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CN-120299606-B - Personalized control system and method for intelligent exercise equipment

CN120299606BCN 120299606 BCN120299606 BCN 120299606BCN-120299606-B

Abstract

The invention discloses an intelligent exercise equipment personalized control system and method, which relate to the technical field of exercise equipment control and comprise the steps of evaluating the physical sign approximation degree between other users to obtain an approximation user; the method comprises the steps of obtaining a history physical sign change record and a history exercise record of an approximate user, obtaining an initial history exercise record and target physical sign data of the user, analyzing exercise reference value of the approximate user to the user to obtain an exercise reference user, obtaining an intelligent exercise equipment, analyzing influence degree of the intelligent exercise equipment on the user exercise effect under different running states of the intelligent exercise equipment to obtain target running data, controlling the running state of the intelligent exercise equipment according to the target running data when the user exercises by using the intelligent exercise equipment, and prompting a message to the user.

Inventors

  • XU JIAN
  • ZHOU YU

Assignees

  • 泰州市鸿运体育器材有限公司

Dates

Publication Date
20260505
Application Date
20250227

Claims (10)

  1. 1. A method for personalized control of an intelligent exercise machine, the method comprising: Step S100, acquiring initial sign data of a user using an intelligent exercise device, acquiring historical initial sign data of other users using the intelligent exercise device, and evaluating the sign approximation degree between the other users and the user to obtain an approximate user; Step 200, acquiring a historical sign change record and a historical exercise record of the approximate user, acquiring an initial historical exercise record and target sign data of the user, and analyzing an exercise reference value of the approximate user to the user to obtain an exercise reference user; the exercise reference value of the approximate user to the user is analyzed, and the exercise reference user is obtained, wherein the specific analysis process is as follows: calculating the similarity degree H of the operation indexes between the approximate user and the user: , Wherein Q x is the value of the running index in the x-th historical exercise record of the approximate user, Q ́ is the average value of the running index in the first g historical exercise records of the approximate user, W x is the value of the running index in the x-th initial historical exercise record of the user, W ́ is the average value of the running index in each initial historical exercise record of the approximate user; Calculating an exercise reference score K for the approximate user for the user: , Wherein m is the total number of each motion index of the user, eta 1 、η 2 is a preset first scoring coefficient and a preset second scoring coefficient respectively, eta 1 +η 2 =1,η 1 >0,η 2 >0;F´ max is a target sign target value after normalization processing between the approximate user and the user, and H z is the similarity degree of a z-th operation index between the approximate user and the user; when the exercise reference score K is larger than a preset reference score threshold, judging that the approximate user has reference value on the exercise of the user, recording the approximate user as the exercise reference user of the user, and acquiring each exercise reference user of the user; Step 300, acquiring historical equipment operation records generated in the use process of the exercise reference user, analyzing the influence degree of the intelligent exercise equipment on the user exercise effect under different operation states, and obtaining target operation data; The intelligent exercise equipment is used for analyzing the influence degree of the intelligent exercise equipment on the user exercise effect under different running states, and the specific analysis process is as follows: acquiring a first historical equipment operation record of the exercise reference user after a characteristic time point, and recording the first historical equipment operation record as a characteristic historical equipment operation record; Acquiring the average value of each element in the operation data set of each operation index of each exercise reference user of the user in the corresponding characteristic historical equipment operation record, and recording the average value as the target value of each operation index in the intelligent exercise equipment in each unit time length after the user starts to exercise; Calculating the characteristic change rate p v =（L v -L v-1 ）/L v-1 ,L v-1 of a certain operation index in the intelligent exercise equipment in the v unit time after the user starts to exercise, wherein the target value of the certain operation index is in the v-1 unit time after the user starts to exercise, and L v is in the v unit time after the user starts to exercise; When the characteristic change rate p v is smaller than a preset change rate threshold value, replacing the value of L v by using the value of L v-1 , judging that the exercise effect of the user is optimal when each operation index in the intelligent exercise equipment is the target value, replacing the target value of each operation index in the intelligent exercise equipment in each unit time after the user starts to exercise, and collecting to obtain target operation data; and step 400, when the user exercises by using the intelligent exercise equipment, controlling the running state of the intelligent exercise equipment according to the target running data, and prompting a message to the user.
  2. 2. The personalized control method for an intelligent exercise machine according to claim 1, wherein the step S100 includes: Step S101, acquiring initial sign data of the user, wherein the initial sign data comprise values of various sign indexes of the user when the intelligent exercise equipment starts to be used; Step S102, acquiring historical initial sign data of other users using the intelligent exercise equipment, wherein the other users use the intelligent exercise equipment to exercise in a historical period, and acquiring values of various sign indexes of the other users when the intelligent exercise equipment starts to be used from the historical initial sign data; Step S103, acquiring each other user using the intelligent exercise equipment, and calculating a characteristic value a= (a △ -a ́)/sigma of the physical sign index of the user in the initial physical sign data, wherein sigma is a standard deviation of the physical sign index of each other user when the intelligent exercise equipment starts to be used, a △ is a value of the physical sign index of the user in the initial physical sign data, and a ́ is an average value of the physical sign index of each other user when the intelligent exercise equipment starts to be used; Step S104, obtaining and collecting characteristic values of all the user' S physical sign indexes in the initial physical sign data to obtain initial characteristic vector A= { a 1 、a 2 、...、a n }, wherein a 1 、a 2 、...、a n is the characteristic value of the 1 st, 2 nd and n th physical sign indexes of the user respectively; step S105, evaluating the sign approximation degree between the other users and the user, wherein the sign approximation degree between the c-th other user and the user is evaluated by the following specific steps: calculating a sign approximation r c between the c-th other user and the user: , Wherein B c is the initial feature vector of the c-th other user; And when the sign approximation value r c is larger than a preset feature approximation threshold, determining sign approximation between the c-th other user and the user, and marking the c-th other user as an approximation user of the user.
  3. 3. The personalized control method for an intelligent exercise machine according to claim 2, wherein the step S200 includes: Step S201, obtaining each approximate user of the user, recording the physical sign state of the approximate user after the exercise by using the intelligent exercise equipment, obtaining the history characteristic change record of the approximate user, and extracting the value of each physical sign index of the approximate user after the exercise from the history characteristic change record; Step S202, acquiring target sign data of the user, wherein the target sign data comprises target values of various sign indexes of the user, acquiring various historical feature change records of the approximate user, and calculating target sign target values of the approximate user in the various historical feature change records to the user, wherein the approximate user in the e-th historical feature change record is used for carrying out sign target value F e of the approximate user to the user: , Wherein n is the total number of the physical sign indexes of the user, a i,target is the target value of the i-th physical sign index of the user, d e,i is the value of each physical sign index of the user after the user is approximately exercised in the e-th historical characteristic change record; Step 203, obtaining the maximum value of the sign target value of the user by the approximate user in each history feature change record, marking the maximum value as the target sign target value between the approximate user and the user, and carrying out normalization processing on the target sign target value; step S204, acquiring a historical exercise record of the approximate user, and acquiring values of various exercise indexes of the approximate user when the approximate user exercises by using the intelligent exercise equipment from the historical exercise record; Recording the exercise process of the user using the intelligent exercise equipment in a history period, obtaining initial history exercise records of the user, obtaining the total number g of the initial history exercise records of the user, obtaining the first g history exercise records of the approximate user, and recording the time point where the g-1 th history exercise record is located as a characteristic time point; Step S205, obtaining values of various sports indexes of the user when the user exercises by using the intelligent exercise equipment from the initial historical exercise record, analyzing exercise reference values of the approximate user to the user, and obtaining various exercise reference users of the user.
  4. 4. A method of personalizing an intelligent exercise machine according to claim 3, wherein step S300 includes: Step 301, acquiring a historical equipment operation record generated in the use process of the exercise reference user, setting unit time length, acquiring an average value of all operation indexes of the intelligent exercise equipment in each unit time length from the historical equipment operation record, and collecting to obtain an operation data set of all operation indexes; step S302, analyzing the influence degree of the intelligent exercise equipment on the user exercise effect under different running states to obtain target running data.
  5. 5. The personalized control method for an intelligent exercise machine according to claim 4, wherein the step S400 includes: Step S401, acquiring target operation data of the user, adjusting each operation index of the intelligent exercise equipment based on the target operation data when the user starts to use the intelligent exercise equipment to start exercise in the current period, controlling the operation state of the intelligent exercise equipment, and sending a prompt to the user; Step S402, after the user finishes exercise by using the intelligent exercise equipment in the current period, acquiring the average value of each element in the operation data set of each operation index in a second historical equipment operation record after the characteristic time point, generating target operation data of the user in the next period in the current period, and so on, acquiring the target operation data of the user in each period after the current period, and controlling the intelligent exercise equipment when the user uses the intelligent exercise equipment to exercise.
  6. 6. An intelligent exercise machine personalized control system for performing an intelligent exercise machine personalized control method of any one of claims 1-5, wherein the system comprises a sign approximation module, an exercise reference analysis module, a goal operational data module, an operational control module; the sign approximation evaluation module is used for evaluating the sign approximation degree between the other users and the users to obtain an approximation user; The exercise reference analysis module is used for analyzing the exercise reference value of the approximate user to the user to obtain an exercise reference user; The target operation data module is used for analyzing the influence degree of the intelligent exercise equipment on the user exercise effect under different operation states to obtain target operation data; The operation control module is used for controlling the operation state of the intelligent exercise equipment according to the target operation data and prompting the user by a message.
  7. 7. The intelligent exercise machine personalized control system of claim 6, wherein the sign approximation assessment module comprises a sign approximation unit, a sign approximation assessment unit; The sign approximation unit is used for calculating sign approximations between other users and the users; The sign approximation evaluation unit is used for evaluating the sign approximation degree between each other user and the user according to the sign approximation value to obtain an approximation user.
  8. 8. The intelligent exercise machine personalized control system of claim 6, wherein the exercise reference analysis module comprises an exercise reference scoring unit, an exercise reference analysis unit; the exercise reference scoring unit is used for calculating exercise reference scores of the users by approximate users; And the exercise reference analysis unit is used for analyzing the exercise reference value of the approximate user to the user according to the exercise reference score to obtain an exercise reference user.
  9. 9. The intelligent exercise machine personalized control system of claim 6, wherein the target operational data module comprises an operational data set unit, a target operational data unit; The running data set unit is used for acquiring a historical equipment running record of an exercise reference user, acquiring the average value of all running indexes of the intelligent exercise equipment in each unit time from the historical equipment running record, and collecting the average value to obtain a running data set of all the running indexes; And the target operation data unit is used for analyzing the influence degree of the intelligent exercise equipment on the user exercise effect under different operation states according to the operation data set to obtain target operation data.
  10. 10. The intelligent exercise machine personalized control system of claim 6, wherein the operation control module comprises an operation control unit; The operation control unit is used for adjusting each operation index of the intelligent exercise equipment according to the target operation data, controlling the operation state of the intelligent exercise equipment and sending a prompt to the user.

Description

Personalized control system and method for intelligent exercise equipment Technical Field The invention relates to the technical field of exercise equipment control, in particular to an intelligent exercise equipment personalized control system and method. Background Along with the continuous development of the intellectualization of the exercise equipment, more and more people can exercise by using the intelligent exercise equipment, and the intelligent exercise equipment has the following advantages that 1, real-time monitoring is realized, heart rate and calories can be monitored in real time by using the intelligent exercise equipment, so that a user can know own physical state in real time, 2, various exercises are realized, various exercise modes and types are stored in the intelligent exercise equipment, the user can adjust according to own preference and demand, the effectiveness and freshness of the exercises are saved, and 3, the safety is high, and the risk of injury caused by improper technology or excessive exercise can be effectively reduced through the monitoring and feedback of the physical state of the user. The common intelligent exercise equipment on the market at present mainly carries out the recommendation of exercise mode to the user through monitoring the physical data such as calories of the user who consumes in the exercise process, then according to user's exercise plan, but in actual process, different user's health status is different, the same exercise intensity can also be different on different users to different user's exercise target is also different, and very few intelligent exercise equipment now can be to equipment and user themselves, the exercise strategy of individuation is made to exercise equipment control, not only can make user's exercise effect decline, even still can lead to the user to be injured in the exercise process. Disclosure of Invention The invention aims to provide an intelligent exercise equipment personalized control system and method, which are used for solving the problems in the prior art. In order to achieve the above purpose, the invention provides a personalized control method of an intelligent exercise equipment, which comprises the following steps: step S100, acquiring initial sign data of a user using the intelligent exercise equipment, acquiring historical initial sign data of other users using the intelligent exercise equipment, and evaluating the sign approximation degree between the other users to obtain an approximate user; Step 200, acquiring a historical sign change record and a historical exercise record of an approximate user, acquiring an initial historical exercise record and target sign data of the user, and analyzing exercise reference value of the approximate user to the user to obtain an exercise reference user; step 300, acquiring an intelligent exercise equipment, analyzing the influence degree of the intelligent exercise equipment on the exercise effect of a user in different running states in the use process of an exercise reference user, and obtaining target running data; Step S400, when a user exercises by using the intelligent exercise equipment, the running state of the intelligent exercise equipment is controlled according to the target running data, and a message prompt is carried out on the user. Further, step S100 includes: Step S101, acquiring initial sign data of a user, wherein the initial sign data comprise values of various sign indexes of the user when the intelligent exercise equipment starts to be used; Step S102, acquiring historical initial sign data of other users using the intelligent exercise equipment, wherein the other users use the intelligent exercise equipment to exercise in a historical period, and acquiring values of various sign indexes of the other users when the intelligent exercise equipment starts to be used from the historical initial sign data; Step S103, obtaining each other user using the intelligent exercise equipment, and calculating a characteristic value a= (a △ -a ́)/sigma of the sign index of the user in the initial sign data, wherein sigma is the standard deviation of the sign index of each other user when the intelligent exercise equipment starts to be used, a △ is the value of the sign index of the user in the initial sign data, and a ́ is the average value of the sign index of each other user when the intelligent exercise equipment starts to be used; step S104, obtaining and collecting characteristic values of all the user' S physical sign indexes in the initial physical sign data to obtain initial characteristic vectors A= { a 1、a2、...、an }, wherein a 1、a2、...、an is the characteristic value of the 1 st, 2 nd and n th physical sign indexes of the user respectively; Step S105, evaluating the sign approximation degree between each other user and the user, wherein the sign approximation degree between the c-th other user and the user is evaluated by the following specific steps: