Rowing motion data processing method and related device

Abstract

The embodiment of the present application provides a method for processing rowing motion data and a related device, wherein the method includes: obtaining the user's historical rowing data; determining multiple rowing ability characterization values ​​of multiple rowing ability indicators; determining the user's first rowing training level; determining the user's target rowing training mode and target rowing training environment; determining the dynamic behavior simulation parameters of the ship dynamic behavior simulation platform; and sending the dynamic behavior simulation parameters to the ship dynamic behavior simulation platform. The embodiment of the present application is used to analyze the user's historical rowing data through the human motion quantitative training system to determine the user's rowing ability level, and conduct targeted training on the user's rowing posture, rowing explosive power, and rowing endurance based on the rowing ability level, which is conducive to improving the user experience, and is conducive to improving the intelligence of the computing device in the human motion quantitative training system in processing rowing data.

Description

Technical Field

[0001] The present application belongs to the technical field of motion data processing, and specifically relates to a rowing motion data processing method and related devices. Background Art

[0002] Rowing is a water sport with high safety risks. If you are not proficient in rowing skills, it is easy to capsize when rowing on real complex water surfaces. At present, rowing training systems can only roughly simulate the behavior of boats in water by setting the simple vibration intensity of the simulation equipment. They cannot simulate different real water environments, nor can they provide targeted auxiliary rowing training for users. Summary of the invention

[0003] The embodiments of the present application provide a rowing motion data processing method and related devices, which determine the user's rowing ability level by analyzing the user's historical rowing data through a human motion quantified training system, and perform targeted training on the user's rowing posture, rowing explosive power, and rowing endurance based on the rowing ability level, which is beneficial to improving user experience and improving the intelligence of the computing device in the human motion quantified training system in processing rowing data.

[0004] In a first aspect, an embodiment of the present application provides a method for processing rowing motion data, which is applied to a computing device in a human motion quantitative training system, wherein the human motion quantitative training system comprises the computing device, a six-degree-of-freedom motion platform, a display device, and a voice broadcast device, wherein the computing device is respectively connected to the six-degree-of-freedom motion platform, the display device, and the voice broadcast device, and the six-degree-of-freedom motion platform comprises a ship dynamic behavior simulation platform; the method comprises:

[0005] Get the user's historical rowing data;

[0006] Determining a plurality of rowing ability characterization values ​​of a plurality of rowing ability indicators according to the historical rowing data, wherein the plurality of rowing ability indicators include at least two of the following: rowing explosive power, rowing posture coordination, rowing endurance, rowing posture accuracy, and number of rowing exercise participations;

[0007] determining a first rowing training level of the user according to the plurality of rowing capacity representation values;

[0008] determining a target rowing training mode and a target rowing training environment of the user according to the first rowing training level, the first rowing ability characterization value of the rowing explosive power, and the second rowing ability characterization value of the rowing endurance;

[0009] Determining dynamic behavior simulation parameters of the vessel dynamic behavior simulation platform according to the target rowing training environment and vessel data of a reference simulated vessel;

[0010] The dynamic behavior simulation parameters are sent to the vessel dynamic behavior simulation platform, and the vessel dynamic behavior simulation platform is used to simulate the behavior of the reference simulated vessel in the target rowing training environment according to the dynamic behavior simulation parameters.

[0011] In a second aspect, an embodiment of the present application provides a rowing motion data processing device, which is applied to a computing device in a human motion quantitative training system, wherein the human motion quantitative training system comprises the computing device, a six-degree-of-freedom motion platform, a display device, and a voice broadcast device, wherein the computing device is respectively connected to the six-degree-of-freedom motion platform, the display device, and the voice broadcast device, wherein the six-degree-of-freedom motion platform comprises a ship dynamic behavior simulation platform; the device comprises an acquisition unit, a determination unit, and a transmission unit; the device comprises an acquisition unit, a determination unit, and a prediction unit, wherein:

[0012] The acquisition unit is used to acquire the user's historical rowing data;

[0013] The determining unit is used to determine a plurality of rowing ability characterization values ​​of a plurality of rowing ability indicators according to the historical rowing data, wherein the plurality of rowing ability indicators include at least two of the following: rowing explosive power, rowing posture coordination, rowing endurance, rowing posture accuracy, and number of rowing exercise participations;

[0014] The determining unit is further configured to determine a first rowing training level of the user according to the plurality of rowing ability representation values;

[0015] The determining unit is further used to determine a target rowing training mode and a target rowing training environment of the user according to the first rowing training level, the first rowing ability characterization value of the rowing explosive power, and the second rowing ability characterization value of the rowing endurance;

[0016] The determination unit is further used to determine the dynamic behavior simulation parameters of the vessel dynamic behavior simulation platform according to the target rowing training environment and the vessel data of the reference simulated vessel;

[0017] The transmission unit is used to send the dynamic behavior simulation parameters to the ship dynamic behavior simulation platform, and the ship dynamic behavior simulation platform is used to simulate the behavior of the reference simulated ship in the target rowing training environment according to the dynamic behavior simulation parameters.

[0018] A third aspect of the present application provides a computing device, comprising: a processor and a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for some or all of the steps described in the first aspect.

[0019] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, wherein the computer program enables a computer to execute instructions of some or all of the steps described in the first aspect of the embodiment of the present application.

[0020] A fifth aspect of the embodiments of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the first aspect of the embodiments of the present application. The computer program product may be a software installation package.

[0021] It can be seen that in the embodiment of the present application, the computing device in the human motion quantification training system can first obtain the user's historical rowing data, and then determine multiple rowing ability characterization values ​​of multiple rowing ability indicators based on the historical rowing data, and the multiple rowing ability indicators include at least two of the following: rowing power, rowing posture coordination, rowing endurance, rowing posture accuracy, and number of rowing exercise participations, and then determine the user's first rowing training level based on the multiple rowing ability characterization values, and further, determine the user's target rowing training mode and target rowing training environment based on the first rowing training level, the first rowing ability characterization value of rowing power, and the second rowing ability characterization value of rowing endurance, and further, determine the dynamic behavior simulation parameters of the ship dynamic behavior simulation platform based on the target rowing training environment and the ship data of the reference simulated ship, and finally, send the dynamic behavior simulation parameters based on the ship dynamic behavior simulation platform, and the ship dynamic behavior simulation platform is used to simulate the behavior of the reference simulated ship in the target rowing training environment based on the dynamic behavior simulation parameters. The user's rowing ability level is determined by analyzing the user's historical rowing data through the computing device in the human motion quantified training system, and the user is given targeted training in rowing posture, rowing explosive power and rowing endurance based on the rowing ability level. This is beneficial to improving user experience and improving the intelligence of the computing device in the human motion quantified training system in processing rowing data. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1A It is a schematic diagram of the architecture of a human motion quantification training system provided in an embodiment of the present application;

[0024] Figure 1B is a schematic diagram of a display device provided in an embodiment of the present application;

[0025] Figure 1C It is a schematic diagram of the architecture of a ship dynamic behavior simulation platform provided in an embodiment of the present application;

[0026] Figure 1D is a schematic diagram of an inclined platform provided in an embodiment of the present application;

[0027] Figure 2 It is a flowchart of a method for processing rowing motion data provided by an embodiment of the present application;

[0028] Figure 3A It is a schematic diagram of a screen of a display device provided in an embodiment of the present application;

[0029] Figure 3B is a schematic diagram of an evaluation interface provided in an embodiment of the present application, and the schematic diagram of the interface is an evaluation interface displayed by a display device;

[0030] Figure 4 is a schematic diagram of the structure of a computing device provided in an embodiment of the present application;

[0031] Figure 5 It is a block diagram of the functional units of a rowing motion data processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0033] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0034] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0035] In the embodiments of the present application, "and / or" describes the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B can represent the following three situations: A exists alone; A and B exist at the same time; B exists alone. Among them, A and B can be singular or plural.

[0036] In the embodiment of the present application, the symbol " / " can indicate that the objects associated with each other are in an "or" relationship. In addition, the symbol " / " can also indicate a division sign, that is, performing a division operation. For example, A / B can indicate A divided by B.

[0037] In the embodiments of the present application, "at least one item" or similar expressions refer to any combination of these items, including any combination of single items or plural items, and refer to one or more, and multiple refers to two or more. For example, at least one item of a, b, or c can represent the following seven situations: a, b, c, a and b, a and c, b and c, a, b, and c. Among them, each of a, b, and c can be an element or a set containing one or more elements.

[0038] In the embodiments of the present application, "equal to" can be used in conjunction with greater than, and is applicable to the technical solution adopted when greater than, and can also be used in conjunction with less than, and is applicable to the technical solution adopted when less than. When equal to is used in conjunction with greater than, it is not used in conjunction with less than; when equal to is used in conjunction with less than, it is not used in conjunction with greater than.

[0039] In order to better understand the solutions of the embodiments of the present application, the electronic devices, related concepts and backgrounds that may be involved in the embodiments of the present application are first introduced below.

[0040] The electronic device of the application embodiment is a device with wireless communication function, which can be called terminal, user equipment (UE), mobile station (MS), mobile terminal (MT), access terminal equipment, vehicle-mounted terminal equipment, industrial control terminal equipment, UE unit, UE station, mobile station, remote station, remote terminal equipment, mobile device, UE terminal equipment, wireless communication equipment, UE agent or UE device, etc. The terminal device can be fixed or mobile. It should be noted that the terminal device can support at least one wireless communication technology, such as LTE, new radio (NR), wideband code division multiple access (WCDMA), etc. For example, the terminal device may be a mobile phone, a tablet computer (pad), a desktop computer, a laptop computer, an all-in-one computer, a vehicle-mounted terminal, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal in industrial control, a wireless terminal in self driving, a wireless terminal in remote medical surgery, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, a wireless terminal in a smart home, a cellular phone, a cordless phone, a session initiation protocol (SIP) phone, a wireless local loop (WLL) station, a personal digital assistant (PDA), a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a wearable device, a terminal device in a future mobile communication network, or a terminal device in a future evolved public mobile land network (PLMN), etc. The electronic device may be a computing device in a human motion quantification training system.

[0041] See also Figure 1A , Figure 1A Schematic diagram of the structure of a human motion quantitative training system provided by an embodiment of the present application. Figure 1AAs shown, the human motion quantitative training system 1 includes a six-degree-of-freedom motion platform 10, a display device 20, a voice broadcasting device 30 and a computing device 40. The six-degree-of-freedom motion platform 10 includes a ship dynamic behavior simulation platform 11, and the computing device 40 is respectively connected to the six-degree-of-freedom motion platform 10, the display device 20 and the voice broadcasting device 30.

[0042] The display device 20 can play the virtual character created by the user sliding the oar to drive the virtual boat to move on the water surface. The virtual character can be a digital person, which is not limited here. The action of the virtual character is synchronized with the action of the user. The voice broadcast device 30 can play the audio of the virtual boat moving on the water surface, such as: the sound generated by the oar contacting the water surface, the sound of the water flow, the sound generated by the water flow contacting the boat, etc.

[0043] Among them, see Figure 1B , Figure 1B It is a schematic diagram of a display device provided in an embodiment of the present application, wherein the display device displays a simulated rowing picture, which includes a character created by a user, a water surface, a boat floating on the water surface, and oars, and the user's movements are synchronized with those of the character.

[0044] The computing device 40 may be a server, a terminal device, a host computer at a user simulation training site, etc., which is not limited here. The computing device 40 may actually model and create a reference simulation ship based on the real data of the ship, and at the same time model and create different water surface environments, for example: a water depth of 150 cm, a water flow speed of 30 cm per second, a water surface slope of 3°, a water surface width of 5 meters, a length of 2 km, obstacles, etc.

[0045] Among them, see Figure 1C , Figure 1C 1 is a schematic diagram of the architecture of a ship dynamic behavior simulation platform provided by an embodiment of the present application. The ship dynamic behavior simulation platform 11 includes a tilting platform 111, a seat 112 and a stretching device 113. The tilting platform 111 is used to simulate the movement behavior of the reference simulated ship in the vertical and horizontal directions on the water surface. For example, the reference simulated ship is first raised by 3 cm, then lowered by 5 cm, and then raised by 2 cm on the water surface. In this process, the tilting platform 111 first tilts 5° to the front side, then tilts 8.8° to the rear side, and then tilts 4.8° to the front side. At the same time, the tilting platform 111 first tilts 4° to the right, then tilts 8° to the left, and then tilts 8° to the right; the seat 112 is used to simulate the reference simulated ship, and the seat 112 can be installed and fixed on the tilting platform. The tilting platform 111 tilts at a certain angle, and the seat 112 also tilts at a certain angle; the stretching device 113 may include a fixing structure 1131 and a tension belt 1132, and the user can pull the tension belt to simulate the user pulling the oar. Optionally, the stretching device 113 includes a tension sensor, and the tension sensor can collect the user's tension; please refer to Figure 1D , Figure 1D It is a schematic diagram of an inclined platform provided in an embodiment of the present application, in which the inclined platform 111 is inclined toward the front side, and the seat 112 is fixed on the inclined platform 111 and inclined at the same angle as the inclined platform 111.

[0046] Wherein, a vibration device is installed on the seat 112, and the vibration device is used for simulating the vibration of the reference simulated ship when the water flow impacts the reference simulated ship.

[0047] Among them, the human motion quantification training system 1 may include a motion capture device 50, which is communicatively connected to the computing device 40. The motion capture device 50 can collect the user's rowing motion posture data and send the motion posture data to the computing device 40.

[0048] The stretching device 113 may also include a rowing ergometer, which is used to record the peak power of the rower. The peak power reflects the power output of the rower. The greater the peak power, the greater the power output of the rower.

[0049] In one possible example, the computing device 40 in the human motion quantitative training system 1 may first obtain the user's historical rowing data, and the computing device 40 then determines multiple rowing ability characterization values ​​of multiple rowing ability indicators based on the historical rowing data, and the multiple rowing ability indicators include at least two of the following: rowing power, rowing posture coordination, rowing endurance, rowing posture accuracy, and number of rowing exercise participations. The computing device 40 then determines the user's first rowing training level based on the multiple rowing ability characterization values. Further, the computing device 40 determines the user's target rowing training mode and target rowing training environment based on the first rowing training level, the first rowing ability characterization value of the rowing power, and the second rowing ability characterization value of the rowing endurance. Further, the computing device 40 determines the dynamic behavior simulation parameters of the ship dynamic behavior simulation platform based on the target rowing training environment and the ship data of the reference simulated ship. Finally, the computing device 40 sends the dynamic behavior simulation parameters to the ship dynamic behavior simulation platform, and the ship dynamic behavior simulation platform is used to simulate the behavior of the reference simulated ship under the target rowing training environment based on the dynamic behavior simulation parameters. The computing device 40 of the human motion quantified training system 1 analyzes the user's historical rowing data to determine the user's rowing ability level, and performs targeted training on the user's rowing posture, rowing explosive power and rowing endurance based on the rowing ability level, which is beneficial to improving the user experience and the intelligence of the computing device in the human motion quantified training system in processing rowing data.

[0050] See also Figure 2 , Figure 2The present invention is a flow chart of a method for processing rowing motion data provided by an embodiment of the present invention, which is applied to a computing device in a human motion quantitative training system, wherein the human motion quantitative training system comprises the computing device, a six-degree-of-freedom motion platform, a display device, and a voice broadcast device, wherein the computing device is respectively connected to the six-degree-of-freedom motion platform, the display device, and the voice broadcast device, wherein the six-degree-of-freedom motion platform comprises a ship dynamic behavior simulation platform, and the method comprises:

[0051] Step S201, obtaining the user's historical rowing data.

[0052] Among them, historical rowing data includes boat data, rowing motion data, and water surface environment data. Boat data includes boat size, total weight, material, and oars. For example, the boat is 7.3 meters long, 0.51 meters wide, weighs 50kg, and weighs 900g and 2.13m long. Water surface environment data includes water surface width, water surface length, water flow speed, water surface wave size, water surface wave frequency, water surface wave direction, obstacles, etc. Rowing motion data includes the number of rowing motion participations, left arm pulling force, left arm pulling force direction, right arm pulling force, right arm pulling force direction, stretching speed, completion time, rowing speed, rowing posture data, oar frequency, starting acceleration, and rowing peak power.

[0053] For example, the water surface environment data are: water surface width 10m, water surface length 5km, water surface wave direction is due north, water flow speed is 1.5m per second, water surface wave height is 3cm, and water surface wave frequency is 0.1Hz.

[0054] Step S202, determining a plurality of rowing ability characterization values ​​of a plurality of rowing ability indicators according to the historical rowing data, wherein the plurality of rowing ability indicators include at least two of the following: rowing explosive power, rowing posture coordination, rowing endurance, rowing posture accuracy, and number of rowing exercise participation times.

[0055] Among them, the starting acceleration can be calculated, for example: starting acceleration a=F1 / m, F1 represents the resultant external force, m represents the total weight of the user and the reference simulated ship, the resultant external force F1=F2-μmg, F2 represents the pulling force of the user's arms, μ represents the dynamic friction factor between the reference simulated ship and the water surface, and g represents the acceleration of gravity.

[0056] Among them, the rowing capacity characterization value of rowing explosive power can be determined according to the starting acceleration and the rowing peak power. The greater the starting acceleration, the greater the rowing peak power, and the greater the rowing capacity characterization value of rowing explosive power.

[0057] Among them, the rowing ability representation value of the rowing posture coordination can be determined by the left arm pulling direction, the right arm pulling direction and the rowing posture data. The higher the consistency between the left arm pulling direction and the right arm pulling direction, the greater the rowing ability representation value of the rowing posture coordination. The more balanced and stable the user's body is according to the rowing posture data analysis, the better the rowing posture coordination is, and the greater the corresponding rowing ability representation value is.

[0058] Among them, the rowing ability representation value of rowing endurance can be determined according to the water surface length and the completion time. When the water surface length is long, for example: 5km, 10km, the user can complete it, and the shorter the completion time is, the stronger the rowing endurance is, and the larger the corresponding rowing ability representation value is.

[0059] Among them, the accuracy of rowing posture can be obtained by comparing and analyzing the rowing posture data and the reference posture. The higher the consistency between the user's rowing posture and the reference posture, the higher the accuracy of the rowing posture, and the greater the corresponding rowing ability representation value.

[0060] The number of times the user participates in rowing exercise may be the sum of the number of times the user actually participates in rowing exercise and the number of times the user participates in simulated rowing training. The more times the user participates in rowing exercise, the greater the corresponding rowing ability representation value.

[0061] Step S203: determining a first rowing training level of the user according to the multiple rowing ability representation values.

[0062] Among them, the higher the first rowing training level, the higher the user's rowing skill proficiency and the more rowing experience; the first rowing training level includes the beginner level and the real-life training level. If the user is at the beginner level, it means that the user is a beginner, has an unstandard rowing posture, and has extremely poor rowing skills, and needs to practice the rowing posture first; if the user is at the real-life training level, it means that the user has a certain level of proficiency in rowing posture and can perform actual operation exercises.

[0063] Step S204: determining a target rowing training mode and a target rowing training environment of the user according to the first rowing training level, the first rowing ability characterization value of the rowing explosive power, and the second rowing ability characterization value of the rowing endurance.

[0064] Among them, the rowing training mode includes teaching training mode and real-life simulation training mode. The teaching training mode mainly teaches users' rowing posture and rowing skills, while the real-life simulation training mode mainly further trains users' rowing explosiveness, endurance and rowing skills.

[0065] Among them, different rowing training environments specifically refer to different water surface environments; the higher the user's first rowing training level, the more complex rowing training environment can be assigned, for example: faster water flow, greater wave fluctuations, and more obstacles.

[0066] Among them, when the user's rowing explosive power is poor, that is, the first rowing ability representation value of rowing explosive power is low, a rowing training environment for targeted training of rowing explosive power can be allocated; when the user's rowing endurance is poor, that is, the second rowing ability representation value of rowing endurance is low, a rowing training environment for targeted training of rowing endurance can be allocated.

[0067] Step S205, determining the dynamic behavior simulation parameters of the vessel dynamic behavior simulation platform according to the target rowing training environment and the vessel data of the reference simulated vessel.

[0068] The dynamic behavior simulation parameters include the shaking parameters of the tilting platform and the vibration parameters of the vibration device.

[0069] Step S206, sending the dynamic behavior simulation parameters to the vessel dynamic behavior simulation platform, and the vessel dynamic behavior simulation platform is used to simulate the behavior of the reference simulated vessel in the target rowing training environment according to the dynamic behavior simulation parameters.

[0070] It can be seen that in the embodiment of the present application, the computing device in the human motion quantification training system can first obtain the user's historical rowing data, and then determine multiple rowing ability characterization values ​​of multiple rowing ability indicators based on the historical rowing data, and the multiple rowing ability indicators include at least two of the following: rowing power, rowing posture coordination, rowing endurance, rowing posture accuracy, and number of rowing exercise participations, and then determine the user's first rowing training level based on the multiple rowing ability characterization values, and further, determine the user's target rowing training mode and target rowing training environment based on the first rowing training level, the first rowing ability characterization value of rowing power, and the second rowing ability characterization value of rowing endurance, and further, determine the dynamic behavior simulation parameters of the ship dynamic behavior simulation platform based on the target rowing training environment and the ship data of the reference simulated ship, and finally, send the dynamic behavior simulation parameters based on the ship dynamic behavior simulation platform, and the ship dynamic behavior simulation platform is used to simulate the behavior of the reference simulated ship in the target rowing training environment based on the dynamic behavior simulation parameters. The user's rowing ability level is determined by analyzing the user's historical rowing data through the computing device in the human motion quantified training system, and the user is given targeted training in rowing posture, rowing explosive power and rowing endurance based on the rowing ability level. This is beneficial to improving user experience and improving the intelligence of the computing device in the human motion quantified training system in processing rowing data.

[0071] In one possible example, in terms of determining the first rowing training level of the user based on the multiple rowing ability characterization values, the above method may include the following steps: when the third rowing ability characterization value of the number of rowing exercise participation times is less than a first preset threshold or the fourth rowing ability characterization value of the rowing posture accuracy is less than a second preset threshold, determining the beginner level of the user, and using the beginner level as the first rowing training level of the user; when the third rowing ability characterization value is greater than or equal to the first preset threshold and the fourth rowing ability characterization value is greater than or equal to the second preset threshold, determining multiple weight coefficients of the multiple rowing ability indicators; and, determining a target rowing ability characterization value based on the multiple weight coefficients and the multiple rowing ability characterization values; and, determining the user's real-life training level based on the target rowing ability characterization value and a plurality of pre-stored preset rowing ability characterization value intervals, and using the real-life training level as the user's first rowing training level.

[0072] The first preset threshold and the second preset threshold can be manually set or the system defaults to be unrestricted. For example, if the third rowing capacity characterization value ranges from 0 to 100 and the fourth rowing capacity characterization value ranges from 0 to 100, the first preset threshold can be 20 and the second preset threshold can be 60.

[0073] Among them, when the number of rowing participation is too small, it means that the user is new to rowing. Considering that rowing is risky, it is easy to capsize and drown. Therefore, these users need to be taught and trained on rowing posture first; if the accuracy of rowing posture is too low, it means that the user is also new to rowing, the posture is not standard, and it is easy to capsize. Therefore, it is also necessary to teach and train on rowing posture first. When the third rowing ability representation value of the user's rowing participation number is greater than or equal to the first preset threshold and the fourth rowing ability representation value of the rowing posture accuracy is greater than or equal to the second preset threshold, it means that the user has a certain proficiency in rowing skills and can simulate rowing training in real scenes.

[0074] Among them, different weights can be set for rowing ability indicators. For example, the weights of rowing explosive power, rowing posture coordination, rowing endurance, rowing posture accuracy and number of rowing exercise participation are 1:2:1:3:3.

[0075] Among them, multiple preset rowing ability representation value intervals correspond to different real-life training levels, for example: 10-30 corresponds to E level, 40-60 corresponds to D level, 60-70 corresponds to C level, 70-80 corresponds to B level, 80-90 corresponds to A level, 90-100 corresponds to A+ level, and the levels from low to high are E, D, C, B, A and A+.

[0076] It can be seen that in this example, the computing device can distinguish between the beginner level and the real-life training level based on the fourth rowing ability characterization value of boat posture accuracy and the third rowing ability characterization value of the number of rowing exercise participation times, which is beneficial for subsequent targeted rowing posture training for users, or rowing endurance and rowing explosive power training for users, which is beneficial for improving user experience and the intelligence of the computing device in processing rowing data.

[0077] In a possible example, the target rowing training mode and the target rowing training environment of the user are determined according to the first rowing training level, the first rowing ability characterization value of the rowing explosive power and the second rowing ability characterization value of the rowing endurance. The above method may include the following steps: when the first rowing training level is the beginner level, the target rowing training mode is determined to be the teaching training mode, and the target rowing training environment is determined to be the teaching training environment; when the first rowing training level is the real-life training level, the target rowing training mode is determined to be the real-life simulation training mode, and a target difficulty level is determined according to the first rowing training level; a plurality of first rowing training environments corresponding to the target difficulty level are determined; at least one second rowing training environment is screened out from the plurality of first rowing training environments according to the first rowing ability characterization value and the second rowing ability characterization value, and the at least one second rowing training environment is used as the target rowing training environment.

[0078] Among them, the teaching training mode mainly teaches users rowing postures, which include seated rowing, barbell rowing posture, one-arm dumbbell rowing, reverse rowing posture, etc. When the user practices the rowing posture, the computing device can obtain the text teaching information and teaching audio corresponding to the rowing posture, and send the text teaching information to the display device, the display device can display the text teaching information, and send the teaching audio to the voice broadcast device, and the voice broadcast device plays the teaching audio.

[0079] See also Figure 3A , Figure 3A It is a screen diagram of a display device provided by an embodiment of the present application, and the screen shows a character, a boat, a paddle, and text teaching information for seated rowing, and the text teaching information for seated rowing is: Starting position: fix your feet on the pedals, bend your knees slightly, and keep your back straight. Hold the paddle with both hands, and adjust the grip distance according to personal comfort. Action process: Use the strength of your back and arms to pull the handle toward your body, while leaning your back back and feeling the contraction of your back muscles. Pause at the top, and then slowly control the handle to return to the starting position. Note: Keep your body stable and avoid shaking or twisting. Pay attention to breathing coordination and avoid holding your breath.

[0080] Among them, compared with the training environment corresponding to the real-life simulation training mode, the teaching training environment has a lower water flow speed, smaller water surface waves, no obstacles, and a low risk of capsizing of the reference simulated ship.

[0081] Among them, rowing training environments of different difficulty levels can be allocated according to the first rowing training level, for example, the difficulty level from low to high can be one star, two stars, three stars, four stars and five stars, E level and D level are allocated one star difficulty level, C level is allocated two stars difficulty level, B level is allocated three stars difficulty level, A level is allocated four stars difficulty level, and A+ level is allocated five stars difficulty level. A single difficulty level corresponds to a plurality of first rowing training environments with different water surface lengths, for example, the water surface lengths are 500m, 1000m, 1500m, 2000m, 2500m, 3000m, 4000m and 5000m, and the plurality of first rowing training environments have the same water surface width, the same water flow speed, the same water surface wave size, the same water surface wave frequency, and the same water surface wave direction.

[0082] The selected second rowing training environment is used to train the user's rowing explosiveness and / or rowing endurance.

[0083] It can be seen that in this example, the computing device determines the corresponding target rowing training environment according to the user's first rowing training level, and assists the user in performing targeted training of rowing posture, rowing explosive power, and rowing endurance, which is conducive to improving user experience and the intelligence of the computing device in processing rowing data.

[0084] In one possible example, in terms of selecting at least one second rowing training environment from the plurality of first rowing training environments according to the first rowing ability characterization value and the second rowing ability characterization value, the method may include the following steps: if the first rowing ability characterization value is less than a third preset threshold value and the second rowing ability characterization value is greater than or equal to a fourth preset threshold value, selecting at least one third rowing training environment whose water surface length is less than a first preset distance from the plurality of first rowing training environments, and using the at least one third rowing training environment as the at least one second rowing training environment; if the first rowing ability characterization value is greater than or equal to the third preset threshold value and the second rowing ability characterization value is greater than or equal to the fourth preset threshold value, selecting at least one third rowing training environment whose water surface length is less than a first preset distance from the plurality of first rowing training environments, and using the at least one third rowing training environment as the at least one second rowing training environment; If the second rowing ability characterization value is less than the fourth preset threshold, at least one fourth rowing training environment whose water surface length is greater than or equal to the second preset distance is screened out from the multiple first rowing training environments, and the at least one fourth rowing training environment is used as the at least one second rowing training environment; if the first rowing ability characterization value is less than the third preset threshold and the second rowing ability characterization value is less than the fourth preset threshold, at least one fifth rowing training environment excluding the third rowing training environment and the fourth rowing training environment is screened out from the multiple first rowing training environments, and the at least one fifth rowing training environment is used as the at least one second rowing training environment.

[0085] Among them, the third preset threshold and the fourth preset threshold can be set manually or by system default, and are not limited here. For example, the range of the first rowing capacity characterization value is 0-100, the range of the second rowing capacity characterization value is 0-100, the third preset threshold is 70, and the fourth preset threshold is 60.

[0086] The first preset distance and the second preset distance can be considered as settings or system defaults, which are not limited here, and the second preset distance is greater than the first preset distance. For example, the first preset distance is 1000m, and the second preset distance is 3000m.

[0087] Among them, the first rowing ability characterization value is less than the third preset threshold and the second rowing ability characterization value is greater than or equal to the fourth preset threshold, which indicates that the user's rowing explosive power is poor. A third rowing training environment with a short distance can be selected, and the user trains for rowing explosive power. For example, a third rowing training environment with a water surface length of 500m and 1000m is selected.

[0088] Among them, if the first rowing ability characterization value is greater than or equal to the third preset threshold and the second rowing ability characterization value is less than the fourth preset threshold, it means that the user's rowing endurance is poor, and the fourth rowing training environment with long distance can be selected. The long-distance rowing training on the surface of the water pays more attention to the stable paddling frequency and speed. The user trains for rowing endurance, for example: selects the fourth rowing training environment with a surface length of 3000m, 4000m and 5000m.

[0089] Among them, the first rowing ability characterization value is less than the third preset threshold value and the second rowing ability characterization value is less than the fourth preset threshold value, indicating that the user's rowing endurance and rowing explosive power are relatively poor, and the fifth rowing training environment of middle distance can be selected. The user trains for rowing explosive power and rowing endurance at the same time, for example: selecting the fifth rowing training environment with a water surface length of 1500m, 2000m and 2500m.

[0090] It can be seen that in this example, the computing device can analyze the user's rowing endurance and rowing explosive power capabilities, and conduct targeted training on rowing endurance and rowing explosive power, which is beneficial to improving user experience and improving the intelligence of the computing device in processing rowing data.

[0091] In one possible example, in terms of determining the dynamic behavior simulation parameters of the vessel dynamic behavior simulation platform based on the target rowing training environment and the vessel data of the reference simulated vessel, the above method may include the following steps: determining the target sway behavior of the reference simulated vessel based on the target rowing training environment and the vessel data; determining the target sway parameters and vibration intensity parameters of the vessel dynamic behavior simulation platform based on the target sway behavior, and using the target sway parameters and the vibration intensity parameters as the dynamic behavior simulation parameters of the reference simulated vessel.

[0092] The target swaying behavior is the periodic swaying behavior of the reference simulated ship under the influence of the target simulated environment.

[0093] Among them, the target swaying behavior can be swaying periodically according to a certain trajectory, for example: the reference simulation ship first tilts 4° to the front end, and tilts 3° to the right end at the same time, holds for 3 seconds, then tilts 4° successively, and tilts 3° to the left end at the same time, returns to the original state after holding for 2 seconds, then tilts 4° to the front end, and tilts 3° to the right end at the same time, holds for 3 seconds, then tilts 4° successively, and tilts 3° to the left end at the same time, returns to the original state after holding for 2 seconds. Then the target swaying parameter tilting platform first tilts 4° to the front end, and tilts 3° to the right end at the same time, holds for 3 seconds, then tilts 4° successively, and tilts 3° to the left end at the same time, returns to the original state after holding for 2 seconds.

[0094] The vibration parameters include vibration frequency parameters and vibration intensity parameters.

[0095] Among them, the greater the tilt degree of the reference simulated ship caused by the target shaking behavior, the greater the wave impact on the reference simulated ship, and the corresponding greater the vibration intensity and vibration frequency of the reference simulated ship; the vibration intensity can be divided into five levels, from low to high: 1, 2, 3, 4 and 5.

[0096] The vibration and shaking occur simultaneously. For example, when the reference simulated ship tilts 4° to the front and 3° to the right for 3 seconds, the waves continue to hit the ship and the vibration of the reference simulated ship continues to exist.

[0097] It can be seen that in this example, the computing device can determine the target sway behavior of the reference simulated ship in the target simulation training environment, and determine the target sway parameters and vibration intensity parameters of the ship dynamic behavior simulation platform based on the target sway behavior. The ship dynamic behavior simulation platform executes the target sway parameters and vibration intensity parameters to realize the simulated target sway behavior, which is beneficial to improving the user's real experience and improving the intelligence of the computing device in processing rowing data.

[0098] In a possible example, after sending the dynamic behavior simulation parameters to the ship dynamic behavior simulation platform, the method may include the following steps: acquiring the user's current motion data in the teaching training environment; determining the proficiency of each rowing teaching action based on the motion data; and adjusting the first rowing training level based on the proficiency of each rowing teaching action to obtain a second rowing training level.

[0099] Among them, the motion data includes motion posture data, left arm tension data and right arm tension data collected by the motion capture device. The left arm tension data includes the left arm tension size and the left arm tension direction, and the right arm tension data includes the right arm tension size and the right arm tension direction.

[0100] Among them, when it is found out based on the motion data that the user's rowing teaching posture is standard and the left and right arms are well coordinated, it means that the user has a high level of proficiency in rowing teaching movements, and the user's rowing training level can be improved, and the beginner level can be adjusted to the real-life training level.

[0101] Among them, when the proficiency of each rowing teaching action is greater than or equal to the seventh preset threshold, it can be said that the user's proficiency in rowing teaching actions is high, and the user's beginner level can be adjusted to the lowest level of the real-life training level.

[0102] The server can evaluate the user's left and right arm coordination, movement posture, rowing explosiveness, and rowing endurance, and generate a corresponding evaluation interface based on the evaluated data. The user can view the corresponding evaluation data by selecting a specific evaluation function module in the evaluation interface displayed on the display device; please refer to Figure 3B , Figure 3B It is a schematic diagram of an evaluation interface provided in an embodiment of the present application. The interface schematic diagram is an evaluation interface displayed by a display device, and has five evaluation function modules for users to choose from, including left arm and right arm coordination evaluation, movement posture evaluation, rowing explosive power evaluation, rowing endurance evaluation and more evaluations.

[0103] It can be seen that in this example, the computing device assists the user in training each teaching movement posture, and combines the user's movement posture data, left arm tension data and right arm tension data to determine the user's proficiency in each rowing teaching movement to adjust the user's rowing training level, which is conducive to improving the intelligence of the computing device in processing rowing data.

[0104] In a possible example, in determining the proficiency of each rowing teaching action based on the motion data, the method may include the following steps: determining the matching degree of each rowing teaching action based on the action posture data and the reference posture data; determining the force coordination characterization value of each rowing teaching action based on the left arm tension data and the right arm tension data; determining a target number of times for each rowing teaching action in which the matching degree is greater than or equal to a fifth preset threshold and the force coordination characterization value is greater than or equal to a sixth preset threshold; and determining the proficiency of each rowing teaching action based on the target number of times.

[0105] The reference posture data is data of standard rowing teaching action posture collected in advance by a motion capture device. The action posture data and the reference posture data can be compared. The higher the matching degree between the two, the more standard the user's action posture is.

[0106] Among them, the higher the consistency between the left arm pulling force and the right arm pulling force in the rowing teaching action, and the higher the consistency between the left arm pulling force direction and the right arm pulling force direction, the higher the coordination of the left and right arms of the user in training the rowing teaching action, and the greater the corresponding force coordination representation value.

[0107] The fifth preset threshold value may be manually set or set by the system by default, and is not limited here. For example, if the range of the matching degree is 0%-100%, the fifth preset threshold value may be 90%.

[0108] Among them, the sixth preset threshold can be set manually or by system default, and is not limited here. For example, if the range of the force coordination representation value is 0-100, the sixth preset threshold can be 85.

[0109] Among them, the more target times, the higher the proficiency of the rowing teaching action trained by the user. Multiple completion number intervals can be set, and each completion number interval corresponds to a proficiency. For example, 1-4 target times correspond to 0% proficiency, 5-9 target times correspond to 5% proficiency, 10-19 target times correspond to 10% proficiency, 20-29 target times correspond to 20% proficiency, 30-39 target times correspond to 30% proficiency, 40-49 target times correspond to 40% proficiency, 50-59 target times correspond to 50% proficiency, 60-69 target times correspond to 60% proficiency, 70-79 target times correspond to 70% proficiency, 80-89 target times correspond to 80% proficiency, 90-99 target times correspond to 90% proficiency, and 100 and above target times correspond to 100% proficiency.

[0110] It can be seen that in this example, the computing device can determine the user's proficiency in rowing teaching movements based on the action posture data, left arm tension data, and right arm tension data, which is conducive to improving the intelligence of the computing device in processing rowing data.

[0111] See also Figure 4 , Figure 4 is a structural schematic diagram of a computing device provided in an embodiment of the present application, which is applied to a computing device in a human motion quantification training system, wherein the human motion quantification training system comprises the computing device, a six-degree-of-freedom motion platform, a display device and a voice broadcast device, wherein the computing device is respectively connected to the six-degree-of-freedom motion platform, the display device and the voice broadcast device, and the six-degree-of-freedom motion platform comprises a ship dynamic behavior simulation platform; Figure 4 As shown, the computing device includes a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs are configured to execute the following steps by the processor:

[0112] Get the user's historical rowing data;

[0113] Determining a plurality of rowing ability characterization values ​​of a plurality of rowing ability indicators according to the historical rowing data, wherein the plurality of rowing ability indicators include at least two of the following: rowing explosive power, rowing posture coordination, rowing endurance, rowing posture accuracy, and number of rowing exercise participations;

[0114] determining a first rowing training level of the user according to the plurality of rowing capacity representation values;

[0115] determining a target rowing training mode and a target rowing training environment of the user according to the first rowing training level, the first rowing ability characterization value of the rowing explosive power, and the second rowing ability characterization value of the rowing endurance;

[0116] Determining dynamic behavior simulation parameters of the vessel dynamic behavior simulation platform according to the target rowing training environment and vessel data of a reference simulated vessel;

[0117] The dynamic behavior simulation parameters are sent to the vessel dynamic behavior simulation platform, and the vessel dynamic behavior simulation platform is used to simulate the behavior of the reference simulated vessel in the target rowing training environment according to the dynamic behavior simulation parameters.

[0118] It can be seen that in the embodiment of the present application, the computing device in the human motion quantification training system can first obtain the user's historical rowing data, and then determine multiple rowing ability characterization values ​​of multiple rowing ability indicators based on the historical rowing data, and the multiple rowing ability indicators include at least two of the following: rowing power, rowing posture coordination, rowing endurance, rowing posture accuracy, and number of rowing exercise participations, and then determine the user's first rowing training level based on the multiple rowing ability characterization values, and further, determine the user's target rowing training mode and target rowing training environment based on the first rowing training level, the first rowing ability characterization value of rowing power, and the second rowing ability characterization value of rowing endurance, and further, determine the dynamic behavior simulation parameters of the ship dynamic behavior simulation platform based on the target rowing training environment and the ship data of the reference simulated ship, and finally, send the dynamic behavior simulation parameters based on the ship dynamic behavior simulation platform, and the ship dynamic behavior simulation platform is used to simulate the behavior of the reference simulated ship in the target rowing training environment based on the dynamic behavior simulation parameters. The user's rowing ability level is determined by analyzing the user's historical rowing data through the computing device in the human motion quantified training system, and the user is given targeted training in rowing posture, rowing explosive power and rowing endurance based on the rowing ability level. This is beneficial to improving user experience and improving the intelligence of the computing device in the human motion quantified training system in processing rowing data.

[0119] In a possible example, in determining the first rowing training level of the user according to the plurality of rowing capacity representation values, the program includes instructions for executing the following steps:

[0120] When the third rowing ability characterization value of the rowing exercise participation number is less than a first preset threshold or the fourth rowing ability characterization value of the rowing posture accuracy is less than a second preset threshold, determining the beginner level of the user, and using the beginner level as the first rowing training level of the user;

[0121] When the third rowing ability characterization value is greater than or equal to the first preset threshold and the fourth rowing ability characterization value is greater than or equal to the second preset threshold, determining a plurality of weight coefficients of the plurality of rowing ability indicators; and,

[0122] determining a target rowing capacity characterization value according to the plurality of weight coefficients and the plurality of rowing capacity characterization values; and,

[0123] The real-life training level of the user is determined according to the target rowing capacity characterization value and a plurality of pre-stored preset rowing capacity characterization value intervals, and the real-life training level is used as the first rowing training level of the user.

[0124] In one possible example, in determining the target rowing training mode and the target rowing training environment of the user according to the first rowing training level, the first rowing ability characterization value of the rowing explosive power, and the second rowing ability characterization value of the rowing endurance, the program includes instructions for executing the following steps:

[0125] When the first rowing training level is the beginner level, determining the target rowing training mode to be a teaching training mode, and determining the target rowing training environment to be a teaching training environment;

[0126] When the first rowing training level is the real-scene training level, determining the target rowing training mode to be the real-scene simulation training mode, and determining a target difficulty level according to the first rowing training level;

[0127] determining a plurality of first rowing training environments corresponding to the target difficulty level;

[0128] At least one second rowing training environment is selected from the plurality of first rowing training environments according to the first rowing capacity characterization value and the second rowing capacity characterization value, and the at least one second rowing training environment is used as the target rowing training environment.

[0129] In one possible example, in the aspect of selecting at least one second rowing training environment from the plurality of first rowing training environments according to the first rowing capacity representation value and the second rowing capacity representation value, the program includes instructions for executing the following steps:

[0130] If the first rowing ability characterization value is less than a third preset threshold and the second rowing ability characterization value is greater than or equal to a fourth preset threshold, at least one third rowing training environment having a water surface length less than a first preset distance is selected from the plurality of first rowing training environments, and the at least one third rowing training environment is used as the at least one second rowing training environment;

[0131] If the first rowing ability characterization value is greater than or equal to the third preset threshold and the second rowing ability characterization value is less than the fourth preset threshold, selecting at least one fourth rowing training environment whose water surface length is greater than or equal to the second preset distance from the plurality of first rowing training environments, and using the at least one fourth rowing training environment as the at least one second rowing training environment;

[0132] If the first rowing capacity characterization value is less than the third preset threshold and the second rowing capacity characterization value is less than the fourth preset threshold, at least one fifth rowing training environment other than the third rowing training environment and the fourth rowing training environment is screened out from the multiple first rowing training environments, and the at least one fifth rowing training environment is used as the at least one second rowing training environment.

[0133] In a possible example, in determining the dynamic behavior simulation parameters of the vessel dynamic behavior simulation platform according to the target rowing training environment and the vessel data of the reference simulated vessel, the program further includes instructions for executing the following steps:

[0134] determining a target swaying behavior of the reference simulated vessel according to the target rowing training environment and the vessel data;

[0135] According to the target sloshing behavior, target sloshing parameters and vibration intensity parameters of the ship dynamic behavior simulation platform are determined, and the target sloshing parameters and the vibration intensity parameters are used as dynamic behavior simulation parameters of the reference simulated ship.

[0136] In a possible example, after sending the dynamic behavior simulation parameters to the ship dynamic behavior simulation platform, the program further includes instructions for executing the following steps:

[0137] Acquire the user's current motion data in the teaching and training environment, the motion data including action posture data, left arm tension data, and right arm tension data;

[0138] Determining the proficiency of each rowing teaching action according to the motion data;

[0139] According to the proficiency of each rowing teaching action, the first rowing training level is adjusted to obtain a second rowing training level.

[0140] In a possible example, the proficiency of each rowing teaching action is determined according to the motion data, and the program further includes instructions for executing the following steps:

[0141] Determining the matching degree of each rowing teaching action according to the action posture data and the reference posture data;

[0142] Determine a force coordination representation value of each rowing teaching action according to the left arm pulling force data and the right arm pulling force data;

[0143] Determine a target number of times for each rowing teaching action in which the matching degree is greater than or equal to a fifth preset threshold and the force coordination representation value is greater than or equal to a sixth preset threshold;

[0144] The proficiency of each rowing teaching action is determined according to the target number of times.

[0145] The above mainly introduces the scheme of the embodiment of the present application from the perspective of the execution process on the method side. It is understandable that, in order to realize the above functions, the computing device includes a hardware structure and / or software module corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment provided in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0146] The embodiment of the present application can divide the computing device into functional units according to the above method example. For example, each functional unit can be divided according to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. It should be noted that the division of units in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0147] In the case of dividing each functional module into corresponding functional modules, Figure 5 A functional unit block diagram of a rowing motion data processing device is given, such as Figure 5 As shown, a computing device applied to a human motion quantitative training system, the human motion quantitative training system comprises the computing device, a six-degree-of-freedom motion platform, a display device and a voice broadcast device, the computing device is respectively connected to the six-degree-of-freedom motion platform, the display device and the voice broadcast device, the six-degree-of-freedom motion platform comprises a ship dynamic behavior simulation platform; the device comprises an acquisition unit, a determination unit and a transmission unit; the rowing motion data processing device comprises: an acquisition unit 501, a determination unit 502 and a transmission unit 503, wherein,

[0148] The acquisition unit 501 is used to acquire the user's historical rowing data;

[0149] The determining unit 502 is used to determine a plurality of rowing ability characterization values ​​of a plurality of rowing ability indicators according to the historical rowing data, wherein the plurality of rowing ability indicators include at least two of the following: rowing explosive power, rowing posture coordination, rowing endurance, rowing posture accuracy, and number of rowing exercise participations;

[0150] The determining unit 502 is further configured to determine a first rowing training level of the user according to the plurality of rowing ability representation values;

[0151] The determining unit 502 is further configured to determine a target rowing training mode and a target rowing training environment of the user according to the first rowing training level, the first rowing ability characterization value of the rowing explosive power, and the second rowing ability characterization value of the rowing endurance;

[0152] The determining unit 502 is further configured to determine the dynamic behavior simulation parameters of the vessel dynamic behavior simulation platform according to the target rowing training environment and the vessel data of the reference simulated vessel;

[0153] The transmission unit 503 is used to send the dynamic behavior simulation parameters to the ship dynamic behavior simulation platform, and the ship dynamic behavior simulation platform is used to simulate the behavior of the reference simulated ship in the target rowing training environment according to the dynamic behavior simulation parameters.

[0154] It can be seen that the rowing motion data processing device described in the embodiment of the present application can first obtain the user's historical rowing data, and then determine multiple rowing ability characterization values ​​of multiple rowing ability indicators based on the historical rowing data, and the multiple rowing ability indicators include at least two of the following: rowing power, rowing posture coordination, rowing endurance, rowing posture accuracy, and number of rowing exercise participation times, and then determine the user's first rowing training level based on the multiple rowing ability characterization values, and further, determine the user's target rowing training mode and target rowing training environment based on the first rowing training level, the first rowing ability characterization value of rowing power, and the second rowing ability characterization value of rowing endurance, and further, determine the dynamic behavior simulation parameters of the ship dynamic behavior simulation platform based on the target rowing training environment and the ship data of the reference simulated ship, and finally, send the dynamic behavior simulation parameters based on the ship dynamic behavior simulation platform, and the ship dynamic behavior simulation platform is used to simulate the behavior of the reference simulated ship under the target rowing training environment based on the dynamic behavior simulation parameters. The user's rowing ability level is determined by analyzing the user's historical rowing data through the computing device in the human motion quantified training system, and the user is given targeted training in rowing posture, rowing explosive power and rowing endurance based on the rowing ability level. This is beneficial to improving user experience and improving the intelligence of the computing device in the human motion quantified training system in processing rowing data.

[0155] In a possible example, in determining the first rowing training level of the user according to the multiple rowing ability representation values, the determining unit 502 is specifically configured to:

[0156] When the third rowing ability characterization value of the rowing exercise participation number is less than a first preset threshold or the fourth rowing ability characterization value of the rowing posture accuracy is less than a second preset threshold, determining the beginner level of the user, and using the beginner level as the first rowing training level of the user;

[0157] When the third rowing ability characterization value is greater than or equal to the first preset threshold and the fourth rowing ability characterization value is greater than or equal to the second preset threshold, determining a plurality of weight coefficients of the plurality of rowing ability indicators; and,

[0158] determining a target rowing capacity characterization value according to the plurality of weight coefficients and the plurality of rowing capacity characterization values; and,

[0159] The real-life training level of the user is determined according to the target rowing capacity characterization value and a plurality of pre-stored preset rowing capacity characterization value intervals, and the real-life training level is used as the first rowing training level of the user.

[0160] In a possible example, in determining the target rowing training mode and the target rowing training environment of the user according to the first rowing training level, the first rowing ability characterization value of the rowing explosive power, and the second rowing ability characterization value of the rowing endurance, the determining unit 502 is specifically configured to:

[0161] When the first rowing training level is the beginner level, determining the target rowing training mode to be a teaching training mode, and determining the target rowing training environment to be a teaching training environment;

[0162] When the first rowing training level is the real-scene training level, determining the target rowing training mode to be the real-scene simulation training mode, and determining a target difficulty level according to the first rowing training level;

[0163] determining a plurality of first rowing training environments corresponding to the target difficulty level;

[0164] At least one second rowing training environment is selected from the plurality of first rowing training environments according to the first rowing capacity characterization value and the second rowing capacity characterization value, and the at least one second rowing training environment is used as the target rowing training environment.

[0165] In a possible example, in the aspect of selecting at least one second rowing training environment from the plurality of first rowing training environments according to the first rowing capacity characterization value and the second rowing capacity characterization value, the determining unit 502 is specifically configured to:

[0166] If the first rowing ability characterization value is less than a third preset threshold and the second rowing ability characterization value is greater than or equal to a fourth preset threshold, at least one third rowing training environment having a water surface length less than a first preset distance is selected from the plurality of first rowing training environments, and the at least one third rowing training environment is used as the at least one second rowing training environment;

[0167] If the first rowing ability characterization value is greater than or equal to the third preset threshold and the second rowing ability characterization value is less than the fourth preset threshold, selecting at least one fourth rowing training environment whose water surface length is greater than or equal to the second preset distance from the plurality of first rowing training environments, and using the at least one fourth rowing training environment as the at least one second rowing training environment;

[0168] If the first rowing capacity characterization value is less than the third preset threshold and the second rowing capacity characterization value is less than the fourth preset threshold, at least one fifth rowing training environment other than the third rowing training environment and the fourth rowing training environment is screened out from the multiple first rowing training environments, and the at least one fifth rowing training environment is used as the at least one second rowing training environment.

[0169] In a possible example, in determining the dynamic behavior simulation parameters of the ship dynamic behavior simulation platform according to the target rowing training environment and the ship data of the reference simulated ship, the determining unit 502 is specifically used to:

[0170] determining a target swaying behavior of the reference simulated vessel according to the target rowing training environment and the vessel data;

[0171] According to the target sloshing behavior, target sloshing parameters and vibration intensity parameters of the ship dynamic behavior simulation platform are determined, and the target sloshing parameters and the vibration intensity parameters are used as dynamic behavior simulation parameters of the reference simulated ship.

[0172] In a possible example, after sending the dynamic behavior simulation parameters to the ship dynamic behavior simulation platform, the determining unit 502 is further specifically used to: obtain the motion data of the user in the teaching and training environment for the current time, the motion data including action posture data, left arm tension data and right arm tension data;

[0173] Determining the proficiency of each rowing teaching action according to the motion data;

[0174] According to the proficiency of each rowing teaching action, the first rowing training level is adjusted to obtain a second rowing training level.

[0175] In a possible example, in determining the proficiency of each rowing teaching action according to the motion data, the determining unit 502 is further specifically configured to:

[0176] Determining the matching degree of each rowing teaching action according to the action posture data and the reference posture data;

[0177] Determine a force coordination representation value of each rowing teaching action according to the left arm pulling force data and the right arm pulling force data;

[0178] Determine a target number of times for each rowing teaching action in which the matching degree is greater than or equal to a fifth preset threshold and the force coordination representation value is greater than or equal to a sixth preset threshold;

[0179] The proficiency of each rowing teaching action is determined according to the target number of times.

[0180] It should be noted that all relevant contents of each step involved in the above method embodiment can be referred to the functional description of the corresponding functional module and will not be repeated here.

[0181] The computing device provided in this embodiment is used to execute the above-mentioned rowing motion data processing method, and thus can achieve the same effect as the above-mentioned implementation method.

[0182] In the case of an integrated unit, the computing device may include a processing module, a storage module and a communication module. The processing module may be used to control and manage the actions of the computing device, for example, it may be used to support the computing device to execute the steps performed by the above functional units. The storage module may be used to support the computing device to execute stored program codes and data, etc. The communication module may be used to support the computing device to communicate with other devices.

[0183] Among them, the processing module can be a processor or a controller. It can implement or execute various exemplary logic boxes, modules and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc. The storage module can be a memory. The communication module can specifically be a device that interacts with other computing devices, such as a radio frequency circuit, a Bluetooth chip, a Wi-Fi chip, etc.

[0184] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments, and the above computer includes a computing device.

[0185] The present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes a control platform.

[0186] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0187] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0188] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0189] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0190] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0191] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the above-mentioned methods in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0192] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, which can include: a flash drive, a read-only memory, a random access memory, a magnetic disk or an optical disk, etc.

[0193] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for processing rowing motion data, characterized in that: A computing device applied to a human motion quantitative training system, the human motion quantitative training system comprising the computing device, a six-degree-of-freedom motion platform, a display device and a voice broadcast device, the computing device being connected to the six-degree-of-freedom motion platform, the display device and the voice broadcast device respectively, the six-degree-of-freedom motion platform comprising a ship dynamic behavior simulation platform; the method comprising: Get the user's historical rowing data; Determine, based on the historical rowing data, a plurality of rowing ability characterization values ​​of a plurality of rowing ability indicators, wherein the plurality of rowing ability indicators include at least two of the following: rowing explosive power, rowing posture coordination, rowing endurance, rowing posture accuracy, and number of rowing exercise participations; determining a first rowing training level of the user according to the plurality of rowing capacity representation values; determining a target rowing training mode and a target rowing training environment of the user according to the first rowing training level, the first rowing ability characterization value of the rowing explosive power, and the second rowing ability characterization value of the rowing endurance; Determining dynamic behavior simulation parameters of the vessel dynamic behavior simulation platform according to the target rowing training environment and vessel data of a reference simulated vessel; Sending the dynamic behavior simulation parameters to the vessel dynamic behavior simulation platform, wherein the vessel dynamic behavior simulation platform is used to simulate the behavior of the reference simulated vessel in the target rowing training environment according to the dynamic behavior simulation parameters; The determining, according to the plurality of rowing capacity representation values, a first rowing training level of the user comprises: When the third rowing ability characterization value of the rowing exercise participation number is less than a first preset threshold or the fourth rowing ability characterization value of the rowing posture accuracy is less than a second preset threshold, determining the beginner level of the user, and using the beginner level as the first rowing training level of the user; When the third rowing ability characterization value is greater than or equal to the first preset threshold and the fourth rowing ability characterization value is greater than or equal to the second preset threshold, determining a plurality of weight coefficients of the plurality of rowing ability indicators; and, determining a target rowing capacity characterization value according to the plurality of weight coefficients and the plurality of rowing capacity characterization values; and, The real-life training level of the user is determined according to the target rowing capacity characterization value and a plurality of pre-stored preset rowing capacity characterization value intervals, and the real-life training level is used as the first rowing training level of the user.

2. The method according to claim 1, characterized in that: The determining, according to the first rowing training level, the first rowing ability characterization value of the rowing explosive power, and the second rowing ability characterization value of the rowing endurance, a target rowing training mode and a target rowing training environment of the user comprises: When the first rowing training level is the beginner level, determining the target rowing training mode to be a teaching training mode, and determining the target rowing training environment to be a teaching training environment; When the first rowing training level is the real-scene training level, determining the target rowing training mode to be the real-scene simulation training mode, and determining a target difficulty level according to the first rowing training level; determining a plurality of first rowing training environments corresponding to the target difficulty level; At least one second rowing training environment is selected from the plurality of first rowing training environments according to the first rowing capacity characterization value and the second rowing capacity characterization value, and the at least one second rowing training environment is used as the target rowing training environment.

3. The method according to claim 2, characterized in that The selecting at least one second rowing training environment from the plurality of first rowing training environments according to the first rowing ability characterization value and the second rowing ability characterization value comprises: If the first rowing ability characterization value is less than a third preset threshold and the second rowing ability characterization value is greater than or equal to a fourth preset threshold, at least one third rowing training environment having a water surface length less than a first preset distance is selected from the plurality of first rowing training environments, and the at least one third rowing training environment is used as the at least one second rowing training environment; If the first rowing ability characterization value is greater than or equal to the third preset threshold and the second rowing ability characterization value is less than the fourth preset threshold, selecting at least one fourth rowing training environment whose water surface length is greater than or equal to the second preset distance from the plurality of first rowing training environments, and using the at least one fourth rowing training environment as the at least one second rowing training environment; If the first rowing capacity characterization value is less than the third preset threshold and the second rowing capacity characterization value is less than the fourth preset threshold, at least one fifth rowing training environment other than the third rowing training environment and the fourth rowing training environment is screened out from the multiple first rowing training environments, and the at least one fifth rowing training environment is used as the at least one second rowing training environment.

4. The method according to claim 1, characterized in that Determining the dynamic behavior simulation parameters of the vessel dynamic behavior simulation platform according to the target rowing training environment and the vessel data of the reference simulated vessel includes: determining a target swaying behavior of the reference simulated vessel according to the target rowing training environment and the vessel data; According to the target sloshing behavior, target sloshing parameters and vibration intensity parameters of the ship dynamic behavior simulation platform are determined, and the target sloshing parameters and the vibration intensity parameters are used as dynamic behavior simulation parameters of the reference simulated ship.

5. The method according to claim 2, characterized in that: After sending the dynamic behavior simulation parameters to the ship dynamic behavior simulation platform, the method further includes: Acquire the user's current motion data in the teaching and training environment, the motion data including action posture data, left arm tension data, and right arm tension data; Determining the proficiency of each rowing teaching action according to the motion data; According to the proficiency of each rowing teaching action, the first rowing training level is adjusted to obtain a second rowing training level.

6. The method according to claim 5, characterized in that Determining the proficiency of each rowing teaching action according to the motion data includes: Determining the matching degree of each rowing teaching action according to the action posture data and the reference posture data; Determine a force coordination representation value of each rowing teaching action according to the left arm pulling force data and the right arm pulling force data; Determine a target number of times for each rowing teaching action in which the matching degree is greater than or equal to a fifth preset threshold and the force coordination representation value is greater than or equal to a sixth preset threshold; The proficiency of each rowing teaching action is determined according to the target number of times.

7. A rowing motion data processing device, characterized in that: A computing device used in a human motion quantitative training system, the human motion quantitative training system comprising the computing device, a six-degree-of-freedom motion platform, a display device and a voice broadcast device, the computing device is respectively connected to the six-degree-of-freedom motion platform, the display device and the voice broadcast device, the six-degree-of-freedom motion platform comprises a ship dynamic behavior simulation platform; the device comprises an acquisition unit, a determination unit and a transmission unit; wherein, The acquisition unit is used to acquire the user's historical rowing data; The determining unit is used to determine a plurality of rowing ability characterization values ​​of a plurality of rowing ability indicators according to the historical rowing data, wherein the plurality of rowing ability indicators include at least two of the following: rowing explosive power, rowing posture coordination, rowing endurance, rowing posture accuracy, and number of rowing exercise participations; The determining unit is further configured to determine a first rowing training level of the user according to the multiple rowing ability characterization values; the determining the first rowing training level of the user according to the multiple rowing ability characterization values ​​comprises: when the third rowing ability characterization value of the rowing exercise participation times is less than a first preset threshold or the fourth rowing ability characterization value of the rowing posture accuracy is less than a second preset threshold, determining the beginner level of the user, and using the beginner level as the first rowing training level of the user; when the third rowing ability characterization value is greater than or equal to the first preset threshold and the fourth rowing ability characterization value is greater than or equal to the second preset threshold, determining multiple weight coefficients of the multiple rowing ability indicators; and, determining a target rowing ability characterization value according to the multiple weight coefficients and the multiple rowing ability characterization values; and, determining the real-life training level of the user according to the target rowing ability characterization value and multiple pre-stored preset rowing ability characterization value intervals, and using the real-life training level as the first rowing training level of the user; The determining unit is further used to determine a target rowing training mode and a target rowing training environment of the user according to the first rowing training level, the first rowing ability characterization value of the rowing explosive power, and the second rowing ability characterization value of the rowing endurance; The determination unit is further used to determine the dynamic behavior simulation parameters of the vessel dynamic behavior simulation platform according to the target rowing training environment and the vessel data of the reference simulated vessel; The transmission unit is used to send the dynamic behavior simulation parameters to the ship dynamic behavior simulation platform, and the ship dynamic behavior simulation platform is used to simulate the behavior of the reference simulated ship in the target rowing training environment according to the dynamic behavior simulation parameters.

8. A computing device, characterized in that The method comprises a processor and a memory, wherein the memory is used to store one or more programs and is configured to be executed by the processor, wherein the program comprises instructions for executing the steps in the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: A computer program for electronic data exchange is stored, wherein the computer program enables a computer to execute the method according to any one of claims 1 to 6.

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