CN111957024A - Wearable Taiji motion gait evaluation and training system based on cloud platform - Google Patents
Wearable Taiji motion gait evaluation and training system based on cloud platform Download PDFInfo
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Abstract
The invention discloses a wearable Taiji motion gait evaluation and training system based on a cloud platform, which comprises a gait parameter acquisition module, a gait parameter processing module, a gait motion function evaluation and training module and a cloud platform module, wherein the gait parameter acquisition module is used for acquiring gait parameters; gait data in the human body Taiji motion are collected in real time by adopting an attitude sensor, a plantar pressure sensor and a surface myoelectric sensor, and the transverse and longitudinal comparison of user Taiji motion gait training is realized based on a cloud platform data fusion algorithm; meanwhile, a big data depth mining algorithm is adopted to realize the reverse analysis from the electromyographic signal to the gait standard; based on the man-machine interaction function of multiple users, clear digital visual guidance can be provided for Taiji teaching, and objective quantitative reference can also be provided for scoring of competition Taiji competition judges; through the integrated design of the encapsulation of each device, the system is portable and wearable, easy to use is reliable, and has good market value.
Description
Technical Field
The invention relates to the field of Taiji motion evaluation and training, in particular to a wearable Taiji motion gait evaluation and training system based on a cloud platform.
Background
Along with the popularization of the national body-building sports, the Taiji sports becomes the body-building sports which is suitable for people of all ages; the Taijiquan is an important component of the Chinese traditional Wushu which is the essence of China and the Chinese non-material cultural heritage, and needs to be put forward, protected and developed by everyone; however, taiji exercise may cause physical damage due to irregular training motion, but currently, there are few taiji exercise evaluation systems in the market, and there are only a few gait evaluation systems (for example, MVN inertial motion capture system developed by Xsens Technologies, the netherlands, and "GaitWatch" three-dimensional gait motion capture and training system released by the chapter and intelligent corporation) that use inertial sensing technology to capture human body motion, and use multi-joint wireless sensors to acquire gait motion parameters of a trainer in real time to provide scientific motion schemes for a testee, and these gait evaluation systems have the disadvantages that: the strength of the muscle in the exercise process cannot be effectively detected, and the fatigue analysis of the muscle cannot be carried out in real time, so that the user can easily generate muscle fatigue and injury due to too long training time and too high training strength; in the existing training process of Taiji sports, a user still can only passively complete training according to videos and characters, digital visual guidance based on a human-computer interaction technology is not provided, and a Taiji sports beginner can easily understand the Taiji sports to cause deviation and boredom; therefore, the portable system for comprehensively, systematically collecting the motion and physiological data of the user in the Taiji motion process at multiple angles is urgently needed, high visualization of detection results and interesting Taiji training is realized, clear digital visual guidance can be provided for teaching of Taiji teachers and apprentices, objective quantitative reference can be provided for scoring of competitive Taiji competition judges, and the actual requirements of vast amateur Taiji enthusiasts and professional Taiji teachers and apprentices are met.
Disclosure of Invention
The wearable Taiji motion gait evaluation and training system is portable, wearable, easy to use and reliable, meets market requirements, can provide clear digital visual guidance for Taiji teaching, and can also provide objective quantitative reference for scoring of athletics Taiji competition judges.
The invention discloses a wearable Taiji motion gait evaluation and training system based on a cloud platform, which comprises a gait parameter acquisition module, a gait parameter processing module, a gait motion function evaluation and training module and a cloud platform module; the gait parameter acquisition module, the gait parameter processing module and the gait motion function evaluation and training module respectively realize the functions of acquiring and processing gait data and feeding back results in Taiji motion, the whole set of system is scientific, reliable, portable and convenient, and the functions of the modules are highly integrated.
The gait motion parameter acquisition module comprises a human motion pose detection and acquisition module, a fatigue detection module and an intelligent insole, can acquire various signals from the foot in real time and upload the signals to an upper computer and a cloud platform, and realizes the acquisition of Taiji motion gait feature data based on a multi-sensor cooperative sensing algorithm.
The posture sensor and the surface electromyography sensor of the human motion pose detection and acquisition module are integrally packaged in a small black box and are provided with leg belts, so that the human motion pose detection and acquisition module can be conveniently fixed on the surface of a human body, collects the angle, angular velocity, angular acceleration and position information of the human body in space in Taiji motion in real time, uploads the angle, angular velocity, angular acceleration and position information to a cloud for data fusion analysis, and synchronously drives the 3D digital Taiji model of the software of the upper computer to move.
The fatigue detection module collects and uploads myoelectric signals of limbs and feet of a human body in real time, muscle fatigue characteristic values are extracted after noise reduction and filtering, and whether the human body is in a training fatigue state or not is analyzed through a cloud platform fusion algorithm.
The intelligent insole comprises a foot type and gait correction module, an even heat module and a wireless communication module, wherein the gait correction module comprises a sole pressure sensor for detecting sole pressure information of a human body, a 12-size motion air bag for carrying out standard correction on the gait foot type of the human body and a surface myoelectric sensor for collecting surface myoelectric signals of the foot part of the human body, the even heat module comprises a temperature sensor, an A/D (analog to digital) converter, a D/A (digital to analog) converter, an embedded control system, an electronic circuit and 8 electric stimulations to stimulate hot holes, and the control on the temperature of muscle masses is realized.
The gait motion parameter processing module is composed of an upper computer algorithm program and can be in two-way communication with the cloud platform module; the gait motion function evaluation and training module consists of a multi-user human-computer interaction module, a virtual game training module and a gait data analysis feedback module; the multi-user human-computer interaction module and the virtual game training module are designed based on a Unity platform, three-dimensional modeling is carried out on motion data of a taiji university teacher stored in a cloud platform in a human-computer interaction interface, one-to-one following training of a user is realized, the user can also set a training mode by himself, and scientific and efficient training is completed according to local conditions and time conditions; the virtual game training module is internally provided with various system training interfaces such as stages, arenas, squares and the like, and also supports user-defined scenes, and a user can shoot scene pictures by himself and transmit the scene pictures into the virtual game training interfaces through a USB (universal serial bus) or a wireless interface to serve as scenes; the virtual game training interface also has a multi-user human-computer interaction training function, and can be used as an objective evaluation reference for the simultaneous movement of a gait analysis assistant and a Taiji action competition competitor which are simultaneously exercised by a master and a brother on the basis of a cloud platform data fusion and data analysis algorithm; the gait analysis feedback module is based on that the motion gait data of the great teacher is stored in the cloud platform module, each training of a user can be uploaded in real time and stored in the cloud, a comparison algorithm based on a cloud numerical value and a deep mining algorithm based on big data are adopted to realize horizontal great teacher-level comparison analysis and longitudinal time self-comparison analysis, the system can also remind the user of the training state, the body fatigue degree and the motion specification needing to be noticed at the moment in real time in the training process of the user, and after the training is finished, the system can automatically generate a motion data report of the moment, provide an all-dimensional and multi-angle motion analysis result and indicate the non-specification part of the motion of the user; the system also provides a motion scheme of the next stage according to the training result of the time, so that the user can train more scientifically and effectively.
The cloud platform module consists of a NoSql distributed database module and a Hadoop unit module, has cloud analysis, cloud storage and cloud computing functions, is mutually connected with the Hadoop unit module by adopting the NoSql distributed database module, and stores motion data and results of a user during Taiji motion training; the cloud platform module deeply excavates collected data based on a MapReduce distributed off-line computing model and provides scientific Taiji gait data analysis results and effective motion schemes for users; the fatigue-gait model algorithm of the cloud platform module reversely analyzes whether gait motions of the Taiji user are standard or not, synchronously monitors muscle fatigue degrees, achieves muscle fatigue early warning, effectively prevents human muscle damage caused by excessive Taiji motion, and enables the Taiji motion gait training to be safer and more reliable.
The wearable Taiji motion gait evaluation and training system based on the cloud platform is a portable wearable design integrated with an MEMS (micro electro mechanical system), and can be embedded into tights and insoles of Taiji users; adopt comparatively power saving's bluetooth communication between each module of system when closely, will automatic switch over for WIFI communication when long-range.
The upper computer software of the man-machine interaction module is compiled by C # and C + +, so that basic operation and data setting can be conveniently carried out on the system, the current motion state of a user can be monitored in real time, and man-machine interaction is more friendly.
Compared with the prior art (product), the invention has the following outstanding advantages: the device can provide interesting gait training while carrying out gait evaluation, effectively reduce the boredom psychology generated by long-time Taiji movement gait training of the user and improve the training efficiency; the cloud platform data fusion algorithm is adopted to realize transverse and longitudinal comparison of Taiji movement gait training of the user, the comparison data is accurately analyzed in multiple dimensions, and an individualized gait training prescription is provided; based on a big data deep mining algorithm, the reverse analysis from the electromyographic signal to gait specification is realized, and a reasonable training duration reference is provided for a user; based on the human-computer interaction function design of multiple users, clear digital visual guidance can be provided for Taiji teaching, and objective quantitative reference can also be provided for scoring of competition Taiji competition judges; the device integrates the design through the encapsulation to each device, can all-round, multi-angle, systematically gather motion and physiological data in the user taiji motion process, is a portable system who realizes that the testing result is high visual and taiji training taste, and convenient easy-to-use, the superior performance has good market value.
Drawings
Fig. 1 is a structural diagram of a wearable taiji motion gait evaluation and training system based on a cloud platform.
Fig. 2 is a functional block diagram of a wearable taiji motion gait evaluation and training system based on a cloud platform.
In fig. 1:
1-a gait motion parameter acquisition module, 2-a gait motion parameter processing module,
3-a gait motion function evaluation and training module, 4-a cloud platform module,
5-a human body motion pose detection and acquisition module, 6-an intelligent insole,
and 7, a fatigue detection module.
Detailed Description
For the purpose of illustrating the details of the structure and operation of the present invention, reference will be made to the accompanying drawings and examples.
As shown in fig. 1, the wearable taiji exercise gait evaluation and training system based on the cloud platform structurally includes a gait parameter acquisition module 1, a gait parameter processing module 2, a gait exercise function evaluation and training module 3 and a cloud platform module 4.
The gait motion parameter acquisition module 1 shown in fig. 1 comprises a human motion pose detection and acquisition module 5, a fatigue detection module 7 and an intelligent insole 6; the gait motion parameter acquisition module consists of nine-axis attitude sensors, is respectively arranged on the waist, the thighs, the calves and the feet of the human body, accurately collects the angle, the angular velocity, the angular acceleration and the position information of the human body in space in real time during motion based on a Kalman filtering motion capture algorithm, uploads the data to the cloud, and drives the 3D model of the upper computer software to move by adopting a data fusion algorithm; the fatigue detection module consists of a surface electromyography sensor, a control panel, a wireless module and a power supply module, wherein the surface electromyography sensor is arranged on the lower limbs and the feet of a human body (embedded in an intelligent insole) to collect electromyography signals of the legs and the feet of the human body in real time, the original electromyography signals collected by the surface electromyography sensor are firstly transmitted to a controller, the data are uploaded to a PC upper computer and a cloud end by the wireless module after simple filtering, the fatigue characteristic values of the human body are collected after noise reduction and filtering, whether the human body is in a training fatigue state or not is analyzed by a cloud platform fusion algorithm, and whether gait motions are standard or not is reversely analyzed by a fatigue-gait model algorithm of a cloud platform, monitoring the muscle fatigue degree of the user in the exercise process, reminding the muscle fatigue state of the user in real time and early warning, effectively preventing muscle damage caused by excessive Taiji exercise and ensuring that the training is safer and more reliable; the intelligent insole based on the plantar pressure sensor comprises a foot shape and gait correcting module, a uniform heat module and a wireless communication module; the wireless communication module is used for uploading various signals collected from the feet to the upper computer and the cloud.
The cloud platform module shown in fig. 1 is composed of a NoSql (not Only sql) distributed database module and a Hadoop unit module, and has cloud analysis, cloud storage and cloud computing functions, the NoSql distributed database module and the Hadoop unit module are connected with each other and used for storing motion data and operation results of a user during training, and the cloud platform deeply excavates collected data based on a MapReduce distributed offline computing model and provides scientific data analysis results and effective motion schemes for the user.
The wearable taiji motion gait evaluation and training system based on the cloud platform shown in fig. 1 combines a biomechanics human body model technology on the basis of an inertial motion sensor and a bluetooth technology, does not need an external camera, a mark point, a transmitter and other auxiliary devices, and transmits data to a notebook computer or a computer terminal in real time through a wireless bluetooth technology, so that the limitation of wired communication on human body motion is avoided; based on a human body model with 23 limb segments and 22 joints in unity, the virtual human is driven in real time through motion data, so that the motion measurement effect can be recorded and checked in real time, and biomechanical parameters are output.
The intelligent insole shown in fig. 1 comprises 12 small sports airbags, a surface myoelectricity sensor, a sole pressure sensor, an electronic circuit and a wireless module; the small-sized motion air bag is a layer of film when not started, swells after being started, is in a globular shape and is used for extruding muscles; the 12 small-sized motion air bags are respectively positioned at 7 muscles and 5 toes (hallux abductor, tendon of flexor hallucis longus, flexor hallucis brevis, abductor hallucis little, flexor hallucis brevis and 5 toes) of the sole of a human body.
The surface electromyography sensor shown in fig. 1 is tightly attached to the skin surface of a leg of a human body, is used for monitoring the muscle condition in real time, and judges the motion state of a body part, the muscle fatigue condition and other physiological data by measuring the fluctuation amplitude of muscle fiber contraction; the electronic circuit and the wireless module realize data acquisition control, data caching, wireless data sending and receiving and small-size moving air bag inflation and deflation control; the foot rehabilitation training device is suitable for users with different requirements, normal people can be used for correcting running postures during running so as to be beneficial to good development and maintenance of bones such as knee joints, foot patients can be used for deliberately exercising certain muscles on soles of feet so as to carry out rehabilitation training efficiently, and athletes can be used for correcting the force-exerting degree and the force-exerting positions of the muscles in specific actions of foot shapes and gaits.
The gait parameter processing module and the gait motion function evaluation and training module shown in fig. 1 are composed of upper computer algorithm programs and are in two-way communication with a cloud platform module, the cloud platform adopts big data fusion analysis processing to extract features of data collected by a user in a motion process and compares the extracted features with master standard data to indicate irregular actions and provide corresponding improvement suggestions, the cloud end can also store motion data of the user every time, the comparison with previous data can be integrated after the training is finished, the self-comparison of the user can be realized in time, and therefore the user can clearly see a place with improved self-ability and find technical defects, and the training score of the user is effectively improved.
The gait motion function evaluation and training module shown in fig. 1 consists of a multi-user human-computer interaction module, a virtual game training module and a gait data analysis feedback module; the human-computer interaction module and the virtual game training module are compiled by using C # language based on the Unity platform; in the man-machine interaction module, firstly, a taiji motion data module of a taiji teacher is acquired, the specific implementation scheme is that the teacher is requested to wear each module of the whole set of system to the most appropriate part of a body, the angle data change, the angular acceleration information, the position information, the surface electromyographic signals and the plantar pressure information of each joint when the teacher performs taiji boxing motion are acquired in real time, noise reduction and filtering processing is performed after data acquisition is completed, each action data is decomposed and normalized, the data is uploaded to the cloud after the data processing is completed, a three-dimensional model is established by using the data as a training standard, and a user can automatically select a training mode and a training difficulty on an upper computer after entering the man-machine interaction module; the training mode is divided into two types, namely Taiji boxing action decomposition training and continuous Taiji sports training, the decomposition mode can be used for carrying out targeted training improvement on weak links of user actions, and the continuous actions can be used for improving the overall performance of the user; the training difficulty is divided into three types, namely a goal level, a medium level and a professional level, and the purpose is to gradually improve the athletic performance of the user; the user can carry out one-to-one following type training according to the three-dimensional model that appears in the system in the human-computer interaction module, and the user also can set up training mode by oneself, carries out scientific and efficient training according to local conditions, according to the time and place, is provided with multiple system training interface in virtual game training module, like stage, arena, square etc. also supports self-defined scene, and the user can shoot the scene picture by oneself, passes into virtual game training interface as the scene through USB or wireless interface.
As shown in fig. 2, the gait motion parameter processing module adopts a kinematics constraint algorithm, data amplification filtering and data fusion, and performs kalman filtering on the linear acceleration in the information acquired by the nine-axis attitude sensor, and then transforms the processed linear acceleration and euler angle according to an euler matrix:
taking the capture of a leg in an extreme motion training system as an example, firstly constructing a physiological model of the leg, realizing the real-time capture of the leg motion by combining the anatomical structure principle and the motion characteristics of the leg, constructing a rigid body hinge simplified model of four degrees of freedom of the leg, then researching a single joint motion measuring method, finally researching the motion measuring methods of two joints, designing a quick and effective calibration method between an inertia unit and the leg joint at the initial moment of joint measurement, compensating the initial error between the joint and the inertia unit, designing a calculation method of the rotation center position of the leg joint in the motion process, and completing a leg joint angle calculation scheme; the fatigue detection module consists of 6 surface electromyographic sensors, a controller single chip microcomputer, a wireless module and a power supply module, wherein the surface electromyographic sensors are arranged on the lower limbs and the feet of a human body (embedded in an intelligent insole) and are used for collecting original electromyographic signals of four limbs and the feet of the human body in real time and transmitting the original electromyographic signals to the controller, the controller single chip microcomputer is connected with the surface electromyographic sensors, a Bluetooth module and the power supply module and is powered by a direct current power supply, data transmission is based on the Bluetooth module and is set in a master-slave relation directly connected with the controller so as to enable the two to be communicated, the data are uploaded to a PC upper computer and a cloud end by the wireless module after simple filtering, fatigue characteristic values of the human body are collected after noise reduction and filtering, whether the human body is in a training fatigue state is analyzed by a cloud platform, the muscle fatigue degree of the user in the exercise process is monitored, the muscle fatigue state of the user is reminded in real time, muscle damage caused by excessive exercise is effectively prevented, and the training is safer and more reliable.
The Taiji gait evaluation standard and feedback function shown in fig. 2 is based on a cloud platform big data depth mining algorithm, a depth neural network feature weight-lifting and correlation analysis method is adopted to carry out action consistency standard judgment, corresponding voice prompts are provided in the training process, a user can also obtain action standard degree prompts given by the system in the movement process, the system distinguishes and prompts the user action standard degree by using different colors, green represents more than 85% of standard actions, yellow represents 60% -85% of standard actions, and red represents that the actions do not accord with the standard specifications; the training of user at every turn also can upload in real time and save in the high in the clouds, carry out horizontal master's level contrastive analysis and longitudinal time self-contrast analysis through high in the clouds numerical value comparison algorithm, the system also can remind training state and the tired degree of health and the action standard that needs notice at this moment of user's training in-process in real time, after the training, the system can automatic generation motion data report, the report can provide the all-round, the motion analysis result of multi-angle, point out the nonstandard part of user's action, the system still can provide the motion scheme of next stage according to the training result, make the user can carry out more scientific and effective training.
The wearable taiji exercise gait evaluation and training system based on the cloud platform shown in fig. 2 is portable and wearable, is simple and convenient to operate, is scientific and reliable, enables a user to enjoy immersive taiji training, improves training performance, enables the training user to enjoy the training mode better, and forms a virtuous cycle of training; the system creatively adds a fatigue detection module, extracts fatigue characteristic values by collecting surface electromyographic signals of upper, lower limbs and feet of a human body, analyzes the real-time muscle fatigue state of a user, and gives a warning to the user when muscles reach physiological fatigue, so that the user can effectively avoid muscle damage caused by excessive movement; the human-computer interaction module and the virtual game module of the system enable a user to carry out interesting exercise training, can effectively increase the interest of exercise, can effectively reduce the boredom of the user caused by long-time training, and improve the training efficiency; through the integrated design of the encapsulation of each device, the system is portable and wearable, easy to use and reliable, and has good market value.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
The working process of the invention is as follows:
firstly, wearing the sports pants and the insoles embedded with the evaluation module, opening an interface of an upper computer, starting the Bluetooth of the wearable device, and carrying out Bluetooth pairing connection with the upper computer; then a user selects a corresponding training module on the software of the upper computer, for example, a professional level is selected, the system takes the motion data of a professional taiji teacher as a standard, the system prompts the start of training after the professional level is selected, the user can carry out one-to-one following type training according to the action of the teacher and displays the training data on the upper computer in real time in a 3D model mode, the motion data of the user in the training process can be uploaded to the cloud end in real time to be compared with the standard data of the teacher, the system reminds the current action of the athlete and the conformity degree of the standard action in real time in different colors and generates a training report after the training is finished to indicate the action which is not standard of the user, so that the transverse teacher comparison is realized, the data of each training of the user can be stored in the cloud end, and the comparison between the training and the previous training data can also occur in the training, longitudinal time comparison is realized; during the exercise, the system can also monitor the muscle fatigue degree of the user in real time by extracting the fatigue characteristic value, and when the muscle reaches a certain fatigue degree, the system can prompt the user to reduce the training intensity or suggest the user to take a rest for a corresponding time; after training is finished, the Bluetooth and the upper computer are closed, the wearable device is placed in a special box and is placed in a dry and cool place; the user can export the training data from the cloud platform to local, prints the analysis, still can directly carry out teletransmission from the cloud platform, reaches taiji professional judges and carries out manual analysis and gives the suggestion, brings the promotion of taiji motion level nature for the user.
The foregoing illustrates and describes the principles, implementations and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (4)
1. A wearable Taiji motion gait evaluation and training system based on a cloud platform is structurally divided into a gait motion parameter acquisition module, a gait motion parameter processing module, a gait motion function evaluation and training module and a cloud platform module; the gait motion parameter acquisition module comprises a human motion pose detection and acquisition module, a fatigue detection module and an intelligent insole; the human body motion pose detection and acquisition module consists of a posture sensor; the fatigue detection module consists of a surface electromyography sensor; the function of the intelligent insole is realized based on a sole pressure sensor; the gait motion parameter processing module consists of an upper computer algorithm program written by C # or C + + language and can be in bidirectional communication with the cloud platform module; the gait motion function evaluation and training module consists of a multi-user human-computer interaction module, a virtual game training module and a gait data analysis feedback module; the cloud platform module consists of a NoSql distributed database module and a Hadoop unit module, has cloud analysis, cloud storage and cloud computing functions, is mutually connected with the Hadoop unit module by adopting the NoSql distributed database module, and stores motion data and results during user Taiji motion training; the cloud platform module deeply excavates collected data based on a MapReduce distributed off-line computing model, and provides scientific Taiji gait data analysis results and effective motion schemes for users.
2. The gait motion parameter acquisition module of claim 1 can acquire various signals from the foot in real time and upload the signals to an upper computer and a cloud platform, and the acquisition of Taiji motion gait feature data is realized based on a multi-sensor cooperative sensing algorithm; the human motion pose detection and acquisition module adopts a Kalman filtering algorithm, can accurately collect the angle, angular velocity, angular acceleration and position information of a human body in space in Taiji motion in real time, uploads the information to the cloud for data fusion analysis, and synchronously drives the 3D digital Taiji model of the upper computer software to move; the fatigue detection module collects and uploads myoelectric signals of limbs and feet of a human body in real time, extracts muscle fatigue characteristic values after noise reduction and filtering, and analyzes whether the human body is in a training fatigue state or not through a cloud platform fusion algorithm; the fatigue-gait model algorithm of the cloud platform module reversely analyzes whether the gait motion of the Taiji user is standard or not, synchronously monitors the muscle fatigue degree, realizes muscle fatigue early warning, effectively prevents human muscle damage caused by excessive Taiji motion, and enables the Taiji motion gait training to be safer and more reliable; the posture sensor and the surface electromyography sensor of the human body motion pose detection and acquisition module are integrally packaged in a small black box and are provided with leg belts, so that the human body motion pose detection and acquisition module can be conveniently fixed on the surface of a human body; sole pressure sensors in the intelligent insole of the human motion pose detection and acquisition module are distributed at corresponding positions of 7 muscles and 5 toes on the sole of the human body and are packaged in the middle layer of the insole; the gesture sensor, the surface electromyography sensor and the plantar pressure sensor of the human body motion pose detection and acquisition module are communicated by Bluetooth and WiFi; the intelligent insole comprises a foot shape and gait correction module, an even heat module and a wireless communication module, wherein the gait correction module comprises a plantar pressure sensor for detecting plantar pressure information of a human body, 12 small motion airbags for carrying out standard correction on the gait foot shape of the human body and a surface myoelectric sensor for collecting surface myoelectric signals of the foot part of the human body, the even heat module comprises a temperature sensor, an A/D (analog to digital) converter, a D/A (digital to analog) converter, an embedded control system, an electronic circuit and 8 electric stimulations to stimulate hot holes, and the control on the temperature of muscle masses is realized.
3. The multi-user human-computer interaction module and the virtual game training module of the gait motion function assessment and training module as claimed in claim 1 are designed based on a Unity platform, in a human-computer interaction interface, the motion data of the taiji university teacher stored in the cloud platform is subjected to three-dimensional modeling, so that one-to-one following training of a user is realized, the user can also set a training mode by himself, and scientific and efficient training is completed according to local conditions and time conditions; the virtual game training module is internally provided with various system training interfaces such as stages, arenas, squares and the like, and also supports user-defined scenes, and a user can shoot scene pictures by himself and transmit the scene pictures into the virtual game training interfaces through a USB (universal serial bus) or a wireless interface to serve as scenes; the virtual game training interface also has the function of multi-user human-computer interaction training and can be used as a gait analysis assistant for teachers and hikers to drill simultaneously and an objective evaluation committee for the simultaneous movement of Taiji action competition participants; the function realization of the multi-user human-computer interaction training is based on a cloud platform data fusion and data analysis algorithm; the gait analysis feedback module is based on a cloud platform big data depth mining algorithm; the cloud platform module stores motion gait data of the great teacher, each training of the user can be uploaded in real time and stored in the cloud, the comparison analysis of the transverse great teacher and the self comparison analysis of the longitudinal time are realized through a cloud numerical value comparison algorithm, the system can also give the training state, the body fatigue degree, the motion specification required to be noticed and the voice feedback of wrong motion of the user in real time in the training process of the user, and after the training is finished, the system can automatically generate a motion data report to provide an all-dimensional and multi-angle motion analysis result and point out the non-specification part of the motion of the user; the system also provides a Taiji training scheme of the next stage according to the training result, so that the user can carry out Taiji exercise training more scientifically and effectively.
4. The cloud platform based wearable taiji motion gait evaluation and training system as claimed in claim 1 is a MEMS (micro electro mechanical system) integrated portable wearable design that can be embedded in the taiji user's sport pants and insoles; adopt comparatively power saving's bluetooth communication between each module of system when closely, will automatic switch over for WIFI communication when long-range.
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