CN103100205A - Auxiliary device suitable for middle and primary school physical education evaluation and achieving method thereof - Google Patents

Abstract

Disclosed is an auxiliary device suitable for middle and primary school physical education evaluation. The auxiliary device is characterized by comprising a motion data collecting module, a motion data obtaining module, an identifying and training module, a health data collecting module and a physical education virtual evaluating module. The motion data collecting module is used for obtaining digital video image data and inertial parameters in an appointed monitored area gauge point and receiving force feedback. The motion data obtaining module is used for processing the obtained digital video image data and the inertial parameters so as to obtain gauge point space coordinates on sports equipment and a human body. The identifying and training module is used for collecting motion trail data of various motion patterns, conducting classified study, conducting classified identification processing for to-be-identified motion, and obtaining analysis results. The health data collecting module is used for collecting relevant health habitus data of the human body and transmitting the relevant data to the physical education virtual evaluating module so as to conduct comprehensive evaluation analysis. The physical education virtual evaluating module is used for conducting comprehensive evaluation analysis to the analysis results obtained by the identifying and training module and the relevant data obtained by the health data collecting module according to relevant motion and habitus standards and achieving the force feedback by combing virtual environment visualization and the motion analysis results and feed, and then comprehensive results are fed back and outputted.

Description

A kind of servicing unit and its implementation that is applicable to the primary and secondary school physical education evaluation and test

Technical field

The present invention relates to the crossing domain of man-machine interaction, virtual reality and area of computer aided evaluation and test, in particular a kind of ancillary technique that is applicable to the primary and secondary school physical education evaluation and test.

Background technology

At present, 3 d human motion simulation and the video analytic system towards athletic training of domestic existing employing identification point seizure and action recognition technology.

CN 101229432A discloses a kind of method of controlling action emulation and system thereof, its method is to utilize signal picker to gather the movable information of Moving Objects, mate with the action figure that defines after being converted into the action figure, the control instruction that the transmission action figure that the match is successful is corresponding is controlled the role action in game, realizes emulation.

CN 1479252A discloses a kind of Three dimension human body exercise imitation result and video same screen comparing method, the method is by extracting the outer parameter of the corresponding video camera of the first frame of sports video, virtual video camera in simulation analysis system is carried out the pilot adjustment, and the quantitative global motion of video camera of the subsequent frame of the first frame of extraction sports video, control accordingly the motion of the virtual video camera in simulation analysis system, and show the Three dimension human body exercise imitation result that it is corresponding, realize with the screen contrast, fast, difference between comparing motion person's execution and standard operation (or simulated actions) exactly, for sportsman and coach propose concrete improvement idea and suggestion.

The method of motion tracking is divided into according to the difference of sensing element at present: inertia tracking, optical tracking, power and mechanical type are followed the trail of, electromagnetic type is followed the trail of, acoustics is followed the trail of etc.CN 101229432A has used the inertia tracer technique, by Inertial Measurement Unit is set on target, measures the data such as acceleration, angular speed, uses based on this mathematical tool to resolve, and obtains the motion conditions of target.The characteristics that inertia is followed the trail of are to realize simply, strong interference immunity; Shortcoming is to obtain all sidedly the motion feature of tracked target, can only finite sum reflects partly the movement characteristic of tracked target.CN 1479252A has used the optical tracking technology, by the Monitor and track of specific luminous point on target being completed the task of motion tracking, is characterized in reflecting all sidedly the motion conditions of object, and precision is high; Shortcoming is to realize comparatively difficulty, and the scope of following the trail of is less.

Foregoing invention has all only been used a certain single technology, and its Technology origin is single, and shortcoming is obvious.

Summary of the invention

The purpose of this invention is to provide a kind of accessory system and its implementation that is applicable to the virtual evaluation and test of primary and secondary school physical education, utilize virtual reality technology and optical tracking to follow the trail of with inertia the motion tracking system that combines, can effectively enlarge the motion tracking scope and in time feed back movable information, collection and the processing of special exercise information in realizing in a big way, and it is applied to the virtual evaluation and test of primary and secondary school physical education.

The technical solution adopted for the present invention to solve the technical problems is:

A kind of servicing unit that is applicable to the virtual evaluation and test of primary and secondary school physical education, described system comprises: exercise data acquisition module 1, be used for obtaining digital video image data and the inertial parameter of specifying the guarded region gauge point, and the reception feedback; Motion capture module 2 is used for resulting digital video image data and inertial parameter are processed, and obtains the gauge point space coordinates on sports apparatus and human body; Identification and training module 3 for the motion trace data that gathers all kinds of patterns, carry out classification learning, and Classification and Identification are made in action to be identified processed, and obtain analysis result; Health data collection module 4 is used for gathering the relevant health-physical fitness data of human body, and related data is reached the virtual evaluation and test module 5 of physical education, to carry out the comprehensive evaluating analysis; The virtual evaluation and test module 5 of physical education, be used for the corresponding data with identification and the final analysis result that obtains of training module 3 and 4 acquisitions of health data collection module, according to relevant motion and physical fitness standard, carry out the comprehensive evaluating analysis, simultaneously the motion analysis result is merged virtual environment visual, realizable force feedback, and feedback output integrated result.

wherein said exercise data acquisition module 1 comprises specificwavelength spot light 11,camera 13, microinertial measurement unit 12,wireless communication module 14 and force feedback unit 15, whereincamera 13 gathers the optical signal of specificwavelength spot light 11, the input wireless connections of the output of microinertial measurement unit 12 andwireless communication module 14, the input wireless connections of the output ofwireless communication module 14 and force feedback unit 15, described motion capture module 2 comprises image characteristics extraction unit 21, three-dimensional fix unit 22, movable information resolves unit 23, Fusion unit 24, wherein image characteristics extraction unit 21 inputs are connected withcamera 13 outputs, image characteristics extraction unit 21 outputs are connected with the input of three-dimensional fix unit 22, the input that movable information resolves unit 23 is connected with the output ofwireless communication module 14, movable information resolves the output of being connected with the three-dimensional fix unit unit 23 and is connected with the input of Fusion unit 24 respectively, described identification and training module 3 comprise training module 31, identification and resolution unit 32, wherein the input of identification and resolution unit 32 is connected with the output of Fusion unit 24, and the output of training module 31 is connected with another input of resolution unit 32 with identification, described health data collection module 4 comprises healthdata collection unit 41,wireless communication module 42, and the output of healthdata collection unit 41 is connected with the input ofwireless communication module 42, the virtual test and appraisal module 5 of described physical education comprises comprehensive evaluatingunit 51, man-machine interaction unit 52,display device 53, wherein the input of comprehensive evaluatingunit 51 is connected with the output that identification and resolution unit 32 are connected with wireless communication module respectively, the input of man-machine interaction unit 52 is connected with the output of identification with resolution unit 32, the output of man-machine interaction unit 52 is connected with the input ofdisplay device 53, another output of man-machine interaction unit 52 and the input wireless connections ofwireless communication module 14.

A kind of implementation method that is applicable to the primary and secondary school physical education evaluation and test, comprise the following steps: A, with the binding of gauge point and measured target, camera is arranged on the dead ahead of appointed area, be used for catching the image of appointed area, obtain the inertial parameter of gauge point motion, and the realizable force feedback effects; B, capturing digital image are also inputted all-purpose computer, obtain the digital video image of target travel; Gather the inertial parameter of gauge point motion; C, to the inertial parameter that gathers with digital video image resolves and Fusion, obtain the gauge point motion mode; D, identify its motor pattern according to the gauge point motion mode, send the virtual evaluation and test module 5 of physical education to; E, the relevant physique health data of collection motion process send the virtual evaluation and test module 5 of physical education to, and the virtual evaluation and test module 5 of physical education is visual with comprehensive evaluating result and virtual interacting environment, and feeds back to the user.

Described step C also comprises: resolve algorithm by adopting corresponding sensor signal Preprocessing Algorithm and athletic posture, utilize the inertial parameter that gathers to calculate instantaneous acceleration, speed, position and the attitude of the relative earth of target; According to digital video image, at first the present invention extracts measured target motion characteristics compositions by two value-based algorithms, and characteristic composition is asked for its center of gravity, obtains the characteristic composition center; Then according to the calculating to selected feature, set up the corresponding relation between feature; According to the corresponding relation between feature, according to BuBumblebee binocular measuring principle, realize that Three dimensional Targets accurately locates; Described step C also comprises: to measured target gauge point motion mode and the inertial parameter that obtains in described step B, by the Multisensor Data Fusion Algorithm of D-S evidence theory, obtain reflecting the consistent data of measured target motion feature;

Described step D also comprises:

D1, gather in advance the sample pattern data of multi-motion, the sample pattern data of pre-collection are marked;

D2, go out one by one the characteristic vector of its motion essence feature of reflection from described sample pattern extracting data;

D3, divide according to described characteristic vector under category regions, make the characteristic vector that only comprises similar sample in each the different classes of zone after division, set up the grader from characteristic vector to mapping relations affiliated classification;

D4, the pattern data of moving target to be detected are processed, extracted its characteristic vector;

D5, the characteristic vector of pattern data to be detected is input to described grader, grader is differentiated according to its characteristic vector, obtains the identification result to these pattern data to be detected, and identification result is carried out Action Semantic resolve.

Described step D2 also comprises:

D21, described sample pattern data are carried out pretreatment, obtain training data;

D22, extract the characteristic component of reflection training data substantive characteristics from training data;

D23, described characteristic component is made up, obtain described characteristic vector;

Described step D4 also comprises:

D41, described pattern data to be detected are carried out pretreatment, obtain Identification Data;

D42, extract the characteristic component of reflection Identification Data substantive characteristics from Identification Data;

D43, described characteristic component is made up, obtain described characteristic vector.

Described step e also comprises:

E1, in motion process, gather simultaneously the relevant physique health data of representation of athletic, and data carried out pretreatment;

E2, combined action analysis result and analysis and health data, in conjunction with predefined evaluation and test scheme and standard, provide the comprehensive evaluating result;

E3, the analysis result that will move merge mutually with virtual environment, and in conjunction with the comprehensive evaluating result, visual feedback is to the user;

E4, when contacting with object in virtual environment, man-machine interaction unit sends back force feedback unit, realizable force feedback effects to dependent interaction information;

Described step e 4 also comprises:

E41, when contacting with object in virtual environment, man-machine interaction unit sends back the force feedback unit to dependent interaction information;

E42, force feedback unit converts relevant information one group of Wave data to and sends to the Motor Control chip;

E43, chip controls motor are according to the running of respective waveforms data, thus the realizable force feedback effects.

Below with reference to drawings and Examples, the present invention is described in detail.

Description of drawings

Fig. 1 is a kind of accessory system schematic block diagram that is applicable to the primary and secondary school physical education evaluation and test of the present invention;

Fig. 2 is exercise data acquisition module schematic block diagram of the present invention;

Fig. 3 is motion capture module schematic block diagram of the present invention;

Fig. 4 is identification of the present invention and parsing module schematic block diagram;

Fig. 5 is health data collection module schematic block diagram of the present invention;

Fig. 6 is the virtual evaluation and test module of physical education of the present invention schematic block diagram;

The specific embodiment

The present invention is based on the accessory system that is applicable to the virtual evaluation and test of primary and secondary school physical education and its implementation of virtual reality technology, can be used for the auxiliary evaluation and test of sports, realize long-range auxiliary evaluation and test, digitlization evaluation and test.

System provided by the invention comprises: moving data acquisition module 1, be used for obtaining digital video image data and the inertial parameter of specifying the guarded region gauge point, and the reception feedback; Motion capture module 2 is used for resulting digital video image data and inertial parameter are processed, and obtains the gauge point space coordinates on sports apparatus and human body; Identification and training module 3 for the motion trace data that gathers all kinds of patterns, carry out classification learning, and Classification and Identification are made in action to be identified processed, and obtain analysis result; Health data collection module 4 is used for gathering the relevant health-physical fitness data of human body, and related data is reached the virtual evaluation and test module 5 of physical education, to carry out the comprehensive evaluating analysis; The virtual evaluation and test module 5 of physical education, be used for the corresponding data with identification and the final analysis result that obtains of training module 3 and 4 acquisitions of health data collection module, according to relevant motion and physical fitness standard, carry out the comprehensive evaluating analysis, simultaneously the motion analysis result is merged virtual environment visual, realizable force feedback, and feedback output integrated result.

wherein said exercise data acquisition module 1 comprises specificwavelength spot light 11,camera 13, microinertial measurement unit 12,wireless communication module 14 and force feedback unit 15, whereincamera 13 gathers the optical signal of specificwavelength spot light 11, the input wireless connections of the output of microinertial measurement unit 12 andwireless communication module 14, the input wireless connections of the output ofwireless communication module 14 and force feedback unit 15, described specificwavelength spot light 11 is for sending monochromatic spot light,camera 14 adopts the visible image capturing head, be used for obtaining the digital video image of specifying guarded region, process for motion capture module 2, microinertial measurement unit 12 and measured target binding, be used for measuring the inertial parameter of measured target, process for described motion capture module 2,wireless communication module 14 is sent to motion capture module 2 with the inertial parameter that microinertial measurement unit 12 obtains by wireless signal, force feedback unit 15, be used for allowing the user experience motion feedback true to nature, comprise microprocessor, digital transfer bus and motor.

described motion capture module 2 comprises image characteristics extraction unit 21, three-dimensional fix unit 22, movable information resolves unit 23, Fusion unit 24, wherein image characteristics extraction unit 21 inputs are connected withcamera 13 outputs, image characteristics extraction unit 21 outputs are connected with the input of three-dimensional fix unit 22, the input that movable information resolves unit 23 is connected with the output ofwireless communication module 14, movable information resolves the output of being connected with the three-dimensional fix unit unit 23 and is connected with the input of Fusion unit 24 respectively, described characteristics of image is got unit 21 inputs and is connected withcamera 14 outputs, utilize two value-based algorithms to obtain the characteristic composition of target travel, three-dimensional fix unit 22 utilizes gauge point to become the position of image in two cameras, utilize the binocular vision algorithm to obtain the three dimensional space coordinate of gauge point, movable information resolves the data of 23 pairs of unit micro inertial measurement unit, 12 outputs and resolves processing, Fusion unit 24 adopts based on the Multisensor Data Fusion Algorithm of D-S evidence theory inertial parameter and the three dimensional space coordinate to moving target and deals with, obtain the pattern data of target.

described identification and training module 3 comprise training module 31, identification and resolution unit 32, wherein the input of identification and resolution unit 32 is connected with the output of Fusion unit 24, the output of the training module 31 described training module 31 that is connected with another input of resolution unit 32 with identification is a grader that trains, the pattern data that gather are in advance processed, detect pattern data to be detected for identification and resolution unit 32, described identification and resolution unit 32 are utilized the result of classification learning, detect pattern data to be detected, described pattern data to be detected are provided by Fusion unit 24.

Described health data collection module 4 comprises healthdata collection unit 41,wireless communication module 42, the output of healthdata collection unit 41 is connected with the input ofwireless communication module 42, described healthdata collection module 41 gathers relevant health-physical fitness data in motion process, bywireless communication module 41, the data that obtain is reached the virtual evaluation and test module 5 of physical education.

the virtual test and appraisal module 5 of described physical education comprises comprehensive evaluatingunit 51, man-machine interaction unit 52,display device 53, wherein the input of comprehensive evaluatingunit 51 is connected with the output that identification and resolution unit 32 are connected with wireless communication module respectively, the input of man-machine interaction unit 52 is connected with the output of identification with resolution unit 32, the output of man-machine interaction unit 52 is connected with the input ofdisplay device 53, another output of man-machine interaction unit 52 and the input wireless connections ofwireless communication module 14, comprehensive evaluatingunit 51 is according to the motion evaluation and test scheme and the standard that set in advance, to identification and the final action analysis result of training module 3, the related data that health data collection module 4 obtains is carried out the analysis-by-synthesis evaluation and test, it is visual that man-machine interaction unit 52 is used for moving analysis result, realize the interaction with virtual environment, and by wireless transmission, the related physical effect information is sent to force feedback unit 15, the realizable force feedback effects, describeddisplay device 53 is used for the analysis result of feedback athletic performance pattern identification, show the comprehensive evaluating result.The input ofdisplay device 53 is connected with computer.

A kind of implementation method that is applicable to the virtual evaluation and test of primary and secondary school physical education provided by the invention comprises the following steps:

A, target be in the positive motion of described display device, will measure one group of inertial parameter with the described microinertial measurement unit 12 of target bind, is sent to described movable information bywireless communication module 14 and resolves unit 23; Simultaneously camera (dual camera) 13 is caught the set of number image of described specificwavelength spot light 11, and it is sent to described image characteristics extraction unit 21;

B, movable information resolve 23 pairs of unit the inertial parameter that obtains adopt suitable sensor signal Preprocessing Algorithm and athletic posture to resolve algorithm (concrete operation method need be provided), calculate instantaneous acceleration, speed, position and the attitude of the relative earth of target, and result is sent to Fusion unit 24; 21 pairs of the image characteristics extraction unit digital video image that obtains carries out the characteristic composition that two value-based algorithms obtain tested racket, three-dimensional fix unit 22 is according to BuBumblebee binocular measuring principle, obtain the three dimensional space coordinate of racket identification point, and be sent to Fusion unit 24; Fusion unit 24 adopts the data message that obtains based on the Multisensor Data Fusion Algorithm of D-S evidence theory inertial parameter and the three dimensional space coordinate to tested racket and deals with, and obtains the pattern data of tested racket;

C, collection exercises pattern sample data, 31 pairs of sample mode data of training module are carried out pretreatment, obtain training data, extract the characteristic vector of reflection data substantive characteristics and according to characteristic vector, it is classified from training data, setting up the grader from characteristic vector to mapping relations affiliated classification; 31 pairs of pattern data to be detected of identification and resolution unit are carried out pretreatment, obtain Identification Data, extract characteristic vector and be input in described grader from Identification Data, grader is differentiated according to its characteristic vector, obtain the identification result to pattern data to be identified, and to just Action Semantic parsing of identification result;

D, healthdata collection unit 41 gathers the relevant physique health data of representation of athletics, and data are carried out pretreatment, transfers to comprehensive evaluatingunit 51 throughwireless communication module 42.

E, comprehensive evaluatingunit 51 will move analysis result and analysis and health data, in conjunction with predefined evaluation and test scheme and standard, provide the comprehensive evaluating result; Simultaneously, man-machine interaction unit 52 will move analysis result and merge mutually with virtual environment, in conjunction with the comprehensive evaluating result, feed back to the user bydisplay device 53 after visual; When contacting with object in virtual environment, man-machine interaction unit 51 is crossedwireless communication module 14 to the dependent interaction information exchange and is sent back force feedback unit 15, force feedback unit 15 converts relevant information one group of Wave data to and sends to the Motor Control chip, the chip controls motor is according to the running of respective waveforms data, thus the realizable force feedback effects.

Claims (10)

1. a servicing unit that is applicable to the primary and secondary school physical education evaluation and test, is characterized in that, described system comprises: exercise data acquisition module (1), be used for obtaining digital video image data and the inertial parameter of specifying the guarded region gauge point, and the reception feedback; Motion capture module (2) is used for resulting digital video image data and inertial parameter are processed, and obtains the gauge point space coordinates on sports apparatus and human body; Identification and training module (3) for the motion trace data that gathers all kinds of patterns, carry out classification learning, and Classification and Identification are made in action to be identified processed, and obtain analysis result; Health data collection module (4) is used for gathering the relevant health-physical fitness data of human body, and related data is reached the virtual evaluation and test module of physical education (5), to carry out the comprehensive evaluating analysis; The virtual evaluation and test module of physical education (5), be used for the corresponding data with identification and the final analysis result that obtains of training module (3) and health data collection module (4) acquisition, according to relevant motion and physical fitness standard, carry out the comprehensive evaluating analysis, simultaneously the motion analysis result is merged virtual environment visual, realizable force feedback, and feedback output integrated result.

2. be applicable to the servicing unit of primary and secondary school physical education evaluation and test as one kind of claim 1, it is characterized in that, described exercise data acquisition module (1) comprises specific wavelength spot light (11), camera (13), micro inertial measurement unit (12), wireless communication module (14) and force feedback unit (15), wherein camera (13) gathers the optical signal of specific wavelength spot light (11), the input wireless connections of the output of micro inertial measurement unit (12) and wireless communication module (14), the input wireless connections of the output of wireless communication module (14) and force feedback unit (15), described motion capture module (2) comprises image characteristics extraction unit (21), three-dimensional fix unit (22), movable information resolves unit (23), Fusion unit (24), wherein image characteristics extraction unit (21) input is connected with camera (13) output, image characteristics extraction unit (21) output is connected with the input of three-dimensional fix unit (22), the input that movable information resolves unit (23) is connected with the output of wireless communication module (14), movable information resolves unit (23) is connected 22 with the three-dimensional fix unit) output be connected with the input of Fusion unit (24) respectively, described identification and training module (3) comprise training module (31), identification and resolution unit (32), wherein identification is connected with the output of Fusion unit (24) with the input of resolution unit (32), and the output of training module (31) is connected with identification another input with resolution unit (32), described health data collection module (4) comprises health data collection unit (41), wireless communication module (42), and the output of health data collection unit (41) is connected with the input of wireless communication module (42), the virtual test and appraisal module of described physical education (5) comprises comprehensive evaluating unit (51), man-machine interaction unit (52), display device (53), wherein the input of comprehensive evaluating unit (51) is connected 42 with resolution unit (32) with wireless communication module with identification respectively) output be connected, the input of man-machine interaction unit (52) is connected with the output of identification with resolution unit (32), the output of man-machine interaction unit (52) is connected with the input of display device (53), the input wireless connections of another output of man-machine interaction unit (52) and wireless communication module (14).

3. one kind is applicable to the implementation method that primary and secondary school physical education is evaluated and tested, it is characterized in that, comprise the following steps: A, with the binding of gauge point and measured target, camera is arranged on the dead ahead of appointed area, be used for catching the image of appointed area, obtain the inertial parameter of gauge point motion, and the realizable force feedback effects; B, capturing digital image are also inputted all-purpose computer, obtain the digital video image of target travel; Gather the inertial parameter of gauge point motion; C, to the inertial parameter that gathers with digital video image resolves and Fusion, obtain the gauge point motion mode; D, identify its motor pattern according to the gauge point motion mode, send the virtual evaluation and test module of physical education (5) to; E, the relevant physique health data of collection motion process send the virtual evaluation and test module of physical education (5) to, and the virtual evaluation and test module of physical education (5) is visual with comprehensive evaluating result and virtual interacting environment, and feeds back to the user.

4. a kind of implementation method that is applicable to primary and secondary school physical education evaluation and test as claimed in claim 3, it is characterized in that, described step C also comprises: resolve algorithm by adopting corresponding sensor signal Preprocessing Algorithm and athletic posture, utilize the inertial parameter that gathers to calculate instantaneous acceleration, speed, position and the attitude of the relative earth of target.

5. a kind of implementation method that is applicable to primary and secondary school physical education evaluation and test as claimed in claim 3, it is characterized in that, described step C also comprises: according to digital video image, at first the present invention extracts measured target motion characteristics composition by two value-based algorithms, characteristic composition is asked for its center of gravity, obtain the characteristic composition center; Then according to the calculating to selected feature, set up the corresponding relation between feature.

6. a kind of implementation method that is applicable to primary and secondary school physical education evaluation and test as claimed in claim 3, it is characterized in that, described step C also comprises: according to the corresponding relation between feature, according to BuBumblebee binocular measuring principle, realize that Three dimensional Targets accurately locates.

7. a kind of implementation method that is applicable to primary and secondary school physical education evaluation and test as claimed in claim 3, it is characterized in that, described step C also comprises: to measured target gauge point motion mode and the inertial parameter that obtains in described step B, by the Multisensor Data Fusion Algorithm of D-S evidence theory, obtain reflecting the consistent data of measured target motion feature.

8. a kind of method that is applicable to the primary and secondary school physical education evaluation and test as claimed in claim 3, is characterized in that, described step D also comprises:

D1, gather in advance the sample pattern data of multi-motion, the sample pattern data of pre-collection are marked;

D2, go out one by one the characteristic vector of its motion essence feature of reflection from described sample pattern extracting data;

D3, divide according to described characteristic vector under category regions, make the characteristic vector that only comprises similar sample in each the different classes of zone after division, set up the grader from characteristic vector to mapping relations affiliated classification;

D4, the pattern data of moving target to be detected are processed, extracted its characteristic vector;

D5, the characteristic vector of pattern data to be detected is input to described grader, grader is differentiated according to its characteristic vector, obtains the identification result to these pattern data to be detected, and identification result is carried out Action Semantic resolve.

9. a kind of implementation method that is applicable to the primary and secondary school physical education evaluation and test as claimed in claim 8, is characterized in that, described step D2 also comprises:

D21, described sample pattern data are carried out pretreatment, obtain training data;

D22, extract the characteristic component of reflection training data substantive characteristics from training data;

D23, described characteristic component is made up, obtain described characteristic vector;

Described step D4 also comprises:

D41, described pattern data to be detected are carried out pretreatment, obtain Identification Data;

D42, extract the characteristic component of reflection Identification Data substantive characteristics from Identification Data;

D43, described characteristic component is made up, obtain described characteristic vector.

10. a kind of implementation method that is applicable to the primary and secondary school physical education evaluation and test as claimed in claim 3, is characterized in that, described step e also comprises:

E1, in motion process, gather simultaneously the relevant physique health data of representation of athletic, and data carried out pretreatment;

E2, combined action analysis result and analysis and health data, in conjunction with predefined evaluation and test scheme and standard, provide the comprehensive evaluating result;

E3, the analysis result that will move merge mutually with virtual environment, and in conjunction with the comprehensive evaluating result, visual feedback is to the user;

E4, when contacting with object in virtual environment, man-machine interaction unit sends back force feedback unit, realizable force feedback effects to dependent interaction information;

Wherein, described step e 4 also comprises:

E41, when contacting with object in virtual environment, man-machine interaction unit sends back the force feedback unit to dependent interaction information;

E42, force feedback unit converts relevant information one group of Wave data to and sends to the Motor Control chip;

E43, chip controls motor are according to the running of respective waveforms data, thus the realizable force feedback effects.

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