CN117064343A - Intelligent AR polarization detection data processing method capable of detecting vital signs - Google Patents
Intelligent AR polarization detection data processing method capable of detecting vital signs Download PDFInfo
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Abstract
The invention relates to the technical field of data processing, in particular to an intelligent AR polarization detection data processing method capable of detecting vital signs, which comprises the following steps: decomposing a historical normal light signal curve corresponding to each vital sign parameter to obtain an initial threshold value of each vital sign parameter; calculating the abnormality degree of the vital sign data sequences corresponding to each vital sign parameter according to the dispersion condition and the change condition of the vital sign data sequences corresponding to each vital sign parameter; obtaining an improved threshold value of the optical signal curve to be transmitted corresponding to each vital sign parameter according to the abnormal degree of all the reference curves of the optical signal curve to be transmitted corresponding to each vital sign parameter; and compressing the optical signal curves to be transmitted corresponding to each vital sign parameter according to the improved threshold. The invention adjusts the threshold parameter of the DP algorithm according to the degree of abnormality, and ensures the authenticity of vital sign data extracted by the optical signal while ensuring the transmission efficiency of the optical signal.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an intelligent AR polarization detection data processing method capable of detecting vital signs.
Background
The intelligent AR polarization detector combines the polarization technology and the augmented reality technology, and the vital sign is detected noninvasively through analyzing the polarization state of light, so that the real-time monitoring of the physiological state of the user is provided, meanwhile, vital sign data of the user can be combined with other environmental information to provide more comprehensive health analysis and guidance, and the intelligent AR polarization detector has potential application prospects in the fields of medical treatment, motion monitoring, biofeedback and the like, and can provide beneficial tools and support for personal health management, pathological diagnosis, treatment and the like.
Polarized light in a specific direction is selected by a polarization filter, the light signal is received and converted by a detector, and finally the received light signal is processed and analyzed to extract and calculate parameters of vital signs.
In order to monitor the physiological state of the user in real time, the real-time performance of optical signal transmission needs to be ensured; because the optical signal is a continuous signal, the data volume is large, and the optical signal needs to be compressed in order to improve the transmission efficiency when the optical signal is transmitted; the douglas-pock algorithm (DP algorithm) is commonly used to compress continuous signals.
The threshold parameters in the DP algorithm determine the compression efficiency and the degree of compressed data loss: the larger the threshold parameter is, the higher the compression efficiency is, the higher the transmission efficiency of the corresponding optical signal is, but the larger the compression data loss degree is, the larger the difference between vital sign data extracted through the optical signal and real vital sign data is, and the vital sign data extracted through the optical signal cannot reflect the real physical condition of a user; the smaller the threshold parameter is, the smaller the compression data loss degree is, the smaller the difference between vital sign data extracted through the optical signal and real vital sign data is, the vital sign data extracted through the optical signal can reflect the real physical condition of a user, but meanwhile, the smaller the compression efficiency is, and the lower the transmission efficiency of the corresponding optical signal is.
Therefore, it is necessary to obtain a threshold parameter in a suitable DP algorithm, and ensure the authenticity of vital sign data extracted by an optical signal while ensuring the transmission efficiency of the optical signal.
Disclosure of Invention
In order to solve the above problems, the present invention provides a method for processing intelligent AR polarization detection data capable of detecting vital signs, the method comprising:
acquiring an optical signal curve and a historical normal optical signal curve corresponding to each vital sign parameter;
decomposing a historical normal light signal curve corresponding to each vital sign parameter to obtain an initial threshold value of each vital sign parameter;
converting the optical signal curve corresponding to each vital sign parameter into a vital sign data sequence corresponding to each vital sign parameter; obtaining a normal range and an early warning range of each vital sign parameter; combining the normal range and the early warning range of each vital sign parameter, and calculating the abnormality degree of the vital sign data sequence corresponding to each vital sign parameter according to the dispersion condition and the change condition of the vital sign data sequence corresponding to each vital sign parameter;
acquiring all reference curves of the optical signal curves corresponding to each vital sign parameter to be transmitted currently; obtaining an improved threshold value of the optical signal curve to be transmitted corresponding to each vital sign parameter according to the abnormal degree of all reference curves of the optical signal curve corresponding to each vital sign parameter to be transmitted currently;
and compressing the optical signal curves to be transmitted corresponding to each vital sign parameter according to the improved threshold.
Further, the obtaining the initial threshold value of each vital sign parameter comprises the following specific steps:
STL decomposition is carried out on the historical normal optical signal curve corresponding to each vital sign parameter, and a periodic item sequence of the historical normal optical signal curve corresponding to each vital sign parameter is obtained; dividing a periodic item sequence of a historical normal optical signal curve corresponding to each vital sign parameter into a plurality of periodic segments according to all extreme points, marking a connecting line of two extreme points of each periodic segment as a datum line of each periodic segment, marking the maximum value of the distances from all data points on each periodic segment to the datum line of each periodic segment as the maximum error of each periodic segment, and marking the average value of the maximum errors of all periodic segments as the initial threshold value of each vital sign parameter.
Further, the calculating the abnormality degree of the vital sign data sequence corresponding to each vital sign parameter includes the following specific steps:
processing and analyzing the received optical signal curve corresponding to each vital sign parameter to obtain a vital sign data sequence corresponding to each vital sign parameter; obtaining a subsequence composed of a plurality of vital sign data continuously exceeding an early warning range in a vital sign data sequence corresponding to each vital sign parameter, and obtaining a plurality of subsequences of the vital sign data sequence corresponding to each vital sign parameter; calculating the degree of abnormality of vital sign data sequences corresponding to each vital sign parameter, wherein a specific calculation formula is as follows:
representing the degree of abnormality of the vital sign data sequence corresponding to the ith vital sign parameter, ++>Representing the variance of the vital sign data sequence corresponding to the ith vital sign parameter,/for>Representing the number of subsequences in the vital sign data sequence corresponding to the ith vital sign parameter,/->Mean rate of change of the jth subsequence of the vital sign data sequence corresponding to the ith vital sign parameter,/th>A length of a j-th subsequence representing a vital sign data sequence corresponding to the i-th vital sign parameter,/and>representing the length of the vital sign data sequence corresponding to the ith vital sign parameter,/for>Mean value of vital sign data exceeding normal range in jth subsequence of vital sign data sequence representing ith vital sign parameter +.>And the degree of exceeding the normal range in the j-th subsequence of the vital sign data sequence corresponding to the i-th vital sign parameter is represented.
Further, the obtaining the improved threshold value of the optical signal curve to be transmitted corresponding to each vital sign parameter includes the following specific steps:
an improved threshold value representing the optical signal profile to be transmitted corresponding to the ith vital sign parameter, +.>An initial threshold value representing the ith vital sign parameter, < +.>The abnormal degree of the S-th reference curve of the light signal curve to be transmitted corresponding to the i-th vital sign parameter is represented, and S represents the preset quantity.
Further, the obtaining the optical signal curve and the historical normal optical signal curve corresponding to each vital sign parameter includes the following specific steps:
the intelligent AR polarization detector selects polarized light in a specific direction through a polarization filter, and receives and converts the obtained optical signals into optical signals corresponding to the first vital sign parameter to the fifth vital sign parameter through the detector;
respectively forming a curve of the optical signals corresponding to each vital sign parameter in a preset time period T according to the sequence, wherein the curve is used as an optical signal curve corresponding to each vital sign parameter and is respectively an optical signal curve corresponding to a first vital sign parameter to an optical signal curve corresponding to a fifth vital sign parameter;
and selecting a curve formed by the optical signals corresponding to each vital sign parameter according to the sequence when the physical health condition of the user is good from the historical data, wherein the time length corresponding to the required curve is 30T, and the curve is used as a historical normal optical signal curve corresponding to each vital sign parameter and is respectively from the historical normal optical signal curve corresponding to the first vital sign parameter to the historical normal optical signal curve corresponding to the fifth vital sign parameter.
Further, the first to fifth vital sign parameters include the following specific steps:
the 5 vital sign parameters of respiration, pulse, body temperature, diastolic pressure and systolic pressure are respectively noted as first vital sign parameter to fifth vital sign parameter.
Further, the obtaining the normal range and the early warning range of each vital sign parameter comprises the following specific steps:
presetting the normal range of each vital sign parameter byAnd->Respectively represent the lower limit and the upper limit of the normal range of the ith vital sign parameter, the normal range of the ith vital sign parameter is +.>The method comprises the steps of carrying out a first treatment on the surface of the Will->Early warning range as i vital sign parameter, < +.>Representing preset parameters.
Further, the step of converting the optical signal curve corresponding to each vital sign parameter into the vital sign data sequence corresponding to each vital sign parameter includes the following specific steps:
and processing and analyzing the received optical signal curve corresponding to each vital sign parameter, extracting and calculating vital sign data, and obtaining a vital sign data sequence corresponding to each vital sign parameter.
Further, the step of obtaining all the reference curves of the optical signal curves corresponding to each vital sign parameter to be transmitted comprises the following specific steps:
acquiring optical signal curves corresponding to each vital sign parameter to be transmitted currently, and respectively marking the optical signal curves to be transmitted corresponding to the first vital sign parameter to the optical signal curves to be transmitted corresponding to the fifth vital sign parameter; and respectively marking the preset number S of optical signal curves corresponding to each vital sign parameter before the optical signal curve corresponding to each vital sign parameter to be transmitted at present as a first reference curve to a sixth reference curve of the optical signal curve corresponding to each vital sign parameter to be transmitted at present according to the sequence from the small time difference to the large time difference at the present moment.
Further, the compressing the optical signal curve to be transmitted corresponding to each vital sign parameter according to the improvement threshold includes the following specific steps:
the improved threshold value of the optical signal curve to be transmitted corresponding to each vital sign parameter is used as a threshold value parameter in a DP algorithm, the optical signal curve to be transmitted corresponding to each vital sign parameter is compressed through the DP algorithm, a compression result is transmitted to an optical signal receiving end, the received compression result is decompressed, the optical signal obtained through decompression is processed and analyzed, vital sign parameters are extracted and calculated, and professional medical staff combines vital sign data of a user and other environmental information to provide more comprehensive health analysis and guidance.
The technical scheme of the invention has the beneficial effects that: in order to monitor the physiological state of a user in real time, the real-time performance of optical signal transmission of the intelligent AR polarization detector needs to be ensured; in order to solve the problem that the reality of vital sign data extracted through optical signals is guaranteed while the transmission efficiency of the optical signals is guaranteed, the method combines the physiological state abnormality of a user and vital sign data in a period before and after the physiological state abnormality of the user to have significance for analyzing the physical state of the user, and the method calculates the abnormality degree of vital sign data sequences corresponding to each vital sign parameter, obtains the improved threshold value of an optical signal curve to be transmitted corresponding to each vital sign parameter according to the abnormality degree of all reference curves of the optical signal curve corresponding to each vital sign parameter to be transmitted currently, reduces the difference between a compression result and the optical signals through the abnormality degree, reduces the difference between the vital sign data extracted through the optical signals and the real vital sign data, and preferentially ensures the reality of the optical signals in the period before and after the physiological state abnormality of the user while guaranteeing the transmission efficiency of the optical signals, so that the vital sign data extracted through the optical signals can reflect the real physical state of the user more.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a method flow chart of a method for processing intelligent AR polarization detection data capable of detecting vital signs according to the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the present invention to achieve the preset purposes, the following detailed description refers to specific implementation, structure, characteristics and effects of an intelligent AR polarization detection data processing method capable of detecting vital signs according to the present invention, with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following specifically describes a specific scheme of the intelligent AR polarization detection data processing method capable of detecting vital signs provided by the invention with reference to the accompanying drawings.
Referring to fig. 1, a method flowchart of a data transmission module of a smart AR polarization detection data processing method capable of detecting vital signs according to an embodiment of the present invention is shown, where the method includes:
in order to monitor the physiological state of the user in real time, the real-time performance of optical signal transmission needs to be ensured; because the optical signal is a continuous signal, the data volume is large, and the optical signal needs to be compressed in order to improve the transmission efficiency when the optical signal is transmitted; the douglas-pock algorithm (DP algorithm) is commonly used to compress continuous signals. The threshold parameters in the DP algorithm determine the compression efficiency and the degree of compressed data loss: the larger the threshold parameter is, the higher the compression efficiency is, the higher the transmission efficiency of the corresponding optical signal is, but the larger the compression data loss degree is, the larger the difference between vital sign data extracted through the optical signal and real vital sign data is, and the vital sign data extracted through the optical signal cannot reflect the real physical condition of a user; the smaller the threshold parameter is, the smaller the compression data loss degree is, the smaller the difference between vital sign data extracted through the optical signal and real vital sign data is, the vital sign data extracted through the optical signal can reflect the real physical condition of a user, but meanwhile, the smaller the compression efficiency is, and the lower the transmission efficiency of the corresponding optical signal is. Therefore, it is necessary to obtain a threshold parameter in a suitable DP algorithm, and ensure the authenticity of vital sign data extracted by an optical signal while ensuring the transmission efficiency of the optical signal.
Considering the purpose of monitoring the physiological state of the user in real time to timely find the physical health problem of the user and remind the user to take a rest and seek medical attention in time, the specific part of the abnormal body of the user can be accurately obtained by analyzing the vital sign data of the abnormal physiological state of the user, the abnormal physiological state of the user can be early warned in advance by analyzing the vital sign data before the abnormal physiological state of the user, the physical recovery condition of the user can be accurately obtained by analyzing the vital sign data after the abnormal physiological state of the user, and whether the possibility of re-abnormality exists or not is judged; in summary, the abnormal physiological state of the user and vital sign data in a period before and after the abnormal physiological state of the user have significance for analyzing the physical state of the user, so that the transmission efficiency of the optical signal is ensured, the authenticity of the optical signal in the abnormal physiological state of the user and the period before and after the abnormal physiological state of the user is ensured preferentially, and the difference between the vital sign data extracted by the optical signal and the real vital sign data is reduced mainly by reducing the threshold parameter in the DP algorithm, so that the vital sign data extracted by the optical signal can reflect the real physical condition of the user more.
When the optical signal is transmitted, the received optical signal is processed and analyzed, vital sign parameters are extracted and calculated, and the vital sign parameters are analyzed to obtain the physiological state of the user; therefore, when transmitting the optical signal, the physiological state of the user cannot be directly obtained according to the optical signal, so that the physiological state of the user is obtained by analyzing the vital sign parameters converted by the optical signal, the threshold parameters in the DP algorithm when the subsequent optical signal is compressed are adjusted by using the current physiological state of the user, the difference between the vital sign data extracted by the optical signal and the real vital sign data is reduced, and the vital sign data extracted by the optical signal can reflect the real physical condition of the user more.
S001, obtaining an optical signal curve corresponding to each vital sign parameter.
It should be noted that, the intelligent AR polarization detector combines the polarization technology and the augmented reality technology, and non-invasively detects vital signs by analyzing the polarization state of light, so as to provide real-time monitoring of the physiological state of the user, and simultaneously combine the vital sign data of the user with other environmental information to provide more comprehensive health analysis and guidance, thus having potential application prospects in the fields of medical treatment, motion monitoring, biofeedback and the like, and providing beneficial tools and support for personal health management, pathological diagnosis, treatment and the like. The method comprises the following steps: polarized light in a specific direction is selected through a polarization filter, light signals are received and converted through a detector, and finally the received light signals are processed and analyzed to extract and calculate parameters of vital signs.
Specifically, the intelligent AR polarization detector selects polarized light in a specific direction through a polarization filter, and receives and converts the obtained optical signal through the detector; in this embodiment, the physiological state of the user needs to be monitored by 5 vital sign data of the respiration, the pulse, the body temperature, the diastolic pressure and the systolic pressure of the user, wherein the 5 vital sign parameters of the respiration, the pulse, the body temperature, the diastolic pressure and the systolic pressure are respectively recorded as the first vital sign parameter to the fifth vital sign parameter, so that 5 generated optical signals are respectively the optical signals corresponding to the first vital sign parameter to the optical signals corresponding to the fifth vital sign parameter.
A period of time T is preset, where the embodiment is described by taking t=10s as an example, and the embodiment is not specifically limited, where T may be determined according to the specific implementation situation.
Further, the curves formed by the optical signals corresponding to each vital sign parameter in the preset time period T according to the sequence are respectively used as the optical signal curves corresponding to each vital sign parameter, and the optical signal curves corresponding to the first vital sign parameter to the optical signal curves corresponding to the fifth vital sign parameter are respectively used as the optical signal curves corresponding to each vital sign parameter.
S002, obtaining a historical normal light signal curve corresponding to each vital sign parameter according to the historical data, and decomposing the historical normal light signal curve corresponding to each vital sign parameter to obtain an initial threshold value of each vital sign parameter.
It should be noted that, in order to monitor the physiological state of the user in real time, the real-time performance of the optical signal transmission needs to be ensured; because the optical signal is a continuous signal, the data volume is large, and the optical signal needs to be compressed in order to improve the transmission efficiency when the optical signal is transmitted; the douglas-pock algorithm (DP algorithm) is commonly used to compress continuous signals. The threshold parameter in the DP algorithm determines the compression efficiency and the compression data loss, so that the present embodiment analyzes the optical signal when the physical health condition of the user is good, and obtains the error of the optical signal under normal conditions as the initial value of the threshold parameter in the DP algorithm.
1. And obtaining a historical normal light signal curve corresponding to each vital sign parameter according to the historical data.
Specifically, a curve formed by the optical signals corresponding to each vital sign parameter according to the sequence when the physical health condition of the user is good is selected from the historical data, the time length corresponding to the required curve is 30T, T represents a preset time period and is used as a historical normal optical signal curve corresponding to each vital sign parameter, and the historical normal optical signal curves corresponding to the first vital sign parameter to the fifth vital sign parameter are respectively; the health condition of the user is provided by combining vital sign data of the user with other environmental information by the professional and medical staff; the health condition of the user is provided by the professional medical staff in combination with the vital sign data of the user and other environmental information, which is a well-known technique in the intelligent AR polarization detector, and will not be described here.
2. And decomposing the historical normal light signal curve corresponding to each vital sign parameter to obtain an initial threshold value of each vital sign parameter.
STL decomposition is carried out on the historical normal optical signal curve corresponding to each vital sign parameter, and a periodic item sequence of the historical normal optical signal curve corresponding to each vital sign parameter is obtained; dividing a periodic item sequence of a historical normal optical signal curve corresponding to each vital sign parameter into a plurality of periodic segments according to all extreme points, marking a connecting line of two extreme points of each periodic segment as a datum line of each periodic segment, marking the maximum value of the distances from all data points on each periodic segment to the datum line of each periodic segment as the maximum error of each periodic segment, and marking the average value of the maximum errors of all periodic segments as the initial threshold value of each vital sign parameter.
S003, acquiring an early warning range of vital sign parameters according to the normal range of the vital sign parameters, and calculating the abnormality degree of vital sign data sequences corresponding to each vital sign parameter according to the dispersion condition and the change condition of the vital sign data sequences corresponding to each vital sign parameter by combining the normal range and the early warning range of the vital sign parameters.
It should be noted that, in this embodiment, by reducing the threshold parameter in the DP algorithm when compressing the optical signal of the abnormal physiological state of the user and the time period before and after the abnormal physiological state of the user, the difference between the vital sign data extracted from the optical signal and the real vital sign data is reduced, so that the vital sign data extracted from the optical signal can reflect the real physical condition of the user more, thereby ensuring the transmission efficiency of the optical signal and preferentially ensuring the authenticity of the optical signal of the abnormal physiological state of the user and the time period before and after the abnormal physiological state of the user.
It should be further noted that, therefore, at the optical signal receiving end, the received optical signal is processed and analyzed, the vital sign parameter is extracted and calculated, the vital sign parameter needs to be simply analyzed, the abnormal degree of the physiological state of the user is determined, the threshold parameter in the DP algorithm when the optical signal curve of the next preset time period is compressed is adjusted according to the abnormal degree of the physiological state of the user, the greater the abnormal degree of the physiological state of the user, the more accurate vital sign data is needed, and the real physical condition of the user is reflected, the smaller the threshold parameter in the DP algorithm is.
1. And obtaining an early warning range of the vital sign parameters according to the normal range of the vital sign parameters.
When the abnormal degree of the physiological state of the user is obtained by analyzing the vital sign parameters, the conventional method generally obtains a normal range by setting an upper limit and a lower limit of the vital sign parameters, and indicates that the vital sign data is normal when the vital sign data is in the normal range of the corresponding vital sign parameters, wherein the normal range of respiration is [12,20], the normal range of pulse is [60,100], the normal range of body temperature is [36.2,37.3], the normal range of diastolic pressure is [60,90], and the normal range of systolic pressure is [90,140]; only when the vital sign data exceeds the normal range, the physiological state of the user is considered to be abnormal, but when the vital sign data of the patient is greatly changed within the normal number range and is very close to the upper limit and the lower limit for a plurality of times, the physiological state of the user is not considered to be abnormal because the vital sign data does not exceed the set normal range, but the physiological state of the user is about to become abnormal even belongs to the abnormality at the moment; therefore, the early warning range of the vital sign parameters is set in combination with the normal range of the vital sign parameters, and the abnormal degree of the physiological state of the user is obtained in combination with the change condition of the vital sign data in the early warning range of the vital sign parameters.
Presetting a parameterWherein the present embodiment->The embodiment is not particularly limited, and is described by taking 0.8 as an example, wherein +.>Depending on the particular implementation.
Specifically, the normal range of the first vital sign parameter is [12,20]The normal range of the second vital sign parameter is [60,100]The normal range of the third vital sign parameter is [36.2,37.3]]The fourth vital sign parameter has a normal range of [60,90]The normal range of the fifth vital sign parameter is [90,140]]The method comprises the steps of carrying out a first treatment on the surface of the By usingAnd->Respectively represent the lower limit and the upper limit of the normal range of the ith vital sign parameter, the normal range of the ith vital sign parameter is +.>The method comprises the steps of carrying out a first treatment on the surface of the Will->As the early warning range of the ith vital sign parameter.
2. And calculating the abnormality degree of the vital sign data sequences corresponding to each vital sign parameter according to the dispersion condition and the change condition of the vital sign data sequences corresponding to each vital sign parameter by combining the normal range and the early warning range of the vital sign parameter.
Specifically, processing and analyzing the received optical signal curve corresponding to each vital sign parameter, extracting and calculating vital sign data, and obtaining a vital sign data sequence corresponding to each vital sign parameter; specific processing and analysis, and extraction and calculation methods are known in the intelligent AR polarization detector, and are not described herein.
Specifically, a subsequence composed of a plurality of vital sign data continuously exceeding an early warning range in a vital sign data sequence corresponding to each vital sign parameter is obtained, and a plurality of subsequences of the vital sign data sequence corresponding to each vital sign parameter are obtained altogether; according to the dispersion condition of the vital sign data sequence corresponding to each vital sign parameter and the change condition of a plurality of subsequences of the vital sign data sequence corresponding to each vital sign parameter, calculating the abnormality degree of the vital sign data sequence corresponding to each vital sign parameter, wherein the specific calculation formula is as follows:
representing the degree of abnormality of the vital sign data sequence corresponding to the ith vital sign parameter, ++>Representation ofVariance of vital sign data sequence corresponding to the ith vital sign parameter,/th vital sign parameter>Representing the number of subsequences in the vital sign data sequence corresponding to the ith vital sign parameter,/->Mean rate of change of the jth subsequence of the vital sign data sequence corresponding to the ith vital sign parameter,/th>Mean value of absolute values of differences of all adjacent two vital sign data in the j-th subsequence of the vital sign data sequence corresponding to the i-th vital sign parameter,/>A length of a j-th subsequence representing a vital sign data sequence corresponding to the i-th vital sign parameter,/and>represents the length of the vital sign data sequence corresponding to the i-th vital sign parameter,mean value of vital sign data exceeding normal range in jth subsequence of vital sign data sequence representing ith vital sign parameter +.>And the degree of exceeding the normal range in the j-th subsequence of the vital sign data sequence corresponding to the i-th vital sign parameter is represented.
Variance of vital sign data sequence corresponding to ith vital sign parameterThe dispersion condition of vital sign data sequences corresponding to the ith vital sign parameter is represented, and the larger the value is, the more the vital sign data of the patient is changed more severely, and the more the physiological state of the user is likely to occurThe greater the degree of abnormality of the vital sign data sequence, the abnormality is generated; average rate of change of the jth subsequence of the vital sign data sequence corresponding to the ith vital sign parameter +.>The change condition of the subsequence is characterized, the larger the value is, the faster the change of vital sign data in the subsequence is, the more likely the vital sign data break through the normal range of vital sign parameters in a short time, the more likely the physiological state of a user is abnormal, and the greater the degree of abnormality of the vital sign data sequence corresponding to the ith vital sign parameter is; />The continuous degree of the data exceeding the early warning range in the j sub-sequence of the vital sign data sequence corresponding to the i vital sign parameter is represented, and the larger the value is, the longer the duration time that the vital sign data of the patient is very close to the upper limit and the lower limit of the normal range of the vital sign parameter is, at the moment, the more abnormal the physiological state of the user is likely to occur, and the greater the abnormal degree of the vital sign data sequence corresponding to the i vital sign parameter is; />The j sub-sequence of the vital sign data sequence corresponding to the i vital sign parameter is represented by the degree exceeding the normal range, and the larger the value is, the larger the degree exceeding the normal range in the sub-sequence is, the larger the degree of abnormality of the physiological state of the user is, and the larger the abnormality degree of the vital sign data sequence corresponding to the i vital sign parameter is; use->As gamma transformation function->The larger the value is, the gamma factorThe smaller the gamma transformation function +.>The greater the degree of abnormality of the vital sign data sequence corresponding to the i-th vital sign parameter, the greater.
It should be noted that, the abnormal degree of the vital sign data sequence calculated in this embodiment is only used for calculating the threshold parameter in the DP algorithm when the optical signal is compressed in the following, and the physical health of the user needs to be combined with the vital sign data of the user and other environmental information by the professional healthcare staff, so as to provide more comprehensive health analysis and guidance.
S004, according to the abnormal degree of all the reference curves of the optical signal curves corresponding to each vital sign parameter to be transmitted currently, obtaining the improved threshold value of the optical signal curve to be transmitted corresponding to each vital sign parameter.
It should be noted that, in this embodiment, in order to improve the transmission efficiency of the polarization detection data, the reality of the optical signal in the front and rear periods of the abnormal physiological state of the user is preferentially ensured, and according to the abnormal degree of the vital sign data sequence corresponding to each vital sign parameter, the threshold parameter in the DP algorithm is adjusted when the optical signal in the rear period is compressed, and mainly by reducing the threshold parameter in the DP algorithm, the difference between the vital sign data extracted by the optical signal and the real vital sign data is reduced, so that the vital sign data extracted by the optical signal can reflect the real physical condition of the user more.
A number S is preset, where the embodiment is described by taking s=6 as an example, and the embodiment is not specifically limited, where S may be determined according to the specific implementation situation.
Specifically, obtaining an optical signal curve corresponding to each vital sign parameter to be transmitted currently, and respectively marking the optical signal curves to be transmitted corresponding to the first vital sign parameter to the optical signal curves to be transmitted corresponding to the fifth vital sign parameter; and respectively marking the optical signal curves corresponding to the S vital sign parameters before the optical signal curve corresponding to each vital sign parameter to be transmitted at present as a first reference curve to a sixth reference curve of the optical signal curve corresponding to each vital sign parameter to be transmitted at present according to the sequence from small to large of the time difference with the current moment.
Further, according to the abnormal degree of all the reference curves of the optical signal curve corresponding to each vital sign parameter to be transmitted currently, an improved threshold value of the optical signal curve to be transmitted corresponding to each vital sign parameter is obtained, and a specific calculation formula is as follows:
an improved threshold value representing the optical signal profile to be transmitted corresponding to the ith vital sign parameter, +.>An initial threshold value representing the ith vital sign parameter, < +.>The abnormal degree of the S-th reference curve of the light signal curve to be transmitted corresponding to the i-th vital sign parameter is represented, and S represents the preset quantity.
In the embodiment, the current physiological state of the user is predicted according to the physiological state of the user within 1 minute before the current moment, and the more abnormal the physiological state of the user within 1 minute before, the greater the possibility of abnormality of the physiological state of the current user; therefore, the present embodiment obtains the improved threshold value of the target optical signal curve according to the abnormality degree of the 6 vital sign data sequences of the previous 1 minute, and the user physiological state which is closer to the current time in time is more important to predict the current user physiological state, so that the abnormality degree of the vital sign data sequence which is closer to the target optical signal curve in time can characterize the abnormality degree of the vital sign data sequence corresponding to the target optical signal curve, the time difference is taken as the gamma factor, the smaller the time difference of the vital sign data sequence which is closer to the target optical signal curve is, the smaller the gamma factor is, and the corresponding gamma function is adoptedThe larger the transformed result is, the smaller the improved threshold value of the optical signal curve to be transmitted corresponding to the ith vital sign parameter is +.>The difference between the vital sign data extracted by the optical signal and the real vital sign data is reduced, so that the vital sign data extracted by the optical signal can reflect the real physical condition of the user.
And S005, compressing the optical signal curve to be transmitted corresponding to each vital sign parameter according to the improvement threshold.
Specifically, an improved threshold value of an optical signal curve to be transmitted corresponding to each vital sign parameter is used as a threshold value parameter in a DP algorithm, the optical signal curve to be transmitted corresponding to each vital sign parameter is compressed through the DP algorithm, a compression result is transmitted to an optical signal receiving end, the received compression result is decompressed, an optical signal obtained through decompression is processed and analyzed, vital sign parameters are extracted and calculated, and professional medical staff combines vital sign data of a user with other environmental information to provide more comprehensive health analysis and guidance.
In order to monitor the physiological state of a user in real time, the real-time performance of optical signal transmission of the intelligent AR polarization detector needs to be ensured; in order to solve the problem that the reality of vital sign data extracted through optical signals is guaranteed while the transmission efficiency of the optical signals is guaranteed, the method combines the physiological state abnormality of a user and vital sign data in a period before and after the physiological state abnormality of the user to have significance for analyzing the physical state of the user, and the method calculates the abnormality degree of vital sign data sequences corresponding to each vital sign parameter, obtains the improved threshold value of an optical signal curve to be transmitted corresponding to each vital sign parameter according to the abnormality degree of all reference curves of the optical signal curve corresponding to each vital sign parameter to be transmitted currently, reduces the difference between a compression result and the optical signals through the abnormality degree, reduces the difference between the vital sign data extracted through the optical signals and the real vital sign data, and preferentially ensures the reality of the optical signals in the period before and after the physiological state abnormality of the user while guaranteeing the transmission efficiency of the optical signals, so that the vital sign data extracted through the optical signals can reflect the real physical state of the user more.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (10)
1. A method for processing intelligent AR polarization detection data capable of detecting vital signs, the method comprising:
acquiring an optical signal curve and a historical normal optical signal curve corresponding to each vital sign parameter;
decomposing a historical normal light signal curve corresponding to each vital sign parameter to obtain an initial threshold value of each vital sign parameter;
converting the optical signal curve corresponding to each vital sign parameter into a vital sign data sequence corresponding to each vital sign parameter; obtaining a normal range and an early warning range of each vital sign parameter; combining the normal range and the early warning range of each vital sign parameter, and calculating the abnormality degree of the vital sign data sequence corresponding to each vital sign parameter according to the dispersion condition and the change condition of the vital sign data sequence corresponding to each vital sign parameter;
acquiring all reference curves of the optical signal curves corresponding to each vital sign parameter to be transmitted currently; obtaining an improved threshold value of the optical signal curve to be transmitted corresponding to each vital sign parameter according to the abnormal degree of all reference curves of the optical signal curve corresponding to each vital sign parameter to be transmitted currently;
and compressing the optical signal curves to be transmitted corresponding to each vital sign parameter according to the improved threshold.
2. The method for processing intelligent AR polarization detection data capable of detecting vital signs according to claim 1, wherein the step of obtaining the initial threshold value of each vital sign parameter comprises the following specific steps:
STL decomposition is carried out on the historical normal optical signal curve corresponding to each vital sign parameter, and a periodic item sequence of the historical normal optical signal curve corresponding to each vital sign parameter is obtained; dividing a periodic item sequence of a historical normal optical signal curve corresponding to each vital sign parameter into a plurality of periodic segments according to all extreme points, marking a connecting line of two extreme points of each periodic segment as a datum line of each periodic segment, marking the maximum value of the distances from all data points on each periodic segment to the datum line of each periodic segment as the maximum error of each periodic segment, and marking the average value of the maximum errors of all periodic segments as the initial threshold value of each vital sign parameter.
3. The method for processing intelligent AR polarization detection data capable of detecting vital signs according to claim 1, wherein the calculating the degree of abnormality of the vital sign data sequence corresponding to each vital sign parameter comprises the following specific steps:
processing and analyzing the received optical signal curve corresponding to each vital sign parameter to obtain a vital sign data sequence corresponding to each vital sign parameter; obtaining a subsequence composed of a plurality of vital sign data continuously exceeding an early warning range in a vital sign data sequence corresponding to each vital sign parameter, and obtaining a plurality of subsequences of the vital sign data sequence corresponding to each vital sign parameter; calculating the degree of abnormality of vital sign data sequences corresponding to each vital sign parameter, wherein a specific calculation formula is as follows:
representing the degree of abnormality of the vital sign data sequence corresponding to the ith vital sign parameter, ++>Representing the variance of the vital sign data sequence corresponding to the ith vital sign parameter,/for>Representing the number of subsequences in the vital sign data sequence corresponding to the ith vital sign parameter,/->Mean rate of change of the jth subsequence of the vital sign data sequence corresponding to the ith vital sign parameter,/th>A length of a j-th subsequence representing a vital sign data sequence corresponding to the i-th vital sign parameter,/and>representing the length of the vital sign data sequence corresponding to the ith vital sign parameter,/for>Mean value of vital sign data exceeding normal range in jth subsequence of vital sign data sequence representing ith vital sign parameter +.>And the degree of exceeding the normal range in the j-th subsequence of the vital sign data sequence corresponding to the i-th vital sign parameter is represented.
4. The method for processing intelligent AR polarization detection data capable of detecting vital signs according to claim 1, wherein the obtaining of the improved threshold value of the optical signal curve to be transmitted corresponding to each vital sign parameter comprises the following specific steps:
an improved threshold value representing the optical signal profile to be transmitted corresponding to the ith vital sign parameter, +.>An initial threshold value representing the ith vital sign parameter, < +.>The abnormal degree of the S-th reference curve of the light signal curve to be transmitted corresponding to the i-th vital sign parameter is represented, and S represents the preset quantity.
5. The method for processing intelligent AR polarization detection data capable of detecting vital signs according to claim 1, wherein the steps of obtaining the optical signal curve and the historical normal optical signal curve corresponding to each vital sign parameter comprise the following specific steps:
the intelligent AR polarization detector selects polarized light in a specific direction through a polarization filter, and receives and converts the obtained optical signals into optical signals corresponding to the first vital sign parameter to the fifth vital sign parameter through the detector;
respectively forming a curve of the optical signals corresponding to each vital sign parameter in a preset time period T according to the sequence, wherein the curve is used as an optical signal curve corresponding to each vital sign parameter and is respectively an optical signal curve corresponding to a first vital sign parameter to an optical signal curve corresponding to a fifth vital sign parameter;
and selecting a curve formed by the optical signals corresponding to each vital sign parameter according to the sequence when the physical health condition of the user is good from the historical data, wherein the time length corresponding to the required curve is 30T, and the curve is used as a historical normal optical signal curve corresponding to each vital sign parameter and is respectively from the historical normal optical signal curve corresponding to the first vital sign parameter to the historical normal optical signal curve corresponding to the fifth vital sign parameter.
6. The method for processing intelligent AR polarization detection data capable of detecting vital signs according to claim 5, wherein the first to fifth vital sign parameters comprise the following specific steps:
the 5 vital sign parameters of respiration, pulse, body temperature, diastolic pressure and systolic pressure are respectively noted as first vital sign parameter to fifth vital sign parameter.
7. The method for processing intelligent AR polarization detection data capable of detecting vital signs according to claim 1, wherein the obtaining of the normal range and the early warning range of each vital sign parameter comprises the following specific steps:
presetting the normal range of each vital sign parameter byAnd->Respectively represent the lower limit and the upper limit of the normal range of the ith vital sign parameter, the normal range of the ith vital sign parameter is +.>The method comprises the steps of carrying out a first treatment on the surface of the Will->Early warning range as i vital sign parameter, < +.>Representing preset parameters.
8. The method for processing intelligent AR polarization detection data of detectable vital signs according to claim 1, wherein the step of converting the optical signal curve corresponding to each vital sign parameter into the vital sign data sequence corresponding to each vital sign parameter comprises the following specific steps:
and processing and analyzing the received optical signal curve corresponding to each vital sign parameter, extracting and calculating vital sign data, and obtaining a vital sign data sequence corresponding to each vital sign parameter.
9. The method for processing intelligent AR polarization detection data capable of detecting vital signs according to claim 1, wherein the step of obtaining all reference curves of the optical signal curves corresponding to each vital sign parameter to be transmitted currently comprises the following specific steps:
acquiring optical signal curves corresponding to each vital sign parameter to be transmitted currently, and respectively marking the optical signal curves to be transmitted corresponding to the first vital sign parameter to the optical signal curves to be transmitted corresponding to the fifth vital sign parameter; and respectively marking the preset number S of optical signal curves corresponding to each vital sign parameter before the optical signal curve corresponding to each vital sign parameter to be transmitted at present as a first reference curve to a sixth reference curve of the optical signal curve corresponding to each vital sign parameter to be transmitted at present according to the sequence from the small time difference to the large time difference at the present moment.
10. The method for processing intelligent AR polarization detection data capable of detecting vital signs according to claim 1, wherein the compressing the optical signal curve to be transmitted corresponding to each vital sign parameter according to the improvement threshold comprises the following specific steps:
the improved threshold value of the optical signal curve to be transmitted corresponding to each vital sign parameter is used as a threshold value parameter in a DP algorithm, the optical signal curve to be transmitted corresponding to each vital sign parameter is compressed through the DP algorithm, a compression result is transmitted to an optical signal receiving end, the received compression result is decompressed, the optical signal obtained through decompression is processed and analyzed, vital sign parameters are extracted and calculated, and professional medical staff combines vital sign data of a user and other environmental information to provide more comprehensive health analysis and guidance.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117649914A (en) * | 2024-01-30 | 2024-03-05 | 陕西省核工业二一五医院 | Patient physical sign real-time monitoring system for gastroscope anesthesia process |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060033879A1 (en) * | 2004-07-01 | 2006-02-16 | Eastman Kodak Company | Scanless virtual retinal display system |
| CN105142498A (en) * | 2013-03-15 | 2015-12-09 | 感知技术有限公司 | Enhanced optical and perceptual digital eyewear |
| US20170103440A1 (en) * | 2015-08-01 | 2017-04-13 | Zhou Tian Xing | Wearable augmented reality eyeglass communication device including mobile phone and mobile computing via virtual touch screen gesture control and neuron command |
| CN107106017A (en) * | 2014-10-30 | 2017-08-29 | 皇家飞利浦有限公司 | Equipment, system and method for extracting physiologic information |
| CN108474956A (en) * | 2015-12-29 | 2018-08-31 | 微软技术许可有限责任公司 | Augmented reality display system with variable focus |
| CN110095866A (en) * | 2018-01-29 | 2019-08-06 | 京东方科技集团股份有限公司 | Augmented reality device, augmented reality system and its information cuing method |
| CN110361866A (en) * | 2019-07-11 | 2019-10-22 | Oppo广东移动通信有限公司 | A kind of transmitted light intensity is adjustable to wear display equipment |
| CN110558956A (en) * | 2019-08-21 | 2019-12-13 | 武汉凯锐普信息技术有限公司 | Vital sign monitoring device |
| CN111916215A (en) * | 2020-06-17 | 2020-11-10 | 扬州大学附属医院 | Cluster/chronic disease early automatic alarm, preliminary feature analysis and risk assessment system |
| CN113509152A (en) * | 2021-09-15 | 2021-10-19 | 深圳市脉度科技有限公司 | Method and device for detecting skin physiological parameters and intelligent terminal |
-
2023
- 2023-10-11 CN CN202311307941.5A patent/CN117064343B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060033879A1 (en) * | 2004-07-01 | 2006-02-16 | Eastman Kodak Company | Scanless virtual retinal display system |
| CN105142498A (en) * | 2013-03-15 | 2015-12-09 | 感知技术有限公司 | Enhanced optical and perceptual digital eyewear |
| CN107106017A (en) * | 2014-10-30 | 2017-08-29 | 皇家飞利浦有限公司 | Equipment, system and method for extracting physiologic information |
| US20170103440A1 (en) * | 2015-08-01 | 2017-04-13 | Zhou Tian Xing | Wearable augmented reality eyeglass communication device including mobile phone and mobile computing via virtual touch screen gesture control and neuron command |
| CN108474956A (en) * | 2015-12-29 | 2018-08-31 | 微软技术许可有限责任公司 | Augmented reality display system with variable focus |
| CN110095866A (en) * | 2018-01-29 | 2019-08-06 | 京东方科技集团股份有限公司 | Augmented reality device, augmented reality system and its information cuing method |
| CN110361866A (en) * | 2019-07-11 | 2019-10-22 | Oppo广东移动通信有限公司 | A kind of transmitted light intensity is adjustable to wear display equipment |
| CN110558956A (en) * | 2019-08-21 | 2019-12-13 | 武汉凯锐普信息技术有限公司 | Vital sign monitoring device |
| CN111916215A (en) * | 2020-06-17 | 2020-11-10 | 扬州大学附属医院 | Cluster/chronic disease early automatic alarm, preliminary feature analysis and risk assessment system |
| CN113509152A (en) * | 2021-09-15 | 2021-10-19 | 深圳市脉度科技有限公司 | Method and device for detecting skin physiological parameters and intelligent terminal |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117649914A (en) * | 2024-01-30 | 2024-03-05 | 陕西省核工业二一五医院 | Patient physical sign real-time monitoring system for gastroscope anesthesia process |
| CN117649914B (en) * | 2024-01-30 | 2024-04-26 | 陕西省核工业二一五医院 | Patient physical sign real-time monitoring system for gastroscope anesthesia process |
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