Skin sensor communication method and device and terminal equipment

Abstract

The invention provides a skin sensor communication method and device and terminal equipment, and is suitable for the technical field of data processing, and the method comprises the steps: carrying out the time sequence feature extraction according to a plurality of pieces of skin physiological monitoring information and a plurality of pieces of skin sensor communication parameter information, obtaining a plurality of pieces of skin physiological monitoring time sequence feature information and a plurality of pieces of skin sensor communication parameter time sequence feature information; and performing matching processing according to the multiple pieces of skin physiological monitoring time sequence feature information and the multiple pieces of skin sensor communication parameter time sequence feature information, and generating multiple pieces of skin sensor communication parameter combination information for communication of multiple skin sensors corresponding to the multiple pieces of skin sensor identification information. According to the application, the transmission stability and accuracy of the skin physiological monitoring information are effectively improved, and communication interference when multiple sensors work simultaneously is avoided, so that the real-time performance and effectiveness of skin condition monitoring are ensured.

Description

Technical Field

[0001] This application belongs to the field of data processing technology, and in particular relates to skin sensor communication methods, devices and terminal equipment. Background Technology

[0002] With the increasing demands in fields such as medical and health monitoring and human-computer interaction, skin sensor technology has developed rapidly, and wireless, flexible, and multimodal skin sensors have become the mainstream direction in the industry. Leveraging advancements in low-power wireless communication protocols and flexible electronic materials, skin sensors can achieve long-term, non-invasive acquisition of skin physiological monitoring information.

[0003] In existing technologies, fixed skin sensors are configured to monitor skin health, and communication data errors are detected through methods such as CRC check. When errors accumulate to a certain level, adaptive baud rate adjustment is initiated to optimize the serial communication parameters of the sensor.

[0004] However, existing technologies are prone to problems such as multi-sensor communication interference, insufficient data transmission stability, and poor compatibility between physiological monitoring information and communication parameters. Summary of the Invention

[0005] In view of this, embodiments of this application provide a skin sensor communication method, apparatus, and terminal device, aiming to solve the problems of insufficient adaptability of communication parameters to physiological monitoring needs, susceptibility to interference in multi-sensor communication, and poor stability and accuracy of data transmission in the prior art.

[0006] The first aspect of this application provides a skin sensor communication method, including: Based on the multiple skin physiological monitoring information and multiple skin sensor communication parameter information, time-series feature extraction is performed to obtain multiple skin physiological monitoring time-series feature information and multiple skin sensor communication parameter time-series feature information. Matching and processing are performed on the multiple skin physiological monitoring time-series feature information and the multiple skin sensor communication parameter time-series feature information to generate multiple skin sensor communication parameter combination information, so that multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

[0007] A second aspect of this application provides a skin sensor communication device, comprising: The information acquisition module is used to acquire multiple skin sensor identification information, multiple skin physiological monitoring information, and multiple skin sensor communication parameter information; the skin sensor identification information, skin physiological monitoring information, and skin sensor communication parameter information are in one-to-one correspondence. The temporal feature information generation module is used to extract temporal features based on the multiple skin physiological monitoring information and the multiple skin sensor communication parameter information to obtain multiple skin physiological monitoring temporal feature information and multiple skin sensor communication parameter temporal feature information. The skin sensor communication parameter combination information generation module is used to perform matching processing based on the multiple skin physiological monitoring time-series feature information and the multiple skin sensor communication parameter time-series feature information to generate multiple skin sensor communication parameter combination information, so that multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

[0008] A third aspect of this application provides a terminal device, the terminal device including a memory and a processor, the memory storing a computer program executable on the processor, the processor executing the computer program to implement the steps of the skin sensor communication method as described in the first aspect above.

[0009] A fourth aspect of this application provides a computer-readable storage medium comprising: storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the skin sensor communication method as described in the first aspect above.

[0010] The beneficial effects of this application embodiment compared with the prior art are: this application ensures that the communication parameters of the skin sensor are compatible with the temporal characteristics of the skin physiological monitoring data, effectively improves the stability and accuracy of skin sensor data transmission, avoids communication interference when multiple skin sensors work together, ensures efficient transmission of skin physiological monitoring data, and provides reliable communication support for accurate monitoring and analysis of skin health status. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the 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.

[0012] Figure 1 This is a schematic diagram illustrating the implementation process of the skin sensor communication method provided in Embodiment 1 of this application; Figure 2 This is a schematic diagram illustrating the implementation process of the skin sensor communication method provided in Embodiment 2 of this application; Figure 3 This is a schematic diagram illustrating the implementation process of the skin sensor communication method provided in Embodiment 3 of this application; Figure 4This is a schematic diagram illustrating the implementation process of the skin sensor communication method provided in Embodiment 4 of this application; Figure 5 This is a schematic diagram illustrating the implementation process of the skin sensor communication method provided in Embodiment 5 of this application; Figure 6 This is a schematic diagram illustrating the implementation process of the skin sensor communication method provided in Embodiment Six of this application; Figure 7 This is a schematic diagram illustrating the implementation process of the skin sensor communication method provided in Embodiment 7 of this application; Figure 8 This is a schematic diagram of the structure of the skin sensor communication device provided in the embodiments of this application; Figure 9 This is a schematic diagram of the terminal device provided in the embodiments of this application. Detailed Implementation

[0013] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0014] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0015] Figure 1 A flowchart illustrating the implementation of the skin sensor communication method provided in Embodiment 1 of this application is shown, and is described in detail below: Step S101: Obtain multiple skin sensor identification information, multiple skin physiological monitoring information, and multiple skin sensor communication parameter information; the skin sensor identification information, skin physiological monitoring information, and skin sensor communication parameter information correspond one-to-one.

[0016] In this embodiment, skin sensor identification information refers to a unique identifier used to distinguish different skin sensors, which may include the sensor's serial number, unique hardware address, etc. This information can be directly obtained by reading the skin sensor's built-in storage module. Skin physiological monitoring information refers to various physiological data reflecting the skin's condition collected by the skin sensor, which may include skin moisture content, skin temperature, skin pH, transepidermal water loss, etc., and can be collected in real time by the skin sensor's detection module. Skin sensor communication parameter information refers to communication-related parameters that affect the data transmission quality and efficiency of the skin sensor, which may include transmission rate, transmission power, communication frequency band, modulation method, etc., and can be read through the skin sensor's communication module configuration interface or obtained through interaction with the associated communication receiving device. In the process of obtaining the above three types of information, an information association mapping table is established to bind each skin sensor identification information with the corresponding skin physiological monitoring information and skin sensor communication parameter information, thereby ensuring that the skin sensor identification information, skin physiological monitoring information, and skin sensor communication parameter information correspond one-to-one.

[0017] Step S102: Based on the multiple skin physiological monitoring information and the multiple skin sensor communication parameter information, perform time-series feature extraction to obtain multiple skin physiological monitoring time-series feature information and multiple skin sensor communication parameter time-series feature information.

[0018] In this embodiment, the acquired multiple skin physiological monitoring information and multiple skin sensor communication parameter information can be preprocessed first. The two types of raw data corresponding to each skin sensor identification information are divided into continuous time series segments according to a fixed time interval. At the same time, outliers and noise interference in the data are removed to ensure the continuity and reliability of the data. Subsequently, time-series features are extracted from the skin physiological monitoring information. Statistical features within each time series segment are calculated, including mean, variance, maximum, minimum, peak frequency, and slope of data change trends. These features reflect the regularity and stability of skin physiological indicators over time. These statistical features are then integrated to generate multiple time-series features for skin physiological monitoring. For the time-series feature extraction of skin sensor communication parameters, the same time series segmentation rules as those for skin physiological monitoring are used. Features such as mean, fluctuation amplitude, rate of change, and stationarity index of communication parameters within each time series segment are calculated. These features reflect the dynamic changes of communication parameters over time. These features are then integrated to generate multiple time-series features for skin sensor communication parameters. This ensures that the time-series features for skin physiological monitoring and the time-series features for skin sensor communication parameters corresponding to each skin sensor identification information accurately match the temporal dimension characteristics of their original data.

[0019] Step S103: Match the multiple skin physiological monitoring time-series feature information and the multiple skin sensor communication parameter time-series feature information to generate multiple skin sensor communication parameter combination information, so that the multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

[0020] In this embodiment, a time-series feature matching rule can be established first. This rule can be preset by the user and includes a correlation threshold for judging the two types of time-series features and a standard for the fit of feature change trends. Then, based on this matching rule, the skin physiological monitoring time-series feature information corresponding to each skin sensor identification information is compared one by one with the time-series feature information of multiple skin sensor communication parameters. The skin sensor communication parameter time-series feature information with a correlation higher than the preset threshold and a change trend fit that meets the standard is selected. Then, the original skin sensor communication parameter information corresponding to the selected skin sensor communication parameter time-series feature information is extracted. Combined with the communication requirements of the skin sensor, different communication parameters are combined. During the combination process, the communication protocol specifications must be followed to avoid parameter conflicts. Then, the validity of the combined parameter set is verified. Combinations that do not meet the communication standards and the working requirements of the skin sensor are eliminated, and combinations that meet the requirements are retained to generate multiple skin sensor communication parameter combination information. The generated multiple skin sensor communication parameter combination information is then associated with the corresponding skin sensor identification information so that multiple skin sensors corresponding to multiple skin sensor identification information can communicate.

[0021] The skin sensor communication method provided in this application ensures that the communication parameters of the skin sensor are compatible with the temporal characteristics of skin physiological monitoring data, effectively improving the stability and accuracy of skin sensor data transmission, avoiding communication interference when multiple skin sensors work together, ensuring efficient transmission of skin physiological monitoring data, and providing reliable communication support for accurate monitoring and analysis of skin health status.

[0022] Figure 2 The flowchart illustrating the implementation of the skin sensor communication method provided in Embodiment 2 of this application is shown. Its difference from Embodiment 1 described above lies in: The skin physiological monitoring information includes skin moisture content monitoring information, skin elasticity monitoring information, skin temperature monitoring information, and skin sebum secretion monitoring information; The skin sensor communication parameter information includes skin sensor communication frequency information, skin sensor communication transmission power information, skin sensor communication time slot allocation information, and skin sensor communication modulation parameter information; Step S102 specifically includes: Step S201: Based on the preset skin physiological monitoring information sampling time sequence window length and the preset skin physiological monitoring information sampling time sequence window sliding step size, the multiple skin moisture content monitoring information, multiple skin elasticity monitoring information, multiple skin temperature monitoring information and multiple skin sebum secretion monitoring information are sampled and processed to obtain multiple skin moisture content monitoring time sequence information, multiple skin elasticity monitoring time sequence information, multiple skin temperature monitoring time sequence information and multiple skin sebum secretion monitoring time sequence information.

[0023] In this embodiment, the preset sampling time series window length for skin physiological monitoring information can be manually preset to determine the time range covered by a single sampling, ensuring that the changing characteristics of skin physiological monitoring information within a reasonable time dimension can be captured. The preset sliding step size of the skin physiological monitoring information sampling time series window can also be manually preset to control the time interval between two adjacent sampling windows, balancing the integrity of the sampling data and processing efficiency. Furthermore, for multiple skin moisture content monitoring information, multiple skin elasticity monitoring information, multiple skin temperature monitoring information, and multiple skin sebum secretion monitoring information, sampling windows are set according to the above-mentioned two preset parameters. Data segments of corresponding lengths are sequentially extracted from the time series of various types of original monitoring information. Then, the integrity of each extracted data segment is checked, and segments with missing data are removed. The segments that pass the check are then arranged in chronological order to generate multiple skin moisture content monitoring time series information, multiple skin elasticity monitoring time series information, multiple skin temperature monitoring time series information, and multiple skin sebum secretion monitoring time series information, thereby ensuring that various types of skin physiological monitoring time series information can accurately reflect the time change trajectory of the corresponding monitoring indicators.

[0024] Step S202: Calculate the average values ​​of the multiple skin moisture content monitoring time series information, multiple skin elasticity monitoring time series information, multiple skin temperature monitoring time series information, and multiple skin sebum secretion monitoring time series information, respectively, to obtain the average values ​​of the multiple skin moisture content monitoring time series information, the multiple skin elasticity monitoring time series information, the multiple skin temperature monitoring time series information, and the multiple skin sebum secretion monitoring time series information.

[0025] In this embodiment, for the generated multiple skin moisture content monitoring time series information, the values ​​of all data points included in each time series information are statistically analyzed one by one. Then, the average level of all data point values ​​within each time series information is calculated to obtain the corresponding skin moisture content monitoring time series mean information. Subsequently, using the same calculation method, the mean values ​​of multiple skin elasticity monitoring time series information, multiple skin temperature monitoring time series information, and multiple skin sebum secretion monitoring time series information are calculated respectively to obtain multiple skin elasticity monitoring time series mean information, multiple skin temperature monitoring time series mean information, and multiple skin sebum secretion monitoring time series mean information. Thus, through mean calculation, the core numerical characteristics of various skin physiological monitoring time series information within the corresponding time window are extracted.

[0026] Step S203: Calculate the variances of the multiple skin moisture content monitoring time series information, multiple skin elasticity monitoring time series information, multiple skin temperature monitoring time series information, and multiple skin sebum secretion monitoring time series information respectively, to obtain the variance information of the multiple skin moisture content monitoring time series information, the multiple skin elasticity monitoring time series information, the multiple skin temperature monitoring time series information, and the multiple skin sebum secretion monitoring time series information.

[0027] In this embodiment, for multiple skin moisture content monitoring time series information, the mean value information of skin moisture content monitoring time series corresponding to each time series information is first obtained. Then, the deviation between the value of each data point in each time series information and the corresponding mean value information is calculated one by one. Then, each deviation is squared. Then, the average level of all squared deviations in each time series information is calculated to obtain the corresponding skin moisture content monitoring time series variance information. Then, the same calculation method is used to calculate the variance of multiple skin elasticity monitoring time series information, multiple skin temperature monitoring time series information, and multiple skin sebum secretion monitoring time series information respectively, to obtain multiple skin elasticity monitoring time series variance information, multiple skin temperature monitoring time series variance information, and multiple skin sebum secretion monitoring time series variance information in turn. Thus, by calculating the variance, the degree of fluctuation of various skin physiological monitoring time series information within the corresponding time window is quantified, supplementing the discrete features that the mean information fails to reflect.

[0028] Step S204: Based on the time-series average information of multiple skin moisture content monitoring, multiple time-series average information of multiple skin elasticity monitoring, multiple time-series average information of multiple skin temperature monitoring, multiple time-series average information of multiple skin sebum secretion monitoring, multiple time-series variance information of multiple skin moisture content monitoring, multiple time-series variance information of multiple skin elasticity monitoring, multiple time-series variance information of multiple skin temperature monitoring, and multiple time-series variance information of multiple skin sebum secretion monitoring, multiple time-series variance information of skin physiological monitoring time-series characteristic information are obtained.

[0029] In this embodiment, a time-series feature integration rule is first established. This rule can be pre-set by the user, clarifying the association methods and integration logic of various mean and variance information. Then, for each time window, the time-series mean information of skin moisture content monitoring, skin elasticity monitoring, skin temperature monitoring, and skin sebum secretion monitoring is associated and bound with the time-series variance information of skin moisture content monitoring, skin elasticity monitoring, skin temperature monitoring, and skin sebum secretion monitoring. Subsequently, the bound information is standardized to unify the data dimensions. Then, the standardized information is integrated into a comprehensive feature set in a preset order to generate the skin physiological monitoring time-series feature information for the corresponding time window. Thus, through the integration of multi-dimensional mean and variance information, the time-series features of the skin physiological state within each time window are comprehensively characterized, ensuring that multiple skin physiological monitoring time-series feature information can fully cover the core time-series attributes of various skin physiological indicators.

[0030] Step S205: Based on the preset sampling timing window length and the preset sliding step size of the skin sensor communication parameter sampling timing window, the multiple skin sensor communication frequency information, multiple skin sensor communication transmit power information, multiple skin sensor communication time slot allocation information, and multiple skin sensor communication modulation parameter information are sampled to obtain multiple skin sensor communication frequency timing information, multiple skin sensor communication transmit power timing information, multiple skin sensor communication time slot allocation timing information, and multiple skin sensor communication modulation parameter timing information.

[0031] In this embodiment, the preset sampling time window length for skin sensor communication parameters can be manually preset to determine the time range of communication parameter acquisition covered by a single sampling, ensuring that the dynamic changes of skin sensor communication parameters within the effective time dimension can be captured. The preset sliding step size of the skin sensor communication parameter sampling time window can also be manually preset to control the time interval between two adjacent communication parameter sampling windows, balancing the representativeness of the sampled data with the efficiency of subsequent processing. Therefore, for multiple skin sensor communication frequency information, multiple skin sensor communication transmit power information, multiple skin sensor communication time slot allocation information, and multiple skin sensor communication modulation parameter information, sampling windows are set according to the two preset parameters mentioned above. Data segments of corresponding lengths are sequentially extracted from the time series of various original communication parameter information. Each extracted data segment is then validated, and segments with abnormal parameters are removed. The validated segments are then arranged in chronological order to generate multiple skin sensor communication frequency timing information, multiple skin sensor communication transmit power timing information, multiple skin sensor communication time slot allocation timing information, and multiple skin sensor communication modulation parameter timing information, thereby ensuring that the timing information of various skin sensor communication parameters accurately reflects the time change patterns of the corresponding communication parameters.

[0032] Step S206: Calculate the average values ​​of the communication frequency timing information, the communication transmission power timing information, the communication time slot allocation timing information, and the modulation parameter timing information of the multiple skin sensors respectively, to obtain the average values ​​of the communication frequency timing information, the communication transmission power timing information, the communication time slot allocation timing information, and the modulation parameter timing information of the multiple skin sensors.

[0033] In this embodiment, for the generated multiple skin sensor communication frequency timing information, the values ​​of all communication frequency data points contained in each timing information are statistically analyzed one by one. Then, the average level of all data point values ​​in each timing information is calculated to obtain the corresponding skin sensor communication frequency timing mean information. Subsequently, the same calculation method is used to calculate the mean of multiple skin sensor communication transmission power timing information, multiple skin sensor communication time slot allocation timing information, and multiple skin sensor communication modulation parameter timing information, respectively, to obtain the mean information of multiple skin sensor communication transmission power timing, multiple skin sensor communication time slot allocation timing, and multiple skin sensor communication modulation parameter timing. Thus, through mean calculation, the core numerical characteristics of various skin sensor communication parameter timing information within the corresponding time window are extracted.

[0034] Step S207: Calculate the variances of the communication frequency timing information, the transmission power timing information, the time slot allocation timing information, and the modulation parameter timing information of the multiple skin sensors respectively, to obtain the communication frequency timing variance information, the transmission power timing variance information, the time slot allocation timing variance information, and the modulation parameter timing variance information of the multiple skin sensors.

[0035] In this embodiment, for the time-series information of multiple skin sensor communication frequencies, the mean time-series information of the skin sensor communication frequencies corresponding to each time-series information is first obtained. Then, the deviation between the value of each communication frequency data point in each time-series information and the corresponding mean information is calculated one by one. Then, each deviation is squared. Then, the average level of all squared deviations in each time-series information is calculated to obtain the corresponding skin sensor communication frequency time-series variance information. Then, using the same calculation method, the variance is calculated for the time-series information of multiple skin sensor communication transmission power, multiple skin sensor communication time slot allocation, and multiple skin sensor communication modulation parameters, respectively. The time-series variance information of multiple skin sensor communication transmission power, multiple skin sensor communication time slot allocation, and multiple skin sensor communication modulation parameters is obtained in sequence. Thus, by calculating the variance, the fluctuation degree of various skin sensor communication parameter time-series information within the corresponding time window is quantified, supplementing the discrete feature dimension missing in the mean information.

[0036] Step S208: Based on the average timing information of the communication frequency of the multiple skin sensors, the average timing information of the transmission power of the multiple skin sensors, the average timing information of the time slot allocation of the multiple skin sensors, the average timing information of the modulation parameters of the multiple skin sensors, the time-series variance information of the communication frequency of the multiple skin sensors, the time-series variance information of the transmission power of the multiple skin sensors, the time-series variance information of the time slot allocation of the multiple skin sensors, and the time-series variance information of the modulation parameters of the multiple skin sensors, the timing feature information of the communication parameters of the multiple skin sensors is obtained.

[0037] In this embodiment, a communication parameter timing feature integration rule is first established. This rule can be preset by the user, clearly defining the association logic and integration order of the mean and variance information of various communication parameters. Then, for the various skin sensor communication parameter data corresponding to each time window, the corresponding skin sensor communication frequency timing mean information, skin sensor communication transmission power timing mean information, skin sensor communication time slot allocation timing mean information, skin sensor communication modulation parameter timing mean information, and skin sensor communication frequency timing variance information, skin sensor communication transmission power timing variance information, skin sensor communication time slot allocation timing variance information, and skin sensor communication modulation parameter timing variance information are associated and bound. Then, the bound information is standardized to unify the data dimensions. Finally, the standardized information is integrated into a comprehensive feature set in a preset order to generate the skin sensor communication parameter timing feature information for the corresponding time window. Thus, by integrating the mean and variance information of multi-dimensional communication parameters, the timing features of skin sensor communication parameters within each time window are comprehensively characterized, ensuring that the timing feature information of multiple skin sensor communication parameters can completely cover the core timing attributes of various communication parameters.

[0038] The skin sensor communication method provided in this application embodiment makes the generated multiple skin physiological monitoring time-series feature information and multiple skin sensor communication parameter time-series feature information fit the actual monitoring and communication needs. It can generate multiple skin sensor communication parameter combination information that is more suitable for various skin physiological monitoring scenarios, effectively enhance the stability and reliability of skin sensor data transmission, ensure the communication efficiency when multiple skin sensors work together, and provide strong communication technology support for the refined monitoring and analysis of skin health status.

[0039] Figure 3 The flowchart illustrating the implementation of the skin sensor communication method provided in Embodiment 3 of this application is shown. The difference between this method and Embodiment 1 is that step S103 specifically includes: Step S301: Perform feature alignment processing based on the multiple skin physiological monitoring time-series feature information and the multiple skin sensor communication parameter time-series feature information to obtain multiple skin physiological monitoring time-series feature alignment information and multiple skin sensor communication parameter time-series feature alignment information.

[0040] In this embodiment, the core basis for feature alignment is determined first by the consistency of the time dimension. That is, it is ensured that each skin physiological monitoring time-series feature information and the corresponding skin sensor communication parameter time-series feature information are within the same time window range. Then, the timestamp information contained in multiple skin physiological monitoring time-series feature information and multiple skin sensor communication parameter time-series feature information is extracted. The two types of feature information with the same timestamp or within the same time interval are initially associated. Then, the dimension of the initially associated feature information is verified. If there is a mismatch in feature dimensions, it is adjusted by filling in missing dimensions or pruning redundant dimensions to ensure that the dimensions of the two types of feature information are completely consistent. Then, the dimension-adjusted skin physiological monitoring time-series feature information and skin sensor communication parameter time-series feature information are bound together to generate multiple skin physiological monitoring time-series feature alignment information and multiple skin sensor communication parameter time-series feature alignment information, thereby ensuring the accuracy and effectiveness of subsequent weighted fusion processing.

[0041] Step S302: Based on the preset skin physiological monitoring feature weight coefficients and the preset skin sensor communication parameter feature weight coefficients, the multiple skin physiological monitoring time sequence feature alignment information and the multiple skin sensor communication parameter time sequence feature alignment information are weighted and fused to obtain multiple skin sensor communication parameter feature fusion information.

[0042] In this embodiment, the preset skin physiological monitoring feature weight coefficients can be manually preset and are used to characterize the importance of different skin physiological monitoring time-series feature alignment information in the fusion process. They can be set according to the priority requirements of the skin monitoring scenario. The preset skin sensor communication parameter feature weight coefficients can also be manually preset and are used to characterize the fusion weight of different skin sensor communication parameter time-series feature alignment information. They can be adjusted according to communication quality requirements. Then, each skin physiological monitoring time-series feature alignment information is associated with the corresponding preset skin physiological monitoring feature weight coefficient, and each skin sensor communication parameter time-series feature alignment information is associated with the corresponding preset skin sensor communication parameter feature weight coefficient. Then, the two types of feature information after association weight are calculated and processed respectively. Finally, the two types of feature information after processing are integrated according to the preset fusion logic to generate multiple skin sensor communication parameter feature fusion information, thereby realizing the effective fusion of the two types of feature information and strengthening the representation ability of key features.

[0043] Step S303: Calculate the cosine similarity based on the fusion information of the communication parameter features of the multiple skin sensors to obtain the similarity information of the communication parameter features of the multiple skin sensors.

[0044] In this embodiment, any two of the multiple skin sensor communication parameter feature fusion information are first selected as a comparison object. All feature fusion information is traversed sequentially to generate multiple comparison combinations. Then, for each comparison combination, the similarity between the two skin sensor communication parameter feature fusion information is measured by the calculation logic of cosine similarity. This calculation process can reflect the angle relationship between the two types of feature fusion information in the feature space. The higher the similarity, the smaller the angle. Then, the calculation results of each comparison combination are recorded to generate the corresponding skin sensor communication parameter feature similarity information. Then, the above process is repeated to complete the similarity calculation of all comparison combinations, and finally, multiple skin sensor communication parameter feature similarity information is obtained.

[0045] Step S304: Based on the skin sensor communication parameter feature similarity information and the preset skin sensor communication parameter feature similarity threshold, the multiple skin sensor communication parameter feature similarity information is filtered and calculated to obtain multiple skin sensor communication parameter combination information, so that multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

[0046] In this embodiment, the preset skin sensor communication parameter feature similarity threshold can be manually preset to define the effective feature similarity range, filter out feature combinations that meet the fusion requirements, and then compare each skin sensor communication parameter feature similarity information with the preset skin sensor communication parameter feature similarity threshold one by one. The original skin sensor communication parameter information corresponding to the feature fusion information with similarity information greater than or equal to the threshold is retained. Then, the retained skin sensor communication parameter information is combined. The combination process strictly follows the communication protocol specifications to avoid conflicts between different parameters. Then, the validity of the combined parameter set is verified, and parameter combinations that do not meet the working requirements of the skin sensor are eliminated. Then, the parameter combinations that pass the verification are sorted to generate multiple skin sensor communication parameter combination information, and associated with multiple corresponding skin sensor identification information, so that multiple skin sensors corresponding to multiple skin sensor identification information can communicate.

[0047] The skin sensor communication method provided in this application generates more accurate and adaptable combination information of multiple skin sensor communication parameters, improves the stability and reliability of skin sensor data transmission, ensures the high efficiency of multiple skin sensors working together, and provides a more solid communication technology guarantee for the accuracy of skin health status monitoring.

[0048] Figure 4 The flowchart illustrating the implementation of the skin sensor communication method provided in Embodiment 4 of this application is shown. The difference between this method and Embodiment 3 above is that step S302 specifically includes: Step S401: Based on the preset skin physiological monitoring feature weight coefficients, the alignment information of the multiple skin physiological monitoring time sequence features is weighted and calculated to obtain the weighted information of the multiple skin physiological monitoring time sequence features.

[0049] In this embodiment, the preset skin physiological monitoring feature weight coefficient can be preset manually, and its value is determined according to the importance of different skin physiological monitoring indicators. For example, in the skin health monitoring scenario, a higher weight coefficient can be set for the time-series feature alignment information related to skin moisture content monitoring. Then, the value of each feature dimension in each skin physiological monitoring time-series feature alignment information is weighted by the corresponding preset skin physiological monitoring feature weight coefficient to obtain the weighted value of each feature dimension. Then, the weighted values ​​of all feature dimensions in the same skin physiological monitoring time-series feature alignment information are integrated to generate the corresponding skin physiological monitoring time-series feature weighted information. Then, the above process is repeated to complete the weighted calculation of all multiple skin physiological monitoring time-series feature alignment information to obtain multiple skin physiological monitoring time-series feature weighted information.

[0050] Step S402: Based on the preset skin sensor communication parameter feature weighting coefficients, the time sequence feature alignment information of the multiple skin sensor communication parameters is weighted to obtain the time sequence feature weighted information of the multiple skin sensor communication parameters.

[0051] In this embodiment, the preset skin sensor communication parameter feature weight coefficients can be preset manually. The setting is based on the degree of influence of different communication parameters on data transmission quality. For example, a higher weight can be set for the timing feature alignment information related to the transmission power of skin sensor communication that affects transmission stability. Then, the feature dimension values ​​of each skin sensor communication parameter timing feature alignment information are calculated with the corresponding preset skin sensor communication parameter feature weight coefficients to obtain the weighted values ​​of each dimension. Then, all weighted dimension values ​​of the same skin sensor communication parameter timing feature alignment information are integrated to generate the corresponding skin sensor communication parameter timing feature weighted information. Then, the weighting processing of all multiple skin sensor communication parameter timing feature alignment information is completed in sequence to obtain multiple skin sensor communication parameter timing feature weighted information.

[0052] Step S403: Normalize the weighted information of the multiple skin physiological monitoring time-series features and the weighted information of the multiple skin sensor communication parameter time-series features to obtain normalized information of the multiple skin physiological monitoring time-series features and the normalized information of the multiple skin sensor communication parameter time-series features.

[0053] In this embodiment, the target range for normalization processing is first determined. This range can be a fixed interval preset by the user to eliminate the dimensional differences between different feature dimensions. Then, for multiple skin physiological monitoring time-series feature weighted information, the proportion of each feature dimension value in each weighted information relative to the maximum and minimum values ​​of all values ​​in that dimension is calculated one by one, and it is converted to the preset target range to obtain the skin physiological monitoring time-series feature normalized information corresponding to each skin physiological monitoring time-series feature weighted information. Then, the same normalization processing method is used to process the time-series feature weighted information of multiple skin sensor communication parameters, unifying the values ​​of each feature dimension to the same target range, generating multiple skin sensor communication parameter time-series feature normalized information. Thus, through normalization processing, it is ensured that the two types of feature information are on the same numerical scale.

[0054] Step S404: Summation calculation is performed based on the normalized information of multiple skin physiological monitoring time-series features and the normalized information of multiple skin sensor communication parameter time-series features to obtain the fusion information of multiple skin sensor communication parameter features.

[0055] In this embodiment, each normalized information of skin physiological monitoring time-series features is first associated with the corresponding normalized information of skin sensor communication parameters time-series features to ensure that the two belong to the same time window and the same feature data corresponding to the same skin sensor identification information. Then, the two types of normalized information after association are summed dimension by dimension. That is, the value of a certain dimension in the normalized information of skin physiological monitoring time-series features is added to the value of the same dimension in the normalized information of skin sensor communication parameters time-series features to obtain the fused value of that dimension. Then, the fused values ​​of all dimensions are integrated to generate the skin sensor communication parameter feature fusion information of the corresponding group. Then, the summation calculation of all associated groups is completed in sequence to finally obtain multiple skin sensor communication parameter feature fusion information, realizing the deep fusion of the two types of feature information.

[0056] The skin sensor communication method provided in this application improves the reliability and relevance of the skin sensor communication parameter feature fusion information, making the subsequent generated multiple skin sensor communication parameter combinations more suitable for actual skin monitoring and communication needs, and effectively enhancing the stability and efficiency of skin sensor data transmission.

[0057] Figure 5 The flowchart illustrating the implementation of the skin sensor communication method provided in Embodiment 5 of this application is shown. The difference between this method and Embodiment 3 above is that step S304 specifically includes: Step S501: Determine whether the skin sensor communication parameter feature similarity information is less than or equal to a preset skin sensor communication parameter feature similarity threshold; if yes, proceed to step S502; if no, proceed to step S503.

[0058] In this embodiment, the preset skin sensor communication parameter feature similarity threshold can be manually preset and used as a criterion to distinguish the degree of correlation between skin sensor communication parameter feature fusion information, clarify the processing direction corresponding to different similarity information, and then compare each skin sensor communication parameter feature similarity information with the preset skin sensor communication parameter feature similarity threshold one by one. The subsequent processing path is determined by the comparison result. If the similarity information of a certain skin sensor communication parameter feature is less than or equal to the threshold, it means that the correlation between the two skin sensor communication parameter feature fusion information is low and splicing processing needs to be performed; if it is greater than the threshold, it means that the correlation between the two is high and separation processing needs to be performed.

[0059] Step S502: The multiple skin sensor communication parameter feature fusion information corresponding to the skin sensor communication parameter feature similarity information are spliced ​​together to obtain skin sensor communication parameter feature splicing information.

[0060] In this embodiment, the core logic of the splicing process is first clarified as follows: integrating the fusion information of multiple skin sensor communication parameter features with low correlation according to the feature dimension order to ensure complete information preservation. Then, the fusion information of multiple skin sensor communication parameter features corresponding to the skin sensor communication parameter feature similarity information is extracted. The number and order of the dimensions of each feature fusion information are checked to ensure dimension matching during splicing. Then, the feature dimensions of multiple skin sensor communication parameter feature fusion information are sequentially connected to form a complete comprehensive feature set. Finally, the integrity of the spliced ​​feature set is checked, and redundant or conflicting dimensions that occur during the splicing process are removed. Finally, the spliced ​​information of skin sensor communication parameter features is generated, thereby achieving effective integration of low correlation feature fusion information.

[0061] Step S503: Separate the multiple skin sensor communication parameter feature fusion information corresponding to the skin sensor communication parameter feature similarity information to obtain multiple skin sensor communication parameter feature separation information.

[0062] In this embodiment, the goal of the separation process is first determined to be to split the fusion information of multiple skin sensor communication parameter features with high correlation, restore the original feature dimensions of each feature fusion information, and then analyze the origin of each feature dimension for the fusion information of multiple skin sensor communication parameter features corresponding to the skin sensor communication parameter feature similarity information, clarify the original feature fusion information corresponding to each feature dimension, and then split the comprehensive feature set into multiple independent feature subsets according to the dimensional division rules of the original feature fusion information. Each subset corresponds to a core feature of the original skin sensor communication parameter feature fusion information. Then, the validity of each feature subset after splitting is verified to ensure that the split feature information is complete and without missing parts, and finally, the separation information of multiple skin sensor communication parameter features is obtained, thereby achieving accurate splitting of highly correlated feature fusion information.

[0063] Step S504: Based on the splicing information of the multiple skin sensor communication parameter features and the separation information of the multiple skin sensor communication parameter features, obtain the multiple skin sensor communication parameter combination information, so that the multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

[0064] In this embodiment, all generated spliced ​​information and separated information of multiple skin sensor communication parameter features are first summarized to establish an association mapping between feature information and skin sensor identification information, ensuring that each feature information can be traced back to the corresponding skin sensor. Then, the original skin sensor communication parameter information corresponding to each feature information is extracted. Combined with the communication protocol specifications of the skin sensor, different types of communication parameters are combined. During the combination process, parameter conflicts are strictly avoided to ensure that the combined parameters meet the working requirements of the skin sensor. Then, the validity of all combined parameter sets is verified, and parameter combinations that do not conform to the communication standard or cannot adapt to the working state of the skin sensor are eliminated. Then, the parameter combinations that pass the verification are sorted to generate multiple skin sensor communication parameter combination information, and they are bound to the corresponding multiple skin sensor identification information, so that multiple skin sensors corresponding to multiple skin sensor identification information can communicate, ensuring the adaptability and reliability of communication parameters.

[0065] The skin sensor communication method provided in this application improves the adaptability and rationality of the subsequent generation of multiple skin sensor communication parameter combinations, effectively enhances the stability and efficiency of skin sensor data transmission, and provides more reliable communication technology support for the accuracy of skin health status monitoring.

[0066] Figure 6 The flowchart illustrating the implementation of the skin sensor communication method provided in Embodiment Six of this application is shown. The difference between this method and Embodiment Three above is that step S304 specifically includes: Step S601: Determine whether the skin sensor communication parameter feature similarity information is greater than or equal to the preset skin sensor communication parameter feature similarity threshold; if yes, proceed to step S602; if no, proceed to step S603.

[0067] In this embodiment, the preset skin sensor communication parameter feature similarity threshold can be manually preset. It is used to define the effective association range of skin sensor communication parameter feature fusion information, clarify the screening criteria for candidate skin sensor communication parameter information, and then compare each skin sensor communication parameter feature similarity information with the preset skin sensor communication parameter feature similarity threshold one by one. Based on the comparison results, the subsequent processing flow is planned: if a certain skin sensor communication parameter feature similarity information is greater than or equal to the threshold, it means that the corresponding skin sensor communication parameter feature fusion information has a high correlation and strong feature effectiveness, and can be directly used as candidate information; if it is less than the threshold, it means that the correlation is low, and the feature effectiveness needs to be strengthened through merging processing, thereby laying the foundation for screening high-quality candidate parameter information.

[0068] Step S602: The fusion information of multiple skin sensor communication parameter features corresponding to the skin sensor communication parameter feature similarity information is used as multiple candidate skin sensor communication parameter information.

[0069] In this embodiment, when the similarity information of skin sensor communication parameters is greater than or equal to a preset threshold, the fusion information of the corresponding multiple skin sensor communication parameters is directly determined as multiple candidate skin sensor communication parameters. Then, the determined multiple candidate skin sensor communication parameters are marked, and their corresponding skin sensor communication parameter feature similarity information and skin sensor identification information are recorded to ensure the traceability of candidate information. Subsequently, the marked multiple candidate skin sensor communication parameters are preliminarily verified to eliminate information with missing feature dimensions or abnormal parameters, thereby ensuring the basic quality of the multiple candidate skin sensor communication parameters.

[0070] Step S603: Merge multiple skin sensor communication parameter feature fusion information corresponding to the skin sensor communication parameter feature similarity information to obtain candidate skin sensor communication parameter information.

[0071] In this embodiment, the core logic of the merging process is to integrate the feature fusion information of multiple skin sensor communication parameters with low correlation, extract the core effective features, and then extract the feature fusion information of multiple skin sensor communication parameter features corresponding to the feature similarity information of skin sensor communication parameters. The dimensions of each feature fusion information are aligned to ensure that the dimensions are consistent during merging. Then, the aligned feature dimensions are merged and calculated by using a feature weighted summation method. The weights can be preset according to the importance of the features. The preset weights can be manually preset to generate a comprehensive feature set. Then, redundant features are removed from the merged feature set, and the core effective features are retained. Finally, candidate skin sensor communication parameter information is obtained, thereby realizing the value mining and effective utilization of low correlation feature fusion information.

[0072] Step S604: Based on the communication parameter information of the multiple candidate skin sensors and the preset skin sensor stability calculation function, calculate the stability function value information of the communication parameters of the multiple candidate skin sensors.

[0073] In this embodiment, the preset skin sensor stability calculation function can be manually preset and is used to quantify and evaluate the communication stability corresponding to the communication parameters of candidate skin sensors. Its input is the communication parameters of the candidate skin sensors, and its output is a function value characterizing the stability. Furthermore, each candidate skin sensor communication parameter is input into the preset skin sensor stability calculation function one by one. Through the function's calculation logic, combined with related indicators such as the fluctuation range of communication parameters, transmission delay, and bit error rate, the corresponding stability quantification result is obtained. Then, each quantification result is associated and labeled with the corresponding candidate skin sensor communication parameter, generating multiple candidate skin sensor communication parameter stability function value information.

[0074] Step S605: Based on the communication parameter information of the multiple candidate skin sensors, the stability function value information of the communication parameters of the multiple candidate skin sensors, and the preset stability threshold information of the communication parameters of the candidate skin sensors, a combination of communication parameters of the multiple skin sensors is obtained, so that the multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

[0075] In this embodiment, the preset stability threshold information for candidate skin sensor communication parameters can be manually preset. This threshold defines the acceptable range of stability for candidate skin sensor communication parameters, filters out candidate information that meets communication stability requirements, and then compares the stability function value of each candidate skin sensor communication parameter with the preset stability threshold information. Candidate skin sensor communication parameters whose stability function values ​​meet the threshold requirements are retained. The original skin sensor communication parameters corresponding to the retained candidate skin sensor communication parameters are then extracted. Combining the communication requirements and protocol specifications of the skin sensor, different communication parameters are combined to avoid parameter conflicts. The combined parameter set is then validated, eliminating combinations that do not meet the working requirements of the skin sensor. The validated parameter combinations are then organized to generate multiple skin sensor communication parameter combinations, which are associated with corresponding skin sensor identification information. This allows multiple skin sensors corresponding to multiple skin sensor identification information to communicate, ensuring communication stability and reliability.

[0076] The skin sensor communication method provided in this application selects stable and compatible communication parameter combinations, effectively improving the reliability and stability of skin sensor communication parameter combination information, ensuring data transmission efficiency when multiple skin sensors work together, and providing a solid communication guarantee for the accuracy of skin health status monitoring.

[0077] Figure 7 The flowchart illustrating the implementation of the skin sensor communication method provided in Embodiment Seven of this application is shown. The difference between this method and Embodiment Six is ​​that step S605 specifically includes: Step S701: Determine whether the stability function value of the candidate skin sensor communication parameter is less than or equal to the preset stability threshold value of the candidate skin sensor communication parameter; if yes, proceed to step S702; if no, proceed to step S703.

[0078] In this embodiment, the preset stability threshold information for candidate skin sensor communication parameters can be manually preset and used as the core standard for judging whether the candidate skin sensor communication parameters meet the communication stability requirements. This clarifies the boundary for screening qualified candidate information. Then, the stability function value information of each candidate skin sensor communication parameter is compared one by one with the preset stability threshold information. The selection of candidate information is determined by the comparison result: if a certain stability function value information is less than or equal to the threshold, it means that the corresponding candidate skin sensor communication parameter information is not stable enough and cannot meet the reliable communication requirements; if it is greater than the threshold, it means that the stability meets the standard and can be used as the basis for subsequent combinations, thereby achieving accurate screening of candidate parameter information.

[0079] Step S702: Delete the candidate skin sensor communication parameter information corresponding to the candidate skin sensor communication parameter stability function value information.

[0080] In this embodiment, when the stability function value of the candidate skin sensor communication parameter is less than or equal to a preset threshold, the corresponding candidate skin sensor communication parameter is directly removed from the candidate set. The deleted candidate skin sensor communication parameter, its corresponding skin sensor identification information, and stability function value information are recorded to form a deletion log, which facilitates subsequent traceability and analysis. The candidate set after deletion is then updated and organized to ensure the integrity and order of the remaining candidate information, thereby eliminating unstable candidate parameter information and improving the quality of subsequent parameter combinations.

[0081] Step S703: The candidate skin sensor communication parameter information corresponding to the candidate skin sensor communication parameter stability function value information is used as the selected skin sensor communication parameter information.

[0082] In this embodiment, when the stability function value of the candidate skin sensor communication parameter is greater than a preset threshold, the corresponding candidate skin sensor communication parameter information is marked as the selected skin sensor communication parameter information. Then, the marked selected skin sensor communication parameter information is subjected to secondary verification to check the completeness of its feature dimensions and the validity of its parameters to ensure that no abnormal information is missed. Subsequently, the selected skin sensor communication parameter information that passes the secondary verification is classified and organized according to the skin sensor identification information to establish a classification index.

[0083] Step S704: Based on the communication parameter information of the multiple selected skin sensors, obtain the combination information of multiple skin sensor communication parameters, so that the multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

[0084] In this embodiment, based on the classification index, multiple selected skin sensor communication parameter information corresponding to each skin sensor identification information is first extracted. Then, combined with the skin sensor communication protocol specifications and actual communication requirements, multiple selected skin sensor communication parameter information corresponding to the same skin sensor identification information is combined. During the combination process, conflicts between different parameters are strictly avoided to ensure that the combined parameters can be normally adapted to the skin sensor communication module. Then, the validity and compatibility of each combined parameter set are verified, and combinations that do not conform to the working parameter range of the skin sensor and cannot achieve normal communication are eliminated. Then, the parameter combinations that pass the verification are associated and bound according to the skin sensor identification information to generate multiple skin sensor communication parameter combination information, so that multiple skin sensors corresponding to multiple skin sensor identification information can communicate, ensuring that each skin sensor can achieve efficient data transmission based on stable and adapted communication parameters.

[0085] The skin sensor communication method provided in this application improves the stability and adaptability of multiple skin sensor communication parameter combinations, effectively reduces the probability of transmission failures during skin sensor communication, ensures continuous and reliable transmission of skin physiological monitoring data, and provides strong communication technology support for continuous and accurate monitoring of skin health status.

[0086] Corresponding to the method in the above embodiments, Figure 8 A structural block diagram of the skin sensor communication device provided in the embodiments of this application is shown. For ease of explanation, only the parts related to the embodiments of this application are shown. Figure 8 The example skin sensor communication device can be the subject of the skin sensor communication method provided in the aforementioned embodiment 1.

[0087] Reference Figure 8 The skin sensor communication device includes: The information acquisition module 810 is used to acquire multiple skin sensor identification information, multiple skin physiological monitoring information, and multiple skin sensor communication parameter information; the skin sensor identification information, skin physiological monitoring information, and skin sensor communication parameter information are in one-to-one correspondence. The temporal feature information generation module 820 is used to extract temporal features based on the multiple skin physiological monitoring information and the multiple skin sensor communication parameter information to obtain multiple skin physiological monitoring temporal feature information and multiple skin sensor communication parameter temporal feature information. The skin sensor communication parameter combination information generation module 830 is used to perform matching processing based on the multiple skin physiological monitoring time-series feature information and the multiple skin sensor communication parameter time-series feature information to generate multiple skin sensor communication parameter combination information, so that multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

[0088] The process by which each module in the skin sensor communication device provided in this application implements its respective function can be found in the foregoing. Figure 1 The description of Embodiment 1 shown will not be repeated here.

[0089] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0090] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0091] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0092] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0093] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance. It should also be understood that although the terms "first," "second," etc., are used in the text to describe various elements in some embodiments of this application, these elements should not be limited by these terms. These terms are merely used to distinguish one element from another. For example, a first table may be named a second table, and similarly, a second table may be named a first table, without departing from the scope of the various described embodiments. Both the first table and the second table are tables, but they are not the same table.

[0094] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0095] The skin sensor communication method provided in this application can be applied to terminal devices such as mobile phones, tablets, wearable devices, in-vehicle devices, laptops, super mobile personal computers, netbooks, and personal digital assistants. This application does not impose any restrictions on the specific type of terminal device.

[0096] Figure 9 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. For example... Figure 9 As shown, the terminal device 9 of this embodiment includes: at least one processor 90 ( Figure 9 (Only one is shown in the image) A memory 91 stores a computer program 92 that can run on the processor 90. When the processor 90 executes the computer program 92, it implements the steps in the various skin sensor communication method embodiments described above, for example... Figure 1 Steps S101 to S103 are shown. Alternatively, when the processor 90 executes the computer program 92, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 8 The functions of modules 810 to 830 are shown.

[0097] The terminal device 9 can be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor 90 and a memory 91. Those skilled in the art will understand that... Figure 9 This is merely an example of terminal device 9 and does not constitute a limitation on terminal device 9. It may include more or fewer components than shown, or combine certain components, or different components. For example, the terminal device may also include input transmission devices, network access devices, buses, etc.

[0098] The processor 90 may be a central processing unit, or it may be other general-purpose processors, digital signal processors, application-specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0099] In some embodiments, the memory 91 may be an internal storage unit of the terminal device 9, such as a hard disk or memory of the terminal device 9. The memory 91 may also be an external storage device of the terminal device 9, such as a plug-in hard disk, smart memory card, secure digital card, flash memory card, etc., equipped on the terminal device 9. Furthermore, the memory 91 may include both internal and external storage units of the terminal device 9. The memory 91 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 91 can also be used to temporarily store data that has been sent or will be sent.

[0100] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0101] This application also provides a terminal device, which includes at least one memory, at least one processor, and a computer program stored in the at least one memory and executable on the at least one processor. When the processor executes the computer program, it causes the terminal device to implement the steps in any of the above method embodiments.

[0102] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0103] This application provides a computer program product that, when run on a terminal device, enables the terminal device to implement the steps described in the various method embodiments above.

[0104] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0105] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0106] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0107] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0108] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A skin sensor communication method, characterized in that, include: Acquire multiple skin sensor identification information, multiple skin physiological monitoring information, and multiple skin sensor communication parameter information; The skin sensor identification information, skin physiological monitoring information, and skin sensor communication parameter information are all in one-to-one correspondence. Based on the multiple skin physiological monitoring information and multiple skin sensor communication parameter information, time-series feature extraction is performed to obtain multiple skin physiological monitoring time-series feature information and multiple skin sensor communication parameter time-series feature information. Matching and processing are performed on the multiple skin physiological monitoring time-series feature information and the multiple skin sensor communication parameter time-series feature information to generate multiple skin sensor communication parameter combination information, so that multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

2. The skin sensor communication method as described in claim 1, characterized in that, The skin physiological monitoring information includes skin moisture content monitoring information, skin elasticity monitoring information, skin temperature monitoring information, and skin sebum secretion monitoring information; The skin sensor communication parameter information includes skin sensor communication frequency information, skin sensor communication transmission power information, skin sensor communication time slot allocation information, and skin sensor communication modulation parameter information; The step of extracting time-series features based on the multiple skin physiological monitoring information and multiple skin sensor communication parameter information to obtain multiple skin physiological monitoring time-series feature information and multiple skin sensor communication parameter time-series feature information specifically includes: Based on the preset sampling time window length and the preset sliding step size of the skin physiological monitoring information sampling time window, the multiple skin moisture content monitoring information, multiple skin elasticity monitoring information, multiple skin temperature monitoring information and multiple skin sebum secretion monitoring information are sampled and processed to obtain multiple skin moisture content monitoring time sequence information, multiple skin elasticity monitoring time sequence information, multiple skin temperature monitoring time sequence information and multiple skin sebum secretion monitoring time sequence information. The average values ​​of the multiple skin moisture content monitoring time series information, multiple skin elasticity monitoring time series information, multiple skin temperature monitoring time series information, and multiple skin sebum secretion monitoring time series information are calculated respectively to obtain the average values ​​of multiple skin moisture content monitoring time series information, multiple skin elasticity monitoring time series information, multiple skin temperature monitoring time series information, and multiple skin sebum secretion monitoring time series information. The variances of the multiple skin moisture content monitoring time series information, multiple skin elasticity monitoring time series information, multiple skin temperature monitoring time series information, and multiple skin sebum secretion monitoring time series information are calculated respectively to obtain the variance information of multiple skin moisture content monitoring time series information, multiple skin elasticity monitoring time series information, multiple skin temperature monitoring time series information, and multiple skin sebum secretion monitoring time series information. Based on the time-series mean information of multiple skin moisture content monitoring, multiple time-series mean information of multiple skin elasticity monitoring, multiple time-series mean information of multiple skin temperature monitoring, multiple time-series mean information of multiple skin sebum secretion monitoring, multiple time-series variance information of multiple skin moisture content monitoring, multiple time-series variance information of multiple skin elasticity monitoring, multiple time-series variance information of multiple skin temperature monitoring, and multiple time-series variance information of multiple skin sebum secretion monitoring, multiple time-series characteristic information of skin physiological monitoring is obtained. Based on the preset sampling timing window length and the preset sliding step size of the skin sensor communication parameter sampling timing window, the multiple skin sensor communication frequency information, multiple skin sensor communication transmit power information, multiple skin sensor communication time slot allocation information, and multiple skin sensor communication modulation parameter information are sampled and processed to obtain multiple skin sensor communication frequency timing information, multiple skin sensor communication transmit power timing information, multiple skin sensor communication time slot allocation timing information, and multiple skin sensor communication modulation parameter timing information; The average values ​​of the communication frequency timing information, the communication transmit power timing information, the communication time slot allocation timing information, and the communication modulation parameter timing information of the multiple skin sensors are calculated respectively to obtain the average value information of the communication frequency timing information, the average value information of the communication transmit power timing information, the average value information of the communication time slot allocation timing information, and the average value information of the communication modulation parameter timing information of the multiple skin sensors. The variances of the communication frequency timing information, the communication transmit power timing information, the communication time slot allocation timing information, and the communication modulation parameter timing information of the multiple skin sensors are calculated respectively to obtain the communication frequency timing variance information, the communication transmit power timing variance information, the communication time slot allocation timing variance information, and the communication modulation parameter timing variance information of the multiple skin sensors. Based on the time-series average information of the communication frequency of the multiple skin sensors, the time-series average information of the transmission power of the multiple skin sensors, the time-series average information of the time slot allocation of the multiple skin sensors, the time-series average information of the modulation parameters of the multiple skin sensors, the time-series variance information of the communication frequency of the multiple skin sensors, the time-series variance information of the transmission power of the multiple skin sensors, the time-series variance information of the time slot allocation of the multiple skin sensors, and the time-series variance information of the modulation parameters of the multiple skin sensors, the time-series characteristic information of the communication parameters of the multiple skin sensors is obtained.

3. The skin sensor communication method as described in claim 1, characterized in that, The step of matching the multiple skin physiological monitoring time-series feature information and the multiple skin sensor communication parameter time-series feature information to generate multiple skin sensor communication parameter combination information for communication between the multiple skin sensor identification information and the multiple skin sensor identification information specifically includes: Based on the multiple skin physiological monitoring time-series feature information and the multiple skin sensor communication parameter time-series feature information, feature alignment processing is performed to obtain multiple skin physiological monitoring time-series feature alignment information and multiple skin sensor communication parameter time-series feature alignment information. Based on preset skin physiological monitoring feature weighting coefficients and preset skin sensor communication parameter feature weighting coefficients, the multiple skin physiological monitoring time-series feature alignment information and the multiple skin sensor communication parameter time-series feature alignment information are weighted and fused to obtain multiple skin sensor communication parameter feature fusion information. Calculate the cosine similarity based on the fusion information of the communication parameter features of the multiple skin sensors to obtain the similarity information of the communication parameter features of the multiple skin sensors; Based on the skin sensor communication parameter feature similarity information and the preset skin sensor communication parameter feature similarity threshold, the multiple skin sensor communication parameter feature similarity information is filtered and calculated to obtain multiple skin sensor communication parameter combination information, so that multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

4. The skin sensor communication method as described in claim 3, characterized in that, The step of weighted fusion processing of the multiple skin physiological monitoring time-series feature alignment information and the multiple skin sensor communication parameter time-series feature alignment information based on preset skin physiological monitoring feature weight coefficients and preset skin sensor communication parameter feature weight coefficients to obtain multiple skin sensor communication parameter feature fusion information specifically includes: Based on preset skin physiological monitoring feature weighting coefficients, the alignment information of the multiple skin physiological monitoring time sequence features is weighted and calculated to obtain the weighted information of the multiple skin physiological monitoring time sequence features. Based on preset skin sensor communication parameter feature weighting coefficients, the time sequence feature alignment information of the multiple skin sensor communication parameters is weighted and calculated to obtain the weighted information of the time sequence features of the multiple skin sensor communication parameters. The weighted information of multiple skin physiological monitoring time-series features and the weighted information of multiple skin sensor communication parameters time-series features are normalized to obtain normalized information of multiple skin physiological monitoring time-series features and normalized information of multiple skin sensor communication parameters time-series features. The fusion information of multiple skin sensor communication parameter features is obtained by summing the normalized information of multiple skin physiological monitoring time-series features and the normalized information of multiple skin sensor communication parameters.

5. The skin sensor communication method as described in claim 3, characterized in that, The step of filtering and calculating the similarity information of the multiple skin sensor communication parameters based on the similarity information of the skin sensor communication parameters and a preset similarity threshold to obtain multiple skin sensor communication parameter combination information for communication between multiple skin sensors corresponding to the multiple skin sensor identification information specifically includes: Determine whether the skin sensor communication parameter feature similarity information is less than or equal to a preset skin sensor communication parameter feature similarity threshold; If so, the multiple skin sensor communication parameter feature fusion information corresponding to the skin sensor communication parameter feature similarity information are spliced ​​together to obtain skin sensor communication parameter feature splicing information; If not, then the multiple skin sensor communication parameter feature fusion information corresponding to the skin sensor communication parameter feature similarity information is separated to obtain multiple skin sensor communication parameter feature separation information; Based on the splicing information of the communication parameter features of the multiple skin sensors and the separation information of the communication parameter features of the multiple skin sensors, a combination of communication parameters of the multiple skin sensors is obtained, so that the multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

6. The skin sensor communication method as described in claim 3, characterized in that, The step of filtering and calculating the similarity information of the multiple skin sensor communication parameters based on the similarity information of the skin sensor communication parameters and a preset similarity threshold to obtain multiple skin sensor communication parameter combination information for communication between multiple skin sensors corresponding to the multiple skin sensor identification information specifically includes: Determine whether the skin sensor communication parameter feature similarity information is greater than or equal to a preset skin sensor communication parameter feature similarity threshold; If so, the fusion information of multiple skin sensor communication parameter features corresponding to the skin sensor communication parameter feature similarity information is used as multiple candidate skin sensor communication parameter information; If not, the multiple skin sensor communication parameter feature fusion information corresponding to the skin sensor communication parameter feature similarity information will be merged to obtain candidate skin sensor communication parameter information. Based on the communication parameter information of the multiple candidate skin sensors and the preset skin sensor stability calculation function, the stability function value information of the communication parameters of the multiple candidate skin sensors is calculated. Based on the communication parameter information of the multiple candidate skin sensors, the stability function value information of the communication parameters of the multiple candidate skin sensors, and the preset stability threshold information of the communication parameters of the candidate skin sensors, a combination of communication parameters of the multiple skin sensors is obtained, so that the multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

7. The skin sensor communication method as described in claim 6, characterized in that, The step of obtaining multiple skin sensor communication parameter combination information based on the multiple candidate skin sensor communication parameter information, the multiple candidate skin sensor communication parameter stability function value information, and the preset candidate skin sensor communication parameter stability threshold information, so as to enable multiple skin sensors corresponding to the multiple skin sensor identification information to communicate, specifically includes: Determine whether the stability function value of the candidate skin sensor communication parameters is less than or equal to a preset stability threshold value for the candidate skin sensor communication parameters; If so, the candidate skin sensor communication parameter information corresponding to the candidate skin sensor communication parameter stability function value information is deleted; If not, the candidate skin sensor communication parameter information corresponding to the candidate skin sensor communication parameter stability function value information shall be used as the selected skin sensor communication parameter information. Based on the communication parameter information of the selected skin sensors, a combination of communication parameter information of multiple skin sensors is obtained, so that multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

8. A skin sensor communication device, characterized in that, include: The information acquisition module is used to acquire multiple skin sensor identification information, multiple skin physiological monitoring information, and multiple skin sensor communication parameter information; The skin sensor identification information, skin physiological monitoring information, and skin sensor communication parameter information are all in one-to-one correspondence. The temporal feature information generation module is used to extract temporal features based on the multiple skin physiological monitoring information and the multiple skin sensor communication parameter information to obtain multiple skin physiological monitoring temporal feature information and multiple skin sensor communication parameter temporal feature information. The skin sensor communication parameter combination information generation module is used to perform matching processing based on the multiple skin physiological monitoring time-series feature information and the multiple skin sensor communication parameter time-series feature information to generate multiple skin sensor communication parameter combination information, so that multiple skin sensors corresponding to the multiple skin sensor identification information can communicate.

9. A terminal device, characterized in that, The terminal device includes a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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