Sports equipment intelligent control system with self-adaptive adjustment function

Abstract

The invention relates to the technical field of sports equipment, and discloses a sports equipment intelligent control system with a self-adaptive adjustment function, and the system comprises a kinematics sensing unit, a power execution unit and a processor electrically connected with the kinematics sensing unit and the power execution unit; the processor is used for identifying a periodic motion rhythm of a user and determining a phase anchor point for applying disturbance; instructing a power execution unit to inject a perturbation signal to a user at the phase anchor point; collecting and analyzing the dynamic response of the user to the disturbance, and enabling the dynamic response to be equivalent to a second-order linear system model, thereby calculating at least one parameter for quantifying the instantaneous motion ability of the user; and on the basis of the ability parameters and the time change trend thereof, a feedforward control law is adopted to foreseeably adjust the training load of the next exercise cycle. According to the method, the neuromuscular control state of the user can be quantified, the training load is actively optimized before the user has obvious fatigue or action deformation, and individuation, intellectualization and safety of training are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of sports equipment, and in particular to an intelligent control system for sports equipment with an adaptive adjustment function. Background Art

[0002] With the advancement of technology, modern sports equipment is evolving towards intelligent and personalized features, aiming to provide users with a more efficient and safer fitness experience. Currently, mainstream smart sports equipment primarily adjusts training load through preset programs or physiological indicator feedback. For example, users can select a preset training mode, and the equipment will adjust resistance or speed according to a fixed schedule. More advanced equipment incorporates heart rate monitoring, attempting to dynamically adjust the load by maintaining the user's heart rate within a specific range.

[0003] However, these existing technical solutions have inherent limitations in terms of real-time performance, accuracy, and predictability. Control methods based on preset programs are essentially open-loop control, completely ignoring individual differences and real-time state changes during training. This makes it difficult to achieve truly personalized training and may lead to poor training results or an increased risk of sports injuries.

[0004] While feedback regulation based on physiological indicators like heart rate achieves a certain degree of closed-loop control, changes in heart rate, as a physiological response indicator, lag significantly behind the fatigue state of the neuromuscular system. This means that by the time the system detects an abnormal heart rate and makes adjustments, the user's muscle control and movement posture may have already declined for some time, and regulatory measures are often remedial rather than preventative. More critically, existing technologies generally lack direct means of quantifying the "quality" of a user's movement. They focus on whether the user has achieved "quantitative" goals (such as power and speed), but lack insight into the real-time stability and control capabilities of the neuromuscular system that supports the movement. Consequently, the system cannot proactively intervene before critical "quality" points, such as instability in the user's movement posture or the emergence of compensatory patterns, are reached.

[0005] Therefore, this field urgently needs a new technical solution that can accurately detect and quantify the user's true athletic ability in real time, especially the dynamic changes during fatigue accumulation, so as to achieve truly feedforward adaptive adjustment of training load. Summary of the Invention

[0006] The technical problem to be solved by the present invention is that the intelligent control systems of sports equipment in the existing technology usually rely on indirect and delayed physiological indicators such as heart rate to feedback and adjust the training load. This method cannot obtain the user's neuromuscular control ability during exercise in real time and directly, resulting in a mismatch between the applied training load and the user's instantaneous exercise ability, making it difficult to balance the safety and effectiveness of training.

[0007] In order to solve the above technical problems, the present invention provides a sports equipment intelligent control system with an adaptive adjustment function.

[0008] The system includes: a kinematic sensing unit configured to collect kinematic data of the user in real time; a powered execution unit configured to apply a training load to a user; as well as, A processor is communicatively connected to the kinematic sensing unit and the power execution unit.

[0009] The processor is configured to perform the following operations: (a) generating one or a series of perturbation signals based on the kinematic data; (b) controlling the power execution unit to inject the perturbation signal during the user's movement; (c) capturing the user's dynamic response to the perturbation signal through the kinematic sensing unit; (d) calculating one or more instantaneous motor performance parameters representing the user's neuromuscular control ability based on the dynamic response; (e) feed-forward adjusting the training load applied by the power execution unit based on the instantaneous exercise capacity parameter.

[0010] In one possible implementation, after calculating the current instantaneous motion capacity parameter based on the dynamic response, the processor is further configured to adaptively adjust the waveform of a subsequently generated micro-disturbance signal, where the adjustment is based on the dynamic response analysis results of one or more historical cycles.

[0011] For example, when the instantaneous motion ability parameter indicates that the user's stability is reduced, the processor automatically switches the subsequent micro-disturbance signal to a low-frequency or smoother waveform; when the instantaneous motion ability parameter indicates that the user's stability is good, it switches to a wide spectrum or pulse type waveform.

[0012] In another possible implementation, before injecting the perturbation signal, the processor is further configured to: First, the kinematic data is analyzed to identify the period and rhythm of the user's movement; Subsequently, at least one phase anchor point with biomechanical significance is calibrated within the identified motion cycle, and the injection time of the perturbation signal is synchronized with the phase anchor point.

[0013] In another possible implementation, the instantaneous motion capability parameter specifically includes the equivalent damping ratio of the user-equipment coupling system. and / or equivalent natural frequency .

[0014] To calculate these parameters, the processor is configured to: First, a deviation signal is generated by comparing the actual motion trajectory after disturbance with an undisturbed reference motion trajectory. ; The calculation is then completed by analyzing the ringing characteristics of the error signal.

[0015] Specifically, the processor identifies two consecutive peaks of the deviation signal in the same direction and , calculate the logarithmic decay rate ; Based on the logarithmic decay rate , calculate the equivalent damping ratio ; By measuring the oscillation period Get the damped natural frequency , and combined with the equivalent damping ratio Calculate the equivalent natural frequency .

[0016] In an implementation applied to multi-degree-of-freedom sports equipment, the processor can also be configured to set the injection axis of the micro-disturbance signal to an axis orthogonal to the axis of the user's main motion direction, which is intended to detect the user's core stability in non-main motion directions.

[0017] As a further combination, the processor may be configured to precisely synchronize the injection of the perturbation signal axially orthogonal to the main motion direction of the user with the aforementioned biomechanically significant phase anchor point.

[0018] In another possible implementation, when feedforward adjusting the training load, the processor is further configured to analyze the time change trend of the instantaneous motion capacity parameter in multiple consecutive motion cycles, and based on the time change trend, predictively adjust the training load applied to the next motion cycle.

[0019] To ensure the technical effect of the present invention, in a specific embodiment, the kinematic sensing unit is a high-resolution encoder, and the power execution unit is a high-fidelity motor or electromagnetic damper that can accurately output torque, so as to ensure the accurate injection of the micro-disturbance signal and the accurate capture of the dynamic response.

[0020] The present invention provides an intelligent control system for sports equipment with an adaptive adjustment function. It has the following beneficial effects: 1. By actively injecting micro-perturbations and analyzing their dynamic responses, the present invention can directly obtain instantaneous motor performance parameters that characterize the user's neuromuscular control ability, rather than relying on indirect and delayed physiological indicators. This makes the control basis more closely related to the user's actual motor state and more real-time. 2. Feedback control: Based on the analysis of the user's instantaneous athletic performance parameters and their changing trends, it can predictively adjust the training load. This adjustment occurs before the user's athletic performance shows a significant decline, thus avoiding the lag of traditional feedback control and effectively preventing posture deformation or safety risks caused by accumulated fatigue. 3. The present invention can achieve targeted detection of the user's specific athletic ability through adaptive and structured design of the waveform, injection timing, and injection axis of the disturbance signal, obtain richer state information than a single disturbance mode, improve the accuracy and dimension of system evaluation, and thus achieve dynamic and precise matching of training load and user ability. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a schematic structural diagram of an intelligent control system for sports equipment with an adaptive adjustment function according to an embodiment of the present invention;

[0022] Figure 2 A schematic diagram of the internal functional modules of a processor according to an embodiment of the present invention;

[0023] Figure 3 The figure is a schematic diagram of the overall control flow of an embodiment of the present invention.

[0024] Among them, 10, kinematic sensing unit; 20, power execution unit; 30, processor; 31, motion rhythm recognition and phase locking module; 32, adaptive micro-disturbance generation and injection module; 33, self-dynamic response analysis and capability parameterization module; 34, feedforward adaptive control module. DETAILED DESCRIPTION

[0025] In order to make the objectives, technical solutions and advantages of the present invention more clear, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0026] Refer to the attached Figure 1 , Figure 1 FIG2 is a schematic diagram of a structure of an intelligent control system for sports equipment with adaptive adjustment function according to an embodiment of the present invention. The system provided by the present invention may include: a kinematic sensing unit 10, a power execution unit 20, and a processor 30.

[0027] The kinematics sensing unit 10 collects kinematic data of the user in real time while using the sports equipment.

[0028] In one embodiment, the kinematic sensing unit 10 is a high-resolution photoelectric encoder mounted on a moving component of a sports device. For example, in a spinning bike, the photoelectric encoder can be coaxially mounted on the flywheel or crankshaft to output a high-frequency pulse signal representing the user's pedaling angular position and angular velocity.

[0029] In other embodiments, the kinematic sensing unit 10 may also be a Hall effect sensor or other sensor devices capable of accurately measuring displacement, velocity or acceleration.

[0030] The power execution unit 20 applies an adjustable training load to the user according to the instructions issued by the processor 30.

[0031] In one embodiment, the power actuator 20 is a servo motor or high-fidelity torque motor coupled to the sports equipment's transmission system. This motor not only provides stable training resistance but also accurately outputs an additional, tiny torque within milliseconds based on control commands, enabling micro-disturbance injection, as described later.

[0032] In another embodiment, the power execution unit 20 may also be an electromagnetic eddy current damper, and the damping torque can be precisely adjusted by controlling the magnitude of its excitation current.

[0033] The processor 30 is in communication with the kinematic sensing unit 10 and the power execution unit 20. The processor 30 is the control core of the system and can be implemented by a microcontroller (MCU), a digital signal processor (DSP), a field programmable gate array (FPGA), or a combination thereof.

[0034] The data collected by the kinematic sensing unit 10 is transmitted to the processor 30 via an input / output (I / O) port or a serial communication interface (such as an SPI or I2C bus). After completing data processing and control decisions, the processor 30 controls the drive circuit of the power actuator 20 through a pulse width modulation (PWM) signal or a digital-to-analog converter (DAC), thereby controlling its output torque.

[0035] Refer to the attached Figure 2 , Figure 2Schematic diagram of the internal functional modules of a processor according to one embodiment of the present invention. The processor 30 may include a motion rhythm recognition and phase locking module 31, the function of which is to provide a precise timing basis for subsequent micro-perturbation injection.

[0036] The motion rhythm recognition and phase locking module 31 receives a real-time kinematic data stream from the kinematic sensing unit 10, which is, for example, a sequence of instantaneous speeds representing the user's motion components. The module firstly calculates the speed sequence Processing is performed to identify the start and end of individual motion cycles.

[0037] In one embodiment, the module uses a peak detection algorithm to identify the speed sequence The time interval between two consecutive positive peak points is defined as the duration of a complete motion cycle, recorded as ,in is the sequence number of the cycle.

[0038] In order to obtain a stable motion cycle evaluation and avoid the influence of fluctuations of a single motion cycle on the overall judgment, the motion rhythm recognition and phase locking module 31 uses the sliding average method to calculate an average cycle This calculation is based on the most recent The duration of a completed exercise cycle is calculated as follows:

[0039] ;

[0040] in, is the average cycle length, is the sliding window size used to calculate the average value, which is a preset integer. For the The duration of a movement cycle.

[0041] To obtain a stable average period Then, the motion rhythm recognition and phase locking module 31 is any moment in the current motion cycle. Calculate a normalized phase The phase is calculated as:

[0042] ;

[0043] in, For the current In this way, any moment in the user's motion cycle is mapped to the phase interval [0, 2π).

[0044] Furthermore, the motion rhythm recognition and phase locking module 31 calibrates a set of phase anchor points with biomechanical significance within the normalized phase interval according to the specific motion pattern and stores them as a set These phase anchor points correspond to specific state transition points during the motion process, such as the phase corresponding to the velocity peak point, the phase corresponding to the velocity zero crossing point, or the phase corresponding to the acceleration peak point. It will be output to the subsequent functional modules and used as the precise time reference for perturbation injection.

[0045] Refer to the attached Figure 2 The processor 30 may also include an adaptive micro-perturbation generation and injection module 32. This module receives phase information from the motion rhythm recognition and phase locking module 31, as well as instantaneous motion performance parameters from the subsequent dynamic response analysis and performance parameterization module 33 (the function of this module will be described in detail later). Its function is to generate and control the injection of a structured micro-perturbation signal that is adapted to the user's state.

[0046] In one embodiment, the perturbation generation process of the module includes waveform adaptive selection. The adaptive micro-perturbation generation and injection module 32 internally stores a perturbation strategy library The library contains a variety of standardized disturbance waveform functions, such as Gaussian pulse function, square wave step function, sine sweep function, etc. This module receives the instantaneous motion capability parameter vector calculated in the previous cycle from the dynamic response analysis and capability parameterization module 33. , and according to the vector, through a preset decision logic, from the disturbance strategy library Select the waveform function to be used in the current period For example, when the parameter vector When the equivalent damping ratio parameter in dictates that the user stability is reduced, the module selects a smoother waveform with energy more concentrated in the low-frequency band for finer detection.

[0047] When generating the disturbance signal, the module also determines its amplitude and axial direction. The user's recent average power output is associated with the user's voluntary force to ensure that the disturbance is small relative to the user's voluntary force. The relationship can be expressed as ,in is a dimensionless preset perturbation coefficient.

[0048] For the embodiment applied to multi-DOF sports equipment, the module also decouples and constructs the disturbance axis. Assume that the unit vector of the user's main motion direction is , one or more unit vectors orthogonal to the main motion direction are This module will eventually output the disturbance torque vector Constructed as follows:

[0049] ;

[0050] in, and are the amplitude components applied to the main motion axis and the orthogonal axis respectively, is the aforementioned adaptively selected disturbance waveform function. By setting a non-zero When the user moves in the main direction, the system can apply a probing perturbation in the orthogonal direction to obtain the core stability information of the user against the unexpected direction disturbance.

[0051] After completing the disturbance signal After the construction of the adaptive perturbation generation and injection module 32 performs the phase-locked injection operation. This module receives the target phase anchor point output from the self-motion rhythm recognition and phase locking module 31. , and continuously monitor the real-time motion phase When detected At the moment of This is sent as a control instruction to the power execution unit 20. The power execution unit 20 then executes the instruction and applies the micro-perturbation to the user. This process ensures that the perturbation is always applied to the motion node with the same biomechanical significance.

[0052] Refer to the attached Figure 2 The processor 30 may also include a dynamic response analysis and capability parameterization module 33. The function of this module is to receive and process the dynamic response data caused by the micro-perturbation injection and convert it into a set of instantaneous motion capability parameters that can quantify the user's neuromuscular control ability.

[0053] Within a preset time window after the perturbation injection, the kinematic sensing unit 10 continuously collects the actual motion trajectory after the disturbance, which is recorded as At the same time, the dynamic response analysis and capability parameterization module 33 generates an undisturbed reference motion trajectory .

[0054] In one embodiment, the reference motion trajectory It is obtained by taking a weighted average of the trajectory data of several complete, undisturbed motion cycles before the disturbance occurs. The module then calculates the deviation signal between the actual trajectory and the reference trajectory :

[0055] ;

[0056] in, is the actual motion trajectory after disturbance, is the reference motion trajectory, is the deviation signal.

[0057] To remove measurement noise and motion artifacts that are not related to the disturbance response, the module uses a digital bandpass filter, such as a Butterworth filter, to filter the deviation signal. Perform filtering to obtain a pure dynamic response signal, which is recorded as .

[0058] Afterwards, the dynamic response analysis and capability parameterization module 33 processes the filtered dynamic response signal Analysis is performed to calculate instantaneous motion performance parameters. This calculation process equates the dynamic behavior of the user interacting with the equipment near the disturbance point to a second-order linear time-invariant (LTI) system model. The general differential equation form of this model can be expressed as:

[0059] ;

[0060] in, is the deviation signal after filtering; is the injected perturbation torque signal; is the equivalent mass of the user-equipment coupling system; is the equivalent damping coefficient that characterizes the energy dissipation capacity of the system; is the equivalent stiffness coefficient that characterizes the system's ability to resist deformation.

[0061] It should be noted that the method of the present invention does not need to directly solve 、 、 The absolute value of the response curve generated by the system is analyzed The morphological characteristics of the model are used to calculate the normalization parameters that are closely related to these coefficients.

[0062] The specific parameters calculated include:

[0063] Logarithmic decay rate For the decay oscillation response caused by pulse-type micro-perturbation, this module Identify the first peak in and the second peak in the same direction Logarithmic decay rate Calculated by the following formula:

[0064] ;

[0065] in, is the amplitude of the first peak, is the amplitude of the second peak in the same direction. Characterizes the rate at which the system dissipates energy.

[0066] Equivalent damping ratio This parameter is a dimensionless key indicator that characterizes the stability of the system and is related to the three equivalent coefficients of the model ( ), which is determined by the calculated logarithmic decay rate The calculation formula is:

[0067] ;

[0068] in, is the ratio of pi. The size of is directly related to the user's ability to suppress oscillations and maintain a stable posture.

[0069] Equivalent natural frequency This parameter is related to the equivalent mass and equivalent stiffness of the model ( ), which reflects the natural oscillation frequency of the system without damping. This module first measures the filtered response signal Oscillation period , which is the time interval between two consecutive peak points. Based on this, the damped natural frequency is calculated Then, combined with the calculated equivalent damping ratio , the undamped equivalent natural frequency is calculated by the following formula: :

[0070] ;

[0071] This parameter Related to the user's ability to quickly recruit and develop muscles.

[0072] Finally, the dynamic response analysis and capability parameterization module 33 will be the current The parameters calculated from the sub-perturbations are integrated into an instantaneous motion capability parameter vector This vector will be output to the adaptive micro-perturbation generation and injection module 32 to determine the next perturbation strategy and serve as a direct basis for training load adjustment.

[0073] Refer to the attached Figure 2 The processor 30 may further include a feedforward adaptive control module 34. The function of this module is to receive the instantaneous motion capacity parameter vector sequence output by the dynamic response analysis and capacity parameterization module 33, and based on this, predictively adjust the training load applied to the user.

[0074] The feedforward adaptive control module 34 not only uses the latest instantaneous motion capability parameter vector ,The time variation trend of the parameter vector in multiple continuous motion cycles is also analyzed.

[0075] In one embodiment, the module calculates the difference between the parameter vectors of the current cycle and the previous cycle to obtain a change trend vector .

[0076] This module uses a feedforward control law to determine the control force to be applied to the next motion cycle (i.e. training load (period) The load is determined by the load of the current cycle. and an adjustment calculated based on the above analysis Jointly decided, the update rules are as follows:

[0077] ;

[0078] Adjustment amount By a preset decision function Generate, the input of this function is the current instantaneous motion ability parameter vector and its changing trend vector ,Right now:

[0079] ;

[0080] Decision function It contains a set of specific decision rules. In one embodiment, the decision rules include:

[0081] Rule 1: When the parameter vector The equivalent damping ratio in There is a significant decrease, that is, the change Less than a preset negative threshold When , it is determined that the user system stability is reduced. At this time, a negative load adjustment is applied, the size of which is the same as The decline is related to, for example ,in is a preset negative feedback gain coefficient.

[0082] Rule 2: When the parameter vector The equivalent natural frequency in When a significant drop occurs, it is determined that the user's rapid response capability is weakened, and a negative load adjustment is also applied.

[0083] Rule 3: When the parameter vector Remain stable or show an improving trend over multiple consecutive cycles (e.g. The user is judged to have adapted to the current load (continuously increasing or stabilizing at a high level). At this point, a fixed, small positive load increment is applied. , in order to achieve a progressive load increase.

[0084] In addition, all calculated training loads for the next cycle Before being sent to the power execution unit 20, it will be checked by a safety constraint module to ensure that its value is always within a preset safety range. [ L min , L max ] To ensure the user's sports safety.

[0085] Refer to the attached Figure 3 , Figure 3 It is a schematic diagram of the overall control flow according to one embodiment of the present invention.

[0086] This process demonstrates the complete operating cycle of the intelligent control system of the present invention. Upon initiation, the system first initializes training parameters. Subsequently, it enters the main control loop: the system continuously collects the user's kinematic data via the kinematic sensing unit 10. The motion rhythm recognition and phase locking module 31 processes this data to identify the motion rhythm and calculate the real-time phase.

[0087] The system continuously determines whether the current motion phase has reached the preset phase anchor point. If not, it returns to continue collecting data. If it has, the adaptive perturbation generation and injection module 32 generates a perturbation signal and injects it into the user's motion via the power actuator 20, locking the signal into the user's motion.

[0088] Next, the system collects dynamic response data triggered by the micro-perturbation and processes it in the dynamic response analysis and performance parameterization module 33. This module analyzes the response and calculates a parameter vector representing the user's instantaneous performance. This parameter vector is then sent to the feedforward adaptive control module 34, which calculates the training load for the next exercise cycle based on this parameter and its historical trend.

[0089] Finally, the system determines whether training has concluded. If not, the system applies a new training load and returns to the beginning of the main control loop to continue the next round of monitoring and adjustment. If training has concluded, the entire process terminates. Through this closed-loop process, the present invention achieves periodic, adaptive, and predictive dynamic adjustment of training load.

[0090] In order to enable those skilled in the art to further understand the present invention, the overall workflow of the present invention will be described below with several specific, non-limiting embodiments.

[0091] Example 1:

[0092] This embodiment provides an application of the system of the present invention on a single-degree-of-freedom intelligent dynamic bicycle.

[0093] The intelligent spinning bike is integrated with the intelligent control system of the present invention, wherein the kinematic sensing unit 10 is a high-resolution photoelectric encoder mounted on the crank shaft, the power execution unit 20 is a servo motor coupled to the flywheel, and the processor 30 is a built-in microcontroller.

[0094] The user starts a high-intensity interval training. In the initial stage, the user pedals, and the motion rhythm recognition and phase locking module 31 in the processor 30 collects encoder data and determines the user's pedaling cycle by identifying the periodic peak of the speed sequence. At the same time, the motion rhythm recognition and phase locking module 31 marks the user's crank in the horizontal forward position (i.e. the starting point of force in biomechanics) as a phase anchor point. .

[0095] During the stable period of training, the adaptive perturbation generation and injection module 32 generates a short-term, pulsed resistance torque as a perturbation signal. Arrival at phase anchor point When , the adaptive micro-disturbance generation and injection module 32 immediately instructs the servo motor to superimpose the pulse resistance torque on the basic training resistance.

[0096] After the micro-disturbance is injected, the photoelectric encoder 10 captures the instantaneous change in the user's pedaling angular velocity. The dynamic response analysis and capability parameterization module 33 compares this disturbed angular velocity curve with the average angular velocity curve of the previous few cycles to obtain the deviation signal e(t). The dynamic response analysis and capability parameterization module 33 analyzes the deviation signal and calculates the user's equivalent damping ratio at that moment. and the equivalent natural frequency When the user is in good physical condition, the response decays rapidly and the calculated The value is at a high level.

[0097] As the training progresses, the user gradually becomes fatigued. After another phase-locked injection of micro-perturbations, the captured dynamic response shows more obvious oscillations and takes longer to recover. The equivalent damping ratio calculated by the dynamic response analysis and capability parameterization module 33 is Significantly lower than the initial value. The feedforward adaptive control module 34 detects The downward trend of the value in the time series has exceeded the preset threshold. Based on this judgment, the feedforward adaptive control module 34 calculates a negative adjustment amount , and before the next exercise cycle begins, the base training resistance output by the servo motor is lowered. This adjustment occurs before the user's pedaling posture shows any noticeable deformation, enabling predictive adjustment of training load.

[0098] Example 2:

[0099] This embodiment provides an application of the system of the present invention on a multifunctional comprehensive training machine (gantry) with multiple degrees of freedom and independent resistance for both arms.

[0100] The training machine features an independent servo motor (20) installed at the exit of each cable, as a power actuator, and an encoder (10) installed on the cable drum. Users use the device to perform standing trunk rotation resistance training ("logger pose"). This exercise primarily rotates the trunk horizontally, requiring the core muscles to maintain forward and backward and lateral stability.

[0101] After the training starts, the motion rhythm recognition and phase locking module 31 recognizes the period and rhythm of the user's rotation movement and marks the moment when the trunk rotates to the maximum angular velocity as the phase anchor point. .

[0102] The adaptive perturbation generation and injection module 32 generates a composite perturbation signal. The signal contains two components: a component Applied in the main direction of motion, that is, applying a small additional resistance to the user's rotational motion; another component Applied in an axis orthogonal to the main motion direction, this orthogonal perturbation is achieved by instructing the servo motors of the two arms to generate a small, instantaneous differential resistance, which generates a lateral perturbation force on the user's torso.

[0103] When the motion rhythm recognition and phase locking module 31 detects that the user's motion reaches the phase anchor point When , the adaptive micro-disturbance generation and injection module 32 instructs the dual-arm servo motor to inject the above-mentioned composite micro-disturbance simultaneously.

[0104] The dynamic response analysis and capability parameterization module 33 collects data from the dual-arm encoders and decomposes the user's dynamic response in the main motion direction and the dynamic response in the lateral direction (orthogonal axis). The dynamic response analysis and capability parameterization module 33 analyzes the response signals in these two directions separately and calculates a set of capability parameters in the main motion direction ( ) and a set of orthogonal capacity parameters ( ). The former characterizes the user's core force generation ability, while the latter directly quantifies the user's core control ability to resist lateral instability.

[0105] The feedforward adaptive control module 34 receives these two sets of parameters. During a training session, the feedforward adaptive control module 34 monitors the user's main motion direction parameters. Still maintains a high level, but its orthogonal direction parameters This indicates that the user's core stability has begun to decline and the quality of his exercise posture has deteriorated in order to maintain the power. The feedforward adaptive control module 34 preferentially calculates a negative training load adjustment based on the downward trend of this orthogonal parameter. , reducing the training resistance in the main movement direction, thereby actively reducing the training intensity when the core stability has not been completely destroyed, ensuring the correctness and safety of the exercise.

[0106] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent control system for sports equipment with adaptive adjustment function, characterized in that: include: a kinematic sensing unit configured to collect kinematic data of the user in real time; a power execution unit configured to apply a training load to a user; a processor, communicatively connected to the kinematic sensing unit and the power execution unit, wherein the processor is configured to: generating one or a series of perturbation signals based on the kinematic data; controlling the power execution unit to inject the micro-disturbance signal during the user's movement; capturing the user's dynamic response to the perturbation signal through the kinematic sensing unit; calculating one or more instantaneous motor performance parameters representing the user's neuromuscular control ability based on the dynamic response; Based on the instantaneous athletic performance parameter, the training load applied by the power execution unit is feed-forward adjusted.

2. The sports equipment intelligent control system with adaptive adjustment function according to claim 1 is characterized in that: The processor is configured to: After calculating the current instantaneous motion capability parameter based on the dynamic response, the waveform of the subsequently generated micro-disturbance signal is adaptively adjusted, wherein the adjustment is based on the dynamic response analysis results of one or more historical cycles.

3. The sports equipment intelligent control system with adaptive adjustment function according to claim 2 is characterized in that: When adaptively adjusting the waveform of the perturbation signal, the processor is configured to: When the instantaneous athletic ability parameter indicates that the user's stability has decreased, automatically switching the subsequent micro-perturbation signal to a low frequency or a smoother waveform; When the instantaneous athletic ability parameter indicates that the user's stability is good, the waveform is switched to a wide spectrum or pulse type.

4. The sports equipment intelligent control system with adaptive adjustment function according to claim 1 is characterized in that: Before injecting the perturbation signal, the processor is further configured to: Analyzing the kinematic data to identify the period and rhythm of the user's movement; At least one phase anchor point with biomechanical significance is calibrated within the motion cycle, and the injection time of the micro-perturbation signal is synchronized with the phase anchor point.

5. The sports equipment intelligent control system with adaptive adjustment function according to claim 1 is characterized in that: The instantaneous athletic ability parameters include: The equivalent damping ratio and / or equivalent natural frequency of the user-equipment coupling system.

6. The sports equipment intelligent control system with adaptive adjustment function according to claim 5 is characterized in that: When calculating the instantaneous athletic ability parameter, the processor is configured to: By comparing the actual motion trajectory after disturbance with the reference motion trajectory without disturbance, a deviation signal is generated; The equivalent damping ratio and / or equivalent natural frequency are calculated by analyzing the attenuated oscillation characteristics of the deviation signal, including its logarithmic decay rate and oscillation period.

7. The sports equipment intelligent control system with adaptive adjustment function according to claim 4 is characterized in that: When the system is applied to multi-degree-of-freedom sports equipment, the processor is configured to: The injection axis of the micro-disturbance signal is set to an axis orthogonal to the axis of the user's main motion direction to detect the user's core stability in the non-main motion direction.

8. The sports equipment intelligent control system with adaptive adjustment function according to claim 1 is characterized in that: When feedforward adjusting the training load based on the instantaneous athletic ability parameter, the processor is further configured to: Analyzing the temporal variation trend of the instantaneous exercise capacity parameter over a plurality of consecutive exercise cycles; Based on the temporal variation trend, the training load applied to the next exercise cycle is proactively adjusted.

9. The sports equipment intelligent control system with adaptive adjustment function according to claim 1, characterized in that: The kinematic sensing unit is a high-resolution encoder; The power execution unit is a high-fidelity motor or electromagnetic damper that can accurately output torque, so as to ensure the accurate injection of the micro-disturbance signal and the accurate capture of the dynamic response.

10. The sports equipment intelligent control system with adaptive adjustment function according to claim 7, characterized in that: The processor is configured to: The injection of a perturbation signal axially orthogonal to the main motion direction of the user is precisely synchronized with the phase anchor point having biomechanical significance.

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