Self-adaptive intelligent bending bird training auxiliary device and method

Abstract

The invention provides a self-adaptive intelligent bending bird training auxiliary device and method, and belongs to the technical field of fitness equipment, and the device comprises the following structures: a forearm binding assembly, an upper arm binding assembly, a bending angle control assembly and a pressure monitoring module; the forearm binding assembly is connected to the big arm binding assembly through two pivots, the forearm binding assembly can rotate around the axes of the pivots relative to the big arm binding assembly, and the buckling angle control assembly is used for enabling the forearm binding assembly to rotate relative to the big arm binding assembly; the pressure monitoring module comprises a controller, a force sensor and an indicator lamp and is used for monitoring the buckling angle control assembly by the arms of the user. According to the device and the method, the stress interval of compensatory force application can be adaptively adjusted, the stress interval is adaptively given in combination with the condition of a user, and when the force application is not in the stress interval, a trainee is prompted to change the force application mode in time.

Description

Technical Field

[0001] This invention belongs to the field of fitness equipment technology, specifically relating to an adaptive intelligent bent-over fly training aid device and method. Background Technology

[0002] The bent-over dumbbell fly is a classic exercise for training the posterior deltoid. The key points of the movement are: keep the elbow joint at a fixed 150-160 degree flexion angle, keep the forearm relaxed, and do not use compensatory force. The force of the bent-over dumbbell fly is mainly transferred from the posterior deltoid to the long head of the triceps brachii.

[0003] The difficulty of the bent-over dumbbell fly exercise stems primarily from incorrect posture and force application. Currently, some products fix the elbow flexion angle to standardize the form. However, these products don't account for forearm compensation. Even with a fixed elbow flexion angle, compensating for forearm movement during the exercise can still lead to suboptimal results from the bent-over dumbbell fly.

[0004] Therefore, it is necessary to design an adaptive intelligent bent-over dumbbell fly training aid device and method to respond promptly to the trainee's forearm compensatory force exertion and remind the user to adjust the force exertion method and standardize the bent-over dumbbell fly training movement. Summary of the Invention

[0005] This invention proposes an adaptive intelligent bent-over fly training aid device and method, which is used to issue timely warnings when the user's bent-over fly training is not standard, reminding the user to adjust their posture.

[0006] For an adaptive intelligent bent-over bird training aid device, including a forearm binding assembly, an upper arm binding assembly, a flexion angle control assembly and a pressure monitoring module;

[0007] The forearm binding assembly includes two forearm uprights arranged side by side along the X direction, an arm base fixedly connected between the two forearm uprights, and a cable tie for binding the forearm on the arm base.

[0008] The upper arm binding assembly includes two upper arm uprights arranged side by side along the X direction, and another arm base is fixedly connected between the two upper arm uprights. The arm base is provided with another cable tie for binding the upper arm.

[0009] The forearm restraint assembly is connected to the upper arm restraint assembly via two pivots. The forearm restraint assembly can rotate relative to the upper arm restraint assembly about the pivot axis. The flexion angle control assembly is used to enable the forearm restraint assembly to rotate relative to the upper arm restraint assembly. The pressure monitoring module includes a controller, force sensor, and indicator light to monitor the compensatory force exerted by the user's arm on the flexion angle control assembly. It promptly reminds the user to adjust their force when the user's force is outside the force range.

[0010] Furthermore, the buckling angle control component includes:

[0011] The electric actuator has a base on its non-telescopic end that is hinged to the upper arm support plate of the upper arm binding assembly via shaft one, with the axis of shaft one along the X direction. The telescopic end is hinged to one end of a linkage plate via shaft two, with the other end of the linkage plate fixedly connected to a pivot, which is fixedly connected to the lower arm support plate. The axes of the pivot and shaft two are along the X direction. A force sensor is installed between the electric actuator body and the base. When the electric actuator is subjected to a human axial force, the electric actuator body and the base together press against the force sensor, causing the force sensor to generate pressure data.

[0012] Furthermore, let point A be the hinge point between shaft 2 and the linkage plate, point B be the hinge point between shaft 1 and the upper arm upright plate, and point C be the hinge point between the pivot and the linkage plate; let the length of line segment BC be a, the length of line segment AC be b, and the length of line segment AB be c. Since the lower arm upright plate 1 and the linkage plate 6 are fixedly connected by pivot 4, it is reasonable to assume that the straight line along the length direction of the lower arm upright plate 1 coincides with the straight line along the length direction of the linkage plate 6; then the angle Dq between the upper arm upright plate and the lower arm upright plate satisfies:

[0013]

[0014] In the formula, Dx represents the extension and retraction of the electric actuator.

[0015] Furthermore, S1: The user selects a training mode on the adaptive intelligent bent-over bird training aid device. The training modes include novice mode and non-novice mode. Based on the mode selected by the user, the corresponding angle Dq and sensitivity coefficient k1 are generated or set.

[0016] S2: After the user wears the adaptive intelligent bent-over fly training aid, the user completes multiple standard bent-over fly exercises without dumbbells, and the average pressure value μ of each exercise without dumbbells is calculated. baseline And based on the average pressure value μ baseline Calculate the standard deviation σ of the standard bent-over fly without dumbbells. baseline Combined with the average pressure value μ baseline σ baseline And the sensitivity coefficient k1, outputting the baseline stress value when the user trains without dumbbells. and

[0017] S3: Obtain pressure data for the bent-over fly exercise while the user is carrying dumbbells, and calculate the average pressure value μ for each movement while carrying dumbbells. current ; and based on the average pressure value μ current Calculate the standard deviation σ of the bent-over fly motion while carrying dumbbells. current Based on the standard deviation σ of the bent-over fly motion while carrying dumbbells. current The standard deviation σ of the standard bent-over fly without dumbbells baseline Calculate the current training fatigue level (Fatigue). Factor (t);

[0018] S4: Average pressure value μ per movement while carrying dumbbells current The standard deviation σ of bent-over fly with dumbbells current And the sensitivity coefficient k1, calculate the pressure reference value when carrying dumbbells. and Based on the stress baseline during training without dumbbells Calculate the training intensity factor Intensity Factor (t);

[0019] S4: Average pressure value μ per movement while carrying dumbbells current The standard deviation σ of bent-over fly with dumbbells current And the sensitivity coefficient k1, calculate the pressure reference value when carrying dumbbells. and Based on the stress baseline during training without dumbbells Calculate the training intensity factor Intensity Factor (t);

[0020] S5: Calculate the training frequency factor based on the interval between two training sessions. Factor (Δt), and based on the training frequency factor. Factor (Δt) and training intensity factor Intensity Factor (t), calculate the environmental factor Environment Factor (t,Δt);

[0021] S6: Based on Fatigue Level Factor (t) and environmental factor Environment Factor (t,Δt), calculate the adaptive threshold Threshold adaptive (t,Δt);

[0022] S7: Combining stress baseline values ​​from training without dumbbells and adaptive threshold Threshold adaptive (t, Δt), determine the force range S of the standard bent-over fly movement when carrying dumbbells. m By comparing the force on the force sensor, it can be determined whether the bent-over fly motion while carrying dumbbells is standard.

[0023] Further, step S3 includes the following steps:

[0024] S3.1: By having the user perform m bent-over flyes while carrying dumbbells, the force data of the electric actuator is collected to obtain the pressure value for each movement. The formula is:

[0025]

[0026] In the formula, T' represents the stress value of the k-th bent-over fly repetition while carrying dumbbells. k F'(t) represents the duration of the k-th bent-over fly motion while carrying dumbbells; F'(t) is a continuous function of the force on the push rod while carrying dumbbells.

[0027] S3.2: Obtain the average stress value μ of the bent-over fly motion while carrying dumbbells in real time. current ;

[0028] The formula is:

[0029]

[0030] In the formula, μ ′baselin is the average stress value during the bent-over fly exercise while carrying dumbbells; m is the number of bent-over fly exercises performed while carrying dumbbells. This represents the pressure value during the k-th repetition while carrying a dumbbell;

[0031] S3.3: Obtain the standard deviation of the bent-over fly motion while the user is carrying dumbbells, using the following formula:

[0032]

[0033] In the formula, σ current The standard deviation of stress during bent-over flyes with dumbbells; μ represents the stress value during the k-th bent-over fly with dumbbells. current The real-time average pressure value during the bent-over fly motion while carrying dumbbells;

[0034] S3.4: Calculate fatigue based on the standard deviation of the stress of the bent-over fly with dumbbells and the standard deviation of the stress of the standard bent-over fly without dumbbells;

[0035]

[0036] In the formula, Fatigue Factor (t) represents fatigue level; σ current σ represents the standard deviation of stress during bent-over flyes with dumbbells. baseline The standard deviation of stress in a standard bent-over fly exercise without dumbbells; T session The current training duration for dumbbell exercises; T standard The standard time is set and varies with the number of groups and the number of repetitions; α and β represent the weights, α = 0.7 and β = 0.3.

[0037] Further, step S4 includes the following steps:

[0038] S4.1: The formula for the reference pressure value when carrying dumbbells is:

[0039] F current1 =μ current -k1×σ current

[0040] F current2 =μ current +k1×σ current

[0041] In the formula, The baseline pressure value for bent-over flyes while carrying dumbbells; μ current σ represents the real-time average pressure value during the bent-over fly motion while carrying dumbbells. current is the standard deviation of stress during bent-over flyes with dumbbells; k1 is the sensitivity coefficient;

[0042] S4.2: Calculate the training intensity factor;

[0043] The formula is:

[0044]

[0045] In the formula, The baseline stress value for bent-over flyes while carrying dumbbells; Indicates the baseline stress level during training without dumbbells; Intensity Factor (t) represents the training intensity factor.

[0046] Furthermore, step S5 specifically includes the following steps:

[0047] S5.1: Calculate the training frequency factor;

[0048] The formula is:

[0049] Frequency Factor(Δt)=f(Δt)

[0050]

[0051] In the formula, Δt represents the time interval between the current training session and the previous training session, in hours;

[0052] Frequency Factor (Δt) represents the training frequency factor;

[0053] S5.2: Calculate environmental factors;

[0054] Environment Factor (t,Δt)=

[0055] 1+δ1×Intensity Factor +δ2×Frequency Factor

[0056] In the formula, Environment Factor δ represents the environmental factor; δ1 and δ2 represent the parameter coefficients, where δ1 = 0.3 and δ2 = 0.2. Intensity Factor Frequency represents the training intensity factor. Factor This represents the training frequency factor.

[0057] Furthermore, in steps S6 and S7, the formula for the adaptive threshold is:

[0058] Threshold adaptive (t,Δt)=Fatigue Factor ×Environment Factor

[0059] In the formula, Threshold adaptive Indicates an adaptive threshold; Fatigue Factor Indicates fatigue level; Environment Factor Indicates environmental factors; stress range

[0060] When the pressure monitored by the force sensor is within the force range S m If the user's bent-over flying motion is correct, then the motion is standard; otherwise, it is not.

[0061] Furthermore, when the user selects the novice mode, the controller defaults to Dq of 150° and sensitivity coefficient k1 = 1.5; when the user selects the non-novice mode, the selection range of Dq is [150°, 160°], and the sensitivity coefficient k1 is set by the user, k1∈[1.5,2]. The user writes the values ​​of Dq and k1 into the controller program through the writing module.

[0062] The beneficial effects that can be achieved by adopting the above technical solution are:

[0063] This method considers factors such as fatigue, training intensity, and training frequency influencing the user's compensatory force exertion during the bent-over fly movement. Furthermore, it collects a pressure baseline value (S2) based on the specific conditions of each step, thereby obtaining the force range S. m In line with the user's own training, when the pressure monitored by the force sensor is within the force range S m If the user's bent-over flying motion is correct, then it is correct; otherwise, it is incorrect. The LED indicator lights emit red and green lights to promptly remind the user whether the motion is correct and to remind the user to change the way of exerting force when the motion is incorrect. Attached Figure Description

[0064] Figure 1 This is a schematic diagram of the overall structure of the device;

[0065] Figure 2 This is a schematic diagram of the buckling angle control component;

[0066] Figure 3 This is a flowchart of Example 2.

[0067] 1. Forearm support plate; 2. Upper arm support plate; 3. Arm base; 4. Pivot; 5. Electric push rod; 6. Linkage plate; 7. Axis 1; 8. Axis 2; 9. Cable tie; 10. LED indicator light. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0069] Example 1: As Figure 1 and Figure 2As shown, an adaptive intelligent bent-over fly training aid device includes a forearm support plate 1, an upper arm support plate 2, an arm base 3, a pivot 4, an electric push rod 5, a linkage plate 6, a first shaft 7, a second shaft 8, cable ties 9, and an LED indicator 10. It is divided into four parts: a forearm binding assembly, an upper arm binding assembly, a flexion angle control assembly, and a pressure monitoring module. The forearm binding assembly and the upper arm binding assembly have the same structure but different dimensions. Taking the forearm binding assembly as an example, it includes the following structure:

[0070] Two forearm uprights 1 are arranged side by side along the X direction, and the length direction of the two forearm uprights 1 is along the Y direction. From a top view, the X direction is perpendicular to the Y direction.

[0071] At least one limiting component includes an arm base 3. From a Y-direction perspective, the limiting plate 2 is a ring with a notch. The arm base 3 is simultaneously fixedly connected to two forearm uprights 1. To facilitate connection, the surface between the arm base 3 and the forearm uprights 1 can be designed as a plane to facilitate bolt and screw hole connection.

[0072] From a top-down perspective, the line connecting the midpoints of the two forearm uprights 1 is defined as line segment L, the perpendicular line passing through the midpoint of line segment L is defined as line M, and the plane passing through line M and along the vertical direction is defined as plane P. All arm bases 3 are symmetrical bodies symmetrical about plane P, with the notch of the arm base 3 facing upwards. In this embodiment, there are two limiting components, arranged side-by-side along the Y direction. Each arm base 3 is provided with a cable tie 9, with its two ends connected to both ends of the arm base 3. One end is fixed with strong adhesive, and the other end is detachably connected with Velcro.

[0073] Compared to the forearm restraint assembly, the upper arm restraint assembly has a larger distance along the X-direction between its two upper arm uprights 2, while the forearm restraint assembly has a smaller distance along the X-direction between its two forearm uprights 1. Therefore, from an X-direction perspective, the two forearm uprights 1 of the forearm restraint assembly are located between the two upper arm uprights 2 of the upper arm restraint assembly. From a Y-direction perspective, the upper arm restraint assembly is located at one end of the forearm restraint assembly along the Y-direction.

[0074] The forearm restraint assembly can rotate relative to the upper arm restraint assembly via a flexion angle control assembly; the flexion angle control assembly includes the following structure:

[0075] Two pivots 4, with their rotation axes along the X direction and symmetrically arranged along plane P, are fixedly connected to the two forearm uprights 1 of the forearm binding assembly. The two upper arm uprights 2 of the upper arm binding assembly are each provided with through holes. The two upper arm uprights 2 of the upper arm binding assembly are respectively fitted onto the corresponding pivots 4 through the corresponding through holes. Bearings are installed in the through holes. The two forearm uprights 1 of the forearm binding assembly rotate relative to the upper arm binding assembly through the bearings and the corresponding pivots 4.

[0076] The electric actuator 5 has a force sensor installed between its main body and base. The non-telescopic end of the base is hinged to the upper arm support plate 2 of the upper arm restraint assembly via shaft 7. The axis of shaft 7 is along the X-direction. This force sensor can monitor the axial pressure changes generated by the user's arm on the actuator in real time, providing core pressure detection data for the adaptive algorithm. When the electric actuator 5 is subjected to axial force from the user's arm, the main body and base of the electric actuator 5 jointly compress the force sensor, thereby generating pressure data.

[0077] The linkage plate 6 has one end fixedly connected to one of the pivots 4, and the other end is hinged to the telescopic end of the electric push rod 5 via a shaft 8. The axis of the shaft 8 is along the X direction.

[0078] When the electric push rod 5 extends or retracts, the electric push rod 5 drives the pivot 4 and the forearm restraint assembly to rotate relative to the upper arm restraint assembly around the axis of the pivot 4 via the linkage plate 6.

[0079] The controller (structure not shown in the figure) is mounted on the upper arm support plate 2 of the upper arm restraint assembly. It is electrically connected to the force sensor and the LED indicator 10 mounted on the upper arm support plate 2, and is equipped with a Bluetooth module, enabling it to connect and communicate with control terminals such as mobile phones. The controller receives pressure data monitored by the force sensor in real time, analyzes the force changes of the user's arm on the push rod based on an adaptive algorithm, and determines whether the trainee has a compensatory tendency when practicing the fly motion. When a compensatory movement is detected, the controller simultaneously triggers a vibration alert and a flashing red LED alarm; when the movement is standard, the green LED remains on to provide positive feedback. The training status and detection results are sent to the user's mobile phone via the Bluetooth module. The user can set the elbow flexion angle via the mobile phone, and the controller calculates the required push rod extension and retraction based on the input angle and controls the movement of the electric push rod 5. The user can also calibrate and zero the controller's pressure detection system via the mobile phone to establish a personalized pressure benchmark model. The controller integrates real-time calculation functions for fatigue coefficients and environmental factors, and can dynamically adjust the judgment threshold to achieve personalized detection of compensatory movements.

[0080] Figure 2 This is a schematic diagram of the side lengths of each side of the buckling angle control component. Point C is the location of pivot 4; point B is the location of axis 1 7; and point A is the location of axis 2 8. A ray is drawn in the negative Y-axis direction with point C as the origin.

[0081] G and D are any points on the ray except C. Line segment BC is parallel to the length direction of the upper arm upright plate 2. Let the length of line segment BC be a, the length of line segment AC be b, and the length of line segment AB be c. Since the lower arm upright plate 1 and the linkage plate 6 are fixedly connected by the pivot 4, it is reasonable to assume that the straight line in the length direction of the lower arm upright plate 1 coincides with the straight line in the length direction of the linkage plate 6.

[0082] Let ∠BCA be q; then ∠BCA satisfies the following relationship:

[0083]

[0084] When the trainee adjusts the angle between the upper arm support plate 2 and the lower arm support plate 1 to Dq, after inputting Dq, the terminal writes the data to the controller. The controller controls the extension and retraction of the electric actuator Dx. The control equation for Dx is:

[0085]

[0086] The procedure for using this device is as follows:

[0087] After the system starts, the user selects a training mode. Training modes include beginner mode and non-beginner mode.

[0088] When the non-beginner mode is selected, the system allows users to adjust the angle parameters as needed. The angle adjustment range is [150°, 160°], and the sensitivity coefficient k1 can be set manually, where k1 ∈ [1.5, 2]. When the beginner mode is selected, the controller's default angle Dq = 150°, and the default sensitivity coefficient k1 = 1.5.

[0089] After selecting the training mode, the user puts the device on their arm and starts the bent-over fly training.

[0090] Example 2: As Figure 3 As shown, an adaptive intelligent bent-over bird training assistance method includes the following steps:

[0091] S1: The user selects a training mode on the adaptive intelligent bent-over bird training aid device and obtains the corresponding angle Dq and sensitivity coefficient k1;

[0092] Specifically, the controller of the adaptive intelligent bent-over bird training aid has a writing module and a mode selection button;

[0093] When the user selects the beginner mode, the controller of the adaptive intelligent bent-over bird training aid adjusts the angle Dq = 150° between the upper arm upright plate 2 and the lower arm upright plate 1, and sets the sensitivity coefficient k1 = 1.5.

[0094] When the user selects the non-beginner mode, the user can write the angle Dq to the controller of the adaptive intelligent bent-over bird training aid device through the writing module. The range of Dq is [150°, 160°]. When the non-beginner mode is selected, the sensitivity coefficient k1∈[1.5,2].

[0095] S2: After the user wears the adaptive intelligent bent-over fly training aid, the user completes 10-15 standard bent-over fly repetitions without dumbbells, and the system outputs the baseline stress value for the user training without dumbbells. Specifically, this includes the following steps:

[0096] S2.1: The user completes n standard bent-over flyes without dumbbells. The force sensor collects the force data of the electric push rod 5 to obtain the pressure value for each movement. The formula is:

[0097]

[0098] In equation (1), T represents the stress value of the k-th standard bent-over fly without dumbbells. k F(t) represents the duration of the k-th standard bent-over fly without dumbbells, obtained by the controller monitoring the force sensor's force duration; F(t) is a continuous function of the force on the push rod without dumbbells, obtained by the pressure data monitored by the controller's force sensor.

[0099] S2.2: Obtain the average stress value for each repetition of the user's standard bent-over fly exercise without dumbbells.

[0100] The formula is:

[0101]

[0102] In equation (2), μ baseline is the average stress value for a standard bent-over fly without dumbbells; n is the number of times a standard bent-over fly can be performed without dumbbells. This represents the pressure value of the k-th repetition without dumbbells.

[0103] S2.3: Obtain the standard deviation of the standard bent-over fly motion when the user is not carrying dumbbells.

[0104] The formula is:

[0105]

[0106] In equation (3), σ baseline μ represents the standard deviation of the stress during a standard bent-over fly without dumbbells. baseline The average stress value for a standard bent-over fly exercise without dumbbells; This represents the duration of the k-th standard bent-over fly without dumbbells.

[0107] S2.4: Outputs the user's baseline stress value when training without dumbbells.

[0108]

[0109] In equations (4) and (5), This represents the baseline stress value during training without dumbbells; μ baseline σ represents the average stress value during a standard bent-over fly exercise without dumbbells. baseline is the standard deviation of the pressure of the standard bent-over fly exercise without dumbbells; k1 is the sensitivity coefficient set in step S1.

[0110] S3: Obtain stress data for the bent-over fly exercise while carrying dumbbells, and calculate the standard deviation of the bent-over fly exercise while carrying dumbbells; calculate the current training fatigue level based on the standard deviation of the bent-over fly exercise while carrying dumbbells.

[0111] This method can adaptively adjust the pressure threshold based on the user's own state, thereby achieving adaptive changes in the force range of the bent-over bird movement.

[0112] Specifically, the following steps are included:

[0113] S3.1: By having the user perform m bent-over flyes while carrying dumbbells, the force data of the electric actuator is collected to obtain the pressure value for each movement. The formula is:

[0114]

[0115] In equation (6), T' represents the stress value of the k-th bent-over fly repetition while carrying dumbbells. k F'(t) represents the duration of the k-th bent-over fly motion while carrying dumbbells, obtained by the controller monitoring the force sensor's force duration; F'(t) is a continuous function of the force on the push rod while carrying dumbbells, obtained by the pressure data monitored by the controller's force sensor.

[0116] S3.2: Obtain the average stress value for each repetition of the bent-over fly exercise while carrying dumbbells.

[0117] The formula is:

[0118]

[0119] In equation (7), μ current represents the real-time average stress value during the bent-over fly exercise while carrying dumbbells; m represents the number of bent-over fly exercises performed while carrying dumbbells. This represents the pressure value during the k-th repetition while carrying a dumbbell;

[0120] S3.3: Obtain the standard deviation of the bent-over fly motion while the user is carrying dumbbells, using the following formula:

[0121]

[0122] In equation (8), σ currentThe standard deviation of stress during bent-over flyes with dumbbells; μ represents the stress value during the k-th bent-over fly with dumbbells. current The real-time average pressure value during the bent-over fly motion while carrying dumbbells;

[0123] S3.4: Calculate fatigue based on the standard deviation of the stress during bent-over flyes with dumbbells and the standard deviation of the stress during standard bent-over flyes without dumbbells.

[0124]

[0125] In equation (9), Fatigue Factor (t) represents fatigue level; σ current σ represents the standard deviation of stress during bent-over flyes with dumbbells. baseline The standard deviation of stress in a standard bent-over fly exercise without dumbbells; T session The current training duration for dumbbell exercises; T standard The standard time is set and varies with the number of groups and the number of repetitions; α and β represent weights, α = 0.5 and β = 0.5.

[0126] S4: Based on the average pressure value and standard deviation of each movement of the bent-over fly with dumbbells, calculate the pressure baseline value when carrying dumbbells, and calculate the training intensity factor through the pressure baseline value.

[0127] S4.1: The formula for the reference pressure value when carrying dumbbells is:

[0128]

[0129] In equations (10) and (11), The baseline pressure value for bent-over flyes while carrying dumbbells; μ current σ represents the real-time average pressure value during the bent-over fly motion while carrying dumbbells. current is the standard deviation of stress during bent-over flyes with dumbbells; k1 is the sensitivity coefficient;

[0130] S4.2: Calculate the training intensity factor.

[0131] The formula is:

[0132]

[0133] In equation (11), The baseline stress value for bent-over flyes while carrying dumbbells; Indicates the baseline stress level during training without dumbbells; Intensity Factor (t) represents the training intensity factor.

[0134] S5: Calculate the training frequency factor based on the interval between two training sessions, and calculate the environment factor based on the training frequency factor and the training intensity factor. This includes the following steps:

[0135] S5.1: Calculate the training frequency factor.

[0136] The formula is:

[0137] Frequency Factor (Δt)=f(Δt)

[0138]

[0139] In equation (12), Δt represents the time interval between the current training session and the previous training session, in hours; Frequency Factor (Δt) represents the training frequency factor.

[0140] S5.2: Calculate environmental factors:

[0141] Environment Factor (t,Δt)=δ1×Intensity Factor +δ2×Frequency Factor (13)

[0142] In equation (13), Environment Factor δ represents the environmental factor; δ1 and δ2 represent the parameter coefficients, where δ1 = 3 and δ2 = 2. Intensity Factor Frequency represents the training intensity factor. Factor This represents the training frequency factor.

[0143] S6: Calculate the adaptive threshold based on fatigue level and environmental factors.

[0144] Threshold adaptive (t,N,Δt)=Fatigue Factor ×Environment Factor (14)

[0145] In equation (14), Threshold adaptive Indicates an adaptive threshold; Fatigue Factor Indicates fatigue level; Environment Factor This represents environmental factors.

[0146] S7: Based on the adaptive threshold and the baseline stress value when training without dumbbells, determine the standard force range for the bent-over fly movement with dumbbells:

[0147] Force range

[0148] When the pressure monitored by the force sensor is within the force range S m Inside, the user's bent-over flying motion is standard; if not within the force zone S m Inside, the crouching bird's movement is not standard.

[0149] Calculation example:

[0150] User information: 75kg, medium build, training with 5kg dumbbells. Standard training time T. standard = 15 minutes, 21 hours since the last training session.

[0151] Initial calibration data: k1 = 1.5; μ baseline =12.5N; σ baseline =0.3N;

[0152] Therefore, the judgment range of the fixed threshold algorithm can be calculated:

[0153] [μ baseline -k1σ baseline ,μ baseline +k1σ baseline = [12.05, 12.95]

[0154] Training frequency factor: Frequency Factor (21)=1×(24-Δt) / 18=0.017

[0155] After training begins:

[0156] Assuming no alarms are triggered after 15 iterations, and there is μ current =12.68N,σ current =0.54N,T session = 3.5 minutes, therefore:

[0157]

[0158]

[0159]

[0160] Environment Factor (t,Δt)=δ1×Intensity Factor +δ2×Frequency Factor

[0161] =0.118

[0162]

[0163] Compared to fixed-threshold algorithms, adaptive algorithms can dynamically adjust the judgment criteria based on the user's actual training status. Test data validates that the allowable range of the adaptive algorithm is expanded by 40%, and the effective allowable range is expanded by 20%. Under different training intensities, the algorithm adjusts the baseline parameters accordingly to adapt to changes in workload. This multi-dimensional adaptive mechanism makes the judgment threshold closer to the user's actual training needs. Compared to the "one-size-fits-all" approach with fixed standards, it can significantly improve user experience and system usability while maintaining detection accuracy.

[0164] Based on the above-described preferred embodiments of the present invention, and through the foregoing description, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. An adaptive intelligent bent-over bird training aid device, characterized in that, Includes forearm binding assembly, upper arm binding assembly, flexion angle control assembly and pressure monitoring module; The forearm binding assembly includes two forearm uprights (1) arranged side by side along the X direction, and an arm base (3) is fixedly connected between the two forearm uprights (1). The arm base (3) is provided with a cable tie (9) for binding the forearm. The upper arm binding assembly includes two upper arm uprights (2) arranged side by side along the X direction, and another arm base (3) is fixedly connected between the two upper arm uprights (2). The arm base (3) is provided with another cable tie (9) for binding the upper arm. The two forearm support plates (1) of the forearm binding assembly are connected to the corresponding upper arm support plate (2) of the upper arm binding assembly via two pivots (4). The forearm binding assembly can rotate relative to the upper arm binding assembly around the axis of the pivot (4). The flexion angle control assembly is used to make the forearm binding assembly rotate relative to the upper arm binding assembly. The pressure monitoring module includes a controller, a force sensor and an indicator light, which are used to monitor the compensatory force exerted by the user's arm on the flexion angle control assembly. When the user's force is not in the force range, the user is promptly reminded to adjust the force.

2. The adaptive intelligent bent-over bird training aid device according to claim 1, characterized in that, The buckling angle control component includes: The electric push rod (5) has its non-telescopic end base hinged to the upper arm support plate (2) of the upper arm binding assembly via shaft one (7), the axis of shaft one (7) is along the X direction; the telescopic end is hinged to one end of the linkage plate (6) via shaft two (8), the other end of the linkage plate (6) is fixedly connected to the pivot (4), the pivot (4) is fixedly connected to the lower arm support plate (1); the axes of the pivot (4) and shaft two (8) are along the X direction, and the force sensor is installed between the electric push rod (5) body and the base. When the electric push rod (5) is subjected to a human axial force, the force is squeezed by the electric push rod (5) body and the base together, causing the force sensor to generate pressure data.

3. The adaptive intelligent bent-over bird training aid device according to claim 2, characterized in that, Let point A be the hinge point between shaft 2 (8) and linkage plate (6), point B be the hinge point between shaft 1 (7) and upper arm upright plate (2), and point C be the hinge point between pivot (4) and linkage plate (6); let the length of line segment BC be a, the length of line segment AC be b, and the length of line segment AB be c; let the line containing the length direction of the lower arm upright plate (1) coincide with the line containing the length direction of the linkage plate (6), then the angle Dq between the upper arm upright plate (2) and the lower arm upright plate (1) satisfies: In the formula, Dx represents the extension or retraction of the electric actuator.

4. An adaptive intelligent bent-over bird training assistance method, based on the adaptive intelligent bent-over bird training assistance device described in claim 3, characterized in that: S1: The user selects a training mode on the adaptive intelligent bent-over bird training aid device. The training modes include beginner mode and non-beginner mode. Based on the mode selected by the user, the device generates or sets the corresponding angle Dq and sensitivity coefficient k1. S2: After the user wears the adaptive intelligent bent-over fly training aid, the user completes multiple standard bent-over fly exercises without dumbbells, and the average pressure value μ of each exercise without dumbbells is calculated. baseline And based on the average pressure value μ baseline Calculate the standard deviation σ of the standard bent-over fly without dumbbells. baseline Combined with the average pressure value μ baseline σ baseline And the sensitivity coefficient k1, outputting the baseline stress value when the user trains without dumbbells. and S3: Obtain pressure data for the bent-over fly exercise while the user is carrying dumbbells, and calculate the average pressure value μ for each movement while carrying dumbbells. current ; and based on the average pressure value μ current Calculate the standard deviation σ of the bent-over fly motion while carrying dumbbells. current Based on the standard deviation σ of the bent-over fly motion while carrying dumbbells. current The standard deviation σ of the standard bent-over fly without dumbbells baseline Calculate the current training fatigue level (Fatigue). Factor (t); S4: Average pressure value μ per movement while carrying dumbbells current The standard deviation σ of bent-over fly with dumbbells current And the sensitivity coefficient k1, calculate the pressure reference value when carrying dumbbells. and Based on the stress baseline during training without dumbbells Calculate the training intensity factor Intensity Factor (t); S5: Calculate the training frequency factor based on the interval between two training sessions. Factor (Δt), and based on the training frequency factor. Factor (Δt) and training intensity factor Intensity Factor (t), calculate the environmental factor Environment Factor (t,Δt); S6: Based on Fatigue Level Factor (t) and environmental factor Environment Factor (t,Δt), calculate the adaptive threshold Threhsold adaptive (t,Δt); S7: Combining stress baseline values ​​from training without dumbbells and adaptive threshold Threshold adaptive (t, Δt), determine the force range S of the standard bent-over fly movement when carrying dumbbells. m By comparing the force on the force sensor, it can be determined whether the bent-over fly motion while carrying dumbbells is standard.

5. The adaptive intelligent bent-over bird training assistance method according to claim 4, characterized in that, Step S3 includes the following steps: S3.1: By having the user perform m bent-over flyes while carrying dumbbells, the force data of the electric actuator is collected to obtain the pressure value for each movement. The formula is: In the formula, T' represents the stress value of the k-th bent-over fly repetition while carrying dumbbells. k F'(t) represents the duration of the k-th bent-over fly motion while carrying dumbbells; F'(t) is a continuous function of the force on the push rod while carrying dumbbells. S3.2: Obtain the average stress value μ for each repetition of the bent-over fly exercise while carrying dumbbells. current ; The formula is: In the formula, μ current is the average stress value during the bent-over fly exercise while carrying dumbbells; m is the number of bent-over fly exercises performed while carrying dumbbells. This represents the pressure value during the k-th repetition while carrying a dumbbell; S3.3: Obtain the standard deviation of the bent-over fly motion while the user is carrying dumbbells, using the following formula: In the formula, σ current The standard deviation of stress during bent-over flyes with dumbbells; μ represents the stress value during the k-th bent-over fly with dumbbells. current The average stress value during a bent-over fly exercise while carrying dumbbells; S3.4: Calculate fatigue based on the standard deviation of the stress of the bent-over fly with dumbbells and the standard deviation of the stress of the standard bent-over fly without dumbbells; In the formula, Fatigue Factor (t) represents fatigue level; σ current σ represents the standard deviation of stress during bent-over flyes with dumbbells. baseline The standard deviation of stress in a standard bent-over fly exercise without dumbbells; T session The current training duration for dumbbell exercises; T standard The standard time is set and varies with the number of groups and the number of repetitions; α and β represent the weights, α = 0.7 and β = 0.

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6. The adaptive intelligent bent-over bird training assistance method according to claim 5, characterized in that, Step S4 includes the following steps: S4.1: The formula for the reference pressure value when carrying dumbbells is: In the formula, The baseline pressure value for bent-over flyes while carrying dumbbells; μ current σ represents the real-time average pressure value during the bent-over fly motion while carrying dumbbells. current is the real-time standard deviation of stress during bent-over flyes with dumbbells; k1 is the sensitivity coefficient; S4.2: Calculate the training intensity factor; The formula is: In the formula, The baseline stress value for bent-over flyes while carrying dumbbells; Indicates the baseline stress level during training without dumbbells; Intensity Factor (t) represents the training intensity factor.

7. The adaptive intelligent bent-over bird training assistance method according to claim 6, characterized in that, Step S5 specifically includes the following steps: S5.1: Calculate the training frequency factor; The formula is: Frequency Factor (Δt)=f(Δt) In the formula, Δt represents the time interval between the current training session and the previous training session, in hours; Frequency Factor (Δt) represents the training frequency factor; S5.2: Calculate environmental factors; Environment Factor (t,Δt)= 1+δ1×Intensity Factor +δ2×Frequency Factor In the formula, Environment Factor δ represents the environmental factor; δ1 and δ2 represent the parameter coefficients, where δ1 = 0.3 and δ2 = 0.

2. Intensity Factor Frequency represents the training intensity factor. Factor This represents the training frequency factor.

8. The adaptive intelligent bent-over bird training assistance method according to claim 7, characterized in that, In steps S6 and S7, the formula for the adaptive threshold is: Threshold adaptive (t,Δt)=Fatigue Factor ×Environment Factor In the formula, Threshold adaptive Indicates an adaptive threshold; Fatigue Factor Indicates fatigue level; Environment Factor Indicates environmental factors; stress range When the pressure monitored by the force sensor is within the force range S m If the user's bent-over flying motion is correct, then the motion is standard; otherwise, it is not.

9. The adaptive intelligent bent-over bird training assistance method according to claim 8, characterized in that, When the user selects the beginner mode, the controller defaults to Dq of 150° and sensitivity coefficient k1 = 1.

5. When the user selects the non-beginner mode, the selection range of Dq is [150°, 160°], and the sensitivity coefficient k1 is set by the user, k1∈[1.5,2]. The user writes the values ​​of Dq and k1 into the controller program through the writing module.

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