CN111265817A - Intelligent treadmill system - Google Patents

Intelligent treadmill system Download PDF

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CN111265817A
CN111265817A CN202010197331.4A CN202010197331A CN111265817A CN 111265817 A CN111265817 A CN 111265817A CN 202010197331 A CN202010197331 A CN 202010197331A CN 111265817 A CN111265817 A CN 111265817A
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training
standard
posture
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马敬奇
钟震宇
卢杏坚
雷欢
王楠
吴亮生
陈再励
何峰
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Guangdong Institute of Intelligent Manufacturing
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    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B22/00—Exercising apparatus specially adapted for conditioning the cardio-vascular system, for training agility or co-ordination of movements
    • A63B22/02—Exercising apparatus specially adapted for conditioning the cardio-vascular system, for training agility or co-ordination of movements with movable endless bands, e.g. treadmills
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    • G06V40/23—Recognition of whole body movements, e.g. for sport training
    • G06V40/25—Recognition of walking or running movements, e.g. gait recognition
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
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    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
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    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
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    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
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    • A—HUMAN NECESSITIES
    • A63—SPORTS; GAMES; AMUSEMENTS
    • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B22/00—Exercising apparatus specially adapted for conditioning the cardio-vascular system, for training agility or co-ordination of movements
    • A63B22/02—Exercising apparatus specially adapted for conditioning the cardio-vascular system, for training agility or co-ordination of movements with movable endless bands, e.g. treadmills
    • A63B2022/0278—Exercising apparatus specially adapted for conditioning the cardio-vascular system, for training agility or co-ordination of movements with movable endless bands, e.g. treadmills with reversible direction of the running surface

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Abstract

The invention discloses an intelligent treadmill system, wherein the system comprises: the system comprises at least one running client, an intelligent algorithm module and a cloud service platform; the running client is used for acquiring running training image data of a training person on a specified running area on the running machine and synchronizing the acquired running training image data into the cloud service platform in real time; the cloud service platform is used for detecting the posture information of the training personnel in the running training image data after receiving the running training image data synchronized in real time, and starting the intelligent algorithm module to analyze the posture information of the training personnel based on the posture information; the intelligent algorithm module is used for analyzing the posture information of the training personnel and pushing the analysis result to the running client for displaying to the training personnel. In the embodiment of the invention, the beats of the trainers during running are more reasonable, the running postures are more standard, the training process is safer, and the better training and body-building effects are achieved.

Description

Intelligent treadmill system
Technical Field
The invention relates to the technical field related to intelligent treadmills, in particular to an intelligent treadmill system.
Background
The main problems of the current treadmill control system are as follows: (1) the treadmill control system drives the treadmill to rotate according to a training course, the rotating speed and the tempo change fixedly, in the actual training process, the step size, the stride frequency and the swing amplitude and frequency of the two arms of the upper limbs of a trainer are difficult to keep consistent with those required by the training course, the exercise tempo is adjusted only by the trainer in the whole training process, the whole course is difficult to keep, and the expected training effect cannot be achieved; (2) running is an important training mode for keeping body health, the standard of running postures plays a crucial role in training effect, and the current running machine lacks an autonomous monitoring mechanism, cannot judge the posture accuracy of a trainer in the running process and seriously affects the training effect; in summary, the fundamental problem of the treadmill system is the disjointing between the control system and the actual exercise information of the trainers, and the lack of a feedback control mechanism between the control system and the actual exercise information of the trainers, which results in a series of problems of poor training effect and low safety in the prior art.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides an intelligent treadmill system which can realize real-time follow-up of a trainer to run on the treadmill system for feedback display, so that the trainer has more reasonable tempo, more standard running posture and safer running process during running, and achieves better training and body building effects.
In order to solve the technical problem, an embodiment of the present invention further provides an intelligent treadmill system, where the system includes at least one running client, an intelligent algorithm module, and a cloud service platform; wherein the content of the first and second substances,
the running client is used for acquiring running training image data of a training person on a specified running area on the running machine and synchronizing the acquired running training image data into the cloud service platform in real time;
the cloud service platform is used for detecting the posture information of the training personnel in the running training image data after receiving the running training image data synchronized in real time, and starting the intelligent algorithm module to analyze the posture information of the training personnel based on the posture information of the training personnel in the running training image data;
the intelligent algorithm module is used for analyzing the posture information of the training personnel and pushing the analysis result to the running client for displaying to the training personnel.
Optionally, the running client includes an image acquisition terminal, a running machine, a local control system and a data display terminal; wherein the content of the first and second substances,
the treadmill is provided with a running area for training a person to run in the running area, and when the person performs running training in the running area, the image acquisition terminal is triggered to acquire running training image data in real time;
the image acquisition terminal is used for acquiring running training image data of a training person in a running area corresponding to the running machine and transmitting the running training image data to the local control system and the data display end in real time;
the local control system and the data display end are used for synchronizing the number of the running training images to a cloud service platform in real time and displaying an analysis result pushed by the intelligent algorithm.
Optionally, the analyzing the posture information of the trainee includes:
calculating the lower limb stride and frequency and the amplitude and frequency of double-arm swinging in the posture information of the training personnel, and comparing the calculation result with the beat requirement of a standard running course to obtain the contrast difference; and/or the presence of a gas in the gas,
calculating the self included angle change of each joint of the trunk, the legs, the two arms and the head of the human body in the posture information of the training personnel during the running process, comparing and analyzing the calculation result of the included angle change with the standard running action, and judging the posture accuracy of the training personnel during the running process; and/or the presence of a gas in the gas,
estimating the body balance of the training personnel by utilizing the posture information of the training personnel, calculating the real-time gravity center position of the training personnel, carrying out self-adaptive control on the rotating speed of the treadmill according to the real-time gravity center position and generating running potential safety hazard early warning information; and/or the presence of a gas in the gas,
analyzing data in the training personnel individual movement database, judging the running training effect development trend of the training personnel accumulated along with movement time, and comprehensively evaluating the training effect of the training personnel.
Optionally, the comparison formula for comparing the calculation result with the tempo requirement of the standard running course is as follows:
Figure BDA0002418094750000031
where n denotes the number of statistical wobble periods, siRepresenting the swing distance recorded for the ith swing cycle, s 'representing the distance of the standard running course swing, f' representing the frequency of the standard running course swing, t representing a preset time period, β1Representing the degree of difference from the standard running course stride β2Indicating the degree of difference from the standard running course swing frequency.
Optionally, calculate the contained angle change of human trunk, shank, both arms, each joint of head oneself in training personnel's the gesture information when running process to carry out contrastive analysis with contained angle change calculated result and standard running action, include:
decomposing the running actions in the posture information of the trainees along a time axis to form a trainee running action sequence, calculating training included angles among human joints of the running actions of the trainees in the trainee running action sequence, and forming running action digital posture data of the trainees according to the time variation of the training included angles;
decomposing the standard running actions along a time axis to form a standard action posture sequence, calculating a standard included angle between human body joints of each standard running action in the standard action posture sequence, and forming standard running action digital posture data according to the standard included angle along time variation;
establishing a running action comparison analysis model based on the running action digital posture data of the training personnel and the standard running action digital posture data;
and carrying out comparative analysis based on the running motion comparative analysis model.
Optionally, the running motion comparative analysis model has the following model formula:
Figure BDA0002418094750000032
wherein the content of the first and second substances,
Figure BDA0002418094750000033
representing the motion similarity of human joints n, delta T representing the difference between T and T', delta representing the overall similarity of human postures αnRepresenting the weight value of the human joint n in the process of evaluating the overall similarity delta of the posture, αnDetermined by a standard running course;
Figure BDA0002418094750000034
representing a standard included angle between human joints n;
Figure BDA0002418094750000035
representing a set formed by standard angles between human joints n; l represents the standard running motion digital posture data, namely
Figure BDA0002418094750000039
Over time tThe change curve of (a) is obtained,
Figure BDA0002418094750000036
Figure BDA0002418094750000037
n∈[1,N]，tm∈[0,T]n represents the number of human body joint points; t represents the movement cycle of the standard running motion;
Figure BDA0002418094750000038
representing the training included angle between human joints n,
Figure BDA0002418094750000041
representing a set formed by training angles between human joints n; l represents the running motion digital attitude data of the trainee, i.e.
Figure BDA0002418094750000042
The curve of the variation with time t,
Figure BDA0002418094750000043
Figure BDA0002418094750000044
n∈[1,N]，tm∈[0,T′]and T' represents the movement period of the training running action of the training person.
Optionally, the adaptively controlling the rotation speed of the treadmill according to the real-time center of gravity position and generating the running warning information include:
and carrying out self-adaptive control on the rotating speed of the treadmill by using an information feedback mechanism according to the relation between the real-time gravity center position and the safe region of the treadmill and generating running early warning information.
Optionally, the performing the comprehensive evaluation of the training effect of the trainee includes:
and comprehensively evaluating the training effect of the trainees by utilizing the development trend of the running training effect and combining the big movement data of the group trainees.
Optionally, after analyzing the posture information of the trainee, the method further includes:
and according to the evaluation of the training effect, combining the group running training big data, and recommending a new more suitable training scheme to the training personnel.
Optionally, the intelligent algorithm module may be deployed in a local control system and a data display end in the client or the cloud service platform.
In the embodiment of the invention, feedback display can be realized in real time according to running of a trainer on the treadmill system, so that the tempo of the trainer is more reasonable during running, the running posture is more standard, the training process is safer, and a better training and body-building effect is achieved; safety early warning in the running process can be carried out in real time, and the safety of the running machine in use is improved; training courses and methods suitable for training personnel can be recommended, and the training effect is further improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic structural component diagram of an intelligent treadmill system in an embodiment of the present invention;
FIG. 2 is a schematic diagram of the structure of an intelligent treadmill system according to another embodiment of the invention;
FIG. 3 is a waveform of a training person running pose sequence compared to a labeled running pose sequence in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
Referring to fig. 1, fig. 1 is a schematic structural component diagram of an intelligent treadmill system according to an embodiment of the present invention.
As shown in fig. 1, an intelligent treadmill system includes at least one running client 11, an intelligent algorithm module 13, and a cloud service platform 12; the running client 11 is used for acquiring running training image data of a training person in a specified running area on the running machine, and synchronizing the acquired running training image data into the cloud service platform 12 in real time; the cloud service platform 12 is configured to detect posture information of a trainer in running training image data after receiving the running training image data synchronized in real time, and start the intelligent algorithm module 13 to analyze the posture information of the trainer based on the posture information of the trainer in the running training image data; the intelligent algorithm module 13 is configured to analyze the posture information of the trainee, and push an analysis result to the running client 11 for displaying to the trainee.
Specifically, an image acquisition terminal in the treadmill client 11 acquires running training image data of a trainer in real time, transmits the running training image data to a local control system and a data display terminal, and synchronizes the running training image data to the cloud service platform 12; then, the intelligent algorithm module 13 is started to perform analysis processing respectively, and the analysis processing result is fed back to the local control system and the data display terminal in the treadmill client 11 for display.
The intelligent algorithm module 13 is started to respectively analyze and process the data, wherein the intelligent algorithm module 13 is started to respectively analyze and process the data, and the method comprises the steps of (1) calculating the stride and the frequency of the lower limbs of the trainee, the swinging amplitude and the swinging frequency of the double arms of the trainee, comparing the stride and the frequency with the beat requirement of the running action marked in a standard running course, evaluating the difference between the stride and the frequency, and providing correction guidance of the action beat for the trainee through; (2) calculating the change of included angles among joints of the trunk, the legs, the arms and the head of a human body in the running process of a trainer, comparing and analyzing the change with the standard running action, evaluating the standard property and the action coordination of the running posture, and providing action guidance for the trainer through information feedback; (3) by estimating the body type of a trainer, recording motion data and posture action data in the running process, establishing an individual training database based on a time axis, analyzing and evaluating the training effect of the trainer through an algorithm, and mining a training scheme more suitable for the trainer to use by combining with the motion big data of group trainers, so as to provide intelligent suggestion guidance for the trainer; (4) the method comprises the steps of calculating the position of a trainer on the treadmill, analyzing the body balance, judging the relation between the position of the feet of the lower limbs and a safe region of the treadmill in real time, detecting the body unbalance state caused by abnormal body posture, predicting the dangerous condition through feedback control, controlling the speed of the treadmill to be reduced by a treadmill system when the safe risk of falling down exists, recovering normal harness after dangerous information is removed, realizing the self-adaptive control of the rotating speed of the treadmill, simultaneously giving an early warning to the trainer, avoiding the falling down phenomenon and improving the safety of the treadmill.
In the embodiment of the invention, feedback display can be realized in real time according to running of a trainer on the treadmill system, so that the tempo of the trainer is more reasonable during running, the running posture is more standard, the training process is safer, and a better training and body-building effect is achieved; safety early warning in the running process can be carried out in real time, and the safety of the running machine in use is improved; training courses and methods suitable for training personnel can be recommended, and the training effect is further improved.
Examples
Referring to fig. 2, fig. 2 is a schematic structural diagram of an intelligent treadmill system according to another embodiment of the invention.
As shown in fig. 2, an intelligent treadmill system includes at least one running client 11, an intelligent algorithm module 13, and a cloud service platform 12; the running client 11 is used for acquiring running training image data of a training person in a specified running area on the running machine, and synchronizing the acquired running training image data into the cloud service platform 12 in real time; the cloud service platform 12 is configured to detect posture information of a trainer in running training image data after receiving the running training image data synchronized in real time, and start the intelligent algorithm module 13 to analyze the posture information of the trainer based on the posture information of the trainer in the running training image data; the intelligent algorithm module 13 is configured to analyze the posture information of the trainee, and push an analysis result to the running client 11 for displaying to the trainee; the running client 11 comprises an image acquisition terminal, a running machine, a local control system and a data display terminal; the treadmill is provided with a running area for training a person to run in the running area, and when the person runs in the running area, the image acquisition terminal is triggered to acquire running training image data in real time; the image acquisition terminal is used for acquiring running training image data of a training person in a running area corresponding to the running machine and transmitting the running training image data to the local control system and the data display end in real time; the local control system and the data display end are used for synchronizing the number of the running training images into a cloud service platform in real time and displaying an analysis result pushed by the intelligent algorithm; in addition, the intelligent algorithm module 13 is internally provided with a group database, a data analysis algorithm, an individual database, a training guidance scheme, and the like.
In a specific implementation process of the present invention, the analyzing the posture information of the trainee includes: calculating the lower limb stride and frequency and the amplitude and frequency of double-arm swinging in the posture information of the training personnel, and comparing the calculation result with the beat requirement of a standard running course to obtain the contrast difference; and/or calculating the self included angle change of each joint of the trunk, the legs, the arms and the head of the human body in the posture information of the training personnel during the running process, comparing and analyzing the calculation result of the included angle change with the standard running action, and judging the posture accuracy of the training personnel during the running process; and/or estimating the body balance of the training personnel by utilizing the posture information of the training personnel, calculating the real-time gravity center position of the training personnel, and carrying out self-adaptive control on the rotating speed of the treadmill according to the real-time gravity center position and generating running potential safety hazard early warning information; and/or analyzing data in the training personnel individual movement database, judging the development trend of the running training effect of the training personnel accumulated along with movement time, and comprehensively evaluating the training effect of the training personnel.
Further, the comparison formula for comparing the calculation result with the tempo requirement of the standard running course is as follows:
Figure BDA0002418094750000071
where n denotes the number of statistical wobble periods, siRepresenting the swing distance recorded for the ith swing cycle, s 'representing the distance of the standard running course swing, f' representing the frequency of the standard running course swing, t representing a preset time period, β1Representing the degree of difference from the standard running course stride β2Indicating the degree of difference from the standard running course swing frequency.
Further, calculate the contained angle change of human trunk, shank, both arms, each joint of head oneself in the process of running among training personnel's the gesture information to carry out contrastive analysis with contained angle change calculation result and standard running action, include: decomposing the running actions in the posture information of the trainees along a time axis to form a trainee running action sequence, calculating training included angles among human joints of the running actions of the trainees in the trainee running action sequence, and forming running action digital posture data of the trainees according to the time variation of the training included angles; decomposing the standard running actions along a time axis to form a standard action posture sequence, calculating a standard included angle between human body joints of each standard running action in the standard action posture sequence, and forming standard running action digital posture data according to the standard included angle along time variation; establishing a running action comparison analysis model based on the running action digital posture data of the training personnel and the standard running action digital posture data; and carrying out comparative analysis based on the running motion comparative analysis model.
Further, the running motion contrastive analysis model has the following model formula:
Figure BDA0002418094750000081
wherein the content of the first and second substances,
Figure BDA0002418094750000082
representing the motion similarity of human joints n, delta T representing the difference between T and T', delta representing the overall similarity of human postures αnRepresenting the weight value of the human joint n in the process of evaluating the overall similarity delta of the posture, αnDetermined by a standard running course;
Figure BDA0002418094750000083
representing a standard included angle between human joints n;
Figure BDA0002418094750000084
representing a set formed by standard angles between human joints n; l represents the standard running motion digital posture data, namely
Figure BDA0002418094750000085
The curve of the variation with time t,
Figure BDA0002418094750000086
Figure BDA0002418094750000087
n∈[1,N]，tm∈[0,T]n represents the number of human body joint points; t represents the movement cycle of the standard running motion;
Figure BDA0002418094750000088
representing the training included angle between human joints n,
Figure BDA0002418094750000089
representing a set formed by training angles between human joints n; l represents the running motion digital attitude data of the trainee, i.e.
Figure BDA00024180947500000812
The curve of the variation with time t,
Figure BDA00024180947500000810
Figure BDA00024180947500000811
n∈[1,N]，tm∈[0,T′]and T' represents the movement period of the training running action of the training person.
Further, the self-adaptive control and the running early warning information generation of the treadmill speed according to the real-time center of gravity position comprise: and carrying out self-adaptive control on the rotating speed of the treadmill by using an information feedback mechanism according to the relation between the real-time gravity center position and the safe region of the treadmill and generating running early warning information.
Further, the performing of comprehensive evaluation of the training effect of the trainee includes: and comprehensively evaluating the training effect of the trainees by utilizing the development trend of the running training effect and combining the big movement data of the group trainees.
Further, after the analyzing the posture information of the trainee, the method further includes: and according to the evaluation of the training effect, combining the group running training big data, and recommending a new more suitable training scheme to the training personnel.
Further, the intelligent algorithm module may be deployed in a local control system and a data display end in the client or the cloud service platform.
Specifically, the stride and the frequency of the lower limbs of the trainee and the swinging amplitude and the frequency of the two arms are calculated, the comparison with a standard running course is carried out, the difference between the stride and the frequency of the lower limbs of the trainee and the swinging amplitude and the frequency of the two arms is calculated, a leg node a is taken as an example, the swinging distance s from a point b to a point c of the node a in the running process and the swinging frequency in time t are counted, and the difference with the standard running course is calculated through the following formula; the existing comparison formula for comparing the calculation result with the tempo requirement of the standard running course is as follows:
Figure BDA0002418094750000091
where n denotes the number of statistical wobble periods, siRepresenting the swing distance recorded for the ith swing cycle, s 'representing the distance of the standard running course swing, f' representing the frequency of the standard running course swing, t representing a preset time period, β1Representing the degree of difference from the standard running course stride β2Indicating the degree of difference from the standard running course swing frequency.
As shown in the question 3, the posture accuracy of the training personnel in the running process is judged by comparing the standard running action; decomposing standard running motion along time axis to form key motion posture sequence, and calculating included angle between human joints in each motion posture
Figure BDA0002418094750000092
Figure BDA0002418094750000093
The set formed by the standard angles between the human joints n,
Figure BDA0002418094750000094
n represents the number of human body nodes; the time parameters are fused to form standard running action digital attitude data L, namely
Figure BDA0002418094750000095
The curve of the variation with time t,
Figure BDA0002418094750000096
Figure BDA0002418094750000097
n∈[1,N]，tm∈[0,T](ii) a T represents the movement cycle of the standard running motion; similarly, when the trainee runs, the actions are decomposed along the time axis to form the action sequence of the trainee, and the included angle between the joints of the human body is calculated when each action gesture is performed
Figure BDA0002418094750000098
Figure BDA0002418094750000099
Representing the training included angle between human joints n,
Figure BDA00024180947500000910
representing a set formed by training angles between human joints n; l represents the running motion digital attitude data of the trainee, i.e.
Figure BDA00024180947500000911
The curve of the variation with time t,
Figure BDA00024180947500000912
n∈[1,N]，tm∈[0,T′]and T' represents the movement period of the training running action of the training person.
Establishing a running action comparison analysis model according to the running action digital posture data of the training personnel and the standard running action digital posture data; the model formula of the running motion comparative analysis model is as follows:
Figure BDA0002418094750000101
wherein the content of the first and second substances,
Figure BDA0002418094750000102
representing the motion similarity of human joints n, delta T representing the difference between T and T', delta representing the overall similarity of human postures αnRepresenting the weight value of the human joint n in the process of evaluating the overall similarity delta of the posture, αnDetermined by a standard running course;
Figure BDA0002418094750000103
representing a standard included angle between human joints n;
Figure BDA0002418094750000104
representing a set formed by standard angles between human joints n; l representsThe standard running motion digital posture data is
Figure BDA0002418094750000105
The curve of the variation with time t,
Figure BDA0002418094750000106
Figure BDA0002418094750000107
n∈[1,N]，tm∈[0,T]n represents the number of human body joint points; t represents the movement cycle of the standard running motion;
Figure BDA0002418094750000108
representing the training included angle between human joints n,
Figure BDA0002418094750000109
representing a set formed by training angles between human joints n; l represents the running motion digital attitude data of the trainee, i.e.
Figure BDA00024180947500001010
The curve of the variation with time t,
Figure BDA00024180947500001011
Figure BDA00024180947500001012
n∈[1,N]，tm∈[0,T′]and T' represents the movement period of the training running action of the training person.
Through feedback of motion similarity variables
Figure BDA00024180947500001013
And delta, guiding the training personnel to perform standard correction on the local posture and adjust the overall movement posture, and enhancing the training effect.
The posture information of the training personnel is utilized to estimate the body balance degree of the training personnel, calculate the gravity center position P of the human body, calculate the relation between the P and the safe region R of the treadmill in real time, realize the self-adaptive control of the rotating speed of the treadmill through an information feedback mechanism, and simultaneously give an early warning to the training personnel, thereby avoiding the occurrence of falling down accidents on the treadmill and improving the safety of the treadmill.
The existing treadmill can not prevent falling, generally, a safety rope is triggered to stop the treadmill after falling, the treadmill is a safety mechanism started after falling, fundamental safety protection is not achieved, and if falling occurs, the damage to people is great; the safety rope needs to be tied on the body during running, has certain constraint and is inconvenient; in the embodiment of the invention, the relationship among the body balance of a human body, a running safety region and a running position is synchronously judged in the running process, the occurrence of danger is pre-judged, and the rotating speed of the running machine is controlled in real time so that the rotating speed is more suitable for training personnel, the falling risk is reduced, meanwhile, the early warning of danger hidden danger is formed, the running personnel is prompted, and accidents such as falling are avoided; the user running experience will be better without adding any additional contact and binding.
Analyzing data in an individual exercise database of the trainees, judging the development trend of the training effect of the trainees accumulated along with exercise time, comprehensively evaluating the training effect of the trainees by combining big exercise data of group trainees, recommending a training course and a method suitable for the trainees, and further improving the training effect.
The intelligent algorithm module can be deployed between the local control system and the data display end or the cloud service platform, and data synchronization can be achieved between the local control system and the data display end or the cloud service platform.
In the embodiment of the invention, feedback display can be realized in real time according to running of a trainer on the treadmill system, so that the tempo of the trainer is more reasonable during running, the running posture is more standard, the training process is safer, and a better training and body-building effect is achieved; safety early warning in the running process can be carried out in real time, and the safety of the running machine in use is improved; training courses and methods suitable for training personnel can be recommended, and the training effect is further improved.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable storage medium, and the storage medium may include: a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic or optical disk, or the like.
In addition, the above detailed description is provided for an intelligent treadmill system provided in the embodiments of the present invention, and a specific example should be adopted herein to explain the principle and the implementation manner of the present invention, and the above description of the embodiments is only used to help understanding the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims (10)

1. An intelligent treadmill system is characterized by comprising at least one running client, an intelligent algorithm module and a cloud service platform; wherein the content of the first and second substances,
the running client is used for acquiring running training image data of a training person on a specified running area on the running machine and synchronizing the acquired running training image data into the cloud service platform in real time;
the cloud service platform is used for detecting the posture information of the training personnel in the running training image data after receiving the running training image data synchronized in real time, and starting the intelligent algorithm module to analyze the posture information of the training personnel based on the posture information of the training personnel in the running training image data;
the intelligent algorithm module is used for analyzing the posture information of the training personnel and pushing the analysis result to the running client for displaying to the training personnel.
2. The intelligent treadmill system of claim 1, wherein the running client comprises an image acquisition terminal, a treadmill and a local control system and data display terminal; wherein the content of the first and second substances,
the treadmill is provided with a running area for training a person to run in the running area, and when the person performs running training in the running area, the image acquisition terminal is triggered to acquire running training image data in real time;
the image acquisition terminal is used for acquiring running training image data of a training person in a running area corresponding to the running machine and transmitting the running training image data to the local control system and the data display end in real time;
the local control system and the data display end are used for synchronizing the number of the running training images to a cloud service platform in real time and displaying an analysis result pushed by the intelligent algorithm.
3. The intelligent treadmill system of claim 1, wherein the analyzing the posture information of the trainee comprises:
calculating the lower limb stride and frequency and the amplitude and frequency of double-arm swinging in the posture information of the training personnel, and comparing the calculation result with the beat requirement of a standard running course to obtain the contrast difference; and/or the presence of a gas in the gas,
calculating the self included angle change of each joint of the trunk, the legs, the two arms and the head of the human body in the posture information of the training personnel during the running process, comparing and analyzing the calculation result of the included angle change with the standard running action, and judging the posture accuracy of the training personnel during the running process; and/or the presence of a gas in the gas,
estimating the body balance of the training personnel by utilizing the posture information of the training personnel, calculating the real-time gravity center position of the training personnel, carrying out self-adaptive control on the rotating speed of the treadmill according to the real-time gravity center position and generating running potential safety hazard early warning information; and/or the presence of a gas in the gas,
analyzing data in the training personnel individual movement database, judging the running training effect development trend of the training personnel accumulated along with movement time, and comprehensively evaluating the training effect of the training personnel.
4. The intelligent treadmill system of claim 3, wherein the comparison formula comparing the calculated results to the tempo requirements of a standard running course is as follows:
Figure FDA0002418094740000021
where n denotes the number of statistical wobble periods, siRepresenting the swing distance recorded for the ith swing cycle, s 'representing the distance of the standard running course swing, f' representing the frequency of the standard running course swing, t representing a preset time period, β1Representing the degree of difference from the standard running course stride β2Indicating the degree of difference from the standard running course swing frequency.
5. The intelligent treadmill system of claim 3, wherein the calculation of the individual angle changes of the body trunk, legs, arms, and head joints during the running process in the posture information of the trainee, and the comparison analysis of the angle change calculation result with the standard running action comprises:
decomposing the running actions in the posture information of the trainees along a time axis to form a trainee running action sequence, calculating training included angles among human body joints of the running actions of the trainees in the trainee running action sequence, and forming running action digital posture data of the trainees according to the time variation of the training included angles;
decomposing the standard running actions along a time axis to form a standard action posture sequence, calculating a standard included angle between human body joints of each standard running action in the standard action posture sequence, and forming standard running action digital posture data according to the standard included angle along time variation;
establishing a running action comparison analysis model based on the running action digital posture data of the training personnel and the standard running action digital posture data;
and carrying out comparative analysis based on the running motion comparative analysis model.
6. The intelligent treadmill system of claim 5, wherein the running motion contrastive analysis model has a model formula as follows:
Figure FDA0002418094740000031
wherein the content of the first and second substances,
Figure FDA0002418094740000032
representing the motion similarity of human joints n, delta T representing the difference between T and T', delta representing the overall similarity of human postures αnRepresenting the weight value of the human joint n in the process of evaluating the overall similarity delta of the posture, αnDetermined by a standard running course;
Figure FDA0002418094740000033
representing a standard included angle between human joints n;
Figure FDA0002418094740000034
representing a set formed by standard angles between human joints n; l represents the standard running motion digital posture data, namely
Figure FDA0002418094740000035
The curve of the variation with time t,
Figure FDA0002418094740000036
Figure FDA0002418094740000037
n∈[1,N]，tm∈[0,T]n represents the number of human body joint points; t represents the movement cycle of the standard running motion;
Figure FDA0002418094740000038
representing the training included angle between human joints n,
Figure FDA0002418094740000039
representing a set formed by training angles between human joints n; l represents the running motion digital attitude data of the trainee, i.e.
Figure FDA00024180947400000310
The curve of the variation with time t,
Figure FDA00024180947400000311
Figure FDA00024180947400000312
n∈[1,N]，tm∈[0,T′]and T' represents the movement period of the training running action of the training person.
7. The intelligent treadmill system of claim 3, wherein adaptively controlling treadmill speed and generating running pre-warning information based on the real-time center of gravity position comprises:
and carrying out self-adaptive control on the rotating speed of the treadmill by using an information feedback mechanism according to the relation between the real-time gravity center position and the safe region of the treadmill and generating running early warning information.
8. The intelligent treadmill system of claim 3, wherein the performing a comprehensive assessment of the exercise performance of the exercise person comprises:
and comprehensively evaluating the training effect of the trainees by utilizing the development trend of the running training effect and combining the big movement data of the group trainees.
9. The intelligent treadmill system of claim 3, further comprising, after analyzing the posture information of the trainee:
and according to the evaluation of the training effect, combining the group running training big data, and recommending a new more suitable training scheme to the training personnel.
10. The intelligent treadmill system of claim 2, wherein the intelligent algorithm module is deployable on a local control system and a data display in the client or the cloud service platform.
CN202010197331.4A 2020-03-19 2020-03-19 Intelligent treadmill system Pending CN111265817A (en)

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