Patent Publication Number: US-2023137560-A1

Title: Assistance system and method for guiding exercise postures in live broadcast

Description:
CROSS-REFERENCE TO RELATED APPLICATION(S) 
     This application claims the priority benefit of TW application serial No. 110141067 filed on Nov. 4, 2021, the entirety of which is hereby incorporated by reference herein and made a part of the specification. 
     BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention relates to an assistance system and a method for 
     guiding exercise postures, more particularly an assistance system and a method for guiding exercise postures in a live broadcast. 
     2. Description of the Related Art 
     A live broadcast system may be used for multiple purposes. Namely the live broadcast system may be used for remote learnings, business web conferences, or even guidance of exercises. The live broadcast system usually includes a server and multiple electronic devices connected to the server. These electronic devices include an instructor electronic device and multiple student electronic devices. The instructor electronic device is used by an instructor, and the student electronic devices are used by students. Both the instructor electronic device and the student electronic devices should include displaying functions as well as internal or external cameras. 
     This way, the student electronic devices may shoot student videos and send the student videos to the instructor electronic device. The instructor device receives the student videos and is able to display the student videos of the multiple student electronic devices simultaneously. With reference to  FIG.  11   ,  FIG.  11    depicts a perspective view of a display of the instructor electronic device  50 . The display includes arrays of the multiple student videos  51 . Through the display, the instructor is able to observe how each of the students is exercising through the multiple student videos  51 . 
     However, since the instructor electronic device  50  attempts to display the multiple student videos  51 , the display of the instructor electronic device  50  is often equally divided by an amount of the multiple student videos  51 . Limited by a size of the display of the instructor electronic device  50 , and especially for cases when the instructor electronic device  50  is a smart phone or a tablet computer, a window size of each of the student videos  51  in the display of the instructor electronic device  50  is greatly reduced. As such, the instructor struggles to clearly observe how each of the students is exercising, and thus the instructor also struggles to offer feedback instructions to the students accordingly. As a result, the students may have a poor live exercising experience without proper feedback instructions from the instructor. 
     SUMMARY OF THE INVENTION 
     An objective of the present invention is to provide an assistance system and an assistance method for guiding exercise postures in a live broadcast to overcome the aforementioned problem, wherein in the prior art, limited by a size of the display of an instructor electronic device, a window size of a student video in the display is greatly reduced, and as such an instructor fails to clearly see and guide exercise postures of students through the small student video in the display. The assistance system for guiding exercise postures in a live broadcast of the present invention includes: 
     a cloud server, storing a teaching video and multiple templates corresponding to different time segments in the teaching video; wherein each one of the templates has multiple preset skeleton checking points and multiple movement threshold values respectively corresponding to the multiple preset skeleton checking points; 
     at least one first electronic device, connecting the cloud server to download and to play the teaching video; wherein each of the at least one first electronic device includes: 
     a camera; wherein when the teaching video is being played in a live broadcast, the camera films a first user for generating a first user video; 
     a skeleton detecting model, generating a skeleton streaming data of the first user according to the first user video; and 
     a skeleton posture differentiating module; wherein in each of the time segments in the teaching video of the live broadcast, the skeleton posture differentiating module analyzes the skeleton streaming data of the first user according to the preset skeleton checking points and the movement threshold values for obtaining multiple action values of the first user at the preset skeleton checking points, and the skeleton posture differentiating module determines whether an abnormality occurs according to the action values and the movement threshold values; when the skeleton posture differentiating module determines the skeleton streaming data is abnormal, the first electronic device outputs an abnormality notification; and 
     a second electronic device, connected to the cloud server and the at least one first electronic device, and having an error auto-notifying interface; wherein when the second electronic device receives the abnormality notification in the live broadcast, the second electronic device displays the abnormality notification and a message corresponding to the abnormality notification through the error auto-notifying interface. 
     The assistance method for guiding exercise postures in a live broadcast of the present invention is used by a cloud server, at least one first electronic device, and a second electronic device. The assistance method for guiding exercise postures in a live broadcast includes: 
     step(a): storing a teaching video and multiple templates in the cloud server; wherein the multiple templates correspond to different time segments in the teaching video; and wherein each one of the templates has multiple preset skeleton checking points and multiple movement threshold values respectively corresponding to the multiple preset skeleton checking points; 
     step(b): downloading and playing the teaching video from the cloud server to the at least one first electronic device in a live broadcast, generating a skeleton streaming data of a first user according to a first user video, analyzing the skeleton streaming data of the first user in each of the time segments according to the preset skeleton checking points and the movement threshold values for obtaining multiple action values of the first user at the preset skeleton checking points, and determining whether an abnormality occurs according to the action values and the movement threshold values; 
     step(c): when the at least one first electronic device determines the skeleton streaming data is abnormal, outputting an abnormality notification from the at least one first electronic device to the second electronic device; and 
     step(d): when the second electronic device receives the abnormality notification in the live broadcast, displaying the abnormality notification and a message corresponding to the abnormality notification through an error auto-notifying interface of the second electronic device. 
     The assistance system and method for guiding exercise postures in a live broadcast of the present invention is suitable for online exercise classes. The present invention is particularly applicable for exercises involving proper postures, such as aerobic dancing, aerobics, boxing, and yoga. As an example, each of the at least one first electronic device is used by a student, and the second electronic device is used by an instructor. Through the present invention, the instructor will be able to teach the student in a private online class or a group online class. The present invention is able to determine whether a posture of the student is abnormal. The error auto-notifying interface of the second electronic device is special, because when the present invention determines the posture of the student to be abnormal, the error auto-notifying interface automatically displays the abnormality notification and the message corresponding to the abnormality notification. The instructor would immediately be notified by the abnormality notification and the message through the error auto-notifying interface, and the instructor would instantly recognize the abnormal posture of the student and react accordingly to the student. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a block diagram of an embodiment of an assistance system for guiding exercise postures in a live broadcast of the present invention. 
         FIG.  2    is a perspective view of a class information file of the present invention. 
         FIG.  3    is a perspective view of a teaching video and multiple corresponding time segments of the teaching video of the present invention. 
         FIG.  4    is a perspective view of multiple preset skeleton checking points of the present invention. 
         FIG.  5    is a perspective view of continuous body motions within a time segment of the present invention. 
         FIG.  6    is a perspective view of an error auto-notifying interface of a second electronic device of the present invention simultaneously showing multiple first user videos and the skeleton streaming data. 
         FIG.  7    is a perspective view of the error auto-notifying interface of the second electronic device of the present invention displaying a message corresponding to an abnormality notification and an abnormality tag on an image. 
         FIG.  8    is a block diagram of a cloud server and the second electronic device of the present invention. 
         FIG.  9    is a flow chart of an embodiment of an assistance method for guiding exercise postures in a live broadcast of the present invention. 
         FIG.  10    is a flow chart of further sub-steps of step S 01  shown in  FIG.  9   . 
         FIG.  11    is a perspective view of a display of a conventional instructor electronic device. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     With reference to  FIG.  1 A , an embodiment of an assistance system for guiding exercise postures in a live broadcast of the present invention includes a cloud server  10 , at least one first electronic device  20 , and a second electronic device  30 . The at least one first electronic device  20  and the second electronic device  30  are connected to the cloud server  10  through internet connection for data transmission. 
     The cloud server  10  is able to store data and stream live videos. The cloud server  10  includes a computer-readable medium  11  for storing at least one class information file  110 . The computer-readable medium  11  may be a hard disk drive (HDD) or a solid-state drive (SSD). In another embodiment, the computer-readable medium  11  is free to be elsewise. Each of the at least one class information file  110  corresponds to an editable file of a live streaming event. 
     With reference to  FIGS.  2  and  3   , in the present embodiment, each of the at least one class information file  110  includes a teaching video  111  and multiple templates  112 . The teaching video  111  consists of multiple video segments with time segments TS. Each of the time segments TS has a starting time t 1  and an ending time t 2 . Each of the time segments TS also corresponds to a set of continuous body motions, such as raising of a hand, raising of a leg, bending over, etc. In other words, when the cloud server  10  streams the teaching video  111 , each set of continuous body motions also is also being accordingly played. The templates  112  correspond to the different time segments TS in the teaching video  111 . The templates  112  represent a standard reference information for the sets of continuous body motions. Each one of the templates  112  includes multiple preset skeleton checking points P and multiple movement threshold values TH 1  respectively corresponding to the multiple preset skeleton checking points P. Furthermore, each one of the templates  112  also includes multiple abnormal movement checking points and multiple abnormal movement reference conditions TH 2  respectively corresponding to the multiple abnormal movement checking points. The abnormal movement checking points may include the preset skeleton checking points P as well as other checking points on the present skeleton. The abnormal movement reference conditions TH 2  may be: 
     having one of the abnormal movement checking points greater than a value at a given time; 
     having one of the abnormal movement checking points lesser than a value at a given time; or 
     having one of the abnormal movement checking points between two values at a given time. 
     The abnormal movement reference conditions TH 2  will be explained more in later parts. 
     With reference to  FIG.  4   , the preset skeleton checking points P for example include parts of a human skeletal figure such as a nose P 1 , shoulders P 2 , elbows P 3 , wrists P 4 , hips P 5 , knees P 6 , ankles P 7 , shoulder angles Al, elbow angles A 2 , knee angles A 3 , or any relative distance, horizontal distance, or vertical distance of any two of the preset skeleton checking points P. The preset skeleton checking points P are free to be elsewise in other embodiments. The movement threshold values TH 1  are default values for movements. The movement threshold values TH 1  are references used to determine whether postures or movement changes are within acceptable ranges. The abnormal movement reference conditions TH 2  are also default data for movements. The abnormal movement reference conditions TH 2  are references used to determine whether postures or movement changes are abnormal. 
     With reference to  FIG.  5   , for example, within the time segment TS, the set of continuous body motions is raising hand while sitting. The preset skeleton checking points P include the wrists P 4  and the elbow angles A 2 . Each of the wrists P 4  corresponds to a first movement threshold value (TH 1 - 1 ). The first movement threshold value (TH 1 - 1 ) is a default distance for vertical movements of each of the wrists P 4  from the starting time t 1  to the ending time t 2 . Such vertical movements can also be described as movements along a Y axis presented in  FIG.  5   . Each of the elbow angles A 2  corresponds to a second movement threshold value (TH 1 - 2 ). The second movement threshold value (TH 1 - 2 ) is a default angle for angular movements of each of the elbow angles A 2  from the starting time t 1  to the ending time t 2 . The abnormal movement checking points include vertical distances between the elbows P 3  and the shoulders P 2 , wherein such vertical distances are height differences along the Y axis presented in  FIG.  5   . In this case, one of the abnormal movement reference conditions TH 2  corresponding to the abnormal movement checking points is having vertical distances between the elbows P 3  and the shoulders P 2  to be less than a given value at the starting time t 1 . 
     The at least one first electronic device  20  is used by at least one first user, or in other words, used by at least one student. The first electronic device  20  may be a smart phone, a tablet computer, a personal computer, a laptop, or an internet connectable television. The first electronic device  20  may be elsewise in other embodiments. The first electronic device  20  is connected to the cloud server  10  for data transmission. For example, the first electronic device  20  downloads the class information file  110  from the cloud server  10  and plays the teaching video  111 . The first electronic device  20  includes a camera  21 , a skeleton detecting model  22 , and a skeleton posture differentiating module  23 . The camera  21  may be an internal camera embedded in the first electronic device  20 , or an external camera. When playing the teaching video  111  in a live broadcast, the camera  21  captures the first user and accordingly generates a first user video  210 . Programs of the skeleton detecting model  22  and the skeleton posture differentiating module  23  are stored in a memory or a memory card of the first electronic device  20 . Programs of the skeleton detecting model  22  and the skeleton posture differentiating module  23  are executed by a central processing unit (CPU) or a graphics processing unit (GPU) of the first electronic device  20 . 
     The skeleton detecting model  22  is connected to the camera  21 , and the skeleton detecting model  22  generates a skeleton streaming data  211  of the first user according to the first user video  210 . In the present embodiment, the first user video  210  is two dimensional ( 2 D) for the first electronic device  20 . The skeleton detecting model  22  uses a skeleton detection to detect positional coordinates of a nose, shoulders, elbows, wrists, hips, knees, and ankles in the first user video  210 , as well as to detect shoulder angles, elbow angles, and knee angles in the first user video  210  to accordingly generate the skeleton streaming data  211 . In other words, the skeleton streaming data  211  includes positional coordinates of a nose, shoulders, elbows, wrists, hips, knees, and ankles, as well as shoulder angles, elbow angles, and knee angles in the first user video  210 . The skeleton detection technique used by the skeleton detecting model  22  is well known in the related art. The skeleton detecting model  22  may also use other existing techniques to detect the aforementioned parts in the first user video  210 . The detection technique used for detecting the aforementioned parts in the first user video  210  is beside the point of the present invention, and therefore further discussion about detection techniques will be omitted. 
     The skeleton posture differentiating module  23  is connected to the skeleton detecting model  22 . In each of the time segments TS of the teaching video  111  of the live broadcast, the skeleton posture differentiating module  23  analyzes the skeleton streaming data  211  of the first user according to the preset skeleton checking points P and the movement threshold values TH 1  for obtaining multiple action values of the first user at the preset skeleton checking points P. For the same example as previously mentioned, the preset skeleton checking points P of the corresponding time segment TS include positional coordinates of the elbows P 3  and elbow angles A 2 . The skeleton posture differentiating module  23  obtains the positional coordinates of the elbows P 3  and the elbow angles A 2  in the skeleton streaming data  211  of the first user. The skeleton posture differentiating module  23  then determines a first action value as vertical positional changes of the positional coordinates of the elbows P 3  in the skeleton streaming data  211  from the starting time t 1  to the ending time t 2  in the time segment TS. The skeleton posture differentiating module  23  also determines a second action value as angle changes of the elbow angles A 2  in the skeleton streaming data  211  from the starting time t 1  to the ending time t 2  in the time segment TS. 
     With the first and second action values, the skeleton posture differentiating module  23  determines whether an abnormality occurs according to these action values and the movement threshold values TH 1 . Said abnormality may be a condition that a posture of the first user is abnormal. When the skeleton posture differentiating module  23  determines the abnormality, the first electronic device  20  outputs an abnormality notification N. The data format of the abnormality notification N can be a text or an image. The abnormality notification N notifies the student that the posture of the student is incorrect, for instance, with a text display of “wrist position too low”. Furthermore, when the skeleton posture differentiating module  23  determines the first action value is below the first movement threshold value (TH 1 - 1 ) or determines the second action value is below the second movement threshold value (TH 1 - 2 ), the first electronic device  20  outputs the abnormality notification N. 
     In other embodiments, the skeleton posture differentiating module  23  analyzes the skeleton streaming data  211  of the first user for obtaining multiple values of the first user at the abnormal movement checking points. The skeleton posture differentiating module  23  further determines whether the obtained values match the abnormal movement reference conditions TH 2 . When determining the obtained values match the abnormal movement reference conditions TH 2 , the first electronic device  20  also outputs the abnormality notification N. Continuing from the previous example, one of the abnormal movement reference conditions, such as a first abnormal movement reference condition (TH 2 - 1 ), is that the vertical distances between the elbows P 3  and the shoulders P 2  should be less than a first abnormal posture value at the starting time t 1 , and another one of the abnormal movement reference conditions, or such as a second abnormal movement reference condition (TH 2 - 2 ), is that the elbow angles A 2  should be less than a second abnormal posture value at the ending time t 2 . In other words, the skeleton posture differentiating module  23  not only determines whether the skeleton streaming data  211  of the first user is abnormal at the preset skeleton checking points P, but also determines whether the skeleton streaming data  211  matches the abnormal movement reference conditions TH 2  at the abnormal movement checking points. When determining the skeleton streaming data  211  matches the abnormal movement reference conditions TH 2  at the abnormal movement checking points, the first electronic device  20  also outputs the abnormality notification N. 
     The second electronic device  30  is used by a second user, or in other words, an instructor. The second electronic device  30  may be a smart phone, a tablet computer, a personal computer, a laptop, or an internet connectable television. The second electronic device  30  may be elsewise in other embodiments. The second electronic device  30  is connected to the cloud server  10  and the at least one first electronic device  20  for data transmission. The second electronic device  30  includes an error auto-notifying interface  31 . The error auto-notifying interface  31  displays the first user video  210  outputted by the first electronic device  20 . Due to privacy reasons, some of the students might individually refrain from sharing the first user video  210  to the instructor. In this case, the second electronic device  30  can still receive the skeleton streaming data  211  of the first user from the first electronic device  20 . 
     With reference to  FIG.  6   , the skeleton streaming data  211  of the students is displayed on the error auto-notifying interface  31  for the instructor, and therefore the instructor would be able to monitor the posture of the student with consent to the student&#39;s privacy concerns. As a result, for each of the students, the error auto-notifying interface  31  shows the first user video  210  of the student or the skeleton streaming data  211  of the student according to a privacy related choice made by the student through the first electronic device  20 . 
     When the second electronic device  30  receives the abnormality notification N from the first electronic device  20  in the live broadcast, the second electronic device  30  displays the abnormality notification N and a message corresponding to the abnormality notification N through the error auto-notifying interface  31 . The message corresponding to the abnormality notification N can be a posture instruction message M, and the data format of the posture instruction message M can be a text or an image. In the present embodiment, the posture instruction message M is used to correct the posture of the student. The posture instruction message M, for instance, can be a text display of “raise the wrist a bit higher, same height with your shoulders”. Furthermore, when the first electronic device  20  outputs the abnormality notification N, a display  24  of the first electronic device  20  also displays the abnormality notification N as well as the corresponding posture instruction message M. This way the student can also be automatically notified about an abnormality of the posture. 
     When the instructor and the student are having a one-on-one private online class, the at least one first electronic device  20  is just a single electronic device. When the instructor and the students are having a one-on-many group online class, the at least one first electronic device  20  is multiple electronic devices, as in the previously mentioned examples. 
     With reference to  FIG.  7   , the error auto-notifying interface  31  of the second electronic device  30  displays an image  310  corresponding to one of the first electronic devices  20 . When the second electronic device  30  receives the abnormality notification N from any one of the first electronic devices  20 , the error auto-notifying interface  31  not only displays the abnormality notification N and the corresponding posture instruction message M, but the error auto-notifying interface  31  also displays an abnormality tag  312  on the image  310  corresponding to the first electronic device  20  that has the abnormality notification N. The abnormality tag  312  is a light halo surrounding the image  310 . The abnormality tag  312  may be elsewise in other embodiments. The abnormality tag  312  aims to create a highlighting effect for the instructor to clearly identify which of the students has the abnormal posture. 
     To further improve efficiency of giving out instructions, when the second electronic device  30  receives the abnormality notification N from the first electronic device  20  in the live broadcast, the second electronic device  30  and the first electronic device  20  conduct a voice or video calling with each other. In other words, when the voice or video calling is initiated, both the second electronic device  30  and the first electronic device  20  respectively turn on microphones. Through microphones, audios of the instructor and the student are respectively detected and recorded into audio messages, and the audio messages are mutually exchanged between the first electronic device  20  and the second electronic device  30 . This way the instructor is able to give out instructions to the student. 
     With reference to  FIG.  8   , the present invention provides the second user a way to fast edit the templates  112  of each of the at least one class information file  110  in the cloud server  10 . The computer-readable medium  11  of the cloud server  10  further stores a template database  12 . The template database  12  stores multiple base templates  120 , and each of the base templates  120  includes multiple base skeleton checking points Pf and multiple base action reference values THf respectively corresponding to the multiple base skeleton checking points Pf. The base skeleton checking points Pf include positional coordinates of a nose, shoulders, elbows, wrists, hips, knees, and ankles, as well as shoulder angles, elbow angles, and knee angles corresponding to the human skeletal figure. The base skeleton checking points Pf may correspond to elsewise in other embodiments. Each of the base action reference values THf is a respective default action value. 
     The second electronic device  30  includes a second electronic device camera  32 , a second electronic device skeleton detecting model  33 , and a skeleton checking interface  34 . The second electronic device camera  32  may be an internal camera embedded in the second electronic device  30 , or an external camera. The second electronic device camera  32  captures the second user and accordingly generates a workout video  321  of the second user. The workout video  321  is then sent to the cloud server  10  as the teaching video  111 . Programs of the second electronic device skeleton detecting model  33  are stored in a memory or a memory card of the second electronic device  30 . Programs of the second electronic device skeleton detecting model  33  are also executed by a CPU or a GPU. The second electronic device skeleton detecting model  33  is electrically connected to the second electronic device camera  32 . The second electronic device skeleton detecting model  33  generates a second user skeleton streaming data  322  according to the workout video  321  of the second user. Further descriptions regarding the second user skeleton streaming data  322  are analogous to further descriptions regarding the skeleton detecting model  22  of the first electronic device  20 . Therefore, further descriptions regarding the second user skeleton streaming data  322  are hereby omitted. 
     The skeleton checking interface  34  is a graphical user interface (GUI) displayable for the second electronic device  30 . The skeleton checking interface  34  is free to be elsewise in other embodiments. The skeleton checking interface  34  displays the second user skeleton streaming data  322 . According to a first user command, the skeleton checking interface  34  sets multiple appointed skeleton checking points Pd in the different time segments TS of the second user skeleton streaming data  322 . The skeleton checking interface  34  then sends the multiple appointed skeleton checking points Pd to the cloud server  10 . The first user command is a command generated by the second user via a touch screen of the second electronic device  30 , or via a keyboard or a mouse connected to the second electronic device  30 . As such, in each of the time segments TS, when the cloud server  10  determines the appointed skeleton checking points Pd match the base skeleton checking points Pf in one of the base templates  120 , the cloud server  10  sets the base templates  120  as the templates  112  of the class information file  110 , sets the base skeleton checking points Pf as the preset skeleton checking points P of the class information file  110 , and sets the base action reference values THE as the movement threshold values TH 1  of the class information file  110 . This way the second user only needs to choose the appointed skeleton checking points Pd through the skeleton checking interface  34  for the cloud server  10  to automatically generate actual class contents for each of the templates  112  of the class information file  110 . Since the second user is saved from personally editing the preset skeleton checking points P and the movement threshold values TH 1  of the templates  112 , the present invention brings convenience to the second user for hosting the online class. 
     On the other hand, the cloud server  10  also determines whether the appointed skeleton checking points Pd received by the second electronic device  30  match the base skeleton checking points Pf of the base templates  120  in any of the given time segments TS. When a mismatch is determined, the cloud server  10  then sets the appointed skeleton checking points Pd as the base skeleton checking points Pf in a new base template, and sets the base action reference values THE in the new base template according to a second user command. This way when the instructor develops a new set of continuous body motions, the cloud server  10  will be able to correspondingly create the new base template. As a result, the class information file  110  will be rich with the new base template in one of the base templates  120  for future uses. 
     With reference to  FIG.  9   , as a conclusion to the aforementioned descriptions,  FIG.  9    depicts an embodiment of an assistance method for guiding exercise postures in a live broadcast of the present invention. The embodiment includes the following steps: 
     Step S 01 : storing a teaching video  111  and multiple templates  112  in a cloud server  10 ; wherein the multiple templates  112  correspond to different time segments TS in the teaching video  111 ; and wherein each one of the templates  112  has multiple preset skeleton checking points P and multiple movement threshold values TH 1  respectively corresponding to the multiple preset skeleton checking points P. 
     Step S 02 : downloading and playing the teaching video  111  from the cloud server  10  to at least one first electronic device  20  in a live broadcast, generating a skeleton streaming data  211  of a first user according to a first user video  210 , analyzing the skeleton streaming data  211  of the first user in each of the time segments TS according to the preset skeleton checking points P and the movement threshold values TH 1  for obtaining multiple action values of the first user at the preset skeleton checking points P, and determining whether an abnormality occurs according to the action values and the movement threshold values TH 1 . 
     Step S 03 : when the first electronic device  20  determines the skeleton streaming data  211  is abnormal, outputting an abnormality notification N from the first electronic device  20  to a second electronic device  30 ; and 
     Step S 04 : when the second electronic device  30  receives the abnormality notification N in the live broadcast, displaying the abnormality notification N and a message corresponding to the abnormality notification N through an error auto-notifying interface  31  of the second electronic device  30 . 
     In some embodiments, the cloud server  10  includes a template database  12 . The template database  12  stores multiple base templates  120 , and each of the base templates  120  includes multiple base skeleton checking points Pf and multiple base action reference values THE respectively corresponding to the multiple base skeleton checking points Pf. 
     With reference to  FIG.  10   , step S 01  includes further sub-steps: 
     Step S 011 : generating a second user skeleton streaming data  322  according to a workout video  321  of a second user, setting multiple appointed skeleton checking points Pd from the second user skeleton streaming data  322  in the different time segments TS according to a first user command, and sending the appointed skeleton checking points Pd from the second electronic device  30  to the cloud server  10 . 
     Step S 012 : in each of the time segments TS, when the cloud server  10  determines the appointed skeleton checking points Pd match the multiple base skeleton checking points Pf in one of the base templates  120 , setting the base templates  120  as the templates  112 , setting the base skeleton checking points Pf as the preset skeleton checking points P, and setting the base action reference values THf as the movement threshold values TH 1 . 
     In some embodiments, for step S 012 , and for each of the time segments TS, when determining the appointed skeleton checking points Pd mismatch the multiple base skeleton checking points Pf in the base templates  120 , the cloud server  10  sets the appointed skeleton checking points Pd as the base skeleton checking points Pf in a new base template, and sets the base action reference values THf in the new base template according to a second user command. The second user command is also a command generated by the second user via a touch screen of the second electronic device  30 , or via a keyboard or a mouse connected to the second electronic device  30 . 
     In some embodiments, each of the templates  112  includes a posture instruction message M. In step S 03 , when the first electronic device  20  outputs the abnormality notification N, display the abnormality notification N and the posture instruction message M corresponding to the abnormality notification N through a display  24  of the first electronic device  20 . 
     In some embodiments and in step S 02 , when the at least one first electronic device  20  is multiple electronic devices, images  310  of the first electronic devices  20  are displayed through the error auto-notifying interface  31  of the second electronic device  30 . In step S 04 , when the second electronic device  30  receives the abnormality notification N from any one of the first electronic devices  20 , a tag  312  on the image  310  of each of the first electronic devices  20  corresponding to the abnormality notification N is displayed through the error auto-notifying interface  31 . 
     In some embodiments, each one of the templates  112  includes multiple abnormal movement checking points and multiple abnormal movement reference conditions TH 2  respectively corresponding to the multiple abnormal movement checking points. In step S 03 , when determining the obtained values of the skeleton streaming data  211  at the abnormal movement checking points in each of the time segments TS match the abnormal movement reference conditions TH 2 , the first electronic device  20  outputs the abnormality notification N. 
     In some embodiments and in step S 04 , after receiving the skeleton streaming data  211  of the first user from the at least one first electronic device  20  to the second electronic device  30 , the second electronic device  30  displays the skeleton streaming data  211  of the first user through the error auto-notifying interface  31  of the second electronic device  30 . 
     In some embodiments and in step S 04 , when receiving the abnormal notification N in the live broadcast, the second electronic device  30  conducts a voice or video calling between the second electronic device  30  and the first electronic device  20 . 
     In conclusion, the present invention has the following advantages: 
     1. The present invention is suitable for a platform of online classes of exercise instructions and for a service application (APP). Especially, the present invention is suitable for online exercise streams, for exercises such as aerobic dancing, boxing, aerobics, yoga, etc. 
     2. When the instructor needs to have a one-to-many group class, the present invention provides the special error auto-notifying interface  31 , wherein when one of the students has an abnormal posture, situation relating to the abnormal posture will be automatically displayed through the error auto-notifying interface  31  for the instructor. Compared to the prior art, rather than having small arrays of student footages for the instructor, the present invention notifies the instructor automatically regarding the abnormal posture of the student, ensuring the instructor is able to immediately identify and address on the abnormal posture of the student. 
     3. If the instructor wants to frequently update online classes in the broadcast, the present invention provides a convenient tool, wherein once the workout video  321  is recorded by the instructor and uploaded to the cloud server  10 , the appointed skeleton checking points Pd for the class can be immediately configured through the skeleton checking interface  34 . This way in every online class, each student can know whether his/her body postures are abnormal through his/her smart phone. 
     4. When the student refuses to share the first user video  210 , the instructor will still be able to receive the potential abnormality notification N and the corresponding posture instruction message M through the second electronic device  30 . 
     The above detail only some embodiments of the present invention, rather than imposing any forms of limitations toward the present invention. Any professionals in related field of the present invention may make use of the aforementioned technical information for equivalent changes. However, without deviating away from the technical information of the present invention, all of the equivalent changes are all encompassed by what is claimed for the present invention.