Training session scheduling method, apparatus and non-volatile computer readable medium

Abstract

A training course scheduling method, device and non-volatile computer readable medium, comprising sensing a maximum capacity value of performing a test exercise item in a unit time; estimating a physical fitness score according to the maximum capacity value; arranging a training exercise item schedule of a training course according to the physical fitness score; sensing a training intensity value of performing a training exercise item in a training time; estimating a unit intensity value of the training exercise item in a unit time according to the training intensity value; comparing the unit intensity value with a preset intensity value corresponding to the training exercise item; updating the preset intensity value of the training exercise item and the maximum capacity value in response to judging that the unit intensity value is greater than the preset intensity value; and estimating a physical fitness score according to the updated maximum capacity value, and updating the training exercise item schedule of the training course according to the updated physical fitness score.

Description

Technical Field

[0001] This invention relates to a training course scheduling method, apparatus, and non-volatile computer reading medium. Background Technology

[0002] Currently, many sports training courses are arranged by assistants or systems according to a predetermined schedule, from easy courses to difficult courses. There is no technology to dynamically adjust the difficulty of the courses in real time and progressively according to the user's physical condition. This results in users receiving unsuitable training courses, making it impossible for them to complete the training courses, or even if they do complete them, they do not achieve the intended effect. Summary of the Invention

[0003] This invention provides a method, apparatus, and non-volatile computer reading medium for scheduling training courses that can progressively and dynamically adjust the training courses according to the user's physical condition.

[0004] The training course scheduling method provided by the present invention is executed by a processing circuit and includes: sensing a user's maximum ability value for performing a test action item within a unit time period using a sensing circuit; estimating the user's fitness score based on the maximum ability value; scheduling a training exercise schedule for a training course based on the fitness score, wherein the training exercise schedule includes at least one training exercise item and a corresponding training time; sensing a training intensity value of the user performing the training exercise item within the training time period using the sensing circuit; estimating a unit intensity value of the training exercise item within the unit time period based on the training intensity value; comparing the unit intensity value with a preset intensity value corresponding to the training exercise item; updating the preset intensity value and the maximum ability value of the training exercise item in response to determining that the unit intensity value is greater than the preset intensity value; and estimating the fitness score based on the updated maximum ability value, so as to update the training exercise schedule for the training course based on the updated fitness score.

[0005] The training course scheduling apparatus provided by the present invention includes: a sensing circuit and a processing circuit coupled to the sensing circuit. The sensing circuit is used to sense the intensity values ​​of a plurality of test action items. The processing circuit is used to execute a training course scheduling method including: sensing a user's maximum ability value for performing a test action item within a unit time period through the sensing circuit; estimating the user's fitness score based on the maximum ability value; scheduling a training action item schedule for a training course based on the fitness score, wherein the training action item schedule includes at least one training action item and a corresponding training time; sensing a training intensity value of the user performing the training action item within the training time period through the sensing circuit; estimating a unit intensity value of the training action item within the unit time period based on the training intensity value; comparing the unit intensity value with a preset intensity value corresponding to the training action item; updating the preset intensity value and the maximum ability value of the training action item in response to determining that the unit intensity value is greater than the preset intensity value; and estimating the fitness score based on the updated maximum ability value, so as to update the training action item schedule of the training course based on the updated fitness score.

[0006] The present invention provides a non-volatile computer-readable medium for storing program code, wherein the program code is read by a processing circuit to execute a training course scheduling method. The training course scheduling method includes sensing a user's maximum ability value for performing a test action item within a unit time period using a sensing circuit; estimating the user's fitness score based on the maximum ability value; scheduling a training exercise schedule for a training course based on the fitness score, wherein the training exercise schedule includes at least one training exercise item and a corresponding training time; sensing a training intensity value of the user performing the training exercise item within the training time period using the sensing circuit; estimating a unit intensity value of the training exercise item within the unit time period based on the training intensity value; comparing the unit intensity value with a preset intensity value corresponding to the training exercise item; updating the preset intensity value and the maximum ability value of the training exercise item in response to determining that the unit intensity value is greater than the preset intensity value; and estimating the fitness score based on the updated maximum ability value to update the training exercise schedule for the training course based on the updated fitness score.

[0007] Because this invention employs a training course scheduling method, it can dynamically adjust the training course in real time and progressively according to the user's physical condition, so as to provide a training course that is more suitable for the user.

[0008] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0009] Figure 1 This is a system block diagram of the training course scheduling device provided in an embodiment of the present invention;

[0010] Figure 2 A flowchart of the training course scheduling method provided in the embodiments of the present invention; and

[0011] Figure 3 This is a flowchart for estimating physical fitness scores provided in an embodiment of the present invention. Detailed Implementation

[0012] First, it should be noted that in the embodiments of the present invention, the coupling methods include: direct electrical connection, and electrical connection through other components, modules, or devices. The term "coupling" as used below will encompass these methods, and will not be elaborated further.

[0013] See Figure 1The diagram shown is a system block diagram of the training course scheduling device provided in an embodiment of the present invention. The training course scheduling device 1 provided by the present invention includes a sensing circuit 2, a processing circuit 3 coupled to the sensing circuit 2, and a non-volatile computer-readable medium 4 coupled to the processing circuit 3. The sensing circuit 2 senses the intensity values ​​of the user's exercise, and the non-volatile computer-readable medium 4 stores code, which is read by the processing circuit 3 to execute the training course scheduling method. It can be noted that the sensing circuit 2 is, for example, a wearable device or an electronic device including at least one of accelerometer and gyroscope functions; the processing circuit 3 is, for example, but not limited to, a smartphone, tablet, computer, or cloud server; and the non-volatile computer-readable medium 4 is, for example, but not limited to, flash memory or hard disk in a smartphone, tablet, computer, or cloud server. Furthermore, the sensing circuit 2, the processing circuit 3, and the non-volatile computer-readable medium 4 may not be located in the same or multiple devices. Exercises include, for example, but not limited to, push-ups, crunches, squats, or other bodyweight or non-bodyweight training or other exercises. The intensity values ​​include the number of repetitions, maximum capacity repetitions, and training capacity ratio. The number of repetitions refers to the number of times the user performs an exercise within a unit of time, such as 1 or 1.5 minutes. For example, the number of push-ups (e.g., 13), crunches (e.g., 14), and squats (e.g., 60) within 1 minute. The maximum capacity repetitions are the maximum number of times the user can perform the exercise within a unit of time. The training capacity ratio is a ratio calculated based on the number of times the user performs the exercise during the training period and the maximum capacity repetitions within the unit of time. Furthermore, based on the aforementioned sensed maximum capacity repetitions of multiple test exercises within a unit of time, such as 1 minute, the processing circuit 3 can infer the maximum capacity repetitions of other exercises performed by the user within a unit of time using cloud-based big data and recommendation system algorithms. The other exercises mentioned above may include, but are not limited to, 19 exercises such as, climber's foot, sit-ups, burpees, alternating lunges, push-ups, and jumping jacks; and the number of repetitions for each exercise may be, for example, 58 climber's foot exercises, 9 sit-ups, 15 burpees, 27 alternating lunges, 3 push-ups, and 70 jumping jacks.

[0014] In addition, the non-volatile computer reading medium 4 stores information on the correspondence between an exercise and multiple ability percentages, such as a lookup table. This lookup table includes multiple ability percentages corresponding to multiple test exercises, where the multiple ability percentages include, but are not limited to, upper limb percentages, core percentages, lower limb percentages, or aerobic percentages. For example, mountain climber's pose: 0% upper limb, 72% core, 8% lower limb, 20% aerobic; sit-ups: 0% upper limb, 100% core, 0% lower limb, 0% aerobic; burpees: 0% upper limb, 20% core, 0% lower limb, 80% aerobic; alternating lunges: 0% upper limb, 14% core, 56% lower limb, 30% aerobic; single-leg push-ups: 100% upper limb, 0% core, 0% lower limb, 0% aerobic; jumping jacks: 3% upper limb, 3% core, 4% lower limb, 90% aerobic. In one embodiment, the information corresponding to action items and multiple capability percentages can also be stored in a database in the cloud.

[0015] See Figure 2 The diagram shows a flowchart of a training course scheduling method provided by an embodiment of the present invention. The training course scheduling method provided by the present invention includes: Step S1: Sensing multiple maximum ability values ​​(e.g., maximum number of repetitions) of a plurality of test actions performed by the user within a unit of time using the sensing circuit 2. Specifically, the processing circuit 3 senses the maximum number of repetitions of test actions performed by the user within a unit of time, such as, but not limited to, 1 or 1.5 minutes, including but not limited to, push-ups, crunches, and squats, using the sensing circuit 2, and calculates the maximum number of repetitions of other actions performed by the user within a unit of time based on the maximum number of repetitions of the test actions performed within a unit of time.

[0016] Step S2: Processing circuit 3 estimates the physical fitness score based on a plurality of maximum ability values, wherein the user's physical fitness score is calculated based on the maximum number of times the user performs a plurality of test actions per unit time and the corresponding plurality of ability percentages. Specifically, as follows... Figure 3As shown, step S2 includes step S21: using the correspondence information between action items and ability percentages, such as a lookup table, to look up the ability percentage corresponding to each test action item; and step S22: calculating the physical fitness score based on the maximum number of times each plurality of test action items can be performed per unit time and the plurality of ability percentages. Specifically, the processing circuit 3 obtains the physical fitness score based on the maximum number of times each plurality of test action items can be performed per unit time and the plurality of ability percentages. In one embodiment, for example, the maximum number of repetitions of a plurality of test items per unit time can be multiplied by a plurality of ability percentages to obtain a fitness score. For example, if the maximum number of push-ups in 1 minute is 13, the maximum number of crunches in 1 minute is 14, and the maximum number of squats in 1.5 minutes is 60, and the percentage of upper limbs, core, lower limbs, and aerobics in the ability percentages are as follows: Push-ups: upper limbs 90%, core 10%, lower limbs 0%, aerobic 0%; Crunches: upper limbs 0%, core 100%, lower limbs 0%, aerobic 0%; Squats: upper limbs 0%, core 0%, lower limbs 80%, aerobic 20%, then after multiplication, the upper limb score is 1,170 (13 x 90), the core score is 1,530 (13 x 10 + 14 x 100), the lower limb score is 4,800 (60 x 80), and the aerobic score is 1,200 (60 x 20). In another embodiment, for example, the maximum number of repetitions of a plurality of test movements per unit time can be multiplied by a plurality of ability percentages and then standardized to obtain a fitness score. For example, if the product results in an upper limb score of 1,170, a core score of 1,530, a lower limb score of 4,800, and an aerobic score of 1,200, then the product of each ability can be further standardized using a database of big data. For example, the fitness score can be standardized to a range of 0 to 100 based on the ranking of the product in the big data. Thus, after standardization, the fitness scores are: upper limb score of 10, core score of 23, lower limb score of 33, and aerobic score of 40. Next, in step S3, the processing circuit 3 arranges a training course schedule based on the user's fitness score, as shown in Table 1. The first column, "Function," represents the function of this training phase; the second column, "Action," represents the action items included in this training phase; the third column, "Training Time," represents the time the user spends performing this action; the fourth column, "Target Ability Ratio," represents the degree of effort the user needs to exert when performing each set of actions, for example, 50% means the user needs to use 50% of their ability to perform this set of actions, and 100% means the user needs to exert all their strength to perform this set of actions; the fifth column, "Number of Sets," represents the number of sets required for this action item.

[0017] Table 1

[0018]

[0019] Refer again Figure 2 Step S4: When the user performs the training course in Table 1, the processing circuit 3 senses the training intensity value of the training actions performed by the user during the training time through the sensing circuit 2, including the number of times and the training ability ratio during the training time, as shown in Table 2. The third column, "Number of times per training session," represents the number of times the user performs the action in each training session; the fourth column, "Training ability ratio," represents the ratio calculated per unit time based on the number of times performed in each training session and the maximum number of times performed.

[0020] Table 2

[0021]

[0022]

[0023] Step S5: Processing circuit 3 estimates the unit intensity value of at least one training exercise per unit time based on the training intensity value of at least one training exercise within the training time. The unit time is typically longer than the training time, and the unit intensity value is typically higher than the training intensity value. Specifically, in one embodiment, taking push-ups as an example, in the first training session, sensing circuit 2 senses the push-up data as follows: 3 times within the 30-second training time, 1 time within the first 15 seconds of the first time interval, and 2 times within the last 15 seconds of the second time interval. Since the 2 times in the second time interval is greater than the 1 time in the first time interval, the number of push-ups per unit time is estimated by multiplying the time by a factor. For example, if the 1-minute unit time is twice the 30-second training time, the estimated number of push-ups per unit time is 3 x 2 = 6. In the third training session, the sensing circuit 2 sensed the data of push-ups in the third group. There were 6 push-ups in the first 15 seconds of the training time, 3 push-ups in the first 15 seconds, and 3 push-ups in the second 15 seconds. Since the number of push-ups in the second 15 seconds is the same as the number of push-ups in the first 15 seconds, the number of push-ups in the third and fourth 15 seconds is estimated to be 3. Therefore, the estimated number of push-ups per unit time is 3 + 3 + 3 + 3 = 12. In the fourth training session, sensing circuit 2 detected 9 push-ups within a 30-second training period, 5 push-ups in the first 15 seconds, and 4 push-ups in the second 15 seconds. Since the number of push-ups in the second 15 seconds is less than the number of push-ups in the first 15 seconds, the number of push-ups per unit time (1 minute) is estimated by decreasing the count. For example, if the number of push-ups in the second 15 seconds is 4, it is 1 less than the number of push-ups in the first 15 seconds. Therefore, the estimated number of push-ups in the third 15 seconds is 4-1=3, and the estimated number of push-ups in the fourth 15 seconds is 3-1=2. Thus, the estimated number of push-ups per unit time is 5+4+3+2=14. If the number of push-ups in a given period is less than 0 due to decreasing calculation, it is estimated as 0. The method for estimating the number of push-ups per unit time described in the above embodiment is for illustrative purposes only and is not intended to be limiting.

[0024] In one embodiment, the training ability percentage can be calculated as follows: (estimated number of repetitions per unit time / maximum capacity repetitions x 100% + target ability percentage) / 2. Taking push-ups as an example, the training ability percentage for the first group is (6 / 13 x 100% + 50%) / 2 = 48%, for the second group it is 79%, for the third group it is 86%, and for the fourth group it is 93%. In another embodiment, the training ability percentage can be calculated as follows: estimated number of repetitions per unit time / maximum capacity repetitions x 100%. Taking push-ups as an example, the training ability percentage for the first group is 6 / 13 x 100% = 46%, for the second group it is 77%, for the third group it is 92%, and for the fourth group it is 108%.

[0025] Step S6: Processing circuit 3 compares the unit intensity value per unit time with a preset intensity value corresponding to at least one action item. In one embodiment, the unit intensity value may be, for example, the training ability ratio mentioned above; the preset intensity value may be, for example, a preset judgment standard preset by the system or defined by the user, such as including the user's maximum ability value, such as the maximum number of repetitions, and / or a preset ability ratio. Taking push-ups as an example, the preset intensity value includes a maximum number of repetitions of 13 and a preset ability ratio of 80%. Processing circuit 3 compares the unit intensity value of each set of push-ups with the preset intensity value.

[0026] Step S7: When the unit intensity value is greater than or equal to the preset intensity value, the processing circuit 3 updates the preset intensity value. In one embodiment, when one set of unit intensity values ​​for an exercise is greater than or equal to the preset intensity value, that is, when the estimated number of repetitions per unit time is greater than or equal to (or greater than) the maximum capacity repetitions and the training ability ratio is greater than or equal to (or greater than) the preset ability ratio, the preset intensity value is updated. Specifically, taking push-ups as an example, the first and second sets of 6 and 10 repetitions per unit time are both less than the maximum capacity repetitions of 13, and the training ability ratios of 48% and 79% are both less than the preset ability ratio of 80%; while the third set, although the training ability ratio of 86% is greater than the preset ability ratio of 80%, has 12 repetitions per unit time, which is less than the maximum capacity repetitions of 13. Therefore, based on the results calculated from the data of the first, second, and third sets, the preset intensity value is not updated. The fourth group's 14 repetitions per unit time is greater than the maximum capacity of 13 repetitions, and the training ability percentage (93%) is less than the preset ability percentage (80%). Therefore, based on the results calculated from the fourth group's data, processing circuit 3 updates the maximum capacity repetitions, and subsequently updates the preset intensity value. For example, the maximum capacity repetitions in the preset intensity value for push-ups are updated to 14 repetitions per unit time. In another embodiment, the preset intensity value may be only the maximum capacity value or only the preset ability percentage, to compare the data of the exercise and determine whether to update the maximum capacity value to update the preset intensity value.

[0027] Step S8: In one embodiment, the processing circuit 3 updates the fitness score based on the updated maximum capacity repetitions, and updates the exercise schedule of the training course based on the updated fitness score. Specifically, the processing circuit 3 calculates the updated maximum capacity repetitions for each exercise item by processing the data of the plurality of test exercise items in Table 2 according to the above embodiment, and calculates the updated fitness score based on the updated maximum capacity repetitions for each exercise item. For example, the upper limb score is 12 points (unchanged), the core score is 24 points (improved), the lower limb score is 33 points (improved), and the aerobic score is 40 points (unchanged). Next, the processing circuit 3 updates the exercise schedule of the training course based on the user's updated fitness score, as shown in Table 3.

[0028] Table 3

[0029]

[0030]

[0031] In summary, because the present invention employs a training course scheduling method, it can dynamically adjust the training course in real time and progressively according to the user's physical condition, so as to provide a training course that is more suitable for the user.

[0032] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the methods and techniques disclosed above without departing from the scope of the present invention to create equivalent embodiments. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A training course scheduling method, characterized in that, Executed via a processing circuit to include: A sensing circuit is used to sense a user’s maximum ability to perform a test action within a unit of time. Estimate the user's overall energy score based on this maximum energy value; A training course schedule is arranged based on the physical fitness score, wherein the training course schedule includes at least one training exercise and a corresponding training time. The sensing circuit senses the training intensity value of the user performing the training action during the training time. Estimate the intensity value of one unit of the training exercise within a unit of time based on the training intensity value; Compare the unit intensity value with a preset intensity value corresponding to the training exercise; In response to the determination that the unit intensity value is greater than the preset intensity value, the preset intensity value of the training exercise and the maximum ability value of the training exercise are updated; and The fitness score is estimated based on the updated maximum ability value, and the training exercise schedule for the training course is updated based on the updated fitness score.

2. The method as described in claim 1, characterized in that, The steps for estimating the user's fitness score based on the maximum ability value include: Find the ability percentage for a given test action by matching the action item with the corresponding ability percentage; and The physical fitness score is calculated based on the maximum ability value and percentage of ability achieved for the test action within a given time period.

3. The method as described in claim 2, characterized in that, The information corresponding to the action item and the ability percentage is provided in a lookup table.

4. The method as described in claim 2, characterized in that, This ability percentage includes upper limb percentage, core percentage, lower limb percentage, and aerobic percentage; and The fitness score includes upper limb score, core score, lower limb score, and aerobic score.

5. The method as described in claim 1, characterized in that, The maximum capability value includes the maximum number of times the user can perform the test action within that unit of time.

6. The method as described in claim 5, characterized in that, The training intensity value includes the number of times the user performs the training exercise for the first time within the training period.

7. The method as described in claim 6, characterized in that, The unit intensity value includes the number of times the user performs the training action within the training time, calculated based on the training intensity value.

8. The method as described in claim 7, characterized in that, The preset strength value includes the maximum number of executions.

9. The method as described in claim 8, characterized in that, The steps for comparing the unit intensity value with the preset intensity value for the corresponding training exercise include: Compare the second number included in the unit intensity value with the maximum number of executions included in the preset intensity value.

10. The method as described in claim 8, characterized in that, The steps to update this maximum ability value include: Update the maximum number of executions for this training exercise.

11. A training course scheduling device, characterized in that, include: A sensing circuit used to sense the intensity of an action. as well as A processing circuit, coupled to the sensing circuit, is used to execute a training course scheduling method; The training course scheduling method includes: A sensing circuit is used to sense a user’s maximum ability to perform a test action within a unit of time. Estimate the user's overall energy score based on this maximum energy value; A training course schedule is arranged based on the physical fitness score, wherein the training course schedule includes at least one training exercise and a corresponding training time. The sensing circuit senses the training intensity value of the user performing the training action during the training time. Estimate the intensity value of one unit of the training exercise within a unit of time based on the training intensity value; Compare the unit intensity value with a preset intensity value corresponding to the training exercise; In response to the determination that the unit intensity value is greater than the preset intensity value, the preset intensity value of the training exercise and the maximum ability value of the training exercise are updated; and The fitness score is estimated based on the updated maximum ability value, and the training exercise schedule for the training course is updated based on the updated fitness score.

12. A non-volatile computer-readable medium, characterized in that, For storing code, wherein the code is read by a processing circuit to execute a training course scheduling method, including: A sensing circuit is used to sense a user’s maximum ability to perform a test action within a unit of time. Estimate the user's overall energy score based on this maximum energy value; A training course schedule is arranged based on the physical fitness score, wherein the training course schedule includes at least one training exercise and a corresponding training time. The sensing circuit senses the training intensity value of the user performing the training action during the training time. Estimate the intensity value of one unit of the training exercise within a unit of time based on the training intensity value; Compare the unit intensity value with a preset intensity value corresponding to the training exercise; In response to the determination that the unit intensity value is greater than the preset intensity value, the preset intensity value of the training exercise and the maximum ability value of the training exercise are updated; and The fitness score is estimated based on the updated maximum ability value, and the training exercise schedule for the training course is updated based on the updated fitness score.

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