the training set until convergence, and the accuracy is verified on the testing set. Finally, the model is solidified.

[0077] In this embodiment, the pre-established temperature, humidity, and pressure mapping library effectively avoids the problems of rigid pressure sensors being difficult to integrate and prone to failure due to the influence of body fluids. Indirect monitoring of contact pressure is achieved through a flexible temperature and humidity sensor array, balancing the soft and thin characteristics of hygiene products with the reliability of monitoring data, while also ensuring user comfort.

[0078] Figure 2 A flowchart illustrating another personalized recommendation method for hygiene products based on usage status monitoring, provided as an embodiment of this application. Optionally, based on the above embodiments, such as... Figure 2 As shown, the method includes:

[0079] S210. Obtain multidimensional physiological data generated by users during the use of hygiene products.

[0080] S220. Obtain ambient temperature and humidity data during the use of hygiene products.

[0081] Specifically, ambient temperature data refers to the temperature of the environment in which the sanitary napkin is used. Ambient humidity data refers to the humidity level of the environment in which the sanitary napkin is used. Temperature and humidity data can be collected using temperature and humidity sensors located at the edges of the sanitary napkin.

[0082] S230. Compensate for skin temperature data based on ambient temperature data, and compensate for skin humidity data based on ambient humidity data.

[0083] Specifically, temperature compensation can be achieved using the dynamic thermal balance correction method, with the compensation formula as follows:

[0084] Compensated skin temperature = original skin temperature + k × (original skin temperature - ambient temperature data).

[0085] Where k is the temperature environment compensation coefficient. k can be determined first through constant temperature experiments and then dynamically adjusted according to the user's state. For example, if the user is in motion (with a large acceleration vector magnitude), since heat generated by motion dominates the change in skin temperature, the temperature environment compensation coefficient should be appropriately reduced.

[0086] Furthermore, humidity compensation can be achieved using the humidity gradient correction method, with the compensation formula as follows:

[0087] Compensated skin humidity = Original skin humidity - α × (Ambient humidity data - Comfort humidity threshold).

[0088] Here, α represents the humidity compensation coefficient. An initial value for α can be set based on the material of the hygiene product. For example, if the surface layer is made of pure cotton with high moisture absorption and a fast sweat absorption rate, the initial value of α is set to 0.15; if the surface layer is made of non-woven fabric with low moisture absorption and easy sweat residue, the initial value of α is set to 0.08; and if the surface layer is made of breathable mesh material with low moisture absorption and fast breathability, the initial value of α is set to 0.05. The initial value of α is then dynamically adjusted based on the user's condition. For example, if the user is exercising, they will sweat more, and since sweat secretion dominates changes in skin humidity, the humidity compensation coefficient should be appropriately reduced.

[0089] S240. Use the compensated skin temperature data and compensated skin humidity data as input to the temperature-humidity-pressure mapping library, and output contact pressure data.

[0090] Specifically, after compensating for ambient temperature and humidity, skin temperature and humidity data are freed from external factors such as environmental interference and motion, accurately reflecting the local environmental conditions at the skin-hygiene product contact interface. The compensated ambient temperature and humidity data are then input into a pre-established temperature-humidity-pressure mapping library. Relying on the pre-defined quantitative correlation model within this library, the contact pressure in the current scenario can be quickly deduced, effectively solving the problem of directly measuring pressure on thin and lightweight hygiene products.

[0091] S250. Determine the user's activity intensity level based on the acceleration vector magnitude.

[0092] S260. Based on skin temperature data, skin humidity data, and contact pressure data, match the configuration parameters of the hygiene products from the hygiene product attribute library.

[0093] S270. Adjust the configuration parameters according to the activity intensity level.

[0094] S280. Divide menstrual period into stages based on menstrual flow data, and generate a set of recommended hygiene products based on the menstrual period stages and the adjusted configuration parameters.

[0095] The technical solution of this application embodiment compensates for skin temperature and humidity data by using ambient temperature and humidity data during the use of hygiene products. This effectively eliminates interference from environmental fluctuations, avoids distortion of the original data, and ensures that the data input into the mapping library more closely matches the actual contact conditions. Simultaneously, inputting the compensated skin temperature and humidity data into a temperature-humidity-pressure mapping library calibrated based on laboratory standard environments effectively avoids pressure back-calculation errors caused by environmental differences. This provides accurate data support for subsequent initial parameter matching, parameter adjustment, and personalized recommendation sequence generation for hygiene products, ensuring that the final hygiene product recommendation results meet the user's real-time usage needs.

[0096] Figure 3 A flowchart illustrating yet another personalized recommendation method for hygiene products based on usage status monitoring, provided as an embodiment of this application. Based on the above embodiments, as... Figure 3 As shown, optionally, the method includes:

[0097] S310. Obtain multidimensional physiological data generated by users during the use of hygiene products.

[0098] S320: Based on skin temperature data, skin humidity data, and a pre-established temperature-humidity-pressure mapping library, obtain contact pressure data between the hygiene product and the user's skin, and determine the user's activity intensity level based on the acceleration vector magnitude.

[0099] S330. Based on skin temperature data and skin humidity data, obtain the breathability requirement level of the sanitary products; based on skin humidity data, obtain the moisture absorption requirement level of the sanitary products; based on contact pressure data, obtain the pressure cushioning requirement level of the sanitary products.

[0100] Specifically, the breathability level of hygiene products is determined based on skin temperature and skin humidity, with the following criteria: Low breathability is required when skin temperature < 34℃ and skin humidity < 65%RH; medium breathability is required when 34℃ ≤ skin temperature < 36℃ or 65%RH ≤ skin humidity < 75%RH; and high breathability is required when skin temperature ≥ 36℃ or skin humidity ≥ 75%RH. The moisture absorption requirement is also categorized based on skin humidity data: Slight moisture absorption is required when skin humidity < 70%RH; medium moisture absorption is required when 75%RH ≤ skin humidity < 85%RH; and heavy moisture absorption is required when skin humidity ≥ 85%RH. Finally, different cushioning requirements are categorized based on contact pressure: Low pressure cushioning is required when contact pressure < 5kPa; medium pressure cushioning is required when contact pressure ≤ 10kPa; and high pressure cushioning is required when contact pressure ≥ 10kPa.

[0101] In this embodiment, the user's breathability needs are dynamically assessed based on skin temperature and humidity data, which can effectively solve the problems of stuffiness and eczema caused by insufficient breathability of traditional sanitary products; the moisture absorption needs are divided into levels based on skin humidity data, which can accurately balance the contradiction between the absorbency performance and product volume of sanitary products; the pressure buffering needs are determined based on contact pressure, which can effectively reduce friction between the user and the sanitary products and the problem of skin indentation, and comprehensively ensure the user's comfort.

[0102] S340. Based on the intensity levels of breathability, moisture absorption, and pressure cushioning requirements, respectively, obtain the breathability parameters, moisture absorption capacity parameters, and pressure cushioning design parameters of the hygiene products from the hygiene product attribute database. For example, the core breathability parameter includes the breathability rate, where a low breathability requirement corresponds to a breathability rate of 800-1200 mm / s, a medium breathability requirement corresponds to a breathability rate of 1200-2000 mm / s, and a high breathability requirement corresponds to a breathability rate greater than 2000 mm / s. The moisture absorption capacity parameter corresponds to the absorption capacity index of the hygiene products, where a light moisture absorption requirement corresponds to an absorption capacity of 10-15 g / g, a moderate moisture absorption requirement corresponds to an absorption capacity of 15-25 g / g, and a heavy moisture absorption requirement corresponds to an absorption capacity greater than 25 g / g. For each pressure cushioning requirement strength level, the corresponding material mechanical parameters and structural design parameters will be retrieved: low pressure cushioning requirements correspond to ordinary cotton layer parameters with a compression rebound rate of 40%-50%, medium pressure cushioning requirements correspond to basic protective barrier parameters with a rebound rate of 50%-70%, and high pressure cushioning requirements correspond to foam padding structural parameters with a rebound rate of >70%.

[0103] In the embodiments of this application, corresponding breathability parameters, moisture absorption capacity parameters, and pressure cushioning design parameters are adapted for different levels of breathability, moisture absorption, and pressure cushioning requirements. This can effectively avoid problems such as stuffiness, leakage, and friction marks caused by traditional "one-size-fits-all" designs, and improve user comfort.

[0104] S350, adjust the configuration parameters according to the activity intensity level.

[0105] Optionally, the user's activity intensity level can include low, medium, and high activity intensity. The configuration parameters are adjusted according to the activity intensity level, including: when the activity intensity level is low, maintaining the breathability and moisture absorption parameters unchanged, and decreasing the pressure cushioning design parameters; when the activity intensity level is medium, maintaining the breathability and moisture absorption parameters unchanged, and increasing the pressure cushioning design parameters; and when the activity intensity level is high, increasing the breathability, moisture absorption, and pressure cushioning design parameters.

[0106] Specifically, low activity intensity reflects users who are likely to spend long periods in a sedentary office environment. By maintaining the breathability and moisture absorption parameters unchanged, the product's dryness during prolonged contact with the skin can be ensured, avoiding stuffiness and discomfort. Simultaneously, reducing pressure cushioning design parameters improves the fit between the product and the skin, reducing the feeling of foreign objects caused by redundant structures. Medium activity intensity reflects users who may be engaged in light physical labor for extended periods. Maintaining the breathability and moisture absorption parameters unchanged can meet the user's basic needs. Targeted improvement of pressure cushioning design parameters effectively counteracts friction and pressure between the product and the user's body during minor movements, preventing leakage due to product movement. High activity intensity reflects users who are likely engaged in activities such as running or brisk walking. Simultaneously improving breathability, moisture absorption, and pressure cushioning design parameters allows for rapid dissipation of heat generated during exercise, reducing sweat buildup, and meeting the increased absorption needs of menstrual blood flow during exercise, while also reducing the risk of product shifting due to vigorous physical activity.

[0107] In this embodiment, by using a dynamic adjustment strategy for the configuration parameters of hygiene products based on the user's activity intensity level, the performance parameters such as breathability and moisture absorption, which are mutually restrictive, can be optimized and balanced. This not only achieves precise matching between product performance and user needs in different usage scenarios, effectively solving the problem of functional redundancy or insufficient performance caused by the fixed parameters of traditional hygiene products adapting to all scenarios, but also avoids increased product costs and decreased user experience caused by functional redundancy while ensuring the core usage needs of each scenario.

[0108] S360, Divide menstrual cycle into stages based on menstrual flow data.

[0109] S370. Select recommended products suitable for each stage of the menstrual cycle from the candidate hygiene products.

[0110] Specifically, selecting recommended products from the candidate sanitary products is equivalent to initial screening for suitable sanitary products for each stage of the menstrual cycle. For example, at the beginning of menstruation, lightweight sanitary products with low absorbency can be selected as recommended options. In the middle of menstruation, products with high absorbency and good breathability can be selected as recommended options. In the later stages of menstruation, products with moderate absorbency but strong antibacterial properties can be selected as recommended options.

[0111] S380: For each physiological stage, the corresponding weights of air permeability parameter, moisture absorption capacity parameter, and pressure buffer design parameter are configured.

[0112] For example, in the early stages of menstruation, breathability should be prioritized, with a high breathability weight to alleviate the stuffiness and discomfort of the initial period. In the middle stages, as menstrual flow increases, a high moisture-wicking weight ensures leak-proof performance while also meeting basic cushioning needs. In the later stages, as flow decreases, a balanced match between breathability and moisture-wicking weights can meet the user's comfort requirements. Therefore, parameters can be configured as follows: In the early stages of menstruation, the breathability parameter weight is 0.6, the moisture-wicking capacity parameter weight is 0.3, and the pressure cushioning design parameter weight is 0.1. In the middle stages of menstruation, the breathability parameter weight is 0.3, the moisture-wicking capacity parameter weight is 0.5, and the pressure cushioning design parameter weight is 0.2. In the later stages of menstruation, the breathability parameter weight is 0.5, the moisture-wicking capacity parameter weight is 0.4, and the pressure cushioning design parameter weight is 0.1.

[0113] In this embodiment, the parameters of sanitary products are configured according to the menstrual cycle stage, which enables dynamic adaptation of the performance of sanitary products to the core needs of different stages of the menstrual cycle, thus overcoming the limitations of traditional fixed parameters.

[0114] S390. Calculate the comprehensive suitability score for each recommended product based on the weights of the air permeability parameter, the moisture absorption capacity parameter, and the pressure buffer design parameter.

[0115] Specifically, the overall fit score can be calculated using the following formula:

[0116] S = W1 × P1 + W2 × P2 + W3 × P3

[0117] Where S is the overall fit score. W1 is the weight of the breathability parameter, W2 is the weight of the moisture absorption capacity parameter, and W3 is the weight of the pressure cushioning design parameter, and W1+W2+W3=1. P1 is the standardized value of the product's breathability parameter, P2 is the standardized value of the product's moisture absorption capacity parameter, and P3 is the standardized value of the product's pressure cushioning design parameter. For example, if the standardized values ​​of a recommended product during the middle of the menstrual cycle are P1=0.4, P2=0.8, and P3=0.5, with corresponding weights W1=0.3, W2=0.5, and W3=0.2, then the overall fit score S=0.3×0.4+0.5×0.8+0.2×0.5=0.62.

[0118] In this embodiment, the comprehensive adaptation score can quantify the suitability of the recommended product, eliminating the limitations of subjective user judgment.

[0119] S300: Generate a hygiene product recommendation scheme based on the comprehensive compatibility score.

[0120] For example, generating a hygiene product recommendation scheme based on the comprehensive compatibility score includes: sorting the recommended products for each menstrual cycle in descending order of their comprehensive compatibility scores, selecting the recommended product with the highest score as the target recommended product for that menstrual cycle. All recommended products corresponding to each menstrual cycle are then integrated to form a hygiene product recommendation scheme covering different user activity stages.

[0121] In this embodiment, the comprehensive adaptation score is calculated based on objective indicators such as user physiological data and product parameters, rather than subjective experience judgments, making the recommendation results more scientific and credible. Compared to manual recommendations or brand marketing-driven recommendations, this method is more aligned with users' real needs and increases user acceptance of the recommendation scheme.

[0122] The technical solution of this application matches the breathability, moisture absorption capacity, and pressure cushioning design parameters of hygiene products based on skin temperature, humidity, and contact pressure data. These configuration parameters are adjusted differentially at different activity intensity levels (low, medium, and high), and parameter weights are assigned according to different stages of the menstrual cycle to calculate a comprehensive fit score. Then, the scores are sorted, target products for each stage are selected, and a full-cycle solution is integrated. This technical solution can accurately match the user's physiological sensations and activity levels, quantifying the product's fit and thus avoiding the subjectivity of recommendations.

[0123] Based on the above embodiments, optionally, after dividing the menstrual period into stages according to menstrual flow data and generating a set of recommended hygiene products based on the menstrual period stages and adjusted configuration parameters, the method further includes: obtaining feedback data from users after using the recommended hygiene products, and updating the recommended hygiene products based on the feedback data.

[0124] For example, users can directly evaluate the comfort, anti-leakage effect, and traffic matching of recommended products, and support quantitative scoring from 1 to 5 points; then, by integrating these subjective feedbacks and objectively collected data, the weights of the corresponding configuration parameters are adjusted in reverse for recommended products with low scores, thereby regenerating an optimized recommendation scheme.

[0125] In this embodiment of the application, by collecting quantitative feedback from users on comfort, leak prevention effect, and traffic matching, and combining it with objective monitoring data, the recommended solution can more accurately match the user's physical preferences and actual needs, avoiding the disconnect between the solution and the real usage scenario.

[0126] Figure 4 This is a schematic diagram illustrating the structure of a personalized hygiene product recommendation system based on usage status monitoring, provided as an embodiment of this application. Figure 4 As shown, the system includes:

[0127] The data acquisition module 410 is used to acquire multidimensional physiological data generated by the user during the use of hygiene products; the multidimensional physiological data includes: acceleration vector magnitude, skin temperature data, skin humidity data and menstrual flow data.

[0128] The contact pressure analysis module 420 is used to obtain contact pressure data between the sanitary products and the user's skin based on skin temperature data, skin humidity data and a pre-established temperature-humidity-pressure mapping library, and to determine the user's activity intensity level based on the acceleration vector magnitude.

[0129] The parameter matching module 430 is used to match the configuration parameters of hygiene products from the hygiene product attribute library based on skin temperature data, skin humidity data, and contact pressure data. The configuration parameters include breathability parameters, moisture absorption capacity parameters, and pressure cushioning design parameters. The configuration parameters are also adjusted according to the activity intensity level.

[0130] The hierarchical recommendation decision module 440 is used to divide menstrual period stages based on menstrual flow data and generate a set of recommended hygiene products based on the menstrual period stages and adjusted configuration parameters.

[0131] The personalized hygiene product recommendation system based on usage status monitoring provided in this application can execute the personalized hygiene product recommendation method based on usage status monitoring provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of the method.

[0132] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this application can be achieved, and this is not limited herein.

[0133] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for personalized recommendation of hygiene products based on usage status monitoring, characterized in that, include: Acquire multidimensional physiological data generated by users during the use of hygiene products; wherein, the multidimensional physiological data includes: acceleration vector magnitude, skin temperature data, skin humidity data, and menstrual flow data; Based on the skin temperature data, the skin humidity data, and a pre-established temperature-humidity-pressure mapping library, the contact pressure data between the hygiene product and the user's skin is obtained, and the user's activity intensity level is determined based on the acceleration vector magnitude. The method for pre-establishing the temperature-humidity-pressure mapping library is as follows: When the tester uses the sanitary product, the pressure parameters of the sanitary product in contact with the tester's skin are obtained, and the temperature and humidity parameters corresponding to the skin contact area are recorded simultaneously. The temperature, humidity and pressure parameters are mapped using a support vector machine model to obtain the temperature-humidity-pressure mapping library. Based on the skin temperature data, the skin humidity data, and the contact pressure data, the configuration parameters of the hygiene products are matched from the hygiene product attribute library; wherein, the configuration parameters include breathability parameters, moisture absorption capacity parameters, and pressure cushioning design parameters; The configuration parameters are adjusted according to the activity intensity level; Based on the menstrual flow data, menstrual periods are divided into stages, and a set of recommended hygiene products is generated based on the menstrual period stages and the adjusted configuration parameters. Before obtaining the contact pressure data between the sanitary product and the user's skin based on the skin temperature data, the skin humidity data, and a pre-established temperature-humidity-pressure mapping library, the method further includes: obtaining the ambient temperature data and ambient humidity data during the use of the sanitary product; obtaining the contact pressure data between the sanitary product and the user's skin based on the skin temperature data, the skin humidity data, and the pre-established temperature-humidity-pressure mapping library includes: The skin temperature data is compensated based on the ambient temperature data, and the skin humidity data is compensated based on the ambient humidity data; The compensated skin temperature data and compensated skin humidity data are used as inputs to the temperature-humidity-pressure mapping library, and the contact pressure data is output.

2. The personalized recommendation method for hygiene products based on usage status monitoring according to claim 1, characterized in that, The acquisition of multidimensional physiological data generated by users during the use of hygiene products includes: The skin temperature data and skin humidity data are collected through a sensor array in the skin contact area of ​​the sanitary product. The acceleration vector magnitude is acquired using a triaxial accelerometer in the non-skin contact area of ​​the sanitary product. The menstrual flow data is obtained through a fluid sensor in the core absorption area of ​​the sanitary product.

3. The personalized recommendation method for hygiene products based on usage status monitoring according to claim 1, characterized in that, The step of matching the configuration parameters of the hygiene product from the hygiene product attribute library based on the skin temperature data, the skin humidity data, and the contact pressure data includes: Based on the skin temperature data and the skin humidity data, the breathability requirement level of the hygiene product is obtained; Based on the skin humidity data, the moisture absorption strength requirement level of the hygiene products is obtained; Based on the contact pressure data, the required pressure cushioning strength level of the sanitary product is obtained; Based on the breathability requirement level, the moisture absorption strength requirement level, and the pressure cushioning strength requirement level, the breathability parameter, the moisture absorption capacity parameter, and the pressure cushioning design parameter of the hygiene product are obtained from the hygiene product attribute library.

4. The personalized recommendation method for hygiene products based on usage status monitoring according to claim 3, characterized in that, The activity intensity levels include low activity intensity, medium activity intensity, and high activity intensity; adjusting the configuration parameters according to the activity intensity levels includes: When the activity intensity level is the low activity intensity, the air permeability parameter and the moisture absorption capacity parameter are kept unchanged, and the pressure buffer design parameter is reduced. When the activity intensity level is medium activity intensity, the air permeability parameter and the moisture absorption capacity parameter remain unchanged, and the pressure buffer design parameter is increased; When the activity intensity level is the high activity intensity, the air permeability parameter, the moisture absorption capacity parameter, and the pressure buffer design parameter are increased.

5. The personalized recommendation method for hygiene products based on usage status monitoring according to claim 1, characterized in that, The step of generating a set of recommended hygiene products based on the menstrual cycle stage and the adjusted configuration parameters includes: Select recommended products suitable for each of the aforementioned menstrual phases from the candidate hygiene products; For each of the aforementioned physiological stages, the corresponding weights for air permeability parameters, moisture absorption capacity parameters, and pressure buffer design parameters are configured respectively; Based on the weights of the air permeability parameter, the moisture absorption capacity parameter, and the pressure buffer design parameter, calculate the comprehensive suitability score for each of the recommended products. The recommended hygiene products are generated based on the comprehensive fit score.

6. The personalized recommendation method for hygiene products based on usage status monitoring according to claim 5, characterized in that, The step of generating the hygiene product recommendation scheme based on the comprehensive fit score includes: The comprehensive fit scores of the recommended products under each menstrual cycle stage are sorted in descending order, and the recommended product with the highest score is selected as the target recommended product for that menstrual cycle stage. Integrate all the recommended products corresponding to the aforementioned menstrual cycle stages to form a hygiene product recommendation scheme that covers different user traffic stages.

7. The personalized recommendation method for hygiene products based on usage status monitoring according to claim 1, characterized in that, After dividing the menstrual period into stages based on the menstrual flow data, and generating a set of recommended hygiene products based on the menstrual period stages and the adjusted configuration parameters, the method further includes: Obtain feedback data from users after they use the hygiene product recommendation scheme, and update the hygiene product recommendation scheme based on the feedback data.

8. A personalized recommendation system for hygiene products based on usage status monitoring, used to implement the personalized recommendation method for hygiene products based on usage status monitoring as described in any one of claims 1 to 7, characterized in that, include: The data acquisition module is used to acquire multidimensional physiological data generated by the user during the use of hygiene products; wherein, the multidimensional physiological data includes: acceleration vector magnitude, skin temperature data, skin humidity data, and menstrual flow data; The contact pressure analysis module is used to obtain the contact pressure data between the hygiene product and the user's skin based on the skin temperature data, the skin humidity data and the pre-established temperature-humidity-pressure mapping library, and to determine the user's activity intensity level based on the acceleration vector magnitude. The parameter matching module is used to match the configuration parameters of the hygiene products from the hygiene product attribute library based on the skin temperature data, the skin humidity data, and the contact pressure data; wherein the configuration parameters include breathability parameters, moisture absorption capacity parameters, and pressure cushioning design parameters; and to adjust the configuration parameters according to the activity intensity level; The hierarchical recommendation decision module is used to divide the menstrual period into stages based on the menstrual flow data, and generate a set of recommended hygiene products based on the menstrual period stages and the adjusted configuration parameters.

Images