A multi-dimensional motion control method and device for a water sports project

Abstract

The application discloses a water sports multi-dimensional motion control method and device, comprising: identifying the periodic deviation of the rowing path according to the paddle handle rotation angular velocity, the trajectory curvature radius and the deviation angle; triggering the rotation radius determination reference update when the deviation angle exceeds the standard range to obtain the adjusted rotation radius determination reference; determining the balance point of the power stroke length extension and the arc trajectory curvature according to the adjusted rotation radius determination reference, and obtaining the paddle handle rotation radius set value corresponding to the balance point; evaluating whether the corresponding proportion of the direction deviation angle and the work stroke length meets the efficiency stable output requirement, identifying the real-time adjustment feedback of the rotation angular velocity after the improvement of the rower's body coordination, and obtaining the stable output level of the propulsion efficiency; and updating the monitoring period of the trajectory curvature radius according to the ship body posture sensing module to maintain the continuity of the holding stability, the power rhythm coherence and the trunk rotation amplitude at the optimal balance point.

Description

Technical Field

[0001] This invention relates to the field of information technology, and in particular to a multi-dimensional motion control method and device for water sports. Background Technology

[0002] As a competitive sport that integrates strength, skill, and coordination, water sports are of great significance in improving athlete performance and optimizing training effects. Whether rowing or canoeing, improving propulsion efficiency directly affects competition results, making it a focal point for coaches and researchers. Research in this area not only influences athletes' competitive levels but also plays a crucial role in the innovation of equipment design and training methods. However, current methods for optimizing propulsion efficiency often overlook the dynamic interaction of multiple factors during the sport. Existing solutions tend to focus on improving single aspects, such as simply increasing power output or adjusting the range of motion, without comprehensively considering the relationships between different variables. This one-sidedness leads to athletes' movements often failing to adapt to real-time changes during competition, significantly diminishing the effectiveness of efficiency improvements. For example, the radius of rotation of the oar handle directly affects the underwater trajectory and power output of the oar blades, but its adjustment is not a simple linear relationship. If the radius is too large, although the distance of force application may increase, the curvature of the oar blades' stroke trajectory will also increase, causing the direction of propulsion to deviate from the direction of the boat's movement, thus reducing the actual effective propulsion. Conversely, if the radius is too small, the distance of force application is limited, and the advantage of power cannot be fully utilized. This contradiction is particularly evident in actual competitions, especially when athletes' physical strength declines or water conditions change, making it difficult to find a suitable balance. Specifically, in rowing, athletes need to adjust the amplitude of their strokes in real time according to their own condition and environmental conditions. For example, in upstream conditions, athletes may tend to increase the radius of rotation to increase the time of force application, but at this time, the trajectory of the paddle blades will deviate more significantly, and some power will be wasted on lateral components unrelated to the direction of forward movement, resulting in limited speed gains for the boat. This efficiency fluctuation caused by the adjustment of the radius of rotation has become a problem that urgently needs to be solved in training and competition. Therefore, finding the optimal balance between the radius of rotation and the deviation of the propulsion direction during the dynamically changing paddling process has become a key issue in improving the propulsion efficiency of water sports. Summary of the Invention

[0003] This invention provides a multi-dimensional motion control method for water sports, mainly including: Collect motion parameters during the paddling process, including at least the angular velocity of the paddle handle rotation, the radius of curvature of the trajectory, and the deviation angle; Based on the motion parameters, the periodic deviation characteristics of the paddling path are identified, and the rotation radius determination criteria are adjusted. The balance point between the force stroke and the trajectory curvature is determined based on the adjusted rotation radius determination benchmark, and the corresponding propeller rotation radius setting value is obtained. The set value of the paddle handle rotation radius guides the paddler to adjust motion parameters and correct deviations in the direction of propulsion. Evaluate the corresponding ratio between the corrected directional deviation angle and the power stroke length to determine the stable output level of propulsion efficiency; The monitoring cycle of the trajectory curvature radius is updated based on the stable output level of the propulsion efficiency to maintain the continuity of the paddling motion.

[0004] Furthermore, motion parameters during the paddling process are collected, including: The sequence of changes in the angular velocity of the propeller shaft is obtained by an inertial measurement unit, and the instantaneous rotation angle is calculated by integrating the angular velocity. The trajectory curvature radius is calculated using data from a three-axis gyroscope, and the deviation angle is recorded simultaneously to form a set of spatial curve parameters. If the deviation angle in the spatial curve parameter group exceeds the preset threshold, the grip force distribution data is collected by the pressure sensor, and the grip stability level is determined according to the standard deviation of the grip force time series. The consistency index of the force exertion rhythm is determined by the coefficient of variation of the time interval between adjacent paddling cycles. By monitoring the changes in the depth of the propeller blades in the water using a water pressure sensor and combining the data on the rotation amplitude of the torso with a motion capture sensor, the correlation coefficient between the duration of underwater stay and the rotation amplitude of the torso is calculated using the sliding window method, thus obtaining a quantitative assessment value of body coordination.

[0005] Furthermore, identifying periodic deviation characteristics of the paddling path based on the motion parameters includes: Perform a Fourier transform on the time series of propeller rotation angular velocity to extract the main frequency components and their amplitudes; By combining the rate of change of the trajectory curvature radius, periodic deviation characteristics are identified based on the phase difference between the frequency components and the curvature changes, and time-domain distribution data including deviation amplitude and deviation frequency are obtained. Based on the time-domain distribution data, the mean and variance of the deviation angle in each period are calculated using the moving average method; If the deviation angle exceeds the range of the mean plus a preset multiple of the standard deviation, the benchmark update mechanism is triggered to obtain the deviation amplitude value of the current period, and then the original rotation radius determination benchmark is corrected to obtain the adjusted benchmark value.

[0006] Furthermore, the balance point between the force application stroke and the trajectory curvature is determined based on the adjusted rotation radius determination criterion, including: The stroke length is calculated by the product of the paddling period and the rotation angle. Obtain the curvature value of the arc trajectory based on the reciprocal of the rotation radius, and construct a matrix relating the travel length to the curvature value; By decomposing the thrust into longitudinal and lateral components, the proportion of the longitudinal thrust component under different rotation radii is calculated to form a numerical sequence. Based on the numerical sequence, the gradient ascent method is used to search for the extreme points of the propulsion force ratio; If there are multiple extreme points, the extreme point with a force stroke length greater than a preset threshold is selected as the candidate equilibrium point; By verifying the constraints, we determine whether the trajectory curvature corresponding to the candidate equilibrium point meets the conditions, and then determine the optimal equilibrium point and the corresponding propeller rotation radius setting value.

[0007] Furthermore, the paddle handle rotation radius setting guides the paddler to adjust motion parameters, including: Based on the set value of the paddle rotation radius, monitor changes in grip force distribution and adjust the grip center position; A fixed-frequency signal is used to guide the force application rhythm, so that the time interval between adjacent paddling cycles tends to be consistent, and periodic data on the deviation of the propulsion direction are obtained. Adjust the blade entry depth according to the periodic data; The timing for water discharge is determined when the pressure value reaches its peak value. The adjustment amount of underwater dwell time is determined by the difference between the deviation angle and the preset benchmark, and a set of work parameters including water depth, water exit timing and dwell time are obtained. Then, the proportional relationship between the corrected directional deviation angle and the work stroke length is calculated.

[0008] Furthermore, the corresponding ratio of the corrected directional deviation angle to the length of the work stroke is evaluated, including: The evaluation is based on the ratio of the directional deviation angle to the length of the work stroke, compared with a preset stable efficiency output threshold. If the ratio value exceeds the threshold range, the adjusted blade entry depth, exit timing and underwater dwell time parameters are arranged in chronological order to form an efficiency fluctuation feature vector. By monitoring the relative motion changes between the paddler's torso and upper limbs, identifying the real-time adjustment needs of the rotational angular velocity, and obtaining a correction sequence that includes the amount and timing of the angular velocity change; The coefficient of variation of propulsion efficiency during a continuous paddling cycle is calculated using the parameter values ​​of the corrected sequence and the efficiency fluctuation feature vector to determine the stable output level.

[0009] Furthermore, updating the monitoring period for the trajectory curvature radius based on the stable output level of the propulsion efficiency includes: Data on changes in the ship's roll and pitch angles are obtained through ship attitude sensing. If the changes in both the roll and pitch angles of the ship exceed the preset requirements, the monitoring cycle is shortened; otherwise, the monitoring cycle is extended to determine the updated monitoring cycle value for the trajectory curvature radius. The sampling frequency of grip stability, force application rhythm continuity, and torso rotation amplitude is adjusted according to the monitoring cycle update value. By maintaining the stability of the grip, the continuity of the force exertion rhythm, and the fluctuation of the torso rotation amplitude within a preset range, the continuity maintenance parameters are obtained to maintain the balance of the paddling motion.

[0010] Furthermore, maintaining the continuity of paddling motion includes: Based on the stable output level of propulsion efficiency, and combined with the updated trajectory curvature radius monitoring cycle, motion parameters during the paddling process are continuously collected. By dynamically adjusting the control strategies for grip stability, force application rhythm continuity, and torso rotation amplitude through real-time changes in the aforementioned motion parameters; Based on the adjusted control strategy, acquire data on the rower's motion coordination in different cycles; By comparing the motion coordination data with a preset benchmark, it is determined whether the propeller rotation radius setting needs further adjustment. If corrections are needed, the baseline is recalculated and adjusted based on the deviation angle and trajectory curvature radius collected in real time to maintain the continuity of the paddling motion at the optimal equilibrium point.

[0011] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: This invention discloses a multi-dimensional motion control method and device for water sports. Addressing the issues of periodic path deviation, unstable propulsion direction, and discontinuous efficiency output during paddling, the method dynamically identifies deviations and updates the rotation radius judgment benchmark by real-time acquisition of paddle handle rotation angular velocity, trajectory curvature radius, deviation angle, and paddle blade parameters, combined with data on paddler grip stability and body coordination. The adjusted benchmark determines the balance point between the force stroke and trajectory curvature, optimizes the paddle handle rotation radius setting, guides the paddler to correct the propulsion direction, and adjusts the paddle blade entry depth and exit timing to ensure the ratio of directional deviation angle to work stroke meets efficiency requirements, ultimately achieving stable propulsion efficiency. Feedback updates the monitoring cycle to maintain the continuity and stability of the overall paddling motion, thus achieving motion control for water sports. The core innovation of this invention lies in its focus on rotation radius optimization, integrating multi-dimensional data for dynamic adjustment to ensure maximum propulsion and stable efficiency, significantly improving paddling performance. Attached Figure Description

[0012] Figure 1 This is a flowchart of a multi-dimensional motion control method for water sports according to the present invention.

[0013] Figure 2 This is a schematic diagram of a multi-dimensional motion control method for water sports according to the present invention.

[0014] Figure 3 This is another schematic diagram of a multi-dimensional motion control method for water sports according to the present invention. Detailed Implementation

[0015] To further understand the content of this invention, a detailed description of the invention is provided in conjunction with the accompanying drawings and embodiments. The specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention. It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0016] Example 1: This invention discloses a multi-dimensional motion control method for water sports, such as... Figure 1-3 Specifically, it can include: S101: Real-time acquisition of paddle handle rotational angular velocity, trajectory curvature radius, deviation angle, paddle blade entry depth, exit timing and underwater dwell time, and simultaneous recording of the paddler's grip stability, power rhythm continuity, body coordination and torso rotation amplitude.

[0017] The inertial measurement unit collects the sequence of changes in the angular velocity of the paddle handle rotation. The instantaneous rotation angle is obtained by integrating the angular velocity, and the radius of curvature of the trajectory is calculated using data from a three-axis gyroscope. Simultaneously, deviation angles are recorded to form a set of spatial curve parameters for the paddle handle motion. If the deviation angle in the spatial curve parameter set exceeds a preset threshold, a pressure sensor is activated to collect grip force distribution data. The grip stability level is determined based on the standard deviation of the grip force over time, and the coefficient of variation of the time interval between adjacent paddling cycles is used to determine the consistency index of the force exertion rhythm. Based on the consistency index of the force exertion rhythm, combined with the change in paddle blade depth monitored by a water pressure sensor, and the torso rotation amplitude data obtained by a motion capture sensor, the Pearson correlation coefficient between underwater dwell time and torso rotation amplitude is calculated using the sliding window method to obtain a quantitative assessment value of body coordination.

[0018] Specifically, in one embodiment, an inertial measurement unit (IMU) is installed 10 centimeters above the paddle handle grip position and uses a three-axis gyroscope to collect real-time data on the angular velocity changes of the paddle handle during paddling. The IMU records the angular velocity data at a sampling frequency of 100 Hz and calculates the instantaneous rotation angle through time integration.

[0019] Specifically, during the paddle entry phase, the angular velocity gradually increases from zero, reaches a peak, and then gradually decreases during the exit phase. By performing second derivative calculations on the angular velocity change curve, points of curvature change are identified, and the trajectory curvature radius is calculated. When the paddle moves underwater, the trajectory curvature radius reflects the degree of curvature of the paddle path, while the deviation angle is obtained by comparing the angle between the actual trajectory and the ideal straight path. This dataset of spatial curve parameters provides fundamental data support for subsequent motion control.

[0020] It should be noted that monitoring the deviation angle is crucial for evaluating paddling efficiency. When the deviation angle exceeds a preset threshold, it indicates a significant deviation in the paddling path, at which point the system activates the pressure sensor array. This pressure sensor array contains eight pressure sensing points, evenly distributed across the paddle handle grip area, with each sensing point independently collecting grip force data.

[0021] For example, grip stability is judged based on the standard deviation of grip force over time. Under stable paddling conditions, the pressure values ​​at each sensing point should remain relatively constant with a small standard deviation. When the athlete is fatigued or their movements become distorted, grip force fluctuates periodically, and the standard deviation increases. The consistency of the stroke rhythm is determined by calculating the coefficient of variation of the time interval between adjacent paddling cycles; a smaller coefficient of variation indicates a more stable rhythm.

[0022] In one possible implementation, a water pressure sensor is installed at the root of the paddle blade to monitor real-time changes in the blade's depth in the water. The water pressure sensor converts the pressure signal into a depth value based on the linear relationship between water pressure and depth. A nine-axis motion sensor is used, fixed at the center of the athlete's back, and acquires trunk rotation amplitude data through Euler angle calculation. During paddling, there is a specific correlation between trunk rotation amplitude and the duration of the paddle blade's underwater stay. This correlation is dynamically analyzed using a sliding window method. The sliding window duration is set to five paddling cycles. The inputs are the underwater stay duration sequence and the trunk rotation amplitude sequence. Within each window, the Pearson correlation coefficient r between the two sequences is calculated, and the output is the r value. r is set with a threshold based on exercise physiology research; when |r|>0.7, it indicates a strong correlation and good body coordination; when |r|<0.3, it indicates poor coordination and the need to adjust the paddling motion. This coordination assessment result is used in a real-time feedback system to provide motion optimization suggestions.

[0023] S102. Identify the periodic deviation of the paddling path based on the angular velocity of the paddle handle, the radius of curvature of the trajectory, and the deviation angle. When the deviation angle exceeds the standard range, trigger the update of the rotation radius determination benchmark to obtain the adjusted rotation radius determination benchmark.

[0024] By performing a Fourier transform on the time series of paddle rotation angular velocity, the dominant frequency components and their corresponding amplitudes are extracted. Combined with the rate of change of the trajectory curvature radius, the periodic deviation characteristics of the paddling path are identified based on the phase difference between the frequency components and the curvature change, resulting in time-domain distribution data containing deviation amplitude and deviation frequency. Based on the time-domain distribution data, the mean and variance of the deviation angle in each period are calculated using a moving average method. This method uses a moving window of size 5 to calculate the mean and variance. If the deviation angle exceeds the range of the mean plus twice the standard deviation, a benchmark update mechanism is triggered to obtain the deviation amplitude value for the current period. The original rotation radius determination benchmark is corrected using the deviation amplitude value. The original benchmark value is the standard value obtained from the trajectory curvature radius calculation mentioned above. Based on the constraint that the product of the deviation amplitude A and the rotation radius R remains constant, this constraint is derived from the physical model assumption to maintain path stability. The correction coefficient K is calculated as the ratio of the deviation amplitude value A to the standard deviation amplitude S, where S is defined as a preset standard value of 1. The adjusted rotation radius determination benchmark is obtained by multiplying the original benchmark value by the reciprocal of K.

[0025] Specifically, in one implementation, the Fourier transform is used to analyze the frequency domain characteristics of the propeller's rotational angular velocity. The Fourier transform converts the time-domain signal to the frequency domain, and the dominant frequency components are identified through spectral analysis.

[0026] Specifically, under normal paddling conditions, angular velocity changes exhibit a regular periodicity, with the dominant frequency component concentrated in a specific frequency band. When the paddler is fatigued or their movements become distorted, multiple frequency peaks appear in the spectrum, indicating a disruption in the paddling rhythm. The rate of change of the trajectory curvature radius is calculated by dividing the curvature difference between adjacent sampling points by the time interval. The phase difference between this rate of change and the dominant frequency component reflects the coordination of the paddling motion. The larger the phase difference, the more pronounced the asynchrony between the change in angular velocity and the degree of trajectory curvature; this asynchrony directly leads to a decrease in propulsion efficiency.

[0027] It should be noted that the time-domain distribution data includes two key parameters: deviation magnitude and deviation frequency. Deviation magnitude characterizes the degree to which the paddling path deviates from the ideal trajectory, while deviation frequency reflects the periodicity of the deviation.

[0028] For example, the window length of the moving average method is set to 5 paddling cycles. Within each window, the mean of the deviation angle is calculated as a baseline, and the variance reflects the dispersion of the deviation. When the deviation angle of a sampling point exceeds the range of the mean plus a preset multiple of the standard deviation, the system determines that an abnormal deviation has occurred. The preset multiple is adjusted according to the athlete's skill level and competition requirements; beginners use a larger multiple to increase error tolerance, while professional athletes use a smaller multiple to strictly control the quality of their movements.

[0029] In one possible implementation, the correction factor is calculated based on the principle of energy conservation. During paddling, the product of the deviation amplitude δ and the rotation radius r represents the work W done per unit time. This constant product ensures the stability of energy output, i.e., W = δ. When the deviation increases, the rotation radius needs to decrease accordingly to maintain a constant amount of work done. The correction factor k is defined as the ratio of the current deviation value δ to the standard deviation δs, i.e., k = δ / δs, where δs is obtained through statistical analysis of historical data from elite athletes. Specifically, this process involves collecting paddling data from at least 100 athletes, calculating the mean and standard deviation, and taking the mean plus one standard deviation as δs. The original rotation radius determination benchmark is multiplied by the reciprocal of the correction factor to obtain the adjusted rotation radius determination benchmark, which is used to guide athletes in adjusting their paddling motion amplitude.

[0030] Preferably, the adjusted rotation radius determination criterion also needs to take into account the influence of water flow conditions, and the correction range should be appropriately increased in a countercurrent environment.

[0031] Understandably, by dynamically updating the rotation radius determination benchmark, adaptive adjustment of the paddling motion is achieved, improving the stability of propulsion efficiency under different conditions.

[0032] S103. Determine the balance point between the extension of the power stroke and the curvature of the arc trajectory based on the adjusted rotation radius judgment benchmark, and obtain the corresponding propeller rotation radius setting value.

[0033] Based on the adjusted rotation radius criterion, the stroke length is calculated using the product of the rowing period T and the rotation angle θ, L = T × θ, where L is the stroke length. Simultaneously, the curvature value of the arc trajectory is obtained from the reciprocal of the rotation radius. A matrix relating stroke length and curvature value is constructed as the stroke-curvature coupling matrix, where matrix elements are filled with the corresponding L and curvature values. Using this stroke-curvature coupling matrix, the propulsion force is decomposed into a longitudinal component along the hull's forward direction and a lateral component perpendicular to the forward direction. The ratio of the longitudinal propulsion force to the total propulsion force under different rotation radii is calculated, forming a numerical sequence of propulsion force proportions. Based on this numerical sequence, the gradient ascent method is used to search for extreme points of the propulsion force proportion. This method starts with an initial value of 0.5, calculates partial derivatives, updates parameters with a step size of 0.01, and iterates until the change is less than 0.001. If multiple extreme points exist, the extreme point with a stroke length greater than 10 is selected as a candidate equilibrium point. By constraining and verifying the candidate equilibrium points, it is determined whether the curvature of their corresponding trajectory is less than the curvature value corresponding to the maximum bending angle allowed by the athlete's joint range of motion. The optimal equilibrium point that satisfies the constraint conditions is obtained, and the set value of the paddle rotation radius corresponding to the equilibrium point is determined.

[0034] Specifically, in one implementation, the stroke-curvature coupling matrix is ​​constructed based on the geometric relationship of the paddling motion. The paddling period is defined as the time required for the paddle blade to complete one full stroke from the point of entry to the point of exit. The product of this period and the rotation angle directly determines the length of the stroke.

[0035] Specifically, as the radius of rotation increases, the arc length corresponding to the same rotation angle increases, and the stroke lengthens accordingly. Simultaneously, the curvature of the arc trajectory is equal to the reciprocal of the radius of rotation; the larger the radius, the smaller the curvature, and the closer the trajectory is to a straight line. Each element of the coupling matrix represents the correspondence between the stroke length and curvature value at a specific radius of rotation. The matrix row index corresponds to different radius values, and the column index corresponds to both the stroke length and curvature value. This matrix representation achieves a quantitative correlation between the extension of the stroke length and the change in trajectory curvature, providing a data foundation for subsequent optimization searches. In practical applications, the matrix construction considers individual differences such as athlete height and wingspan, and normalization eliminates the influence of individual differences, making the matrix universal.

[0036] It should be noted that the vector decomposition of propulsion follows the parallelogram law of mechanics. The propulsion force generated by the propeller blades in water can be decomposed into a longitudinal component along the direction of the ship's movement and a lateral component perpendicular to the direction of movement. The longitudinal component directly contributes to the ship's forward movement, while the lateral component causes the ship to drift and lose energy.

[0037] For example, during rowing training in still water, athletes row at a constant frequency, with the direction of propulsion aligned with the tangent of the paddle's trajectory. When the radius of rotation is small, the paddle trajectory is nearly straight, the propulsion is primarily longitudinal with a small lateral component, resulting in high propulsion efficiency but a short stroke. As the radius of rotation increases, the trajectory becomes more curved, extending the stroke, but the angle at which the propulsion direction deviates from the forward direction increases, leading to a greater lateral component. Some energy is then consumed in overcoming lateral resistance.

[0038] In one possible implementation, the gradient ascent method is used to search for the extreme points of the propulsion force ratio. Starting with an initial rotation radius value, the gradient ascent method calculates the partial derivative of the propulsion force ratio with respect to the rotation radius, updates the rotation radius value along the positive gradient direction, and iterates the search until the gradient approaches zero. During the search, an adaptive step-size strategy is employed: a larger initial step size to accelerate convergence, and a gradually decreasing step size as the search approaches an extreme point to improve accuracy. When multiple extreme points exist, the extreme point with a stroke length greater than a preset threshold is selected as a candidate equilibrium point by comparing the stroke lengths corresponding to each extreme point. The preset threshold is determined based on the race distance and the athlete's endurance level, using the formula T=D / (E). 1.2), where T is the threshold (in meters), D is the race distance (in meters), and E is the endurance level (unitless, ranging from 1 to 10).

[0039] For example, in short-distance races, D=100 meters, E=2, and the threshold is 41.7 meters to pursue explosive power; in long-distance races, D=1000 meters, E=8, and the threshold is 104.2 meters to ensure sustained output. This multi-extreme-point processing mechanism ensures that a suitable balance point can be found in different competition scenarios, improving the adaptability of the method.

[0040] Preferably, the constraint verification of the candidate equilibrium point includes both physiological constraints and mechanical constraints. Physiological constraints mainly consider the athlete's joint range of motion limitations, while mechanical constraints involve the physical characteristics of the oars.

[0041] Specifically, the maximum allowable flexion angle of an athlete's joints is pre-determined using a motion capture system. In rowing, the shoulder, elbow, and wrist joints have physiological limits to their range of motion; exceeding these limits can lead to movement distortion or even injury. There is a correlation between trajectory curvature and joint flexion angle; the greater the curvature, the greater the required joint flexion angle. By converting the trajectory curvature corresponding to candidate equilibrium points into joint flexion angles, it is determined whether the angle is within the physiologically permissible range.

[0042] In one embodiment, for a male rower who is 180 cm tall, the maximum abduction angle of the shoulder joint is 170 degrees, the maximum flexion angle of the elbow joint is 145 degrees, and the maximum dorsiflexion angle of the wrist joint is 70 degrees. Based on these physiological limitations, the maximum allowable trajectory curvature is calculated to be the reciprocal of 0.8 meters. When the curvature value corresponding to a candidate equilibrium point is less than this maximum value, the physiological constraints are considered met.

[0043] Understandably, through the above multiple constraint verifications, it is ensured that the final determined propeller rotation radius setting can both optimize propulsion efficiency and meet ergonomic requirements.

[0044] For example, in actual competitions, when encountering headwinds, the search strategy is automatically adjusted, and the rotation radius setting is appropriately increased to extend the power stroke, compensate for the speed loss caused by wind resistance, and ensure that the adjusted action is still within the athlete's physiological tolerance range.

[0045] S104. By setting the rotation radius of the paddle handle, the paddler is guided to adjust the grip stability and the continuity of the force exertion rhythm to correct the periodic deviation of the propulsion direction. The paddle entry depth, exit timing and underwater dwell time are adjusted simultaneously to determine the corresponding ratio between the corrected directional deviation angle and the power stroke length.

[0046] Based on the set value of the propeller rotation radius, the grip center of gravity position is adjusted by monitoring changes in grip force distribution through a pressure sensor. Simultaneously, a fixed-frequency signal guides the force application rhythm, aligning the time intervals between adjacent paddling cycles to obtain periodic data on the deviation of the propulsion direction. Using this periodic data, the propeller entry depth is adjusted according to the degree of deviation. When the pressure sensor detects a peak pressure value, the exit timing is determined. The difference between the deviation angle (the angle of deviation in the propulsion direction) and a preset benchmark is used to determine the extension or reduction of the underwater dwell time, resulting in a set of actual work parameters including entry depth, exit timing, and dwell time. Using these actual work parameters, the corrected directional deviation angle is calculated based on the angle between the actual propeller trajectory and the ideal straight trajectory. The work stroke length is obtained by integrating the propeller displacement underwater, and the deviation angle value is divided by the stroke length to determine their proportional relationship.

[0047] Specifically, in one implementation, a pressure sensor array is distributed across the paddle handle grip area to determine the grip center of gravity position by monitoring pressure changes at each point in real time. The pressure sensor array comprises eight sensing points in two rows, each independently collecting pressure data and transmitting it to a central processing unit. When the paddle handle rotation radius setting changes, the ideal grip center of gravity position is calculated based on the new radius value. By comparing the deviation between the actual grip center of gravity and the ideal position, adjustment feedback is provided to the athlete. Adjusting the grip center of gravity directly affects the transmission efficiency; when the center of gravity moves forward, the lever arm lengthens but control becomes more difficult; when the center of gravity moves backward, controllability improves but the power output weakens. A fixed-frequency signal is implemented via a metronome or vibration cue, with the frequency set according to the paddling cycle. Each signal corresponds to the starting point of a single power stroke. The athlete adjusts the timing of their power stroke according to the signal rhythm, ensuring consistent time intervals between adjacent paddling cycles to achieve stable propulsion output. By recording the time intervals and corresponding deviation angles of multiple consecutive paddling cycles, periodic data on propulsion direction deviation is generated, reflecting the correlation between motion stability and propulsion efficiency. A water pressure sensor is installed on the back of the propeller blade to monitor changes in water pressure acting on it. When the blade enters the water, the water pressure increases from zero, remains relatively stable during underwater propulsion, and reaches its peak pressure before exiting the water.

[0048] For example, the difference between the deviation angle and the preset reference determines the adjustment amount of the underwater dwell time. When the deviation angle is greater than the reference value, it indicates that the direction of propulsion is seriously deviated, and the underwater dwell time is extended to increase the effective work time; when the deviation angle is less than the reference value, the dwell time is shortened to increase the paddling frequency.

[0049] In one possible implementation, the actual work parameters include three key parameters: entry depth, exit timing, and underwater dwell time. These three parameters interact and jointly determine the work output of a single stroke. The entry depth is calculated using water pressure; the greater the depth, the greater the water resistance on the paddle blades, resulting in a more significant work output but also greater physical exertion.

[0050] Preferably, the direction deviation angle is calculated based on the geometric relationship between the actual blade trajectory and the ideal straight trajectory, and the angle between the two trajectories is calculated using the arctangent function.

[0051] Specifically, the included angle θ = arctan(Δy / Δx), where Δy and Δx are the coordinate differences between the two trajectories in the vertical and horizontal directions, respectively. The working stroke length is obtained by integrating the displacement of the blade underwater, with the integration interval from the entry point to the exit point. The specific integration function is L = ∫v(t)dt, where v(t) is the velocity function of the blade over time, and the displacement data comes from real-time measurement or simulation data of the blade's motion trajectory.

[0052] Understandably, the ratio of deviation angle to stroke length reflects the efficiency characteristics of paddling motion; the smaller the ratio, the smaller the directional deviation per unit stroke, and the higher the propulsion efficiency.

[0053] S105. Evaluate whether the corresponding ratio of the directional deviation angle and the length of the work stroke meets the requirements for stable efficiency output, identify the real-time adjustment feedback of the rotational angular velocity after the paddler's body coordination is improved, and obtain a stable output level of propulsion efficiency.

[0054] Based on the ratio of the directional deviation angle to the length of the working stroke, an evaluation is performed against a preset stable efficiency output threshold of 0.8 to 1.2. If the ratio exceeds the threshold range, the adjusted blade entry depth, exit timing, and underwater dwell time parameters are arranged in chronological order to form an efficiency fluctuation feature vector. If the ratio is within the threshold range, efficiency is considered stable, and the vector formation step is skipped. Using the efficiency fluctuation feature vector, motion sensors pre-installed on the paddler's torso and upper limbs monitor the relative motion changes between the torso and upper limbs. As body coordination improves, the synchronization of torso and arm movements increases, identifying the real-time adjustment needs of rotational angular velocity, resulting in an angular velocity correction sequence containing the amount and timing of angular velocity changes. By multiplying the changes in the angular velocity correction sequence by the parameter values ​​in the efficiency fluctuation feature vector and summing the results, the standard deviation of propulsion efficiency over a continuous paddling cycle is calculated and divided by the mean, yielding the coefficient of variation as the stable output level of propulsion efficiency. The specific calculation process is as follows: Let the angular velocity correction sequence be A = {a1, a2, ..., an}, where ai is the i-th change, and the efficiency fluctuation characteristic vector be V = {v1, v2, ..., vn}, where vi is the i-th parameter value. Then, the summation S = ∑(ai) vi), the coefficient of variation CV = (standard deviation SD / mean M), where SD and M are calculated based on propulsion efficiency data over 10 consecutive cycles.

[0055] Specifically, in one implementation, the efficiency stability output threshold is set based on statistical analysis of historical training data. By collecting paddling data from 100 elite athletes at different training stages, including the ratio of directional deviation angle to work stroke length, the distribution range of these ratios is calculated: first, the mean μ and standard deviation σ are calculated, then μ-σ to μ+σ are taken as the upper and lower limits of the threshold, for example, 0.1 to 0.3. When the actual ratio value exceeds this range, it indicates abnormal fluctuations in paddling efficiency. The efficiency fluctuation feature vector is constructed using a temporal arrangement, arranging the three parameters—blade entry depth, exit timing, and underwater dwell time—from the actual work parameter set obtained in S104 according to the time sequence of the paddling cycle.

[0056] Specifically, each paddling cycle generates a set of three-dimensional data points, and the data points from five consecutive cycles form a 15-dimensional feature vector. This vector reflects the variation of paddling motion over time, and the degree of fluctuation in the values ​​of each element in the vector is directly related to the stability of efficiency. Changes in water depth affect the initial propulsive force, the timing of exiting the water determines the termination point of effective work, and the duration of underwater stay is proportional to the total work done. The coordinated changes of these three parameters constitute the dynamic characteristics of paddling efficiency. Motion sensors are installed in the center of the athlete's back and on the outer side of the upper arm to monitor the movement trajectory of the torso and arm, respectively.

[0057] For example, as body coordination improves, the phase difference between trunk twisting and arm swing decreases, and their movement rhythms tend to synchronize. The angular velocity correction sequence records the time and amount of each adjustment, and the sequence length is the same as the number of paddling cycles.

[0058] In one possible implementation, the coefficient of variation is calculated using propulsion efficiency data from 10 consecutive paddling cycles. Propulsion efficiency is defined as the ratio of effective propulsion force to total output force, measured by a force sensor. The standard deviation reflects the dispersion of the efficiency value, the mean represents the average efficiency level, and the ratio of the two, i.e., the coefficient of variation, characterizes the relative stability of the efficiency output.

[0059] Preferably, when the coefficient of variation is less than 0.1, it is judged as high stability output; between 0.1 and 0.2, it is medium stability; and greater than 0.2, it is low stability, indicating poor consistency of the athlete's movements.

[0060] Understandably, by monitoring and adjusting in real time, a dynamic optimization process was achieved, transforming the efficiency from fluctuating to stable.

[0061] S106. Feedback is given to the hull attitude perception module based on the stable output level of propulsion efficiency, and the monitoring cycle of trajectory curvature radius is updated to maintain grip stability, force exertion rhythm continuity and torso rotation amplitude continuity at the optimal balance point.

[0062] Based on the stable output level of propulsion efficiency, the ship's roll and pitch angle changes are acquired through the hull attitude sensing module, which includes accelerometers and gyroscopes. When the change exceeds a preset threshold, the monitoring cycle is shortened; conversely, the monitoring cycle is extended, thus determining the monitoring cycle update value for the trajectory curvature radius. Using this monitoring cycle update value, the sampling frequency of grip stability, force exertion rhythm continuity, and torso rotation amplitude is adjusted according to this cycle. By dynamically adjusting these values, the fluctuations of the three parameters are maintained within the optimal balance point, thus obtaining parameters for maintaining the continuity of grip, rhythm, and rotation.

[0063] Specifically, the hull attitude sensing module includes a three-axis accelerometer and a gyroscope to monitor the hull's roll and pitch angles in real time. When the propulsion efficiency output is consistently high, it indicates stable paddling action, resulting in minimal hull attitude fluctuations. When the roll angle change is less than 5 degrees and the pitch angle change is less than 3 degrees, the monitoring cycle is extended from the default 0.1 seconds to 0.2 seconds, reducing the data acquisition frequency and lowering the system load. The monitoring cycle update value is inversely proportional to the magnitude of attitude change. When significant hull sway occurs, the monitoring cycle is automatically shortened to 0.1 seconds to improve the ability to capture detailed motion. The module uses low-power sensors, supporting high-frequency sampling without increasing system load.

[0064] Preferably, the sampling frequency is adjusted using a graded control method: the sampling frequency for grip stability is 100Hz, the sampling frequency for force exertion rhythm continuity is 50Hz, and the sampling frequency for torso rotation amplitude is 20Hz. This graded sampling frequency achieves continuous control of the paddling motion.

[0065] Example 2: This invention discloses an apparatus for implementing the multi-dimensional motion control method for water sports in Embodiment 1, comprising: Data acquisition module: used to collect motion parameters during paddling, including at least the angular velocity of the paddle handle rotation, the radius of curvature of the trajectory, and the deviation angle; Analysis module: used to analyze the motion parameters, identify the periodic deviation characteristics of the paddling path based on the motion parameters, and adjust the rotation radius determination benchmark based on the periodic deviation characteristics; Calculation module: used to determine the balance point between the power stroke and the trajectory curvature based on the adjusted rotation radius determination benchmark, and to obtain the corresponding propeller rotation radius setting value; Instruction module: Used to guide the paddler to adjust motion parameters based on the paddle handle rotation radius setting value.

[0066] It should be noted that the data acquisition module mentioned above specifically includes various sensors and inertial measurement units. Furthermore, the process of analyzing parameters and calculating data related to motion parameters in each of the above modules is described in Example 1, and will not be elaborated here to avoid redundancy.

[0067] In summary, the multi-dimensional motion control method and device for water sports disclosed in this invention addresses the problems of periodic path deviation, unstable propulsion direction, and discontinuous efficiency output during paddling. By real-time acquisition of paddle handle rotation angular velocity, trajectory curvature radius, deviation angle, and related paddle blade parameters, combined with data on the paddler's grip stability and body coordination, the invention dynamically identifies deviations and updates the rotation radius judgment benchmark. This invention determines the balance point between the force stroke and trajectory curvature using the adjusted benchmark, optimizes the paddle handle rotation radius setting, guides the paddler to correct the propulsion direction, and adjusts the paddle blade entry depth and exit timing to ensure that the ratio of directional deviation angle to work stroke meets efficiency requirements. Ultimately, this achieves stable propulsion efficiency output, and by updating the monitoring cycle through feedback, it maintains the continuity and stability of the overall paddling motion, thereby realizing motion control for water sports.

[0068] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the concept of this application. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A multi-dimensional motion control method for water sports, characterized in that, include: Collect motion parameters during the paddling process, including at least the angular velocity of the paddle handle rotation, the radius of curvature of the trajectory, and the deviation angle; Based on the motion parameters, the periodic deviation characteristics of the paddling path are identified, and the rotation radius determination criteria are adjusted. The balance point between the force stroke and the trajectory curvature is determined based on the adjusted rotation radius determination benchmark, and the corresponding propeller rotation radius setting value is obtained. The set value of the paddle handle rotation radius guides the paddler to adjust motion parameters and correct deviations in the direction of propulsion. Evaluate the corresponding ratio between the corrected directional deviation angle and the power stroke length to determine the stable output level of propulsion efficiency; The monitoring cycle of the trajectory curvature radius is updated based on the stable output level of the propulsion efficiency to maintain the continuity of the paddling motion.

2. The multi-dimensional motion control method for water sports as described in claim 1, characterized in that, The collection of motion parameters during the paddling process includes: The sequence of changes in the angular velocity of the propeller shaft is obtained by an inertial measurement unit, and the instantaneous rotation angle is calculated by integrating the angular velocity. The trajectory curvature radius is calculated using data from a three-axis gyroscope, and the deviation angle is recorded simultaneously to form a set of spatial curve parameters. If the deviation angle in the spatial curve parameter group exceeds the preset threshold, the grip force distribution data is collected by the pressure sensor, and the grip stability level is determined according to the standard deviation of the grip force time series. The consistency index of the force exertion rhythm is determined by the coefficient of variation of the time interval between adjacent paddling cycles. By monitoring the changes in the depth of the propeller blades in the water using a water pressure sensor and combining the data on the rotation amplitude of the torso with a motion capture sensor, the correlation coefficient between the duration of underwater stay and the rotation amplitude of the torso is calculated using the sliding window method, thus obtaining a quantitative assessment value of body coordination.

3. The multi-dimensional motion control method for water sports as described in claim 1, characterized in that, The step of identifying the periodic deviation characteristics of the paddling path based on the motion parameters includes: Perform a Fourier transform on the time series of propeller rotation angular velocity to extract the main frequency components and their amplitudes; By combining the rate of change of the trajectory curvature radius, periodic deviation characteristics are identified based on the phase difference between the frequency components and the curvature changes, and time-domain distribution data including deviation amplitude and deviation frequency are obtained. Based on the time-domain distribution data, the mean and variance of the deviation angle in each period are calculated using the moving average method; If the deviation angle exceeds the range of the mean plus a preset multiple of the standard deviation, the benchmark update mechanism is triggered to obtain the deviation amplitude value of the current period, and then the original rotation radius determination benchmark is corrected to obtain the adjusted benchmark value.

4. The multi-dimensional motion control method for water sports as described in claim 1, characterized in that, The step of determining the balance point between the force application stroke and the trajectory curvature based on the adjusted rotation radius determination benchmark includes: The stroke length is calculated by the product of the paddling period and the rotation angle. Obtain the curvature value of the arc trajectory based on the reciprocal of the rotation radius, and construct a matrix relating the travel length to the curvature value; By decomposing the thrust into longitudinal and lateral components, the proportion of the longitudinal thrust component under different rotation radii is calculated to form a numerical sequence. Based on the numerical sequence, the gradient ascent method is used to search for the extreme points of the propulsion force ratio; If there are multiple extreme points, the extreme point with a force stroke length greater than a preset threshold is selected as the candidate equilibrium point; By verifying the constraints, we determine whether the trajectory curvature corresponding to the candidate equilibrium point meets the conditions, and then determine the optimal equilibrium point and the corresponding propeller rotation radius setting value.

5. The multi-dimensional motion control method for water sports as described in claim 1, characterized in that, The method of guiding the paddler to adjust motion parameters through the paddle handle rotation radius setting includes: Based on the set value of the paddle rotation radius, monitor changes in grip force distribution and adjust the grip center position; A fixed-frequency signal is used to guide the force application rhythm, so that the time interval between adjacent paddling cycles tends to be consistent, and periodic data on the deviation of the propulsion direction are obtained. Adjust the blade entry depth according to the periodic data; The timing for water discharge is determined when the pressure value reaches its peak value. The adjustment amount of underwater dwell time is determined by the difference between the deviation angle and the preset benchmark, and a set of work parameters including water depth, water exit timing and dwell time are obtained. Then, the proportional relationship between the corrected directional deviation angle and the work stroke length is calculated.

6. The multi-dimensional motion control method for water sports as described in claim 1, characterized in that, The evaluation of the corresponding ratio between the corrected directional deviation angle and the length of the work stroke includes: The evaluation is based on the ratio of the directional deviation angle to the length of the work stroke, compared with a preset stable efficiency output threshold. If the ratio value exceeds the threshold range, the adjusted blade entry depth, exit timing and underwater dwell time parameters are arranged in chronological order to form an efficiency fluctuation feature vector. By monitoring the relative motion changes between the paddler's torso and upper limbs, identifying the real-time adjustment needs of the rotational angular velocity, and obtaining a correction sequence that includes the amount and timing of the angular velocity change; The coefficient of variation of propulsion efficiency during a continuous paddling cycle is calculated using the parameter values ​​of the corrected sequence and the efficiency fluctuation feature vector to determine the stable output level.

7. The multi-dimensional motion control method for water sports as described in claim 1, characterized in that, The monitoring cycle for updating the trajectory curvature radius based on the stable output level of the propulsion efficiency includes: Data on changes in the ship's roll and pitch angles are obtained through ship attitude sensing. If the changes in both the roll and pitch angles of the ship exceed the preset requirements, the monitoring cycle is shortened; otherwise, the monitoring cycle is extended to determine the updated monitoring cycle value for the trajectory curvature radius. The sampling frequency of grip stability, force application rhythm continuity, and torso rotation amplitude is adjusted according to the monitoring cycle update value. By maintaining the stability of the grip, the continuity of the force exertion rhythm, and the fluctuation of the torso rotation amplitude within a preset range, the continuity maintenance parameters are obtained to maintain the balance of the paddling motion.

8. The multi-dimensional motion control method for water sports as described in claim 1, characterized in that, Maintaining the continuity of paddling motion includes: Based on the stable output level of propulsion efficiency, and combined with the updated trajectory curvature radius monitoring cycle, motion parameters during the paddling process are continuously collected. By dynamically adjusting the control strategies for grip stability, force application rhythm continuity, and torso rotation amplitude through real-time changes in the aforementioned motion parameters; Based on the adjusted control strategy, acquire data on the rower's motion coordination in different cycles; By comparing the motion coordination data with a preset benchmark, it is determined whether the propeller rotation radius setting needs further adjustment. If corrections are needed, the baseline is recalculated and adjusted based on the deviation angle and trajectory curvature radius collected in real time to maintain the continuity of the paddling motion at the optimal equilibrium point.

9. An apparatus for implementing the multi-dimensional motion control method for water sports as described in any one of claims 1-8, characterized in that, include: Data acquisition module: used to collect motion parameters during paddling, including at least the angular velocity of the paddle handle rotation, the radius of curvature of the trajectory, and the deviation angle; Analysis module: used to analyze the motion parameters, identify the periodic deviation characteristics of the paddling path based on the motion parameters, and adjust the rotation radius determination benchmark based on the periodic deviation characteristics; Calculation module: used to determine the balance point between the power stroke and the trajectory curvature based on the adjusted rotation radius determination benchmark, and to obtain the corresponding propeller rotation radius setting value; Instruction module: Used to guide the paddler to adjust motion parameters based on the paddle handle rotation radius setting value.

Images