A method and device for determining motion parameters

Abstract

The embodiment of the present invention discloses a method and device for determining motion parameters. The method comprises: obtaining the q-axis current value generated when a motor drives a treadmill; determining the characteristic data of the treadmill in each current cycle according to the q-axis current value, wherein the characteristic data of the treadmill comprises a plurality of characteristic moments and the q-axis current values ​​corresponding to the plurality of characteristic moments, and the plurality of characteristic moments constitute a current cycle in which the motor completes a load mutation process; determining the motion parameters of the athlete on the treadmill according to the characteristic data of the treadmill. Through the present invention, the technical problem that the treadmill in the related art has inaccurate detection results and low precision when detecting the motion parameters of the athlete is solved, and the technical effect of improving the accuracy and precision of the treadmill in detecting the motion parameters is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of treadmill data processing, and in particular to a method and device for determining motion parameters. Background Art

[0002] When a user uses a treadmill, it is necessary to obtain the user's current number of steps, speed, kilometers and other data in real time, and display them through a display panel, APP, etc. and use them as the data basis for big data analysis. As for how to obtain motion parameters, the following technical solutions are usually adopted in the prior art: installing sensor devices such as gratings or pressure-sensitive sensors on the treadmill pedals, and detecting human body movements to count steps, calculate speed and kilometers; however, this technical solution is not only costly, but also the system is relatively complex and has a high failure rate. Once a failure occurs, the detected motion parameters will be inaccurate. For another example, the prior art determines the kilometers and speed based on the speed of the treadmill motor multiplied by the speed ratio of the belt, and determines the number of steps based on the number of peaks of the phase current; however, this technical solution is prone to low accuracy of the detected motion parameters due to the non-constant speed of the treadmill, the uncertainty of the user's movements on the treadmill, and the error counting caused by the number of statistical peaks.

[0003] To address the above-mentioned problems, no effective solutions have been proposed yet. Summary of the invention

[0004] The embodiments of the present invention provide a method and device for determining motion parameters, so as to at least solve the technical problem in the related art that a treadmill has inaccurate detection results and low precision when detecting motion parameters of an athlete.

[0005] According to one aspect of an embodiment of the present invention, a method for determining motion parameters is provided, comprising: obtaining a q-axis current value generated when a motor drives a treadmill; determining characteristic data of the treadmill in each current cycle based on the q-axis current value, wherein the characteristic data of the treadmill includes a plurality of characteristic moments and q-axis current values ​​corresponding to the plurality of characteristic moments, and the plurality of characteristic moments constitute one current cycle in which the motor completes a load mutation process; determining the motion parameters of an athlete on the treadmill based on the characteristic data of the treadmill.

[0006] Optionally, the multiple characteristic moments include at least: a load mutation start moment, a first load peak moment, a heavy load stabilization start moment, a heavy load stabilization end moment, a second load peak moment and a no-load moment.

[0007] Optionally, when the characteristic moment is the starting moment of the load mutation, characteristic data of the treadmill in each current cycle is determined according to the q-axis current value, including: judging whether the q-axis current value is greater than or equal to a first current threshold of the motor, wherein the first current threshold is the product of the q-axis current value of the motor in a no-load state and a first predetermined multiple; when the q-axis current value is less than the first current threshold, continuing to judge whether the q-axis current value is greater than or equal to the first current threshold until the q-axis current value is greater than or equal to the first current threshold; when the q-axis current value is greater than or equal to the first current threshold, determining that the motor is at the starting moment of the load mutation, and using the q-axis current value as the q-axis current value corresponding to the starting moment of the load mutation.

[0008] Optionally, when the characteristic moment is the first load peak moment or the second load peak moment, characteristic data of the treadmill in each current cycle is determined according to the q-axis current value, including: judging whether the q-axis current value at the next moment is less than the q-axis current value at the previous moment; when the q-axis current value at the next moment is greater than or equal to the q-axis current value at the previous moment, continuing to judge whether the q-axis current value at the next moment is less than the q-axis current value at the previous moment until the q-axis current value at the next moment is less than the q-axis current value at the previous moment; when the q-axis current value at the next moment is less than the q-axis current value at the previous moment, determining that the motor is at the first load peak moment or the second load peak moment, wherein, when the motor is at the first load peak moment, the q-axis current value at the previous moment is used as the q-axis current value corresponding to the first load peak moment; or, when the motor is at the second load peak moment, the q-axis current value at the previous moment is used as the q-axis current value corresponding to the second load peak moment.

[0009] Optionally, when the characteristic moment is the start moment of heavy-load stabilization, characteristic data of the treadmill in each current cycle are determined according to the q-axis current value, including: judging whether the q-axis current value is within the first predetermined current range of the motor for multiple consecutive times; determining that the motor is at the start moment of heavy-load stabilization when the q-axis current value is within the first predetermined current range for multiple consecutive times, and using the q-axis current value as the q-axis current value corresponding to the start moment of heavy-load stabilization; wherein, the first predetermined current range is determined based on a first average current value and an error current value, and the first average current value is calculated based on the q-axis current values ​​at multiple moments when the motor is in a heavy-load stable state.

[0010] Optionally, when the characteristic moment is the end moment of the heavy-load stability, characteristic data of the treadmill in each current cycle are determined according to the q-axis current value, including: judging whether the q-axis current value is greater than or equal to the second current threshold of the motor, wherein the second current threshold is the product of the average q-axis current value corresponding to the motor in the heavy-load stable state and a second predetermined multiple; when the q-axis current value is less than the second current threshold, continuing to judge whether the q-axis current value is greater than or equal to the second current threshold until the q-axis current value is greater than or equal to the second current threshold; when the q-axis current value is greater than or equal to the second current threshold, determining that the motor is at the end moment of the heavy-load stability, and using the q-axis current value as the q-axis current value corresponding to the end moment of the heavy-load stability.

[0011] Optionally, when the characteristic moment is the no-load moment, characteristic data of the treadmill in each current cycle is determined according to the q-axis current value, including: judging whether the q-axis current value is within the second predetermined current range of the motor for multiple consecutive times; determining that the motor is at the no-load moment when the q-axis current value is within the second predetermined current range for multiple consecutive times, and using the q-axis current value as the q-axis current value corresponding to the no-load moment; wherein, the second predetermined current range is determined based on a second average current value and an error current value, and the second average current value is calculated based on the q-axis current values ​​of the motor in a no-load state in multiple current cycles.

[0012] Optionally, the motion parameter is the number of motion steps, and the motion parameters of the athlete on the treadmill are determined according to the characteristic data of the treadmill, including: according to multiple characteristic moments in the characteristic data of the treadmill, which are respectively the load mutation start moment, the first load peak moment, the heavy load stabilization start moment, the heavy load stabilization end moment, the second load peak moment and the no-load moment, it is determined that the athlete has completed a step on the treadmill, and the number of motion steps is updated; wherein, the load mutation start moment is used as the start moment of the athlete's motion on the treadmill.

[0013] Optionally, the motion parameter is motion mileage, and the motion parameter of the athlete on the treadmill is determined based on the characteristic data of the treadmill, including: calculating the time required for the athlete to complete a step on the treadmill based on the characteristic data of the treadmill; obtaining the operating parameters of the motor when the athlete completes a step on the treadmill based on the required time; calculating the mileage required for the athlete to complete a step on the treadmill based on the operating parameters of the motor, and updating the motion mileage.

[0014] Optionally, the motion parameter is motion speed, and the motion parameter of the athlete on the treadmill is determined based on the characteristic data of the treadmill, including: calculating the time required for the athlete to complete a step on the treadmill based on the characteristic data of the treadmill; determining the mileage of the athlete to complete a step on the treadmill; and calculating the motion speed of the athlete to complete a step on the treadmill based on the required time and the mileage.

[0015] According to another aspect of an embodiment of the present invention, a motion parameter determination device is also provided, including: an acquisition module, used to obtain the q-axis current value generated when a motor drives a treadmill; a first determination module, used to determine the characteristic data of the treadmill in each current cycle based on the q-axis current value, wherein the characteristic data of the treadmill includes multiple characteristic moments and the q-axis current values ​​corresponding to the multiple characteristic moments, and the multiple characteristic moments constitute one current cycle of the motor completing a load mutation process; a second determination module, used to determine the motion parameters of the athlete on the treadmill based on the characteristic data of the treadmill.

[0016] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute any one of the method steps described above.

[0017] In an embodiment of the present invention, the q-axis current value generated when the motor drives the treadmill is obtained; according to the q-axis current value, the characteristic data of the treadmill in each current cycle is determined, wherein the characteristic data of the treadmill includes multiple characteristic moments and the q-axis current values ​​corresponding to the multiple characteristic moments, and the multiple characteristic moments constitute a current cycle of the motor completing the load mutation process; according to the characteristic data of the treadmill, the motion parameters of the athlete on the treadmill are determined. In other words, the embodiment of the present invention does not need to use a sensor device, that is, according to the q-axis current value generated when the motor drives the treadmill, the characteristic data of the treadmill in each current cycle is calculated, and then the characteristic data of the treadmill in each current cycle is used to calculate the motion parameters of the athlete on the treadmill in real time, thereby solving the technical problem of inaccurate detection results and low precision of the treadmill in the related art when detecting the motion parameters of the athlete, and achieving the technical effect of improving the accuracy and precision of the treadmill in detecting the motion parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0019] Figure 1A flow chart of a method for determining motion parameters provided by an embodiment of the present invention;

[0020] Figure 2 A schematic diagram of characteristic data of a treadmill within a current cycle provided by an optional embodiment of the present invention;

[0021] Figure 3 A schematic diagram of a motion parameter determination device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0023] It should be noted that the terms "first", "second" and the like in the specification, claims and drawings of the present invention are used to distinguish different objects rather than to limit a specific order.

[0024] According to one aspect of an embodiment of the present invention, a method for determining motion parameters is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown here.

[0025] Figure 1 A flow chart of a method for determining motion parameters provided by an embodiment of the present invention, such as Figure 1 As shown, the method comprises the following steps:

[0026] Step S102, obtaining the q-axis current value generated when the motor drives the treadmill;

[0027] When the motor drives the treadmill, the q-axis current value can be collected in real time or according to a predetermined time period. The predetermined time period can be flexibly set according to the specific application scenario, and the time interval represented is relatively short, for example, 0.05ms, 0.15ms, 5ms, etc.

[0028] In addition, when the athlete is exercising on the treadmill, his / her movements at different times act on the treadmill, causing the load of the treadmill to change continuously, which will cause the q-axis current value generated when the motor drives the treadmill to change continuously. It should be noted that when the athlete is exercising on the treadmill, the q-axis current value has a periodic change law.

[0029] Step S104, determining characteristic data of the treadmill in each current cycle according to the q-axis current value, wherein the characteristic data of the treadmill includes a plurality of characteristic moments and the q-axis current values ​​corresponding to the plurality of characteristic moments, and the plurality of characteristic moments constitute a current cycle of the motor completing a load mutation process;

[0030] Optionally, an adaptive learning algorithm is used to process the q-axis current value generated when the motor drives the treadmill, and characteristic data of the treadmill in each current cycle is automatically identified.

[0031] The above-mentioned multiple characteristic moments include but are not limited to the load mutation start moment, the first load peak moment, the heavy load stability start moment, the heavy load stability moment, the heavy load stability end moment, the second load peak moment and the no-load moment. For example, the load mutation start moment, the first load peak moment, the heavy load stability start moment, the heavy load stability moment, the heavy load stability end moment, the second load peak moment and the no-load moment can constitute a current cycle of the motor completing the load mutation process; for another example, the load mutation start moment, the first load peak moment, the heavy load stability start moment, the heavy load stability end moment, the second load peak moment and the no-load moment can also constitute a current cycle of the motor completing the load mutation process. It should be noted that the load mutation start moment is the start moment of a current cycle of the motor completing the load mutation process, and the no-load moment is the end moment of a current cycle of the motor completing the load mutation process. In addition, the characteristic data of the treadmill in each current cycle corresponds to the movement of the athlete on the treadmill one by one, that is, the movement of the athlete at different times on the treadmill will have a characteristic moment corresponding to the q-axis current value corresponding to it. It should be noted that multiple moments can be spaced between every two characteristic moments.

[0032] Step S106, determining the exercise parameters of the athlete on the treadmill according to the characteristic data of the treadmill.

[0033] Optionally, based on multiple characteristic moments in the characteristic data of the treadmill, the exercise parameters of the athlete on the treadmill can be accurately calculated. The above exercise parameters include but are not limited to exercise time, exercise steps, exercise mileage, and exercise speed. Exercise mileage is also called kilometers.

[0034] In an embodiment of the present invention, the q-axis current value generated when the motor drives the treadmill is obtained; according to the q-axis current value, the characteristic data of the treadmill in each current cycle is determined, wherein the characteristic data of the treadmill includes multiple characteristic moments and the q-axis current values ​​corresponding to the multiple characteristic moments, and the multiple characteristic moments constitute a current cycle of the motor completing the load mutation process; according to the characteristic data of the treadmill, the motion parameters of the athlete on the treadmill are determined. In other words, the embodiment of the present invention does not need to use a sensor device, that is, according to the q-axis current value generated when the motor drives the treadmill, the characteristic data of the treadmill in each current cycle is calculated, and then the characteristic data of the treadmill in each current cycle is used to calculate the motion parameters of the athlete on the treadmill in real time, thereby solving the technical problem of inaccurate detection results and low precision of the treadmill in the related art when detecting the motion parameters of the athlete, and achieving the technical effect of improving the accuracy and precision of the treadmill in detecting the motion parameters.

[0035] In an optional embodiment, the multiple characteristic moments include at least: a load mutation start moment, a first load peak moment, a heavy load stabilization start moment, a heavy load stabilization end moment, a second load peak moment and a no-load moment.

[0036] Optionally, the above-mentioned multiple characteristic moments may be, in sequence, the load mutation start moment, the first load peak moment, the heavy load stabilization start moment, the heavy load stabilization end moment, the second load peak moment and the no-load moment.

[0037] Figure 2 A schematic diagram of characteristic data of a treadmill within a current cycle provided by an optional embodiment of the present invention, such as Figure 2 As shown, t1, t2, t3, t4, t5, t6 and t7 constitute a current cycle of a completed load mutation process, wherein t1 is the load mutation starting moment of this current cycle, t2 is the first load peak value (i.e., the athlete lands on the treadmill, q-axis current peak value) moment of this current cycle, t3 is the heavy load stability start moment of this current cycle (i.e., the athlete is stationary on the treadmill), t4 is the heavy load stability moment of this current cycle, t5 is the heavy load stability end moment of this current cycle, t6 is the second load peak value (i.e., the athlete takes off on the treadmill, q-axis current peak value) moment of this current cycle, and t7 is the no-load (the athlete is completely detached from the treadmill) moment of this current cycle. Through the above seven characteristic moments and the corresponding q-axis current values, the calculation of running steps, speed, posture, and mileage can be realized. In addition, t0 is the no-load (the athlete is completely detached from the treadmill) moment of the previous current cycle.

[0038] In an optional embodiment, when the characteristic moment is the starting moment of the load mutation, the characteristic data of the treadmill in each current cycle is determined according to the q-axis current value, including: judging whether the q-axis current value is greater than or equal to the first current threshold of the motor, wherein the first current threshold is the product of the q-axis current value of the motor in a no-load state and a first predetermined multiple; when the q-axis current value is less than the first current threshold, continuing to judge whether the q-axis current value is greater than or equal to the first current threshold until the q-axis current value is greater than or equal to the first current threshold; when the q-axis current value is greater than or equal to the first current threshold, determining that the motor is at the starting moment of the load mutation, and using the q-axis current value as the q-axis current value corresponding to the starting moment of the load mutation.

[0039] In order to avoid false triggering, it is necessary to determine whether the q-axis current value is greater than or equal to the first current threshold of the motor. If the q-axis current value is less than the first current threshold, it will continue to determine whether the q-axis current value is greater than or equal to the first current threshold until the q-axis current value is greater than or equal to the first current threshold; if the q-axis current value is greater than or equal to the first current threshold, it can be determined that the motor is at the start of a sudden load change, and the q-axis current value is used as the q-axis current value corresponding to the start of the sudden load change. It should be noted that the above-mentioned first current threshold is the product of the q-axis current value of the motor in the no-load state and the first predetermined multiple, and the first predetermined multiple can be set according to actual needs. For example, the first predetermined multiple can be 1.1, 1.2, 1.5, etc.

[0040] In the above-mentioned embodiment of the present application, the q-axis current value is compared with the first current threshold value, and the comparison result is used to determine whether the motor is at the starting moment of the load mutation and the q-axis current value corresponding to the characteristic moment, thereby effectively avoiding the misjudgment of the characteristic moment caused by the q-axis current value being too small.

[0041] In an optional embodiment, when the characteristic moment is the first load peak moment or the second load peak moment, the characteristic data of the treadmill in each current cycle is determined according to the q-axis current value, including: judging whether the q-axis current value at the next moment is less than the q-axis current value at the previous moment; when the q-axis current value at the next moment is greater than or equal to the q-axis current value at the previous moment, continuing to judge whether the q-axis current value at the next moment is less than the q-axis current value at the previous moment, until the q-axis current value at the next moment is less than the q-axis current value at the previous moment; when the q-axis current value at the next moment is less than the q-axis current value at the previous moment, determining that the motor is at the first load peak moment or the second load peak moment, wherein, when the motor is at the first load peak moment, the q-axis current value at the previous moment is used as the q-axis current value corresponding to the first load peak moment; or, when the motor is at the second load peak moment, the q-axis current value at the previous moment is used as the q-axis current value corresponding to the second load peak moment.

[0042] It should be noted that the first load peak moment and the second load peak moment use the same judgment method. For example, after determining that the motor is at the start of the load mutation, it can be determined whether the q-axis current value at the next moment is less than the q-axis current value at the previous moment; if the q-axis current value at the next moment is greater than or equal to the q-axis current value at the previous moment, it can be determined whether the q-axis current value at the next moment is less than the q-axis current value at the previous moment, until the q-axis current value at the next moment is less than the q-axis current value at the previous moment; if the q-axis current value at the next moment is less than the q-axis current value at the previous moment, it can be determined that the motor is at the first load peak moment, and the q-axis current value at the previous moment is used as the q-axis current value corresponding to the first load peak moment. For another example, after determining that the motor is at the end of heavy-load stability, it is possible to determine whether the q-axis current value at the next moment is less than the q-axis current value at the previous moment; if the q-axis current value at the next moment is greater than or equal to the q-axis current value at the previous moment, it is possible to continue to determine whether the q-axis current value at the next moment is less than the q-axis current value at the previous moment, until the q-axis current value at the next moment is less than the q-axis current value at the previous moment; if the q-axis current value at the next moment is less than the q-axis current value at the previous moment, it can be determined that the motor is at the second load peak moment, and the q-axis current value at the previous moment is used as the q-axis current value corresponding to the second load peak moment.

[0043] In the above-mentioned embodiment of the present application, by comparing the q-axis current value at the next moment with the q-axis current value at the previous moment, the first load peak moment or the second load peak moment can be accurately determined.

[0044] In an optional embodiment, when the characteristic moment is the start moment of heavy load stabilization, characteristic data of the treadmill in each current cycle is determined according to the q-axis current value, including: judging whether the q-axis current value is in the first predetermined current range of the motor for multiple consecutive times; determining that the motor is in the start moment of heavy load stabilization when the q-axis current value is in the first predetermined current range for multiple consecutive times, and using the q-axis current value as the q-axis current value corresponding to the start moment of heavy load stabilization; wherein the first predetermined current range is determined according to the first average current value and the error current value, and the first average current value is calculated based on the q-axis current values ​​at multiple moments when the motor is in the heavy load stable state.

[0045] Optionally, after determining that the motor is at the second load peak moment, it is necessary to determine whether the q-axis current value is within the first predetermined current range of the motor for multiple consecutive times; if the q-axis current value is within the first predetermined current range for multiple consecutive times, it can be determined that the motor is at the beginning of heavy load stabilization, and the q-axis current value is used as the q-axis current value corresponding to the beginning of heavy load stabilization; it should be noted that the above-mentioned first predetermined current range is determined based on the first average current value and the error current value, and the first average current value is the average value calculated based on the q-axis current values ​​at multiple moments when the motor is in the heavy load stable state, and the above-mentioned error current value can be set according to the needs of the application scenario, and will not be repeated here one by one.

[0046] In the above-mentioned embodiment of the present application, whether the motor is at the heavy load stabilization start time is determined by judging whether the q-axis current value is in the first predetermined current range for multiple times in a row, thereby accurately calculating the heavy load stabilization start time.

[0047] In an optional embodiment, when the characteristic moment is the end moment of heavy-load stability, the characteristic data of the treadmill in each current cycle is determined according to the q-axis current value, including: judging whether the q-axis current value is greater than or equal to the second current threshold of the motor, wherein the second current threshold is the product of the average q-axis current value corresponding to the motor in the heavy-load stable state and the second predetermined multiple; when the q-axis current value is less than the second current threshold, continuing to judge whether the q-axis current value is greater than or equal to the second current threshold until the q-axis current value is greater than or equal to the second current threshold; when the q-axis current value is greater than or equal to the second current threshold, determining that the motor is at the end moment of heavy-load stability, and using the q-axis current value as the q-axis current value corresponding to the end moment of heavy-load stability.

[0048] In order to more accurately determine the end time of the motor being in a heavy-load stable state, it is necessary to determine whether the q-axis current value is greater than or equal to the second current threshold of the motor; if the q-axis current value is less than the second current threshold, it is possible to continue to determine whether the q-axis current value is greater than or equal to the second current threshold until the q-axis current value is greater than or equal to the second current threshold; if the q-axis current value is greater than or equal to the second current threshold, it is possible to determine that the motor is in the end time of heavy-load stability, and use the q-axis current value as the q-axis current value corresponding to the end time of heavy-load stability. It should be noted that the above-mentioned second current threshold is the product of the average q-axis current value corresponding to the motor being in a heavy-load stable state and the second predetermined multiple; the average q-axis current value corresponding to the motor being in a heavy-load stable state is obtained by averaging the q-axis current values ​​at multiple moments when the motor is in a heavy-load stable state, and the second predetermined multiple can be set according to actual needs, for example, the second predetermined multiple can be 1.1, 1.2, 1.5, etc.

[0049] In the above-mentioned embodiment of the present application, the q-axis current value is compared with the second current threshold, and the comparison result is used to determine whether the motor is at the end of the load mutation and the q-axis current value corresponding to the characteristic moment, so as to more accurately obtain the end of the heavy load stability.

[0050] In an optional embodiment, when the characteristic moment is a no-load moment, characteristic data of the treadmill in each current cycle is determined based on the q-axis current value, including: judging whether the q-axis current value is within the second predetermined current range of the motor for multiple consecutive times; determining that the motor is at a no-load moment when the q-axis current value is within the second predetermined current range for multiple consecutive times, and using the q-axis current value as the q-axis current value corresponding to the no-load moment; wherein the second predetermined current range is determined based on a second average current value and an error current value, and the second average current value is calculated based on the q-axis current values ​​of the motor in a no-load state for multiple current cycles.

[0051] In order to accurately calculate the end time of a current cycle in which the motor completes the load mutation process, it is necessary to determine whether the q-axis current value is within the second predetermined current range of the motor for multiple consecutive times; if the q-axis current value is within the second predetermined current range for multiple consecutive times, it can be determined that the motor is at a no-load moment, and the q-axis current value is used as the q-axis current value corresponding to the no-load moment; it should be noted that the above-mentioned second predetermined current range is determined based on the second average current value and the error current value, and the second average current value is calculated based on the q-axis current values ​​of the motor in a no-load state in multiple current cycles, and the above-mentioned error current value can be set according to the needs of the application scenario, and will not be repeated here one by one; in addition, the value of the second average current value in the first current cycle is the q-axis current value of the motor that is always in a no-load state.

[0052] In the above-mentioned implementation mode of the present application, whether the motor is in the no-load moment is determined by judging whether the q-axis current value is in the second predetermined current range for multiple times in a row, thereby accurately calculating the no-load moment.

[0053] In an optional embodiment, the above-mentioned motion parameter is the number of motion steps, and the motion parameters of the athlete on the treadmill are determined according to the characteristic data of the treadmill, including: according to multiple characteristic moments in the characteristic data of the treadmill, which are respectively the start moment of load mutation, the first load peak moment, the start moment of heavy load stability, the end moment of heavy load stability, the second load peak moment and the no-load moment, it is determined that the athlete has completed a step on the treadmill, and the number of motion steps is updated; wherein, the start moment of load mutation is used as the start moment of the athlete's motion on the treadmill.

[0054] Since the start time to the end time of the sportsman's movement on the treadmill corresponds to the order of appearance of multiple characteristic moments in the characteristic data of the treadmill, then the load mutation start time can be used as the start time of the sportsman's movement on the treadmill, and the no-load time can be used as the end time of the sportsman's movement on the treadmill. Therefore, the multiple characteristic moments in the characteristic data of the treadmill are the load mutation start time, the first load peak time, the heavy load stable start time, the heavy load stable end time, the second load peak time and the no-load time in sequence, so that it can be determined that the sportsman completes a step on the treadmill and the number of movement steps is updated. The above-mentioned no-load time is the starting time of the no-load state. Updating the number of movement steps is to add 1 to the running step number corresponding to the previous step, so as to obtain the running step number corresponding to the current step.

[0055] In the above-mentioned embodiment of the present application, the order of occurrence of multiple characteristic moments in the characteristic data of the treadmill determined according to the q-axis current value is used to complete the step counting of the athlete on the treadmill, so as to more accurately calculate the number of steps taken by the athlete on the treadmill.

[0056] In an optional embodiment, the above-mentioned motion parameters are motion mileage. According to the characteristic data of the treadmill, the motion parameters of the athlete on the treadmill are determined, including: calculating the time required for the athlete to complete a step on the treadmill according to the characteristic data of the treadmill; obtaining the operating parameters of the motor when the athlete completes a step on the treadmill according to the required time; calculating the mileage required for the athlete to complete a step on the treadmill according to the operating parameters of the motor, and updating the motion mileage.

[0057] Optionally, the time required for the athlete to complete one step on the treadmill is calculated based on the time difference between the start of the load mutation and the no-load moment in the current cycle, that is, the time from the start of the load mutation to the no-load moment, and then the operating parameters of the motor in the current cycle are obtained, that is, the number of motor revolutions within the required time range, the speed ratio of the motor to the belt, the belt drive wheel diameter and other operating parameters, and finally the mileage of the athlete completing one step on the treadmill is calculated based on the motor operating parameters. The mileage of the athlete completing one step on the treadmill can be calculated by the following expression:

[0058] S=π·K·R·D

[0059] Among them, S represents the distance the athlete completes one step on the treadmill, K represents the speed ratio of the motor to the belt, R represents the number of revolutions of the motor in the time required for the athlete to complete one step on the treadmill, D represents the diameter of the belt drive pulley, and π represents pi.

[0060] In addition, updating the exercise mileage means adding the running mileage corresponding to the previous step to the mileage of the current athlete completing one step on the treadmill, thereby obtaining the running mileage corresponding to the current step.

[0061] In the above-mentioned embodiment of the present application, the time required for the athlete to complete one step on the treadmill can be calculated based on the characteristic data of the treadmill, and the operating parameters of the motor when the athlete completes one step on the treadmill within the required time can be obtained. Then, the mileage of the athlete completing one step on the treadmill can be calculated using the operating parameters of the motor, and the exercise mileage can be updated to accurately obtain the athlete's exercise mileage on the treadmill.

[0062] In an optional embodiment, the above-mentioned motion parameter is motion speed, and the motion parameter of the athlete on the treadmill is determined according to the characteristic data of the treadmill, including: calculating the time required for the athlete to complete a step on the treadmill according to the characteristic data of the treadmill; determining the mileage required for the athlete to complete a step on the treadmill; and calculating the motion speed of the athlete to complete a step on the treadmill according to the required time and mileage.

[0063] Optionally, firstly, the time required for the athlete to complete one step on the treadmill is calculated based on the time difference between the start of the load mutation and the no-load moment in the current cycle, that is, the time from the start of the load mutation to the no-load moment; then the operating parameters of the motor in the current cycle are obtained, that is, the number of motor revolutions within the required time range, the speed ratio of the motor to the belt, the diameter of the belt drive wheel and other operating parameters; finally, based on the operating parameters of the motor, the mileage required for the athlete to complete one step on the treadmill is calculated; finally, based on the required time and mileage, the movement speed of the athlete to complete one step on the treadmill is calculated. The movement speed of the athlete to complete one step on the treadmill can be calculated by the following expression:

[0064]

[0065] Among them, S represents the distance that the athlete completes in one step on the treadmill, K represents the speed ratio of the motor to the belt, R represents the number of revolutions of the motor in the time required for the athlete to complete one step on the treadmill, D represents the diameter of the belt drive pulley, π represents pi, and ΔT represents the time from the start of the load mutation to the no-load moment, that is, the time required for the athlete to complete one step on the treadmill.

[0066] In the above-mentioned embodiment of the present application, the time and mileage required for an athlete to complete one step on the treadmill can be calculated based on the characteristic data of the treadmill, and then the movement speed of the athlete to complete one step on the treadmill can be calculated using the required time and mileage, so that the real-time movement speed can be accurately obtained.

[0067] According to another aspect of the embodiments of the present invention, a motion parameter determination device is provided. Figure 3 A schematic diagram of a motion parameter determination device provided by an embodiment of the present invention, such as Figure 3 As shown, the motion parameter determination device includes: an acquisition module 32, a first determination module 34 and a second determination module 36. The motion parameter determination device is described in detail below.

[0068] An acquisition module 32 is used to acquire the q-axis current value generated when the motor drives the treadmill;

[0069] A first determination module 34, connected to the acquisition module 32, is used to determine characteristic data of the treadmill in each current cycle according to the q-axis current value, wherein the characteristic data of the treadmill includes a plurality of characteristic moments and the q-axis current values ​​corresponding to the plurality of characteristic moments, and the plurality of characteristic moments constitute a current cycle in which the motor completes a load mutation process;

[0070] The second determination module 36 is connected to the first determination module 34 and is used to determine the exercise parameters of the athlete on the treadmill according to the characteristic data of the treadmill.

[0071] In an embodiment of the present invention, the motion parameter determination device adopts the method of obtaining the q-axis current value generated when the motor drives the treadmill; according to the q-axis current value, determining the characteristic data of the treadmill in each current cycle, wherein the characteristic data of the treadmill includes multiple characteristic moments and the q-axis current values ​​corresponding to the multiple characteristic moments, and the multiple characteristic moments constitute a current cycle of the motor completing the load mutation process; according to the characteristic data of the treadmill, determining the motion parameters of the athlete on the treadmill. In other words, the embodiment of the present invention does not need to use a sensor device, that is, according to the q-axis current value generated when the motor drives the treadmill, the characteristic data of the treadmill in each current cycle is calculated, and then the characteristic data of the treadmill in each current cycle is used to calculate the motion parameters of the athlete on the treadmill in real time, thereby solving the technical problem of inaccurate detection results and low precision of the treadmill in the related art when detecting the motion parameters of the athlete, and achieving the technical effect of improving the accuracy and precision of the treadmill in detecting the motion parameters.

[0072] It should be noted here that the above-mentioned acquisition module 32, first determination module 34 and second determination module 36 correspond to steps S102 to S106 in the method embodiment, and the examples and application scenarios implemented by the above-mentioned modules and corresponding steps are the same, but are not limited to the contents disclosed in the above-mentioned method embodiment.

[0073] In an optional embodiment, the multiple characteristic moments include at least: a load mutation start moment, a first load peak moment, a heavy load stabilization start moment, a heavy load stabilization end moment, a second load peak moment and a no-load moment.

[0074] In an optional embodiment, the above-mentioned first determination module 34 includes: a first judgment unit, used to judge whether the q-axis current value is greater than or equal to the first current threshold of the motor when the characteristic moment is the starting moment of the load mutation, wherein the first current threshold is the product of the q-axis current value of the motor in the no-load state and a first predetermined multiple; a first processing unit, used to continue to judge whether the q-axis current value is greater than or equal to the first current threshold when the q-axis current value is less than the first current threshold, until the q-axis current value is greater than or equal to the first current threshold; a second processing unit, used to determine that the motor is at the starting moment of the load mutation when the q-axis current value is greater than or equal to the first current threshold, and use the q-axis current value as the q-axis current value corresponding to the starting moment of the load mutation.

[0075] In an optional embodiment, the first determination module 34 includes: a second judgment unit, which is used to judge whether the q-axis current value at the next moment is less than the q-axis current value at the previous moment when the characteristic moment is the first load peak moment or the second load peak moment; a third processing unit, which is used to continue to judge whether the q-axis current value at the next moment is less than the q-axis current value at the previous moment when the q-axis current value at the next moment is greater than or equal to the q-axis current value at the previous moment, until the q-axis current value at the next moment is less than the q-axis current value at the previous moment; a fourth processing unit, which is used to determine whether the motor is at the first load peak moment or the second load peak moment when the q-axis current value at the next moment is less than the q-axis current value at the previous moment, wherein when the motor is at the first load peak moment, the q-axis current value at the previous moment is used as the q-axis current value corresponding to the first load peak moment; or, when the motor is at the second load peak moment, the q-axis current value at the previous moment is used as the q-axis current value corresponding to the second load peak moment.

[0076] In an optional embodiment, the above-mentioned first determination module 34 includes: a third judgment unit, used to judge whether the q-axis current value is in the first predetermined current range of the motor for multiple consecutive times when the characteristic moment is the start moment of heavy load stabilization; a fifth processing unit, used to determine that the motor is at the start moment of heavy load stabilization when the q-axis current value is in the first predetermined current range for multiple consecutive times, and use the q-axis current value as the q-axis current value corresponding to the start moment of heavy load stabilization; wherein, the first predetermined current range is determined based on the first average current value and the error current value, and the first average current value is calculated based on the q-axis current values ​​at multiple moments when the motor is in the heavy load stable state.

[0077] In an optional embodiment, the above-mentioned first determination module 34 includes: a fourth judgment unit, which is used to judge whether the q-axis current value is greater than or equal to the second current threshold of the motor when the characteristic moment is the end moment of overload stability, wherein the second current threshold is the product of the average q-axis current value corresponding to the motor in the overload stable state and the second predetermined multiple; a sixth processing unit, which is used to continue to judge whether the q-axis current value is greater than or equal to the second current threshold when the q-axis current value is less than the second current threshold, until the q-axis current value is greater than or equal to the second current threshold; a seventh processing unit, which is used to determine that the motor is at the end moment of overload stability when the q-axis current value is greater than or equal to the second current threshold, and use the q-axis current value as the q-axis current value corresponding to the end moment of overload stability.

[0078] In an optional embodiment, the above-mentioned first determination module 34 includes: a fifth judgment unit, used to judge whether the q-axis current value is in the second predetermined current range of the motor for multiple consecutive times when the characteristic moment is a no-load moment; an eighth processing unit, used to determine that the motor is in a no-load moment when the q-axis current value is in the second predetermined current range for multiple consecutive times, and use the q-axis current value as the q-axis current value corresponding to the no-load moment; wherein, the second predetermined current range is determined based on the second average current value and the error current value, and the second average current value is calculated based on the q-axis current value of the motor in a no-load state for multiple current cycles.

[0079] In an optional embodiment, the above-mentioned motion parameter is the number of motion steps, and the above-mentioned second determination module 36 includes: a first determination unit, which is used to determine that the athlete has completed a step on the treadmill and update the number of motion steps based on multiple characteristic moments in the characteristic data of the treadmill, namely, the start moment of the load mutation, the first load peak moment, the start moment of the heavy load stability, the end moment of the heavy load stability, the second load peak moment and the no-load moment; wherein, the start moment of the load mutation is used as the start moment of the athlete's movement on the treadmill.

[0080] In an optional embodiment, the above-mentioned motion parameter is motion mileage, and the above-mentioned second determination module 36 includes: a first calculation unit, used to calculate the time required for the athlete to complete a step on the treadmill according to the characteristic data of the treadmill; an acquisition unit, used to obtain the operating parameters of the motor when the athlete completes a step on the treadmill according to the required time; a second calculation unit, used to calculate the mileage required for the athlete to complete a step on the treadmill according to the operating parameters of the motor, and update the motion mileage.

[0081] In an optional embodiment, the above-mentioned motion parameter is motion speed, and the above-mentioned second determination module 36 includes: a third calculation unit, used to calculate the time required for the athlete to complete a step on the treadmill based on the characteristic data of the treadmill; a second determination unit, used to determine the mileage required for the athlete to complete a step on the treadmill; and a fourth calculation unit, used to calculate the motion speed of the athlete to complete a step on the treadmill based on the required time and mileage.

[0082] According to another aspect of an embodiment of the present invention, there is further provided an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute any one of the above method steps.

[0083] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. A method for determining motion parameters, characterized in that: include: Get the q-axis current value generated when the motor drives the treadmill; According to the q-axis current value, characteristic data of the treadmill in each current cycle is determined, wherein the characteristic data of the treadmill includes a plurality of characteristic moments and the q-axis current values ​​corresponding to the plurality of characteristic moments, and the plurality of characteristic moments constitute one current cycle of the motor completing a load mutation process; the plurality of characteristic moments at least include: a load mutation start moment, a first load peak moment, a heavy load stabilization start moment, a heavy load stabilization end moment, a second load peak moment, and a no-load moment; Determining the exercise parameters of the athlete on the treadmill according to the characteristic data of the treadmill; Among them, when the characteristic moment is the start moment of the heavy-load stabilization, according to the q-axis current value, the characteristic data of the treadmill in each current cycle is determined, including: judging whether the q-axis current value is in the first predetermined current range of the motor for multiple consecutive times; when the q-axis current value is in the first predetermined current range for multiple consecutive times, determining that the motor is in the start moment of the heavy-load stabilization, and using the q-axis current value as the q-axis current value corresponding to the start moment of the heavy-load stabilization; wherein, the first predetermined current range is determined based on a first average current value and an error current value, and the first average current value is calculated based on the q-axis current values ​​at multiple moments when the motor is in the heavy-load stable state.

2. The method according to claim 1, characterized in that When the characteristic moment is the load mutation start moment, determining characteristic data of the treadmill in each current cycle according to the q-axis current value includes: Determine whether the q-axis current value is greater than or equal to a first current threshold of the motor, wherein the first current threshold is the product of the q-axis current value of the motor in a no-load state and a first predetermined multiple; When the q-axis current value is less than the first current threshold, continue to determine whether the q-axis current value is greater than or equal to the first current threshold until the q-axis current value is greater than or equal to the first current threshold; When the q-axis current value is greater than or equal to the first current threshold, it is determined that the motor is at the load mutation starting moment, and the q-axis current value is used as the q-axis current value corresponding to the load mutation starting moment.

3. The method according to claim 1, characterized in that When the characteristic moment is the first load peak moment or the second load peak moment, determining characteristic data of the treadmill in each current cycle according to the q-axis current value includes: Determine whether the q-axis current value at the next moment is less than the q-axis current value at the previous moment; If the q-axis current value at the next moment is greater than or equal to the q-axis current value at the previous moment, then continue to determine whether the q-axis current value at the next moment is less than the q-axis current value at the previous moment, until the q-axis current value at the next moment is less than the q-axis current value at the previous moment; When the q-axis current value at the next moment is less than the q-axis current value at the previous moment, it is determined that the motor is at the first load peak moment or the second load peak moment, wherein, when the motor is at the first load peak moment, the q-axis current value at the previous moment is used as the q-axis current value corresponding to the first load peak moment; or, when the motor is at the second load peak moment, the q-axis current value at the previous moment is used as the q-axis current value corresponding to the second load peak moment.

4. The method according to claim 1, characterized in that: When the characteristic moment is the heavy load stabilization end moment, determining characteristic data of the treadmill in each current cycle according to the q-axis current value includes: Determine whether the q-axis current value is greater than or equal to a second current threshold of the motor, wherein the second current threshold is the product of an average q-axis current value corresponding to the motor being in a heavy-load stable state and a second predetermined multiple; When the q-axis current value is less than the second current threshold, continue to determine whether the q-axis current value is greater than or equal to the second current threshold until the q-axis current value is greater than or equal to the second current threshold; When the q-axis current value is greater than or equal to the second current threshold, it is determined that the motor is at the heavy load stabilization end time, and the q-axis current value is used as the q-axis current value corresponding to the heavy load stabilization end time.

5. The method according to claim 1, characterized in that When the characteristic moment is the no-load moment, determining characteristic data of the treadmill in each current cycle according to the q-axis current value includes: Determining whether the q-axis current value is within a second predetermined current range of the motor for multiple consecutive times; When the q-axis current value is within the second predetermined current range for multiple times in a row, determining that the motor is at the no-load moment, and using the q-axis current value as the q-axis current value corresponding to the no-load moment; The second predetermined current range is determined based on a second average current value and an error current value, and the second average current value is calculated based on q-axis current values ​​of the motor in a no-load state during multiple current cycles.

6. The method according to claim 1, characterized in that The motion parameter is the number of motion steps. According to the characteristic data of the treadmill, the motion parameter of the athlete on the treadmill is determined, including: According to the multiple characteristic moments in the characteristic data of the treadmill, namely, the start moment of the load mutation, the first load peak moment, the start moment of heavy load stabilization, the end moment of heavy load stabilization, the second load peak moment and the no-load moment, it is determined that the athlete has completed a step on the treadmill, and the number of movement steps is updated; wherein, the start moment of the load mutation is used as the start moment of the athlete's movement on the treadmill.

7. The method according to claim 1, characterized in that The exercise parameter is the exercise mileage. According to the characteristic data of the treadmill, the exercise parameter of the athlete on the treadmill is determined, including: Calculating the time required for the athlete to complete one step on the treadmill based on the characteristic data of the treadmill; According to the required time, obtaining the operating parameters of the motor when the athlete completes a step on the treadmill; The mileage of a step completed by the athlete on the treadmill is calculated based on the operating parameters of the motor, and the exercise mileage is updated.

8. The method according to claim 1, characterized in that: The motion parameter is the motion speed. According to the characteristic data of the treadmill, the motion parameter of the athlete on the treadmill is determined, including: Calculating the time required for the athlete to complete one step on the treadmill based on the characteristic data of the treadmill; Determining the mileage of a step completed by the athlete on the treadmill; The speed at which the athlete completes one step on the treadmill is calculated based on the required time and the mileage.

9. A motion parameter determination device, characterized in that: include: An acquisition module is used to obtain the q-axis current value generated when the motor drives the treadmill; A first determining module is used to determine the characteristic data of the treadmill in each current cycle according to the q-axis current value, wherein the characteristic data of the treadmill includes a plurality of characteristic moments and the q-axis current values ​​corresponding to the plurality of characteristic moments, and the plurality of characteristic moments constitute one current cycle of the motor completing a load mutation process; the plurality of characteristic moments at least include: a load mutation start moment, a first load peak moment, a heavy load stabilization start moment, a heavy load stabilization end moment, a second load peak moment, and a no-load moment; A second determination module is used to determine the exercise parameters of the athlete on the treadmill according to the characteristic data of the treadmill; Among them, the first determination module includes: a third judgment unit, used to judge whether the q-axis current value is in the first predetermined current range of the motor for multiple consecutive times when the characteristic moment is the start moment of the heavy load stabilization; a fifth processing unit, used to determine that the motor is at the start moment of the heavy load stabilization when the q-axis current value is in the first predetermined current range for multiple consecutive times, and use the q-axis current value as the q-axis current value corresponding to the start moment of the heavy load stabilization; wherein, the first predetermined current range is determined based on a first average current value and an error current value, and the first average current value is calculated based on the q-axis current values ​​at multiple moments when the motor is in the heavy load stable state.

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