Detailed Description
The application provides a real-time detection method and a real-time detection system for fatigue situations of epidemic prevention personnel, which are used for solving the technical problem that the prior art has no related method suitable for detecting the fatigue states of the epidemic prevention personnel and has poor detection effect on the fatigue states of the epidemic prevention personnel.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments.
Example 1
As shown in fig. 1, the embodiment of the application provides a real-time detection method for fatigue situations of epidemic prevention personnel, which specifically comprises the following steps:
Step 100, collecting and acquiring a plurality of types of real-time sign data of epidemic prevention personnel, and acquiring a plurality of real-time sign data sets as result data;
in the embodiment of the application, the epidemic prevention personnel is the personnel performing epidemic situation prevention and control work, and is preferably the personnel performing epidemic prevention work such as nucleic acid detection, vaccine injection and the like.
And collecting a plurality of types of real-time physical sign data of epidemic prevention personnel to obtain a plurality of real-time physical sign data sets. The real-time physical sign data are preferably electrocardiographic and galvanic skin physical sign data, the physical sign data can avoid the influence of protective clothing and protective masks of epidemic prevention personnel, the real-time physical sign data which can reflect the real state of epidemic prevention personnel can be acquired and obtained, and after the acquisition is completed, the real-time physical sign data sets are stored as result data.
The step S100 in the method provided by the embodiment of the application comprises the following steps:
s110, acquiring electrocardio data and skin conductance level data of the epidemic prevention personnel;
S120, performing feature extraction on the electrocardiograph data and the skin electric conduction level data until the time length of the electrocardiograph data and the skin electric conduction level data reaches a third preset time length to obtain HR data, HF data and SCL data;
And S130, taking the HR data, the HF data and the SCL data as the result data, and emptying the current data cache.
Specifically, based on medical detection means in the prior art, real-time electrocardiographic data and skin electric conduction level data of epidemic prevention personnel are detected and obtained.
And continuously collecting until the time length of the electrocardiograph data and the dermatologic conduction level data reaches a third preset time length, wherein the third preset time length can be set according to requirements, and the electrocardiograph data and the dermatologic conduction level data of the time length required to be collected and acquired have a certain representativeness, so that the too short time length is avoided. Preferably, the third preset time period is 5Min.
Feature extraction is performed on the acquired electrocardiographic data and the electrocardiographic conduction level data, and HR (Heart rate) data, HF data and SCL (skin conductivity level) data are obtained based on electrocardiographic data analysis means and skin electrical analysis means in the prior art, wherein HR data can be obtained based on heart rate data in electrocardiographic data, HF high-frequency data can be obtained based on heart rate variability analysis methods in the prior art, fourier transformation is performed on electrocardiographic data during RR, and SCL data can be obtained based on skin electrical data.
And taking the HR data, the HF data and the SCL data as current result data, wherein the corresponding time period of the result data is a third preset time length. And then, continuously collecting the result data in the next third preset time length time period, buffering and clearing the current data, and taking the current result data as a data base for detecting the fatigue state of epidemic prevention personnel to carry out the next judgment analysis.
Step 200, judging whether the result data contains resting state data or not, and obtaining a judging result;
In the embodiment of the application, whether the result data contains resting state data or not is judged, wherein the resting state data is electrocardio and skin electricity data of a human being in a conscious and relaxed state. The judgment result can be obtained by judging whether resting state data exists in the result data based on the judgment method in the prior art and the experience of electrocardiograph and skin electric detection of epidemic prevention personnel.
Step 300, if the judgment result is negative, continuously acquiring and acquiring a plurality of types of real-time sign data of the epidemic prevention personnel until the time length of the result data is greater than a first preset time length, and deleting the result data;
In the embodiment of the present application, if the determination result in step S200 is no, if no resting state data exists in the current result data, it is reflected that the current epidemic prevention personnel is not in a fatigue state, no further analysis processing is required to be performed according to the result data, the result data is temporarily stored, and the real-time physical sign data of the epidemic prevention personnel is continuously collected and whether the resting state data exists is determined, that is, steps S100 to S200 are repeated.
Thus, a plurality of types of real-time sign data of epidemic prevention personnel are continuously acquired and obtained, when the accumulated time length of the result data is longer than the first preset time length, the result data of the epidemic prevention personnel in the first preset time length have no rest state data, so that the memory is saved, and the currently stored result data are deleted.
The first predetermined time period is preferably a longer time period, preferably 3 hours.
Step 400, if the judgment result is yes, continuously acquiring and acquiring a plurality of types of real-time sign data of the epidemic prevention personnel until the time length of the result data is greater than a second preset time length, wherein the second preset time length is smaller than the first preset time length;
If the result of the step S200 is yes, the rest state data exists in the result data, so that the epidemic prevention personnel may have a fatigue state, and the result data needs to be analyzed and processed to calculate the probability of the fatigue state of the epidemic prevention personnel.
Specifically, the collection of the real-time sign data of the epidemic prevention personnel is continued to increase the data scale until the time length of the accumulated result data is greater than the second preset time length. The second preset time length is smaller than the first preset time length, the second preset time length needs to meet the data scale requirement of data analysis, and preferably, the second preset time length is 1h.
S500, analyzing the rest state data and the accumulated data in the result data to obtain an analysis result;
Specifically, on the basis of step S400, there is resting state data in the result data, the resting state data in the result data is extracted to obtain resting state electrocardiographic data and resting state galvanic skin data, other data are accumulated electrocardiographic data and accumulated galvanic skin data, and the resting state data and accumulated data in the result data are analyzed to serve as a data basis for detecting whether the epidemic prevention personnel has fatigue.
The step S500 in the method provided by the embodiment of the present application includes:
s510, carrying out data classification on the result data to obtain the resting state data and the accumulated data;
S520, comparing a plurality of data characteristics of the resting state data and the accumulated data by using a Kruskal-Wallis method to obtain a comparison result;
S530, according to the comparison result, recording and obtaining、、As a result of the analysis.
Specifically, the accumulated result data is classified to obtain resting state data and accumulated data. The Kruskal-Wallis method was used to compare the data characteristics of the resting state data and the accumulated data. Specifically, a plurality of data features of resting HR data and accumulated HR data, resting HF data and accumulated HF data, resting SCL data and accumulated SCL data are compared, and a comparison result is obtained.
Wherein, to avoid the interference of the data error, the first 10% and the last 10% of the data in the plurality of data characteristics in the resting state data are deleted before the comparison, and then the comparison of the plurality of data characteristics of the resting state data and the accumulated data is performed.
According to the comparison result, recording the probability that the resting state HR data and the accumulated HR data come from the same population in the comparison resultIn the same way, obtain、As a result of the above analysis.
The embodiment of the application obtains the resting state data and the accumulated data by classifying the result data, and then compares and analyzes each characteristic of the resting state data and the accumulated data based on the Kruskal-Wallis method to obtain、、As a data base for detecting and judging the fatigue condition of epidemic prevention personnel, the characteristics of resting state data and accumulated data in the result data are fully utilized.
And S600, calculating the probability value of the fatigue condition of the epidemic prevention personnel according to the analysis result and outputting the probability value.
As shown in fig. 2, step S600 in the method provided by the embodiment of the present application includes:
s610, according to the、、Performing multi-factor judgment to obtain a judgment result;
s620, calculating and outputting the probability value according to the judging result.
Wherein, step S610 includes:
s611 judging the、、If any one of the above is more than 0.8, obtaining a first-level judgment result;
s612, if the primary judgment result is yes, continuing to judge whether the primary judgment result exists>Or (b)>Or (b)>Obtaining a secondary judgment result;
and S613, generating a judging result based on the primary judging result and the secondary judging result.
Before calculating the probability value of the fatigue condition of epidemic prevention personnel, judging whether the possible fatigue condition is met or not according to the analysis result.
Specifically, judge、、If any one of the above is more than 0.8, obtaining a first-level judgment result.
Further, if the first-level judgment result is yes, continuing to judge whether the first-level judgment result exists>Or (b)>Or (b)>And obtaining a secondary judgment result.
And obtaining a final judgment result according to the first-level judgment result and the second-level judgment result. According to the method provided by the embodiment of the application, the specific judging conditions are set, so that the analysis result is judged, whether the electrocardio data and the skin electricity data conditions of possible fatigue of epidemic prevention personnel occur or not is judged, further, the probability value is calculated according to the judging result, and the fatigue state detection analysis of the epidemic prevention personnel can be more accurately carried out.
Step S620 in the method provided by the embodiment of the present application includes:
s621, if the first-level judgment result and the second-level judgment result are both yes, calculatingObtaining the probability value and outputting the probability value;
S622, if the primary judgment result or the secondary judgment result is negative, the probability value is 0 and is output.
If the primary judgment result and the secondary judgment result are both yes in the judgment result of the step S610 in the above step, the method is based on the above、、The probability value of the fatigue state of epidemic prevention personnel is calculated as follows:
And P is the probability value, and is calculated and obtained and used as the probability value of the fatigue state of the current epidemic prevention personnel to be output.
If the first-level or second-level judgment result in the judgment result of step S610 is negative, it may be judged that the fatigue state of the epidemic prevention personnel does not occur, and the probability value is 0 and output as the current fatigue state detection result of the epidemic prevention personnel.
Fig. 3 shows a flowchart of a method provided by an embodiment of the present application.
In summary, the real-time detection method for the fatigue condition of epidemic prevention personnel provided by the application has the following technical effects:
According to the embodiment of the application, the fatigue state detection of epidemic prevention personnel is carried out by detecting real-time physical sign data comprising electrocardio data, skin electricity data and the like, so that noise and influence of epidemic prevention masks and protective clothing during work of the epidemic prevention personnel can be avoided, and the operation condition of the epidemic prevention personnel is adapted.
Example two
Based on the same inventive concept as the real-time detection method of the fatigue condition of the epidemic prevention personnel in the foregoing embodiment, the present invention further provides a real-time detection system of the fatigue condition of the epidemic prevention personnel, as shown in fig. 4, where the system includes:
the result data acquisition module 11 is used for acquiring a plurality of types of real-time sign data of epidemic prevention personnel to obtain a plurality of real-time sign data sets as result data;
A rest state data judging module 12, configured to judge whether rest state data exists in the result data, and obtain a judging result;
The result data processing module 13 is configured to continuously acquire multiple types of real-time sign data of the epidemic prevention personnel if the determination result is negative, until the time length of the result data is greater than a first preset time length, and delete the result data;
The continuous acquisition module 14 is configured to continuously acquire multiple types of real-time sign data of the epidemic prevention personnel if the determination result is yes, until the time length of the result data is greater than a second preset time length, where the second preset time length is less than the first preset time length;
The data analysis module 15 is used for analyzing the rest state data and the accumulated data in the result data to obtain an analysis result;
And the fatigue probability calculation module 16 is used for calculating the probability value of the fatigue condition of the epidemic prevention personnel according to the analysis result and outputting the probability value.
Further, the result data acquisition module 11 is further configured to implement the following functions:
Acquiring electrocardiographic data and skin electric conduction level data of the epidemic prevention personnel;
performing feature extraction on the electrocardiograph data and the skin electric conduction level data until the time length of the electrocardiograph data and the skin electric conduction level data reaches a third preset time length to obtain HR data, HF data and SCL data;
And taking the HR data, the HF data and the SCL data as the result data, and emptying the current data cache.
Further, the rest state data determining module 12 is further configured to implement the following functions:
judging whether the multiple evaluation indexes are overrule indexes or not, and obtaining a judging result;
and according to the judging result, carrying out weight distribution determination on the multiple evaluation indexes which are not overrule indexes.
Further, the data analysis module 15 is further configured to implement the following functions:
Data classification is carried out on the result data to obtain the resting state data and the accumulated data;
comparing a plurality of data characteristics of the resting state data and the accumulated data by using a Kruskal-Wallis method to obtain a comparison result;
From the comparison result, record and obtain、、As a result of the analysis.
Further, the fatigue probability calculation module 16 is further configured to implement the following functions:
according to the described、、Performing multi-factor judgment to obtain a judgment result;
and calculating and outputting the probability value according to the judging result.
Wherein according to the said、、And performing multi-factor judgment, including:
Judging the said、、If any one of the above is more than 0.8, obtaining a first-level judgment result;
if the primary judgment result is yes, continuing to judge whether the primary judgment result exists>Or (b)>Or (b)>Obtaining a secondary judgment result;
And generating the judging result based on the primary judging result and the secondary judging result.
Wherein the calculating and outputting the probability value includes:
If the first-level judgment result and the second-level judgment result are both yes in the judgment results, calculatingObtaining the probability value and outputting the probability value;
and if the primary judging result or the secondary judging result is negative, the probability value is 0 and is output.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The specification and figures are merely exemplary illustrations of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents that fall within the scope of the application. It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the scope of the application. Thus, the present application is intended to include such modifications and alterations insofar as they come within the scope of the application or the equivalents thereof.