CN111261264A - Intelligent physique testing device and method and storage medium - Google Patents
Intelligent physique testing device and method and storage medium Download PDFInfo
- Publication number
- CN111261264A CN111261264A CN202010140475.6A CN202010140475A CN111261264A CN 111261264 A CN111261264 A CN 111261264A CN 202010140475 A CN202010140475 A CN 202010140475A CN 111261264 A CN111261264 A CN 111261264A
- Authority
- CN
- China
- Prior art keywords
- test
- data
- module
- temperature
- test data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012360 testing method Methods 0.000 title claims abstract description 231
- 238000000034 method Methods 0.000 title claims abstract description 27
- 230000002159 abnormal effect Effects 0.000 claims abstract description 36
- 230000036772 blood pressure Effects 0.000 claims abstract description 27
- 210000003205 muscle Anatomy 0.000 claims abstract description 27
- 238000010191 image analysis Methods 0.000 claims abstract description 15
- 238000013031 physical testing Methods 0.000 claims abstract description 13
- 238000004364 calculation method Methods 0.000 claims abstract description 11
- 238000012545 processing Methods 0.000 claims abstract description 9
- 238000003331 infrared imaging Methods 0.000 claims abstract description 8
- 230000008569 process Effects 0.000 claims abstract description 7
- 210000004072 lung Anatomy 0.000 claims abstract description 5
- 238000010998 test method Methods 0.000 claims description 14
- 238000005452 bending Methods 0.000 claims description 9
- 230000036760 body temperature Effects 0.000 claims description 9
- 238000001914 filtration Methods 0.000 claims description 6
- 238000012800 visualization Methods 0.000 claims description 6
- 238000005192 partition Methods 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 4
- 230000005457 Black-body radiation Effects 0.000 claims description 3
- 230000008859 change Effects 0.000 claims description 3
- 210000000056 organ Anatomy 0.000 claims description 3
- 210000001835 viscera Anatomy 0.000 claims description 3
- 230000000007 visual effect Effects 0.000 claims description 3
- 238000005303 weighing Methods 0.000 claims description 3
- 238000005259 measurement Methods 0.000 abstract description 8
- 230000036541 health Effects 0.000 abstract description 4
- 238000007726 management method Methods 0.000 abstract description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000000053 physical method Methods 0.000 description 2
- 230000005856 abnormality Effects 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H30/00—ICT specially adapted for the handling or processing of medical images
- G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
- A61B5/091—Measuring volume of inspired or expired gases, e.g. to determine lung capacity
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/107—Measuring physical dimensions, e.g. size of the entire body or parts thereof
- A61B5/1072—Measuring physical dimensions, e.g. size of the entire body or parts thereof measuring distances on the body, e.g. measuring length, height or thickness
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biomedical Technology (AREA)
- Pathology (AREA)
- Epidemiology (AREA)
- Primary Health Care (AREA)
- Cardiology (AREA)
- Physiology (AREA)
- Physics & Mathematics (AREA)
- Pulmonology (AREA)
- Biophysics (AREA)
- Radiology & Medical Imaging (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Heart & Thoracic Surgery (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Veterinary Medicine (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Abstract
The invention belongs to the technical field of health management, and discloses intelligent physique test equipment, a method and a storage medium, wherein the intelligent physique test equipment is provided with: the physique test module is used for carrying out physique test and acquiring physique test data; the camera module is used for acquiring human body posture images and human face images in the physical testing process in real time; the infrared imaging module is used for collecting infrared images of the physical examiners; the data processing module is used for processing the collected related test data; judging whether the test data is abnormal or not; the calculation module is used for calculating the BMI, the fat rate and the muscle rate; the image analysis module is used for analyzing the acquired infrared image; and the constitution scoring module is used for carrying out comprehensive constitution scoring. The invention can realize the comprehensive measurement of the human body constitution information and improve the accuracy of the constitution measurement result by collecting and calculating the height, the weight, the BMI, the fat rate, the muscle rate, the lung capacity and the blood pressure of the human body.
Description
Technical Field
The invention belongs to the technical field of health management, and particularly relates to intelligent physique test equipment, method and storage medium.
Background
Currently, the closest prior art: with the development of social economy, the health awareness of people is improved, more and more units provide health exercise suggestions for better understanding and mastering the physical quality of employees, and the regular physical fitness detection of the employees is started after the enterprise exercise culture is built. Under the large background, a more efficient, scientific, reasonable, complete and accurate physique detection system is urgently needed, and the overall physique examination is carried out through standard quantification. At present, the physical testing equipment on the market has few types of measurement, cannot realize integral physical measurement, and has unrepresentative results of physical testing.
In summary, the problems of the prior art are as follows: at present, the physical testing equipment on the market has few measurement types, cannot realize integral physical measurement, and has unrepresentative physical testing results and inaccurate testing results.
Disclosure of Invention
In view of the problems of the prior art, the present invention provides an intelligent physical fitness test device, method and storage medium.
The present invention is achieved as such, an intelligent physical fitness test apparatus, which is provided with:
the physical testing module is connected with the central control module and is used for carrying out relevant physical tests and acquiring physical testing data;
the data reading module is connected with the central control module and used for acquiring the uploaded relevant physical fitness test data by utilizing the reading and writing equipment;
the camera module is connected with the central control module and is used for acquiring human body posture images and human face images in the physical fitness test process in real time;
the infrared imaging module is connected with the central control module and is used for collecting the infrared image of the physical examiner through the thermal infrared imager;
the height acquisition module is connected with the central control module and is used for acquiring height information through the measuring scale;
the weight acquisition module is connected with the central control module and is used for acquiring weight information through the weight scale;
the vital capacity testing module is connected with the central control module and is used for acquiring vital capacity testing information through the vital capacity tester;
the blood pressure acquisition module is connected with the central control module and is used for acquiring blood pressure information through the sphygmomanometer;
the central control module is connected with the physique test module, the data reading module, the camera module, the infrared imaging module, the height acquisition module, the weight acquisition module, the vital capacity test module, the blood pressure acquisition module, the data processing module, the supplementary test module, the calculation module, the image analysis module, the physique grading module, the storage module and the display module and is used for controlling the normal operation of each module;
the data processing module is connected with the central control module and is used for filtering, classifying, summarizing and counting the collected related test data; judging whether the test data is abnormal or not;
the supplementary test module is connected with the central control module and is used for conducting supplementary test on specific projects when the test data are abnormal;
the computing module is connected with the central control module and used for computing the BMI, the fat rate and the muscle rate through a computing program based on the acquired related test data;
the image analysis module is connected with the central control module and is used for analyzing the acquired infrared image through an analysis program;
the constitution scoring module is connected with the central control module and is used for carrying out comprehensive constitution scoring on the basis of the test data, the BMI, the fat rate, the muscle rate and the infrared image analysis result which are obtained by calculation, the human posture image and other related test data;
the storage module is connected with the central control module and is used for storing physical testing data, human posture images, infrared images, height, weight, BMI, fat rate, muscle rate, vital capacity, blood pressure and comprehensive physical score;
and the display module is connected with the central control module and is used for displaying the physical fitness test data, the human posture image, the infrared image, the height, the weight, the BMI, the fat rate, the muscle rate, the vital capacity, the blood pressure and the comprehensive physical fitness score through the display.
Further, the fitness test module comprises:
the physique test module comprises a step test unit, a back force meter test unit, a longitudinal jump test unit, a seat body forward bending test unit and a closed-eye single-foot standing test unit;
step testing unit: the device is used for carrying out step test and obtaining relevant step test data;
back force meter test unit: the device is used for carrying out the back force meter test and acquiring the test data of the relevant back force meter;
a longitudinal jump testing unit: the device is used for carrying out a longitudinal jump test and acquiring the forward bending test data of the relative seat body;
seat body anteflexion test unit: the device is used for carrying out seat body forward flexion test and obtaining relevant seat body forward flexion test data;
closed-eye one-foot standing test unit: the method is used for carrying out the eye-closing single-foot standing test and obtaining relevant eye-closing single-foot standing test data.
Another object of the present invention is to provide an intelligent fitness test method applied to the intelligent fitness test device, the intelligent fitness test method including:
step testing, back force meter testing, longitudinal jump testing, seat body forward bending testing and closed-eye single-foot standing testing are carried out to obtain relevant physique testing data; or acquiring the uploaded relevant physical fitness test data by using read-write equipment;
acquiring a human body posture image and a human face image in the physical fitness test process in real time; collecting an infrared image of the physical examiner through an infrared thermal imager; collecting height information through a measuring scale; acquiring weight information through a weighing scale; acquiring vital capacity test information through a vital capacity tester; collecting blood pressure information through a sphygmomanometer;
step three, filtering, classifying, summarizing and counting the collected related test data; judging whether the test data is abnormal or not; when the test data is abnormal, performing the supplementary test of a specific project;
step four, calculating the BMI, the fat rate and the muscle rate through a calculation program based on the acquired related test data; analyzing the collected infrared image through an analysis program; performing comprehensive body constitution grading based on the test data, the BMI, the fat rate, the muscle rate and the infrared image analysis result obtained by calculation, the human body posture image and other related test data;
step five, storing physique test data, human posture images, infrared images, height, weight, BMI, fat rate, muscle rate, vital capacity, blood pressure and comprehensive physique scores; and displaying the physical test data, the human posture image, the infrared image, the height, the weight, the BMI, the fat rate, the muscle rate, the lung capacity, the blood pressure and the comprehensive physical score through a display.
Further, in the second step, the acquiring the infrared image of the physical examiner by the thermal infrared imager includes:
(1) establishing a multi-section linear model between the output of the thermal infrared imager and the FPA calibration temperature interval at the temperature of each black body;
(2) according to the multi-section linear model, the output of the thermal infrared imager corresponding to each black body temperature outside the FPA calibration temperature interval is predicted;
(3) correcting the output of the thermal infrared imager by sections, and eliminating the distortion of the output of the thermal infrared imager caused when the temperature of the FPA changes in the FPA calibration temperature interval and outside the FPA calibration temperature interval;
(4) and according to the Planck formula, establishing a functional relation between the output of the corrected thermal infrared imager and the Kelvin temperature in a segmented manner.
Further, in the step (1), the establishing of the multi-segment linear model between the FPA calibration temperature interval and the output of the thermal infrared imager at the black body temperature includes:
at room temperature, aligning the thermal infrared imager to a black body radiation source with fixed temperature, recording output values of the thermal infrared imager along with the change of the FPA temperature, and obtaining curves of the FPA temperature and the thermal infrared imager output under different black body temperatures;
dividing the FPA temperature into a plurality of intervals to obtain the FPA temperature and the output of the thermal infrared imager, wherein a linear model which is consistent with y-kx + b in each segmented interval is obtained.
Further, in the third step, the determining whether the test data has the abnormality includes:
1) judging whether each item of test data is omitted or repeated; if the data is missing or repeated, the data is abnormal; if not, the data is not abnormal;
2) judging whether each item of test data is within a normal standard threshold value, and if the item of test data exceeds the normal standard threshold value, judging that the data is abnormal;
3) judging whether each item of test data has larger difference, if so, comparing whether the face images and the human body posture images acquired in the two test items are consistent, and if so, judging that the data is not abnormal; if the data are inconsistent, judging that the data are abnormal;
4) and judging whether the test data of the test items corresponding to the multiple tests have large differences, if so, comparing whether the face images and the human body posture images acquired by the two times of test data are consistent, if so, judging that the data are not abnormal, and if not, judging that the data are abnormal.
Further, in the fourth step, the method for analyzing the collected infrared image comprises:
extracting temperature data of the infrared image from 5 dimensions including thermal state distribution, viscera, meridian points, anatomical partitions and color parts of the five zang organs to obtain a visual data result;
analyzing data in the visualization result data through heat comparison, and calculating to obtain reference data of each dimension;
and comparing the reference value of each dimension with the infrared image to obtain an analysis report.
Further, the method for extracting the temperature data comprises the following steps:
the thermal state distribution expresses temperature data from three aspects of symmetry, regularity and cold and heat distinguishing; the temperature data of the meridian points is derived from the temperature average value of each point fitting point and 5 adjacent pixel points; the temperature data of the anatomical partition comprises a highest value, a lowest value, a range, a standard deviation and an overall difference, wherein the overall difference is a difference value between an area temperature mean value and a trunk overall temperature mean value of an area to which the area belongs.
Further, the method for analyzing the data in the visualization result data through heat comparison comprises the following steps:
selecting two areas S1 and S2 with the same number of pixel points, respectively calculating temperature mean values T and T of the areas S1 and S2, and then according to the following formula:
T＝(T+T)/2
calculating the temperature mean value T of the two areas S1 and S2; and then by the following formula:
R＝P*T/P*T
calculating the heat ratio R of the areas S1 and S2;
wherein, P is the number of pixel points with the temperature higher than the average value T in the region S1, T is the temperature average value of P pixel points in the region S1, P is the number of pixel points with the temperature higher than the average value T in the region S2, and T is the temperature average value of P pixel points in the region S2.
Another object of the present invention is to provide a computer-readable storage medium storing instructions which, when executed on a computer, cause the computer to perform the intelligent fitness test method.
In summary, the advantages and positive effects of the invention are: the invention can realize the comprehensive and intelligent physical test and automatically output the test scores; meanwhile, the test result is accurate, reliable and comprehensive. Meanwhile, the test scoring of the invention not only depends on the test data, but also comprises the results of posture analysis and image analysis, thereby ensuring the comprehensiveness and representativeness of the physique scoring; meanwhile, the invention can avoid the situation that someone replaces the test, and the identity is confirmed through image comparison, thereby ensuring the accuracy and reliability of the test result.
According to the invention, the infrared image of the human body is collected and analyzed, so that the temperature information of the human body is comprehensively grasped; by collecting and calculating the height, the weight, the BMI, the fat rate, the muscle rate, the lung capacity and the blood pressure of the human body, the comprehensive measurement of the body constitution information of the human body can be realized, and the accuracy of the body constitution measurement result is improved.
Drawings
Fig. 1 is a block diagram of an intelligent fitness test device according to an embodiment of the present invention;
in the figure: 1. a physique test module; 2. a data reading module; 3. a camera module; 4. an infrared imaging module; 5. a height acquisition module; 6. a weight acquisition module; 7. a vital capacity testing module; 8. a blood pressure acquisition module; 9. a central control module; 10. a data processing module; 11. a supplementary measurement module; 12. a calculation module; 13. an image analysis module; 14. a constitution scoring module; 15. a storage module; 16. and a display module.
Fig. 2 is a flowchart of an intelligent fitness test method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In view of the problems of the prior art, the present invention provides an intelligent fitness test device, which is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the intelligent physical fitness test device provided by the embodiment of the present invention is provided with:
and the physique test module 1 is connected with the central control module 9 and used for carrying out related physique tests and acquiring physique test data.
And the data reading module 2 is connected with the central control module 9 and is used for acquiring the uploaded relevant physical fitness test data by using the reading and writing equipment.
The camera module 3 is connected with the central control module 9 and is used for acquiring human body posture images and human face images in the physical fitness test process in real time.
And the infrared imaging module 4 is connected with the central control module 9 and is used for collecting the infrared images of the physical examinees through the thermal infrared imager.
And the height acquisition module 5 is connected with the central control module 9 and is used for acquiring height information through a measuring scale.
And the weight acquisition module 6 is connected with the central control module 9 and is used for acquiring weight information through the weight scale.
And the vital capacity testing module 7 is connected with the central control module 9 and is used for acquiring vital capacity testing information through the vital capacity tester.
And the blood pressure acquisition module 8 is connected with the central control module 9 and is used for acquiring blood pressure information through the sphygmomanometer.
The central control module 9 is connected with the physique test module 1, the data reading module 2, the camera module 3, the infrared imaging module 4, the height acquisition module 5, the weight acquisition module 6, the vital capacity test module 7, the blood pressure acquisition module 8, the data processing module 10, the supplementary measurement module 11, the calculation module 12, the image analysis module 13, the physique scoring module 14, the storage module 15 and the display module 16, and is used for controlling the normal operation of each module.
The data processing module 10 is connected with the central control module 9 and is used for filtering, classifying, summarizing and counting the collected related test data; and judging whether the test data is abnormal or not.
And the supplementary test module 11 is connected with the central control module 9 and is used for performing supplementary test on a specific project when the test data is abnormal.
And the calculating module 12 is connected with the central control module 9 and used for calculating the BMI, the fat rate and the muscle rate through a calculating program based on the acquired related test data.
And the image analysis module 13 is connected with the central control module 9 and is used for analyzing the acquired infrared images through an analysis program.
And the constitution grading module 14 is connected with the central control module 9 and is used for carrying out comprehensive constitution grading on the basis of the test data, the BMI, the fat rate, the muscle rate, the infrared image analysis result, the human body posture image and other related test data obtained by calculation.
And the storage module 15 is connected with the central control module 9 and is used for storing physical testing data, human posture images, infrared images, height, weight, BMI, fat rate, muscle rate, vital capacity, blood pressure and comprehensive physical score.
And the display module 16 is connected with the central control module 9 and is used for displaying the physical fitness test data, the human posture image, the infrared image, the height, the weight, the BMI, the fat rate, the muscle rate, the vital capacity, the blood pressure and the comprehensive physical fitness score through a display.
The physique test module 1 provided by the embodiment of the invention comprises:
the physique test module 1 comprises a step test unit, a back force meter test unit, a longitudinal jump test unit, a seat body forward bending test unit and a closed-eye single-foot standing test unit.
Step testing unit: the method is used for carrying out step test and obtaining relevant step test data.
Back force meter test unit: the method is used for carrying out the back force meter test and acquiring relevant back force meter test data.
A longitudinal jump testing unit: the method is used for carrying out longitudinal jump test and obtaining the forward bending test data of the relative sitting position body.
Seat body anteflexion test unit: the method is used for carrying out seat body forward flexion test and obtaining relevant seat body forward flexion test data.
Closed-eye one-foot standing test unit: the method is used for carrying out the eye-closing single-foot standing test and obtaining relevant eye-closing single-foot standing test data.
As shown in fig. 2, the intelligent fitness test method provided by the embodiment of the invention includes:
s101, obtaining relevant physical testing data through step testing, back force meter testing, longitudinal jump testing, seat body forward bending testing and closed-eye single-foot standing testing; or the uploaded relevant physical fitness test data is acquired by utilizing the read-write equipment.
S102, acquiring a human body posture image and a human face image in the physical fitness test process in real time; collecting an infrared image of the physical examiner through an infrared thermal imager; collecting height information through a measuring scale; acquiring weight information through a weighing scale; acquiring vital capacity test information through a vital capacity tester; blood pressure information is collected by a sphygmomanometer.
S103, filtering, classifying, summarizing and counting the collected related test data; judging whether the test data is abnormal or not; and when the test data is abnormal, performing the supplementary test of the specific item.
S104, calculating the BMI, the fat rate and the muscle rate through a calculation program based on the acquired related test data; analyzing the collected infrared image through an analysis program; and carrying out comprehensive body constitution grading based on the test data, the BMI obtained by calculation, the fat rate, the muscle rate, the infrared image analysis result, the human body posture image and other related test data.
S105, storing physique test data, human posture images, infrared images, height, weight, BMI, fat rate, muscle rate, vital capacity, blood pressure and comprehensive physique scores; and displaying the physical test data, the human posture image, the infrared image, the height, the weight, the BMI, the fat rate, the muscle rate, the lung capacity, the blood pressure and the comprehensive physical score through a display.
In step S102, acquiring an infrared image of a physical examiner by a thermal infrared imager according to an embodiment of the present invention includes:
(1) and establishing a multi-section linear model between the output of the thermal infrared imager and the FPA calibration temperature interval at the black body temperature.
(2) And predicting the output of the thermal infrared imager corresponding to the temperature of each black body outside the FPA calibration temperature interval according to the multi-section linear model.
(3) And correcting the output of the thermal infrared imager by sections, and eliminating the distortion of the output of the thermal infrared imager caused by the variation of the FPA temperature in the FPA calibration temperature interval and outside the FPA calibration temperature interval.
(4) And according to the Planck formula, establishing a functional relation between the output of the corrected thermal infrared imager and the Kelvin temperature in a segmented manner.
In step (1), the establishing of the multi-segment linear model between the FPA calibration temperature interval and the output of the thermal infrared imager at the black body temperature according to the embodiment of the present invention includes:
and at room temperature, aligning the thermal infrared imager to a black body radiation source with fixed temperature, recording the output value of the thermal infrared imager along with the change of the FPA temperature, and obtaining curves of the FPA temperature and the thermal infrared imager output under different black body temperatures.
Dividing the FPA temperature into a plurality of intervals to obtain the FPA temperature and the output of the thermal infrared imager, wherein a linear model which is consistent with y-kx + b in each segmented interval is obtained.
In step S103, the determining whether the test data is abnormal according to the embodiment of the present invention includes:
1) judging whether each item of test data is omitted or repeated; if the data is missing or repeated, the data is abnormal; if not, the data is not abnormal.
2) And judging whether each item of test data is within a normal standard threshold, and if the item of test data exceeds the threshold, judging that the data is abnormal.
3) Judging whether each item of test data has larger difference, if so, comparing whether the face images and the human body posture images acquired in the two test items are consistent, and if so, judging that the data is not abnormal; if the data are inconsistent, judging that the data are abnormal.
4) And judging whether the test data of the test items corresponding to the multiple tests have large differences, if so, comparing whether the face images and the human body posture images acquired by the two times of test data are consistent, if so, judging that the data are not abnormal, and if not, judging that the data are abnormal.
In step S104, the method for analyzing the acquired infrared image provided by the embodiment of the present invention includes:
and extracting temperature data of the infrared image from 5 dimensions including thermal state distribution, viscera, meridian points, anatomical subareas and color parts of the five zang organs to obtain a visual data result.
And analyzing data in the visualization result data through heat comparison, and calculating to obtain reference data of each dimension.
And comparing the reference value of each dimension with the infrared image to obtain an analysis report.
The method for extracting the temperature data provided by the embodiment of the invention comprises the following steps:
the thermal state distribution expresses temperature data from three aspects of symmetry, regularity and cold and heat distinguishing; the temperature data of the meridian points is derived from the temperature average value of each point fitting point and 5 adjacent pixel points; the temperature data of the anatomical partition comprises a highest value, a lowest value, a range, a standard deviation and an overall difference, wherein the overall difference is a difference value between an area temperature mean value and a trunk overall temperature mean value of an area to which the area belongs.
The method for analyzing the data in the visualization result data through heat comparison provided by the embodiment of the invention comprises the following steps:
selecting two areas S1 and S2 with the same number of pixel points, respectively calculating temperature mean values T and T of the areas S1 and S2, and then according to the following formula:
T＝(T+T)/2
calculating the temperature mean value T of the two areas S1 and S2; and then by the following formula:
R＝P*T/P*T
the heat ratio R of the areas S1 and S2 is calculated.
Wherein, P is the number of pixel points with the temperature higher than the average value T in the region S1, T is the temperature average value of P pixel points in the region S1, P is the number of pixel points with the temperature higher than the average value T in the region S2, and T is the temperature average value of P pixel points in the region S2.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. The utility model provides an intelligence physique test equipment, its characterized in that, intelligence physique test equipment is provided with:
the physical testing module is connected with the central control module and is used for carrying out relevant physical tests and acquiring physical testing data;
the data reading module is connected with the central control module and used for acquiring the uploaded relevant physical fitness test data by utilizing the reading and writing equipment;
the camera module is connected with the central control module and is used for acquiring human body posture images and human face images in the physical fitness test process in real time;
the infrared imaging module is connected with the central control module and is used for collecting the infrared image of the physical examiner through the thermal infrared imager;
the height acquisition module is connected with the central control module and is used for acquiring height information through the measuring scale;
the weight acquisition module is connected with the central control module and is used for acquiring weight information through the weight scale;
the vital capacity testing module is connected with the central control module and is used for acquiring vital capacity testing information through the vital capacity tester;
the blood pressure acquisition module is connected with the central control module and is used for acquiring blood pressure information through the sphygmomanometer;
the central control module is connected with the physique test module, the data reading module, the camera module, the infrared imaging module, the height acquisition module, the weight acquisition module, the vital capacity test module, the blood pressure acquisition module, the data processing module, the supplementary test module, the calculation module, the image analysis module, the physique grading module, the storage module and the display module and is used for controlling the normal operation of each module;
the data processing module is connected with the central control module and is used for filtering, classifying, summarizing and counting the collected related test data; judging whether the test data is abnormal or not;
the supplementary test module is connected with the central control module and is used for conducting supplementary test on specific projects when the test data are abnormal;
the computing module is connected with the central control module and used for computing the BMI, the fat rate and the muscle rate through a computing program based on the acquired related test data;
the image analysis module is connected with the central control module and is used for analyzing the acquired infrared image through an analysis program;
the constitution scoring module is connected with the central control module and is used for carrying out comprehensive constitution scoring on the basis of the test data, the BMI, the fat rate, the muscle rate and the infrared image analysis result which are obtained by calculation, the human posture image and other related test data;
the storage module is connected with the central control module and is used for storing physical testing data, human posture images, infrared images, height, weight, BMI, fat rate, muscle rate, vital capacity, blood pressure and comprehensive physical score;
and the display module is connected with the central control module and is used for displaying the physical fitness test data, the human posture image, the infrared image, the height, the weight, the BMI, the fat rate, the muscle rate, the vital capacity, the blood pressure and the comprehensive physical fitness score through the display.
2. The intelligent fitness test device of claim 1, wherein the fitness test module comprises:
the physique test module comprises a step test unit, a back force meter test unit, a longitudinal jump test unit, a seat body forward bending test unit and a closed-eye single-foot standing test unit;
step testing unit: the device is used for carrying out step test and obtaining relevant step test data;
back force meter test unit: the device is used for carrying out the back force meter test and acquiring the test data of the relevant back force meter;
a longitudinal jump testing unit: the device is used for carrying out a longitudinal jump test and acquiring the forward bending test data of the relative seat body;
seat body anteflexion test unit: the device is used for carrying out seat body forward flexion test and obtaining relevant seat body forward flexion test data;
closed-eye one-foot standing test unit: the method is used for carrying out the eye-closing single-foot standing test and obtaining relevant eye-closing single-foot standing test data.
3. An intelligent fitness test method applied to the intelligent fitness test device of claims 1-2, the intelligent fitness test method comprising:
step testing, back force meter testing, longitudinal jump testing, seat body forward bending testing and closed-eye single-foot standing testing are carried out to obtain relevant physique testing data; or acquiring the uploaded relevant physical fitness test data by using read-write equipment;
acquiring a human body posture image and a human face image in the physical fitness test process in real time; collecting an infrared image of the physical examiner through an infrared thermal imager; collecting height information through a measuring scale; acquiring weight information through a weighing scale; acquiring vital capacity test information through a vital capacity tester; collecting blood pressure information through a sphygmomanometer;
step three, filtering, classifying, summarizing and counting the collected related test data; judging whether the test data is abnormal or not; when the test data is abnormal, performing the supplementary test of a specific project;
step four, calculating the BMI, the fat rate and the muscle rate through a calculation program based on the acquired related test data; analyzing the collected infrared image through an analysis program; performing comprehensive body constitution grading based on the test data, the BMI, the fat rate, the muscle rate and the infrared image analysis result obtained by calculation, the human body posture image and other related test data;
step five, storing physique test data, human posture images, infrared images, height, weight, BMI, fat rate, muscle rate, vital capacity, blood pressure and comprehensive physique scores; and displaying the physical test data, the human posture image, the infrared image, the height, the weight, the BMI, the fat rate, the muscle rate, the lung capacity, the blood pressure and the comprehensive physical score through a display.
4. The intelligent fitness test method of claim 3, wherein in step two, the step of collecting the infrared image of the physical examinee by the thermal infrared imager comprises:
(1) establishing a multi-section linear model between the output of the thermal infrared imager and the FPA calibration temperature interval at the temperature of each black body;
(2) according to the multi-section linear model, the output of the thermal infrared imager corresponding to each black body temperature outside the FPA calibration temperature interval is predicted;
(3) correcting the output of the thermal infrared imager by sections, and eliminating the distortion of the output of the thermal infrared imager caused when the temperature of the FPA changes in the FPA calibration temperature interval and outside the FPA calibration temperature interval;
(4) and according to the Planck formula, establishing a functional relation between the output of the corrected thermal infrared imager and the Kelvin temperature in a segmented manner.
5. The intelligent fitness test method of claim 4, wherein in step (1), the establishing of the multi-segment linear model between the FPA calibration temperature interval and the output of the thermal infrared imager at each black body temperature comprises:
at room temperature, aligning the thermal infrared imager to a black body radiation source with fixed temperature, recording output values of the thermal infrared imager along with the change of the FPA temperature, and obtaining curves of the FPA temperature and the thermal infrared imager output under different black body temperatures;
dividing the FPA temperature into a plurality of intervals to obtain the FPA temperature and the output of the thermal infrared imager, wherein a linear model which is consistent with y-kx + b in each segmented interval is obtained.
6. The intelligent fitness test method of claim 3, wherein in step three, the determining whether the test data is abnormal comprises:
1) judging whether each item of test data is omitted or repeated; if the data is missing or repeated, the data is abnormal; if not, the data is not abnormal;
2) judging whether each item of test data is within a normal standard threshold value, and if the item of test data exceeds the normal standard threshold value, judging that the data is abnormal;
3) judging whether each item of test data has larger difference, if so, comparing whether the face images and the human body posture images acquired in the two test items are consistent, and if so, judging that the data is not abnormal; if the data are inconsistent, judging that the data are abnormal;
4) and judging whether the test data of the test items corresponding to the multiple tests have large differences, if so, comparing whether the face images and the human body posture images acquired by the two times of test data are consistent, if so, judging that the data are not abnormal, and if not, judging that the data are abnormal.
7. The intelligent fitness test method of claim 3, wherein in step four, the method for analyzing the acquired infrared images comprises:
extracting temperature data of the infrared image from 5 dimensions including thermal state distribution, viscera, meridian points, anatomical partitions and color parts of the five zang organs to obtain a visual data result;
analyzing data in the visualization result data through heat comparison, and calculating to obtain reference data of each dimension;
and comparing the reference value of each dimension with the infrared image to obtain an analysis report.
8. The intelligent fitness test method of claim 7, wherein the temperature data is extracted by:
the thermal state distribution expresses temperature data from three aspects of symmetry, regularity and cold and heat distinguishing; the temperature data of the meridian points is derived from the temperature average value of each point fitting point and 5 adjacent pixel points; the temperature data of the anatomical partition comprises a highest value, a lowest value, a range, a standard deviation and an overall difference, wherein the overall difference is a difference value between an area temperature mean value and a trunk overall temperature mean value of an area to which the area belongs.
9. The intelligent fitness test method of claim 7, wherein the method of analyzing the data in the visualization data by heat comparison comprises:
selecting two areas S1 and S2 with the same number of pixel points, respectively calculating temperature mean values T and T of the areas S1 and S2, and then according to the following formula:
T＝(T+T)/2
calculating the temperature mean value T of the two areas S1 and S2; and then by the following formula:
R＝P*T/P*T
calculating the heat ratio R of the areas S1 and S2;
wherein, P is the number of pixel points with the temperature higher than the average value T in the region S1, T is the temperature average value of P pixel points in the region S1, P is the number of pixel points with the temperature higher than the average value T in the region S2, and T is the temperature average value of P pixel points in the region S2.
10. A computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the intelligent fitness test method of any one of claims 3-9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010140475.6A CN111261264A (en) | 2020-03-03 | 2020-03-03 | Intelligent physique testing device and method and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010140475.6A CN111261264A (en) | 2020-03-03 | 2020-03-03 | Intelligent physique testing device and method and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111261264A true CN111261264A (en) | 2020-06-09 |
Family
ID=70954722
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010140475.6A Pending CN111261264A (en) | 2020-03-03 | 2020-03-03 | Intelligent physique testing device and method and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111261264A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112862996A (en) * | 2020-12-31 | 2021-05-28 | 合肥指南针电子科技有限责任公司 | Supervision method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201683882U (en) * | 2010-04-26 | 2010-12-29 | 李智勇 | Human body physical health detection and fitness tester |
| CN104537245A (en) * | 2014-12-31 | 2015-04-22 | 深圳泰山在线科技有限公司 | Physical monitoring method and system with audit function |
| CN104688233A (en) * | 2015-02-11 | 2015-06-10 | 深圳泰山在线科技有限公司 | Physique test machine |
| CN108852302A (en) * | 2018-07-19 | 2018-11-23 | 王燕申 | Traditional Chinese medicine digital visualization system and method |
| CN109540297A (en) * | 2018-10-23 | 2019-03-29 | 昆山优尼电能运动科技有限公司 | Thermal infrared imager scaling method based on FPA temperature |
| CN109903832A (en) * | 2019-02-21 | 2019-06-18 | 安徽工程大学 | A kind of acquisition of physique test data and detection system and method |
-
2020
- 2020-03-03 CN CN202010140475.6A patent/CN111261264A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201683882U (en) * | 2010-04-26 | 2010-12-29 | 李智勇 | Human body physical health detection and fitness tester |
| CN104537245A (en) * | 2014-12-31 | 2015-04-22 | 深圳泰山在线科技有限公司 | Physical monitoring method and system with audit function |
| CN104688233A (en) * | 2015-02-11 | 2015-06-10 | 深圳泰山在线科技有限公司 | Physique test machine |
| CN108852302A (en) * | 2018-07-19 | 2018-11-23 | 王燕申 | Traditional Chinese medicine digital visualization system and method |
| CN109540297A (en) * | 2018-10-23 | 2019-03-29 | 昆山优尼电能运动科技有限公司 | Thermal infrared imager scaling method based on FPA temperature |
| CN109903832A (en) * | 2019-02-21 | 2019-06-18 | 安徽工程大学 | A kind of acquisition of physique test data and detection system and method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112862996A (en) * | 2020-12-31 | 2021-05-28 | 合肥指南针电子科技有限责任公司 | Supervision method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104382570A (en) | Digitized full-automatic health condition detection device | |
| JP2018163680A5 (en) | ||
| US20070299360A1 (en) | Systems and Methods for Analyzing and Assessing Dementia and Dementia-Type Disorders | |
| CN107361760B (en) | Magnetocardiogram instrument diagnosis system and magnetocardiogram instrument using the same | |
| Herrick et al. | Quantitative nailfold capillaroscopy—update and possible next steps | |
| CN106419938B (en) | A kind of attention deficit hyperactivity disorder (ADHD) detection system based on kinergety release estimation | |
| CN104185020B (en) | A kind of system and method detecting stereoscopic vision fatigue strength | |
| WO2021040373A1 (en) | Complex stress index-based stress management method | |
| CN112150327A (en) | A test system for student's physique detects | |
| CN105852797A (en) | Stereoscopic display visual fatigue detection system based on electrocardiosignals | |
| CN111588353A (en) | Body temperature measuring method | |
| CN111854964A (en) | Method and device for measuring body temperature, temperature measuring tool and storage medium | |
| CN115517681A (en) | Method and system for monitoring mood fluctuation and evaluating emotional disorder state of MD (MD) patient | |
| CN111261264A (en) | Intelligent physique testing device and method and storage medium | |
| US11941811B2 (en) | Method for assessing cardiothoracic ratio and cardiothoracic ratio assessment system | |
| CN110659594A (en) | Thermal comfort attitude estimation method based on AlphaPose | |
| CN115019972A (en) | Medical image data sharing system based on big data analysis | |
| CN105433901A (en) | Method and application used for measuring body fat | |
| CN114176532A (en) | Clinical verification method for determining cfPWV parameters and application system thereof | |
| KR101978900B1 (en) | Apparatus, and method for examining pulmonary function using face image, and computer readable recording medium for recoring the same | |
| CN111370095A (en) | IC card based traditional Chinese medicine constitution distinguishing and conditioning test system and test method | |
| CN112002422A (en) | Medical information processing system, medical information processing apparatus, computer device, and storage medium | |
| CN112488493B (en) | Medical imaging physician focus recognition capability assessment method, system and computer readable medium for fusing position information | |
| Aldred et al. | Application of thermography to estimate respiratory rate in the emergency room: The journal Temperature toolbox | |
| CN113425279B (en) | Animal experiment method for respiratory distress syndrome |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200609 |