CN119007839A - MRNA-based skin evaluation method - Google Patents
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Abstract
本发明公开了基于mRNA的皮肤评价方法，本发明通过从待检测皮肤样本中提取mRNA，通过构建的mRNA表达数据库将提取的mRNA逆转录成cDNA，并定量其表达水平，将得到的mRNA表达数据与数据库中的取值范围匹配，生成老化程度值；同时收集目标皮肤区域的生理样本，测量角质层含水量、经表皮失水率和皮脂含量，获取目标人物的性别和年龄信息并输入评估模型，模型输出目标人物性别和年龄信息所对应的参考数据集合，结合生理学参数和老化程度值，计算皮肤评估指数，从而提供了一种全面、客观的皮肤老化评估方法，不仅基于mRNA表达数据，还结合了生理学参数和个人信息，使得评估结果更为准确和个性化。
The present invention discloses a skin evaluation method based on mRNA. The present invention extracts mRNA from a skin sample to be detected, reversely transcribes the extracted mRNA into cDNA through a constructed mRNA expression database, quantifies its expression level, matches the obtained mRNA expression data with a value range in the database, and generates an aging degree value; at the same time, physiological samples of a target skin area are collected, the water content of the stratum corneum, the transepidermal water loss rate and the sebum content are measured, the gender and age information of a target person is obtained and input into an evaluation model, the model outputs a reference data set corresponding to the gender and age information of the target person, combines physiological parameters and aging degree values, and calculates a skin evaluation index, thereby providing a comprehensive and objective skin aging evaluation method, which is not only based on mRNA expression data, but also combines physiological parameters and personal information, so that the evaluation result is more accurate and personalized.
Description
Technical Field
The invention relates to the technical field of skin evaluation, in particular to a skin evaluation method based on mRNA.
Background
In the field of modern medical cosmetology, accurate assessment of skin condition is critical to achieving effective skin management and treatment; with the aging, skin aging is a general concern, but how to accurately and objectively evaluate the skin aging degree is still a challenge, and conventional skin evaluation methods mainly depend on subjective judgment of dermatologists or morphological analysis based on optical imaging technology, and although these methods provide a certain degree of skin condition information, they often lack enough molecular level information, so that it is difficult to comprehensively reflect the real health condition of skin.
In recent years, with the development of molecular biology technology, particularly the breakthrough of mRNA technology, a new view angle is provided for the molecular mechanism research of skin aging; mRNA is taken as an intermediate product of gene expression, and the change of the expression level of the mRNA in cells can reflect the biological state and the functional change of the cells; thus, an mRNA-based skin evaluation method is expected to provide a new, more accurate skin aging evaluation means.
However, prior art mRNA-based skin evaluations also suffer from the following disadvantages:
The skin aging degree is evaluated by mRNA alone, the skin state cannot be comprehensively reflected, the mRNA expression data and physiological parameters of the target person cannot be comprehensively analyzed, and the gender and age information of the target person are comprehensively considered in the process, so that an all-around skin evaluation result is provided;
When skin evaluation is performed on a target person, the change trend of the skin aging state of the target person along with time cannot be tracked through historical tracing and time sequence analysis, and only single skin aging evaluation is often considered, so that lack of depth and pertinence are evaluated.
For this reason, a skin evaluation method based on mRNA is proposed.
Disclosure of Invention
In view of the above, the present invention provides a skin evaluation method based on mRNA to solve the problems set forth in the above-mentioned background art.
The aim of the invention can be achieved by the following technical scheme: a method of mRNA-based skin assessment comprising:
collecting a sample: determining a target skin area to be acquired based on a target person, collecting a sample from the target skin area as a skin sample to be detected, and extracting mRNA from the skin sample to be detected;
And (3) ageing judgment: pre-constructing an mRNA expression database, reversely transcribing mRNA extracted from a skin sample to be detected into cDNA, and quantifying the expression level of the cDNA as mRNA expression data of a target skin area of a target person at the current time point; inputting mRNA expression data of a target person in a target skin area at a current time point into a pre-constructed mRNA expression database, so as to generate an aging degree value L of the target person in the target skin area at the current time point;
Comprehensive evaluation: collecting a sample from a target skin area of a target person, taking the sample as a physiological sample to be evaluated, and carrying out comprehensive analysis on the basis of the physiological sample to be evaluated of the target skin area and an aging degree value L to obtain a skin evaluation index Ct of the target person in the target skin area at the current time point;
History trace: based on the skin evaluation index Ct of the target person in the target skin area at the current time point, extracting the skin evaluation index Ct of the target person near X times before the current time point, and comprehensively analyzing to obtain the skin state change index Rw of the target person in the time interval; wherein X > 5;
Outputting a result: based on the skin evaluation index Ct and the skin state change index Rw of the target person at the current time point, the skin aging level and the state trend level of the target person at the current time point are output.
In some embodiments, the aging degree value L of the target skin region of the target person at the current time point is generated, specifically:
The built mRNA expression database is internally provided with value ranges corresponding to each group of mRNA expression data, and each group of value ranges corresponds to one aging degree value respectively; and matching the mRNA expression data of the target person in the target skin area at the current time point with each group of value ranges in the mRNA expression database, so as to obtain the aging degree value of the target person in the target skin area at the current time point, and marking the aging degree value as L.
In some embodiments, the skin assessment index Ct of the target person at the current time point of the target skin region is obtained, specifically:
measuring the stratum corneum water content, the transepidermal water loss rate and the sebum content of the physiological sample to be evaluated based on the physiological sample to be evaluated of the target skin area, and marking the stratum corneum water content, the transepidermal water loss rate and the sebum content as S, Y and P respectively;
Acquiring personal information of a target person and extracting the gender and age of the target person from the personal information; inputting the gender and the age of the target person into a pre-constructed evaluation model, wherein the evaluation model comprises age value ranges of each group corresponding to different sexes, and setting each age value range of the different sexes to correspond to one reference data set; the reference data set comprises a reference aging degree value, a reference stratum corneum water content, a reference transepidermal water loss rate and a reference sebum content;
After the evaluation model receives the gender and age of the target person, outputting a reference data set corresponding to the target person;
extracting aging degree value L, horny layer water content S, transepidermal water loss rate Y and sebum content P of target person, and substituting into formula Performing weighted calculation to obtain a skin evaluation index Ct of the target person; wherein the method comprises the steps of、、AndThe reference aging degree value, the reference stratum corneum water content, the reference transepidermal water loss rate and the reference sebum content corresponding to the target person are respectively represented.
In some embodiments, the skin evaluation index Ct of the target person is extracted X times before the current time point, and is comprehensively analyzed, specifically:
Based on the skin evaluation index Ct of the target person of the near X times before the current time point and the skin evaluation index Ct of the current time point, carrying out time sequence arrangement so as to obtain a time sequence data set of the target person in the time interval;
calculating differences between two adjacent sets of skin assessment indices Ct in the time series dataset; in the calculation process, if the difference value calculated by two groups of skin evaluation indexes Ct is a negative number; the difference calculated by the two sets of skin assessment indices Ct is marked as a degree-reduced value; if the difference value calculated by the two groups of skin evaluation indexes Ct is a positive number; the difference calculated by the two sets of skin evaluation indices Ct is marked as an ascending-degree value;
Taking absolute values of all groups of degree reduction values of the marks, and summing the absolute values to be used as a degree reduction total value of the target person corresponding to the target skin area; summing the degree rising values of the groups of marks to obtain a degree rising total value of the target skin area corresponding to the target person; calculating the ratio of the degree ascending total value to the degree descending total value, namely the degree ascending total value/the degree descending total value, and obtaining the change ratio of the target person in the time interval;
Extracting skin evaluation indexes Ct of the target person near X times before the current time point, calculating the average value, marking the calculated average value as an evaluation average value, and calculating the ratio of the calculated average value to the skin evaluation indexes Ct of the target person at the current time point, namely the skin evaluation indexes Ct/the evaluation average value at the current time point; and obtaining the index ratio of the target person in the time interval.
In some embodiments, the skin state change index Rw of the target person in the time interval is obtained, specifically:
The method comprises the steps of presetting weight coefficients of a change ratio and an index ratio, multiplying the change ratio and the index ratio of a target person in the time interval by the corresponding preset weight coefficients respectively, and then summing to obtain a skin state change index Rw of the target person in the time interval.
In some embodiments, the skin aging level and the state trend level of the target person at the current time point are output, specifically:
Presetting each group of index value ranges of the skin evaluation index Ct, setting each group of index value ranges to correspond to a skin aging grade respectively, and matching the skin evaluation index Ct of the target person at the current time point with each preset group of index value ranges to obtain the skin aging grade of the target person at the current time point;
Presetting three groups of index value ranges of a skin state change index Rw, and setting each group of index value ranges to correspond to a state trend grade respectively; and matching the skin state change index Rw of the target person at the current time point with three preset index value ranges, so as to obtain the state trend grade of the target person at the current time point.
In some embodiments, further comprising:
Consultation specialist: after receiving the skin aging grade and the state trend grade of the current time point, if an expert is required to be consulted, acquiring the state information of each expert at the current trigger time point after triggering an application signaling, analyzing to obtain a consultation priority value Zg of each expert at the current trigger time point, selecting a corresponding expert based on the analysis result of the consultation priority value Zg of each expert, and establishing a consultation window; the state information includes estimated wait time, expert experience, and expert evaluation.
In some embodiments, based on the analysis result of the consultation priority value Zg of each expert, selecting a corresponding expert and establishing a consultation window, specifically:
After the application signaling is triggered, an expert in an online state at the current trigger time point is obtained as a expert to be selected; counting the number of pending consultations of each expert to be selected at the current trigger time point, presetting estimated processing time length of single consultation, and multiplying the number of pending consultations of each expert to be selected by the preset estimated processing time length to obtain estimated waiting time length f1 of each expert to be selected at the current trigger time point;
acquiring the service life and the historical evaluation of each expert to be selected at the current trigger time point, wherein the historical evaluation is the satisfaction degree scoring of a user on the consultation process after the consultation of the expert is completed;
taking the service life of each expert to be selected as the expert experience f2 of each expert to be selected; taking the average value of the satisfaction degree scores of all the to-be-selected experts to obtain an expert score f3 of all the to-be-selected experts;
Based on the preset preference degree of the current target person, obtaining the influence weight factors of the pre-estimated waiting time length f1, the expert experience f2 and the expert score f3 corresponding to the current target person; and according to the formula Weighting calculation is carried out, and consultation priority values Zg of all the to-be-selected experts are obtained; wherein u1, u2 and u3 respectively represent the influence weight factors of the estimated waiting time period f1, the expert experience f2 and the expert score f3 corresponding to the preference degree of the current target person;
and selecting the expert to be selected with the largest consultation priority value Zg as the expert to be selected of the current target person, and establishing a consultation window with the expert when the target person is reached.
Compared with the prior art, the invention has the beneficial effects that:
The invention extracts mRNA from skin sample to be detected, reversely transcribes the extracted mRNA into cDNA through constructed mRNA expression database, quantifies the expression level of the cDNA, and matches the obtained mRNA expression data with the value range in the database to generate an aging degree value; meanwhile, a physiological sample of a target skin area is collected, the water content of the stratum corneum, the water loss rate of the epidermis and the sebum content are measured, sex and age information of a target person are obtained and input into an evaluation model, the model outputs a reference data set corresponding to the sex and age information of the target person, and a skin evaluation index is calculated by combining physiological parameters and aging degree values, so that a comprehensive and objective skin aging evaluation method is provided, and the evaluation result is more accurate and personalized on the basis of mRNA expression data and physiological parameters and personal information;
The invention extracts the skin evaluation index of the target person near X times before the current time point based on the skin evaluation index of the target person in the target skin area at the current time point, and comprehensively analyzes the skin evaluation index to obtain the skin state change index of the target person in the time interval, thereby reflecting the skin change trend of the target person in the time interval, tracking the change trend of the skin state through the analysis of historical data, and providing more information for skin health management.
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Further details, features and advantages of the application are disclosed in the following description of exemplary embodiments with reference to the following drawings, in which:
FIG. 1 is a flow chart of the present invention.
Detailed Description
Several embodiments of the present application will be described in more detail below with reference to the accompanying drawings in order to enable those skilled in the art to practice the application. The present application may be embodied in many different forms and objects and should not be limited to the embodiments set forth herein. These embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the application to those skilled in the art. The examples do not limit the application.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and/or the present specification and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
Referring to fig. 1, the mRNA-based skin evaluation method includes:
Collecting a sample: determining a target skin area to be acquired based on the target person; collecting a sample from a target skin area using a non-invasive or minimally invasive method; as a skin sample to be tested; extracting mRNA from a skin sample to be tested using a specific biochemical method; ensuring the integrity and purity of mRNA so as to facilitate accurate subsequent analysis;
And (3) ageing judgment: pre-constructing an mRNA expression database, reversely transcribing mRNA extracted from a skin sample to be detected into cDNA, and quantifying the expression level of the cDNA as mRNA expression data of a target skin area of a target person at the current time point; analysis of cDNA using qPCR or RNA-seq techniques to quantify the level of expression of a particular gene; inputting mRNA expression data of a target person in a target skin area at a current time point into a pre-constructed mRNA expression database, so as to generate an aging degree value L of the target person in the target skin area at the current time point;
the method comprises the following steps:
The built mRNA expression database is internally provided with value ranges corresponding to each group of mRNA expression data, and each group of value ranges corresponds to one aging degree value respectively; the range of the aging degree value is set to be 1-10, and the higher the aging degree value is, the higher the biological age of the target skin area is;
Matching mRNA expression data of a target person in a target skin area at a current time point with each group of value ranges in an mRNA expression database, so as to obtain an aging degree value of the target person in the target skin area at the current time point, and marking the aging degree value as L;
Each set of value ranges comprises mRNA expression data under different skin aging states; by matching, a quantized aging value can be obtained by combining the set value range and the aging degree value. This value may reflect the biological age of the individual's skin;
Comprehensive evaluation: repeatedly collecting samples from a target skin area of a target person, and performing comprehensive analysis to obtain a skin evaluation index Ct of the target person in the target skin area at the current time point based on the physiological sample to be evaluated of the target skin area and the aging degree value L as a physiological sample to be evaluated;
the method comprises the following steps:
measuring the stratum corneum water content, the transepidermal water loss rate and the sebum content of the physiological sample to be evaluated based on the physiological sample to be evaluated of the target skin area, and marking the stratum corneum water content, the transepidermal water loss rate and the sebum content as S, Y and P respectively;
Measuring the moisture content of the physiological sample to be evaluated using a non-invasive skin moisture measuring instrument, such as a capacitive method or an optical sensor;
measuring the transepidermal water loss rate of the physiological sample to be evaluated using a TEWL measurement instrument;
measuring sebum secretion of a physiological sample to be evaluated by using a grease analysis instrument;
the higher the skin ageing degree, the lower the water content of the stratum corneum, the higher the transepidermal water loss, and the lower the sebum content;
Acquiring personal information of a target person and extracting the gender and age of the target person from the personal information; inputting the gender and the age of the target person into a pre-constructed evaluation model, wherein the evaluation model comprises age value ranges of each group corresponding to different sexes, and setting each age value range of the different sexes to correspond to one reference data set; the reference data set comprises a reference aging degree value, a reference stratum corneum water content, a reference transepidermal water loss rate and a reference sebum content;
After the evaluation model receives the gender and age of the target person, outputting a reference data set corresponding to the target person;
extracting aging degree value L, horny layer water content S, transepidermal water loss rate Y and sebum content P of target person, and substituting into formula Performing weighted calculation to obtain a skin evaluation index Ct of the target person; wherein the method comprises the steps of、、AndRespectively representing a reference aging degree value, a reference stratum corneum water content, a reference transepidermal water loss rate and a reference sebum content corresponding to the target person;
history trace: based on the skin evaluation index Ct of the target person in the target skin area at the current time point, extracting the skin evaluation index Ct of the target person near X times before the current time point, and comprehensively analyzing to obtain the skin state change index Rw of the target person in the time interval; wherein X is more than 5, and the specific value is set by a technician according to the actual condition of the target person;
the method comprises the following steps:
Based on the skin evaluation index Ct of the target person of the near X times before the current time point and the skin evaluation index Ct of the current time point, carrying out time sequence arrangement so as to obtain a time sequence data set of the target person in the time interval;
ensuring that each index is associated with its corresponding point in time, reflecting the change in skin condition over time;
calculating differences between two adjacent sets of skin assessment indices Ct in the time series dataset; the difference calculation formula can be expressed as WhereinAn index indicating the current point in time,An index indicating the previous time point;
In the calculation process, if the difference value calculated by two groups of skin evaluation indexes Ct is a negative number; i.e. the index of the current time point is smaller than the index of the previous time point, the calculated result is a negative number; the difference calculated by the two sets of skin assessment indices Ct is marked as a degree-reduced value; if the difference value calculated by the two groups of skin evaluation indexes Ct is a positive number; i.e. the index of the current time point is larger than the index of the previous time point, the calculated result is a positive number; the difference calculated by the two sets of skin evaluation indices Ct is marked as an ascending-degree value;
according to the difference value calculation result, the change of skin aging degree of the target person in the time interval is explained;
Taking absolute values of all groups of degree reduction values of the marks, and summing the absolute values to be used as a degree reduction total value of the target person corresponding to the target skin area; summing the degree rising values of the groups of marks to obtain a degree rising total value of the target skin area corresponding to the target person; calculating the ratio of the degree ascending total value to the degree descending total value, namely the degree ascending total value/the degree descending total value, and obtaining the change ratio of the target person in the time interval;
Degree decrease value: when the index Ct of the current time point is smaller than the index of the previous time point, the difference is a negative number, which indicates that the skin aging degree is reduced or improved;
Degree rise value: when the index Ct of the current time point is greater than the index of the previous time point, the difference is a positive number, which indicates that the skin aging degree is increased or deteriorated;
if the change ratio is greater than 1, it means that the degree of skin aging generally increases over the time interval as indicated by the degree of increase being greater than the total degree of decrease.
If the change ratio is less than 1, it means that the degree of skin aging generally tends to decrease in the time interval, as the degree of increase is lower than the total degree of decrease.
If the change ratio is close to 1, the total value of the rising and falling degrees is similar, the skin aging degree is not changed greatly in the time interval, and the relative stability is kept.
Extracting skin evaluation indexes Ct of the target person near X times before the current time point, calculating the average value, marking the calculated average value as an evaluation average value, and calculating the ratio of the calculated average value to the skin evaluation indexes Ct of the target person at the current time point, namely the skin evaluation indexes Ct/the evaluation average value at the current time point; obtaining the index ratio of the target person in the time interval;
The index ratio may show whether the skin assessment index at the current point in time is above or below the average level of the last period of time; this helps to identify the tendency of the skin condition to improve or worsen;
the method comprises the steps of presetting weight coefficients of a change ratio and an index ratio, multiplying the change ratio and the index ratio of a target person in a time interval by corresponding preset weight coefficients respectively, and then summing to obtain a skin state change index Rw of the target person in the time interval;
Outputting a result: outputting the skin aging grade and the state trend grade of the target person at the current time point based on the skin evaluation index Ct and the skin state change index Rw of the target person at the current time point;
the method comprises the following steps:
Presetting each group of index value ranges of the skin evaluation index Ct, setting each group of index value ranges to correspond to a skin aging grade respectively, and matching the skin evaluation index Ct of the target person at the current time point with each preset group of index value ranges to obtain the skin aging grade of the target person at the current time point; the higher the skin evaluation index Ct is, the higher the skin aging grade is obtained by corresponding matching;
Presetting three groups of index value ranges of a skin state change index Rw, and setting each group of index value ranges to correspond to a state trend grade respectively; matching the skin state change index Rw of the target person at the current time point with three preset index value ranges, so as to obtain the state trend grade of the target person at the current time point; the state trend grade comprises a good trend, a general trend and a hidden danger trend, and the higher the skin state change index Rw is, the higher the possibility of matching the hidden danger trend correspondingly is;
Consultation specialist: after receiving the skin aging grade and the state trend grade of the current time point, if an expert is required to be consulted, acquiring the state information of each expert at the current trigger time point after triggering an application signaling, analyzing to obtain a consultation priority value Zg of each expert at the current trigger time point, selecting a corresponding expert based on the analysis result of the consultation priority value Zg of each expert, and establishing a consultation window; the state information comprises estimated waiting time, expert experience and expert evaluation;
the method comprises the following steps:
After the application signaling is triggered, an expert in an online state at the current trigger time point is obtained as a expert to be selected; counting the number of pending consultations of each expert to be selected at the current trigger time point, presetting estimated processing time length of single consultation, and multiplying the number of pending consultations of each expert to be selected by the preset estimated processing time length to obtain estimated waiting time length f1 of each expert to be selected at the current trigger time point;
Acquiring the service life and the historical evaluation of each expert to be selected at the current trigger time point, wherein the historical evaluation is the satisfaction degree scoring of a user on the consultation process after the consultation of the expert is completed; the range is set between 1 and 5, and the higher the score is, the more satisfied the user is;
taking the service life of each expert to be selected as the expert experience f2 of each expert to be selected; taking the average value of the satisfaction degree scores of all the to-be-selected experts to obtain an expert score f3 of all the to-be-selected experts;
Based on the preset preference degree of the current target person, obtaining the influence weight factors of the pre-estimated waiting time length f1, the expert experience f2 and the expert score f3 corresponding to the current target person; presetting by the current target person; and according to the formula Weighting calculation is carried out, and consultation priority values Zg of all the to-be-selected experts are obtained; wherein u1, u2 and u3 respectively represent the influence weight factors of the estimated waiting time period f1, the expert experience f2 and the expert score f3 corresponding to the preference degree of the current target person;
selecting the expert to be selected with the largest consultation priority value Zg as the expert to be selected of the current target person, and establishing a consultation window with the expert when the current target person is reached;
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (8)
1. A method for evaluating skin based on mRNA, comprising:
collecting a sample: determining a target skin area to be acquired based on a target person, collecting a sample from the target skin area as a skin sample to be detected, and extracting mRNA from the skin sample to be detected;
And (3) ageing judgment: pre-constructing an mRNA expression database, reversely transcribing mRNA extracted from a skin sample to be detected into cDNA, and quantifying the expression level of the cDNA as mRNA expression data of a target skin area of a target person at the current time point; inputting mRNA expression data of a target person in a target skin area at a current time point into a pre-constructed mRNA expression database, so as to generate an aging degree value L of the target person in the target skin area at the current time point;
Comprehensive evaluation: collecting a sample from a target skin area of a target person, taking the sample as a physiological sample to be evaluated, and carrying out comprehensive analysis on the basis of the physiological sample to be evaluated of the target skin area and an aging degree value L to obtain a skin evaluation index Ct of the target person in the target skin area at the current time point;
History trace: based on the skin evaluation index Ct of the target person in the target skin area at the current time point, extracting the skin evaluation index Ct of the target person near X times before the current time point, and comprehensively analyzing to obtain the skin state change index Rw of the target person in the time interval; wherein X > 5;
Outputting a result: based on the skin evaluation index Ct and the skin state change index Rw of the target person at the current time point, the skin aging level and the state trend level of the target person at the current time point are output.
2. The mRNA-based skin evaluation method according to claim 1, wherein the aging degree value L of the target skin region of the target person at the current time point is generated, specifically:
The built mRNA expression database is internally provided with value ranges corresponding to each group of mRNA expression data, and each group of value ranges corresponds to one aging degree value respectively; and matching the mRNA expression data of the target person in the target skin area at the current time point with each group of value ranges in the mRNA expression database, so as to obtain the aging degree value of the target person in the target skin area at the current time point, and marking the aging degree value as L.
3. The mRNA-based skin evaluation method according to claim 2, wherein the skin evaluation index Ct of the target person's target skin area at the current time point is obtained, specifically:
measuring the stratum corneum water content, the transepidermal water loss rate and the sebum content of the physiological sample to be evaluated based on the physiological sample to be evaluated of the target skin area, and marking the stratum corneum water content, the transepidermal water loss rate and the sebum content as S, Y and P respectively;
Acquiring personal information of a target person and extracting the gender and age of the target person from the personal information; inputting the gender and the age of the target person into a pre-constructed evaluation model, wherein the evaluation model comprises age value ranges of each group corresponding to different sexes, and setting each age value range of the different sexes to correspond to one reference data set; the reference data set comprises a reference aging degree value, a reference stratum corneum water content, a reference transepidermal water loss rate and a reference sebum content;
After the evaluation model receives the gender and age of the target person, outputting a reference data set corresponding to the target person;
extracting aging degree value L, horny layer water content S, transepidermal water loss rate Y and sebum content P of target person, and substituting into formula Performing weighted calculation to obtain a skin evaluation index Ct of the target person; wherein the method comprises the steps of、、AndThe reference aging degree value, the reference stratum corneum water content, the reference transepidermal water loss rate and the reference sebum content corresponding to the target person are respectively represented.
4. The mRNA-based skin evaluation method according to claim 3, wherein the skin evaluation index Ct of the target person X times before the current time point is extracted and comprehensively analyzed, specifically:
Based on the skin evaluation index Ct of the target person of the near X times before the current time point and the skin evaluation index Ct of the current time point, carrying out time sequence arrangement so as to obtain a time sequence data set of the target person in the time interval;
calculating differences between two adjacent sets of skin assessment indices Ct in the time series dataset; in the calculation process, if the difference value calculated by two groups of skin evaluation indexes Ct is a negative number; the difference calculated by the two sets of skin assessment indices Ct is marked as a degree-reduced value; if the difference value calculated by the two groups of skin evaluation indexes Ct is a positive number; the difference calculated by the two sets of skin evaluation indices Ct is marked as an ascending-degree value;
Taking absolute values of all groups of degree reduction values of the marks, and summing the absolute values to be used as a degree reduction total value of the target person corresponding to the target skin area; summing the degree rising values of the groups of marks to obtain a degree rising total value of the target skin area corresponding to the target person; calculating the ratio of the degree ascending total value to the degree descending total value, namely the degree ascending total value/the degree descending total value, and obtaining the change ratio of the target person in the time interval;
Extracting skin evaluation indexes Ct of the target person near X times before the current time point, calculating the average value, marking the calculated average value as an evaluation average value, and calculating the ratio of the calculated average value to the skin evaluation indexes Ct of the target person at the current time point, namely the skin evaluation indexes Ct/the evaluation average value at the current time point; and obtaining the index ratio of the target person in the time interval.
5. The mRNA-based skin evaluation method according to claim 4, wherein the skin state change index Rw of the target person in the time interval is obtained, specifically:
The method comprises the steps of presetting weight coefficients of a change ratio and an index ratio, multiplying the change ratio and the index ratio of a target person in the time interval by the corresponding preset weight coefficients respectively, and then summing to obtain a skin state change index Rw of the target person in the time interval.
6. The mRNA-based skin evaluation method according to claim 5, wherein the skin aging level and the state trend level of the target person at the current time point are output, specifically:
Presetting each group of index value ranges of the skin evaluation index Ct, setting each group of index value ranges to correspond to a skin aging grade respectively, and matching the skin evaluation index Ct of the target person at the current time point with each preset group of index value ranges to obtain the skin aging grade of the target person at the current time point;
Presetting three groups of index value ranges of a skin state change index Rw, and setting each group of index value ranges to correspond to a state trend grade respectively; and matching the skin state change index Rw of the target person at the current time point with three preset index value ranges, so as to obtain the state trend grade of the target person at the current time point.
7. The mRNA-based skin evaluation method according to claim 1, further comprising:
Consultation specialist: after receiving the skin aging grade and the state trend grade of the current time point, if an expert is required to be consulted, acquiring the state information of each expert at the current trigger time point after triggering an application signaling, analyzing to obtain a consultation priority value Zg of each expert at the current trigger time point, selecting a corresponding expert based on the analysis result of the consultation priority value Zg of each expert, and establishing a consultation window; the state information includes estimated wait time, expert experience, and expert evaluation.
8. The mRNA-based skin evaluation method according to claim 7, wherein based on the consultation priority Zg analysis result of each expert, selecting the corresponding expert and establishing a consultation window, specifically:
After the application signaling is triggered, an expert in an online state at the current trigger time point is obtained as a expert to be selected; counting the number of pending consultations of each expert to be selected at the current trigger time point, presetting estimated processing time length of single consultation, and multiplying the number of pending consultations of each expert to be selected by the preset estimated processing time length to obtain estimated waiting time length f1 of each expert to be selected at the current trigger time point;
acquiring the service life and the historical evaluation of each expert to be selected at the current trigger time point, wherein the historical evaluation is the satisfaction degree scoring of a user on the consultation process after the consultation of the expert is completed;
taking the service life of each expert to be selected as the expert experience f2 of each expert to be selected; taking the average value of the satisfaction degree scores of all the to-be-selected experts to obtain an expert score f3 of all the to-be-selected experts;
Based on the preset preference degree of the current target person, obtaining the influence weight factors of the pre-estimated waiting time length f1, the expert experience f2 and the expert score f3 corresponding to the current target person; and according to the formula Weighting calculation is carried out, and consultation priority values Zg of all the to-be-selected experts are obtained; wherein u1, u2 and u3 respectively represent the influence weight factors of the estimated waiting time period f1, the expert experience f2 and the expert score f3 corresponding to the preference degree of the current target person;
and selecting the expert to be selected with the largest consultation priority value Zg as the expert to be selected of the current target person, and establishing a consultation window with the expert when the target person is reached.
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