CN106454039B - Seat body anteflexion detector based on thing networking and machine vision - Google Patents
Seat body anteflexion detector based on thing networking and machine vision Download PDFInfo
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- CN106454039B CN106454039B CN201610915452.1A CN201610915452A CN106454039B CN 106454039 B CN106454039 B CN 106454039B CN 201610915452 A CN201610915452 A CN 201610915452A CN 106454039 B CN106454039 B CN 106454039B
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Abstract
The invention discloses a seat body forward flexion detector based on the Internet of things and machine vision, which comprises a machine body, wherein the machine body is provided with an embedded controller, a camera, a shooting key, a ZigBee module, a Wi-Fi module, a display screen, a rechargeable power supply and a power switch; the camera is used for shooting the forward bending posture of the sitting body of the tested person to obtain a detection image; the embedded controller is used for receiving the detection image, processing the image to obtain the evaluation of the angle and the flexibility between the upper body and the lower body of the tested person, and outputting the evaluation to the display screen; the shooting key is used for controlling the camera to shoot images; the ZigBee module is used for realizing the communication of the Internet of things between the detector and an upper computer and between the detector and other detectors and realizing the wireless uploading of detection data; and the Wi-Fi module is used for realizing the connection between the detector and the Internet. According to the invention, the angle between the upper body and the lower body when the sitting body bends forward is detected, so that the flexibility of the human body is accurately reflected, and the wireless transmission effect of the detection data is realized based on the Internet of things.
Description
Technical Field
The invention belongs to the field of physical testing, and particularly relates to a seat forward bending detector based on Internet of things and machine vision for physical fitness testing.
Background
Flexibility is an important index of physical quality, and forward bending of a sitting position is a project required in national student physical health standards, so that the aim of testing the physical flexibility of students is fulfilled. At present, a mechanical seat body forward bending tester is mainly adopted to detect the flexibility of the body, the bending degree of the upper body is tested, and the evaluation index is the maximum distance which can be reached by the forward extension of fingers. The testing method replaces the angle of joint movement with the distance of finger protrusion when bending, and the measuring mode has serious defects because different limb lengths can greatly influence the distance of finger protrusion, increase the measuring error and reduce the detection effectiveness. Research shows that if the moving angle of the body joint can be measured conditionally, the influence of the length of the limb on the measurement effectiveness can be overcome, and the accuracy of the body flexibility test is improved. On the other hand, data detected by the mechanical seat body forward bending tester needs to be manually recorded and manually input into a related computer management system, so that the efficiency is low, and errors are easy to occur.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a method for detecting the forward flexion of a sitting body based on the internet of things and machine vision, which measures the angle between an upper body and a lower body when the sitting body bends forward, thereby accurately reflecting the flexibility of the human body and realizing wireless transmission of detection data based on the internet of things.
In order to achieve the purpose, the invention provides a seat body forward flexion detector based on the internet of things and machine vision, which comprises a machine body, wherein the machine body is provided with an embedded controller, a camera connected with a data input end of the embedded controller, a shooting button connected with the data input end of the embedded controller, a ZigBee module connected with a data output end of the embedded controller, a Wi-Fi module connected with the data output end of the embedded controller, a display screen connected with the data output end of the embedded controller, a rechargeable power supply connected with the data input end of the embedded controller, and a power switch arranged between the embedded controller and the rechargeable power supply and used for controlling the on-off of the power supply; the camera is used for shooting the forward bending posture of the sitting body of the tested person to obtain a detection image; the embedded controller is used for receiving the detection image, processing the image to obtain the evaluation of the angle and the flexibility between the upper body and the lower body of the tested person, and outputting the evaluation to the display screen; the shooting key is used for controlling the camera to shoot images; the ZigBee module is used for realizing the communication of the Internet of things between the detector and an upper computer and between the detector and other detectors and realizing the wireless uploading of detection data; the Wi-Fi module is used for realizing the connection between the detector and the Internet.
Preferably, the shooting key is pressed for a short time to realize real-time shooting, and the long press is used for delayed shooting.
Preferably, the camera shooting comprises the following two cases:
(1) the assistant assists in shooting: the knee side of the tested person is opposite to the detector camera, and the assistant finishes shooting by pressing a shooting key for a short time;
(2) the testee independently finishes shooting: the testee presses the shooting button for a long time to shoot in a delayed mode, the testee moves to the position which is 1 m away from the detector camera and on the same horizontal plane with the detector within the time delay shooting range, the knee side face of the testee is opposite to the detector camera, and the camera automatically finishes shooting when the shooting delay time is over.
Preferably, the embedded controller is configured to receive the detection image, and perform data processing on the image to obtain an angle formed between the upper body and the lower body of the subject, specifically as follows: the embedded controller calculates the angle formed between the upper body and the lower body of the tested person by taking the shoulder, the crotch and the ankle of the tested person in the image as characteristic points.
Preferably, the embedded controller is configured to receive the detection image, and perform data processing on the image to obtain the flexibility evaluation, specifically as follows:
the flexibility is scored from 0 to 100 points, with 0 being the lowest point and 100 being the highest point, and the flexibility score is calculated according to the measured angle β according to the following formula:
male:
female:
compared with the prior art, the invention has the following beneficial effects:
according to the invention, the visual detection is adopted to replace the traditional mechanical scale test, so that the accuracy of the forward bending test of the sitting body can be effectively improved, the test result can be automatically recorded, the Internet of things technology is utilized, the test data can be conveniently uploaded and managed, the measurement of the angle between the upper body and the lower body when the sitting body is bent forward is realized, the flexibility of the human body is accurately reflected, and the wireless transmission of the detection data is realized based on the Internet of things.
Drawings
Fig. 1 is a schematic structural diagram of a seat body forward bending detector based on the internet of things and machine vision.
Fig. 2 is a schematic block diagram of a seat body forward bending detector based on the internet of things and machine vision.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings.
As shown in fig. 1-2, a seat forward flexion detector based on internet of things and machine vision comprises a machine body 1, wherein the machine body 1 is provided with an embedded controller 2, a camera 3 connected with a data input end of the embedded controller 2, a shooting key 4 connected with the data input end of the embedded controller 2, a ZigBee module 5 connected with a data output end of the embedded controller 2, a Wi-Fi module 6 connected with the data output end of the embedded controller 2, a display screen 7 connected with the data output end of the embedded controller 2, a rechargeable power supply 8 connected with the data input end of the embedded controller 2, and a power switch 9 arranged between the embedded controller 2 and the rechargeable power supply 8 and used for controlling on-off of the power supply.
The rechargeable power supply 8 is provided with a charging port 10.
The camera 3 is used for shooting the forward bending posture of the sitting body of the tested person to acquire a detection image.
The embedded controller is a main controller of the system and has the functions of logic control, storage, input and output, image processing and the like. The embedded controller is used for receiving the detection image, processing the image to obtain the angle and flexibility evaluation formed between the upper body and the lower body of the tested person, and outputting the evaluation to the display screen.
The display screen is used for displaying the forward bending angle of the measured sitting body and the body flexibility of the measured person reflected by the measured angle.
The shooting key is used for controlling the camera to shoot images. The shooting key is pressed for a short time to realize real-time shooting, and the long press is used for delayed shooting.
The ZigBee module is used for realizing the communication of the Internet of things between the detector and an upper computer and between the detector and other detectors and realizing the wireless uploading of the detection data. The upper computer is a data management device with a ZigBee module.
The Wi-Fi module is used for realizing connection between the detector and the Internet, and data networking is facilitated.
The rechargeable power supply enables the detector to work without connecting wires, and portable operation of the detector is achieved.
The power switch controls the on-off between the rechargeable power supply and the embedded controller.
When the device is applied, the traditional mechanical scale test is replaced, the accuracy of the seat body forward bending test can be effectively improved, the test result can be automatically recorded, and the test data can be conveniently uploaded and managed by using the Internet of things technology.
The specific working process of the invention is as follows:
1) the detector is placed on a horizontal surface.
2) The power switch 9 is pressed down to switch on the power supply of the detector.
3) There are two situations when shooting: the first condition is that an assistant assists in shooting, the tested person sits on the same horizontal plane with the detector, the distance between the tested person and the detector is 1 m, the knee side face is opposite to the detector, the forward bending test of the sitting body is executed, and the assistant finishes shooting by pressing a shooting key for a short time; the second situation is that the tested person independently finishes shooting, the tested person presses a shooting button for 2 seconds, the camera delays for 5 seconds to shoot, the tested person moves to the position which is on the same horizontal plane with the detector and is 1 meter away from the detector within 5 seconds, the knee side face is over against the detector, the forward bending action of the seat body is executed, and the camera automatically finishes shooting after 5 seconds are over.
The long press time and the delay time of the photographing key should not be construed as limiting the present invention herein. The key performance can be limited according to actual use conditions or determined by purchasing key performance.
4) The embedded controller 2 obtains the image shot by the camera 3, processes the image, executes a characteristic extraction and matching algorithm, and calculates the angle formed between the upper body and the lower body of the tested person by taking the shoulder, the crotch and the ankle of the tested person as characteristic points
5) The display screen 7 displays the measured angle and the flexibility reflected by the measured angle, and the evaluation method comprises the following steps: the flexibility is scored from 0 to 100 points, with 0 being the lowest point and 100 being the highest point, and the flexibility score is calculated according to the measured angle β according to the following formula:
male:
female:
6) if data measured by the detector need to be collected and counted, the detector can transmit the data to an upper computer through the Internet of things by using the ZigBee module 5, the upper computer is a data management device with the ZigBee module 5, and a transmission path can be single-hop transmission or multi-hop transmission through other detectors.
7) If the measured data need to be shared and applied to other networked computer management systems, the detector can upload the data to a computer by using the Wi-Fi module 6, so that internet sharing is realized.
8) After the power supply is exhausted, the power can be replenished through the charging port 10.
What has been described above are merely some embodiments of the present invention. It will be apparent to those skilled in the art that various changes and modifications can be made without departing from the inventive concept herein, and it is intended to cover all such modifications and variations as fall within the scope of the invention.
Claims (4)
1. A seat body anteflexion detector based on the Internet of things and machine vision, which is characterized in that,
the intelligent camera comprises a machine body, wherein the machine body is provided with an embedded controller, a camera connected with a data input end of the embedded controller, a shooting key connected with the data input end of the embedded controller, a ZigBee module connected with a data output end of the embedded controller, a Wi-Fi module connected with the data output end of the embedded controller, a display screen connected with the data output end of the embedded controller, a rechargeable power supply connected with the data input end of the embedded controller and a power switch arranged between the embedded controller and the rechargeable power supply and used for controlling the on-off of the power supply;
the camera is used for shooting the forward bending posture of the sitting body of the tested person to obtain a detection image;
the embedded controller is used for receiving the detection image, processing the image to obtain the evaluation of the angle and the flexibility between the upper body and the lower body of the tested person, and outputting the evaluation to the display screen;
the shooting key is used for controlling the camera to shoot images;
the ZigBee module is used for realizing the communication of the Internet of things between the detector and an upper computer and between the detector and other detectors and realizing the wireless uploading of detection data;
the Wi-Fi module is used for realizing the connection between the detector and the Internet;
the embedded controller is used for receiving the detection image and processing the image to obtain the angle formed between the upper body and the lower body of the tested person, and the embedded controller is specifically as follows: the embedded controller calculates the angle formed between the upper body and the lower body of the tested person by taking the shoulder, the crotch and the ankle of the tested person in the image as characteristic points.
2. The Internet of things and machine vision based seat body forward flexion detector of claim 1, wherein the shooting key is used for shooting in real time in a short press mode and used for shooting in a delayed mode in a long press mode.
3. The internet of things and machine vision based seat body forward flexion detector of claim 1, wherein the camera shooting comprises the following two conditions:
(1) the assistant assists in shooting: the knee side of the tested person is opposite to the detector camera, and the assistant finishes shooting by pressing a shooting key for a short time;
(2) the testee independently finishes shooting: the testee presses the shooting button for a long time to shoot in a delayed mode, the testee moves to the position which is 1 m away from the detector camera and on the same horizontal plane with the detector within the time delay shooting range, the knee side face of the testee is opposite to the detector camera, and the camera automatically finishes shooting when the shooting delay time is over.
4. The internet of things and machine vision based seat body forward flexion detector of claim 1, wherein the embedded controller is configured to receive a detection image, and perform data processing on the image to obtain the flexibility evaluation, and specifically the following steps are performed:
the flexibility is scored from 0 to 100 points, with 0 being the lowest point and 100 being the highest point, and the flexibility score is calculated according to the measured angle β according to the following formula:
male:
female:
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| CN109211116A (en) * | 2017-06-30 | 2019-01-15 | 深圳泰山体育科技股份有限公司 | The optical calibrating and measurement method of flexibility test |
| CN108111755A (en) * | 2017-12-20 | 2018-06-01 | 广东技术师范学院 | A kind of recognition methods of picked angle of human body and device |
| CN111012357A (en) * | 2019-12-06 | 2020-04-17 | 西南交通大学 | Seat body forward-bending detection device and method based on image recognition |
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| AU2007201433A1 (en) * | 2006-07-04 | 2008-01-24 | Strang, Alan Wayne Mr | Sit and Reach Carry Case Flexibility Assessment Apparatus |
| KR101037924B1 (en) * | 2010-12-24 | 2011-05-30 | 대한센서 주식회사 | A seat and reach measuring apparatus |
| CN103099602B (en) * | 2011-11-10 | 2016-04-06 | 深圳泰山在线科技有限公司 | Based on the physical examinations method and system of optical identification |
| CN103577686A (en) * | 2013-09-11 | 2014-02-12 | 奥美之路(北京)技术顾问有限公司 | Chinese people health-related fitness evaluation model |
| CN104688233A (en) * | 2015-02-11 | 2015-06-10 | 深圳泰山在线科技有限公司 | Physique test machine |
| CN105608467B (en) * | 2015-12-16 | 2019-03-22 | 西北工业大学 | Non-contact type physique constitution of students assessment method based on Kinect |
| CN105769210A (en) * | 2016-05-09 | 2016-07-20 | 中科院合肥技术创新工程院 | Wearable home body posture detection Internet of Things terminal |
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