Linear machine for improving eye position deviation and improving visual quality of single eye and double eyes

Abstract

The invention provides a linear machine for improving eye position deviation and improving monocular and binocular visual quality, comprising a wearable sensing unit which is configured to be worn by a user and comprises a myoelectricity sensing assembly used for collecting myoelectricity signals of temporalis of the user; a wireless transmitting module; the desktop type execution unit is physically separated from the wearable sensing unit and communicates with the wearable sensing unit through a wireless communication link, and the desktop type execution unit comprises a sighting mark assembly capable of moving along a motion track; the driving assembly is used for driving the sighting mark assembly to move; the wireless receiving module is used for receiving data from the wearable sensing unit; the second processing module is configured to control the driving assembly according to the data received from the wireless receiving module and a training mode of a preset logic so as to achieve movement or on-site stopping of the sighting mark assembly, the heavy driving part is completely separated from the light sensing part, and therefore the sighting mark assembly can be conveniently moved. And the problems of load-bearing feeling, pressure feeling and discomfort caused by traditional integrated equipment are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vision training, and in particular to a straight line machine for improving eye position deviation and improving monocular and binocular vision quality. BACKGROUND

[0002] The visual convergence function, that is, the ability of the two eyes to converge inward to fixate on different distance objects, is the basis for maintaining clear, single stereoscopic vision. Convergence dysfunction is a common visual problem that can cause symptoms such as visual fatigue, diplopia, and reading difficulty, and scientific vision training is a recognized effective and non-invasive treatment method in clinical practice.

[0003] Existing vision training devices have many limitations in form and function. Traditional tools such as convergence balls and Brock strings rely on manual operation by the user, and the process is tedious and difficult to quantify. Some integrated electric devices attempt to integrate all components such as motors, sliding rails, and sensors into a head-mounted device, resulting in a heavy and uncomfortable device to wear, making it difficult for users to persist in training for a long time.

[0004] In addition, there are also some desktop electric devices that overcome the weight and power supply problems, but their control methods usually rely on physical buttons or pre-set fixed programs, and cannot directly contact the user's real-time subjective training intentions and physiological state. Even a few devices attempt to introduce biological signals (such as electromyography, EMG), but their control logic only stays at the simple threshold switch level and cannot achieve personalized adaptive adjustment. SUMMARY

[0005] The present application aims to solve the above problems.

[0006] To solve the above technical problems, the technical solution adopted by the present application is: A straight line machine for improving eye position deviation and improving monocular and binocular vision quality, comprising a wearable sensing unit configured to be worn by a user, comprising: an electromyography sensing assembly for collecting electromyography signals of the user's temporal muscle; a wireless sending module; a desktop execution unit physically separated from the wearable sensing unit and communicating through a wireless communication link, the desktop execution unit comprising: a target assembly movable along a movement track; a driving assembly for driving the movement of the target assembly; a wireless receiving module for receiving data from the wearable sensing unit; a second processing module configured to control the driving assembly to move or stop in place the target assembly according to the data received from the wireless receiving module and according to a preset logic training mode.

[0007] Further, the wearable sensing unit further comprises a first processing module configured to process the collected electromyography signals to extract a signal feature parameter and send the signal feature parameter out through the wireless sending module.

[0008] Further, the signal characteristic parameter is a root mean square value of the electromyography signal.

[0009] Further, the second processing module runs a preset logic of an adaptive training system, the logic being: setting a start threshold and a stop threshold according to the received data; when the signal strength represented by the received data is higher than the start threshold, controlling the driving assembly to drive the target assembly to move forward; and when the signal strength is lower than the stop threshold, controlling the driving assembly to stop according to the preset logic.

[0010] Further, the adaptive training system is further configured to adjust the moving speed of the target assembly in real time according to the signal strength.

[0011] Further, the moving speed is positively correlated with the difference between the signal strength and the start threshold.

[0012] Further, the desktop execution unit further comprises a start position sensor arranged at the start point of the movement track; when performing the automatic reset operation, the second processing module controls the driving assembly to stop after the start position sensor detects that the target assembly has returned to the start point.

[0013] A control system applied to a linear machine, the system being arranged on a desktop execution unit and performing wireless communication with a wearable sensing unit, the system comprising: a wireless data receiving module for receiving a characteristic parameter representing the electromyography signal strength of a user sent by the sensing unit; a user state calibration and modeling module for establishing a personalized user model comprising a start threshold and a stop threshold according to the characteristic parameter; a training mode management module for selecting between at least a continuous training mode and a cyclic training mode; and a core control decision module configured to compare the real-time received characteristic parameter with the thresholds in the model, and generate a driving instruction for controlling a target assembly to move according to the comparison result and the selected training mode, the driving instruction comprising forward, stop and reset.

[0014] A control method applied to a linear machine, the method being performed by a desktop execution unit in a distributed visual training device, the method comprising the following steps: receiving real-time characteristic parameters representing the electromyography signal strength of a user from a wearable sensing unit through a wireless communication link; when the received real-time characteristic parameters are higher than a preset start threshold, driving a target assembly to move forward; when the received real-time characteristic parameters are higher than a preset start threshold, driving a target assembly to move forward; if the training mode is a continuous training mode, stopping the movement of the target assembly; and if the training mode is a cyclic training mode, driving the target assembly to return to a training start point from its current position.

[0015] Further, the method further comprises: adjusting the moving speed of the target assembly in real time according to the value of the real-time characteristic parameter when driving the target assembly to move forward; and performing a calibration step before starting the training, which comprises: automatically setting the start threshold and the stop threshold according to the characteristic parameters of the user in the relaxed state and the focused state.

[0016] Compared with the prior art, the beneficial effects of the present application include: 1. By completely separating the heavy driving components from the light sensing components, the user only needs to wear a light sensing headband, which solves the problems of weight, compression and discomfort caused by traditional integrated devices.

[0017] 2. The desktop execution unit can use stable external AC power to provide strong and continuous power to the motor, ensuring smooth, accurate and long-distance target movement. At the same time, the larger internal space also allows the use of higher-performance processors, more reliable mechanical structures and more abundant user interaction interfaces.

[0018] 3. The core adaptive system customizes training parameters for different users through automated user modeling, and dynamically adjusts the difficulty according to the real-time effort level during training, which constitutes an efficient biofeedback closed loop, significantly improving the scientificity and effectiveness of training. BRIEF DESCRIPTION OF DRAWINGS

[0019] The disclosure of the present application will be described with reference to the accompanying drawings. It should be understood that the drawings are for illustrative purposes only and are not intended to limit the scope of protection of the present application. In the drawings, the same reference numerals are used to refer to the same components. Among them: Figure 1 is a device structure diagram.

[0020] Figure 2 is a driving assembly structure diagram.

[0021] Figure 3 is a driving assembly top view.

[0022] Figure 4 is a data processing module and data transmission module schematic diagram.

[0023] Figure legend: 10, wireless communication link; 110, headband; 200, target assembly; 300, driving assembly; 310, motor; 320, lead screw; 330, sliding table; 400, electromyographic sensing assembly; 410, dry electrode; 501, first processing module; 502, second processing module; 511, wireless transmission module; 512, wireless reception module. DETAILED DESCRIPTION

[0024] It is easy to understand that, according to the technical solutions of the present application, those skilled in the art can propose various structures and implementation modes that can be replaced with each other without changing the essential spirit of the present application. Therefore, the following specific embodiments and drawings are only exemplary descriptions of the technical solutions of the present application, and should not be considered as the whole or as a limitation or restriction on the technical solutions of the present application.

[0025] The device comprises the following parts: The wearable sensing unit comprises a lightweight headband 110 for the user to wear on the head, and the following components are integrated on the headband 110: The electromyography sensing assembly 400 comprises a pair of dry electrodes 410 for directly contacting the skin of the user's temples, which are used to capture weak bioelectric signals (EMG) generated by the contraction of the temporal muscle related to the accommodation function.

[0026] The first processing module 501 comprises a low-power microcontroller MCU, which is responsible for amplifying, filtering and preliminary calculating the original signals collected by the dry electrodes 410, and the calculated results can be the root mean square value , as a signal feature parameter.

[0027] for the electromyography signal; N is the total number of sampling points in the calculation window; is the signal amplitude of the i-th sampling point in the window.

[0028] The wireless sending module 511 is used to send the key data processed by the first processing module 501 through low-power Bluetooth.

[0029] The power supply unit comprises a micro rechargeable battery, which is used to supply power to the power-consuming elements in the wearable sensing unit.

[0030] The desktop execution unit is placed on the desktop and is used to execute the movement of the visual target, and comprises the following parts: The visual target assembly 200 comprises a visual target for the user to gaze at and a support seat supporting the visual target, and the visual target is fixed on the support seat.

[0031] The driving assembly 300 comprises a precise linear guide rail, a sliding table 330 slidingly connected on the guide rail, a motor 310 installed on one side of the guide rail, a screw rod 320 fixedly connected with the output shaft of the motor, and the sliding table 330 and the screw rod 320 are threadedly connected, and the support seat is fixed on the sliding table 330. When the motor 310 rotates, the sliding table 330 can be driven to move along the guide rail horizontally, or to approach or move away from the eyes of the user through the screw rod sliding table structure.

[0032] The control and communication system comprises a wireless receiving module 512 for receiving data sent from the wireless sending module 511, and a second processing module 502 composed of a more powerful MCU.

[0033] The user interface comprises a display screen, mode selection buttons, etc., and shows relevant information to the operator.

[0034] The power module is connected to an external power source and provides power for all power-consuming elements in the desktop execution unit.

[0035] When the device is in use, the following steps are taken: S1. The user wears the headband 110 and sticks the two dry electrodes 410 to the temporalis muscle.

[0036] S2. When the user starts focusing on the target, the temporalis muscle contracts, generating an EMG signal, which is received by the dry electrodes 410 and transmitted to the first processing module 501.

[0037] S3. The first processing module 501 processes the signal into an RMS value representing its intensity, and then sends this value out through the wireless sending module 511.

[0038] S4. The wireless receiving module 512 of the desktop execution unit receives this value and immediately hands it over to the second processing module 502, which makes a judgment based on the pre-set logic and controls the motor 310 to rotate or stop, thereby driving the target to move closer to the user or stop in place.

[0039] Specifically, when the user relaxes, the EMG signal weakens, and the dry electrodes 410 can only receive a very small value. According to the pre-set logic, the second processing module 502 will immediately stop sending signals to the driving circuit of the motor 310, and the motor 310 will stop rotating, and the target will stop in place. At this time, according to the user's use requirements, the subsequent process continues, and when the user chooses to continue training, the target can be temporarily stopped in place; when the user chooses to repeat the previous training, the operator can let the motor 310 reverse drive the target to reset through the second processing module 502.

[0040] Further, before S1, the second processing module 502 must identify the current user through a brief calibration process by finding the two extreme points of the user's muscle strength range, thereby establishing a reasonable training scale that belongs to the user.

[0041] Specifically, the user's lower limit of ability and upper limit of ability need to be found respectively.

[0042] Lower limit of ability (relaxation baseline B) The operator guides the user to fully relax, at which time the collected EMG RMS value is not zero, but there is a small baseline fluctuation. The second processing module 502 obtains a baseline value B representing the true resting level of the user through statistical calculation.

[0043] ; For the relaxed state The overall mean of the value sequence, the calculation formula is: ; For the relaxed state The overall standard deviation of the value sequence, ; N is the total number of data points, that is, the length of the RMS sequence.

[0044] This formula is not simply taking the average, but using the average + 3 times the standard deviation to set a high enough threshold to ensure that only signals that truly exceed the baseline fluctuation are considered valid, thereby greatly avoiding false triggers caused by small tremors.

[0045] Upper limit of ability (maximum voluntary contraction MVC) The operator guides the user to focus with maximum effort, at which time the maximum value in the collected RMS value is defined as the maximum voluntary contraction value MVC of the user.

[0046] Between the interval [B, MVC], the system generates a scale from 0-100% that is unique to the current user, and all subsequent training will be based on this relative scale rather than any fixed absolute voltage value.

[0047] The second processing module 502 automatically calculates two key thresholds, namely the start threshold and the stop threshold ; Start threshold : Among them, is the start sensitivity coefficient ( ), which controls the minimum signal strength required for activation. A higher requires a stronger signal to trigger the action, thereby avoiding false triggers. This means that the start line is not a fixed value, but a percentage of the user's ability range (for example =20%). This means that users with strong muscle strength and users with weak muscle strength have different start thresholds, but the start difficulty feels similar, and the operator can select the appropriate value for the user during multiple tests.

[0048] Stop threshold : wherein, is the stop sensitivity coefficient (0 ), and needs to satisfy . A lower makes the system stop responding when the signal is slightly reduced, improving control safety. This means that the stop line must be set lower than the start line (e.g. = 10%), to form a hysteresis interval, preventing the device from frequently starting and stopping due to small fluctuations in the signal near the start line, reducing user experience.

[0049] After calibration, the second processing module 502 will execute the following decision loop at a very high frequency (e.g. 10 times per second) during training: S4.1, obtain the latest real-time value from the headband 110.

[0050] S4.2, determine the size relationship between and ; S4.2.1, when > , it means that the user is in a training state, and the second processing module 502 controls the motor 310 to rotate, driving the target to gradually approach the user; S4.2.2, when < , the user is in a relaxed state, and the second processing module 502 controls the motor 310 to stop rotating, and the target stops in place; S4.2.3, when ≤ ≤ , the current position of the target is maintained unchanged.

[0051] In S4.2.1, , This formula calculates the percentage of the current signal strength in the ability interval above the start line.

[0052] If the user just barely exceeds the start line, the percentage is small, and the speed is close to the minimum speed, .

[0053] If the user approaches the upper limit of their ability MVC, the percentage is large, and the speed is close to the maximum speed, .

[0054] This achieves speed proportional to the effort paid by the user, providing excellent feedback and control.

[0055] Further, in order to make the target have the reset ability, the application also has the following design: Scheme one, when the user's eye muscle relaxes and the electromyographic signal intensity is lower than the preset stop threshold, the second processing module 502 determines the user's intention to end, and automatically drives the motor 310 to reverse.

[0056] Scheme two, the operator can press the reset button on the target at any time, which will generate an electrical signal with the highest priority, directly instructing the second processing module 502 to override all other states and drive the motor 310 to reverse to reset the target.

[0057] Wherein, no matter what way to start, after the motor 310 reverses, the target start position sensor will continue to monitor the target position, and once it is detected that the target returns to the initial point, it will immediately send a stop signal to the second processing module 502 to complete the accurate reset. The sensor is installed on the inner wall of the device shell, opposite the start point of the sliding table 330.

[0058] The advantages of this scheme are: 1. By completely separating the heavy driving components from the light sensing components, the user only needs to wear a light sensor headband, solving the weight, compression and discomfort problems caused by traditional integrated devices.

[0059] 2. The desktop execution unit can use stable external AC power supply to provide strong and continuous power for the motor, ensuring smooth, accurate and long-distance movement of the target. At the same time, the larger internal space also allows the use of higher performance processors, more reliable mechanical structures and more abundant user interaction interfaces.

[0060] 3. The core adaptive system automatically models different users to customize training parameters, and can dynamically adjust the difficulty according to the real-time effort during training, which constitutes an efficient biofeedback loop, significantly improving the scientificity and effectiveness of training.

[0061] The technical scope of the present application is not limited to the content in the above description, and those skilled in the art can make various modifications and changes to the above embodiments without departing from the technical idea of the present application, and these modifications and changes should all be within the protection scope of the present application.

Claims

1. A linear imaging system for improving eye alignment deviation and enhancing monocular and binocular visual quality, characterized in that, include Wearable sensing units, configured to be worn by a user, include: Electromyography (EMG) sensor assembly, used to acquire EMG signals from the user's temporalis muscle; Wireless transmission module; A desktop execution unit, physically separate from the wearable sensing unit and communicating with it via a wireless communication link, the desktop execution unit comprising: A sight assembly that can move along a motion track; A drive assembly for driving the movement of the target assembly; A wireless receiving module is used to receive data from the wearable sensing unit; The second processing module is configured to control the drive assembly based on data received from the wireless receiving module and according to a preset logic training mode, so as to move or stop the target assembly in place.

2. A linear imaging system for improving eye alignment deviation and enhancing monocular and binocular visual quality according to claim 1, characterized in that, The wearable sensing unit further includes a first processing module, which is configured to process the acquired electromyographic signals to extract a signal feature parameter and transmit the signal feature parameter through the wireless transmission module.

3. A linear imaging system for improving eye alignment deviation and enhancing monocular and binocular visual quality according to claim 1, characterized in that, The signal characteristic parameter is the root mean square value of the electromyographic signal.

4. A linear imaging system for improving eye alignment deviation and enhancing monocular and binocular visual quality according to claim 1, characterized in that, The second processing module runs a set of preset logic for an adaptive training system, the logic being: Set a start threshold and a stop threshold based on the received data; When the signal strength represented by the received data is higher than the activation threshold, the drive assembly is controlled to drive the target assembly forward; When the signal strength is lower than the stop threshold, the drive assembly is controlled to stop according to preset logic.

5. A linear imaging system for improving eye alignment deviation and enhancing monocular and binocular visual quality according to claim 4, characterized in that, The adaptive training system is also configured to adjust the forward speed of the target assembly in real time according to the magnitude of the signal strength.

6. A linear imaging system for improving eye alignment deviation and enhancing monocular and binocular visual quality according to claim 5, characterized in that, The forward speed is positively correlated with the difference between the signal strength and the activation threshold.

7. A linear imaging system for improving eye alignment deviation and enhancing monocular and binocular visual quality according to claim 1, characterized in that, The desktop execution unit also includes a starting position sensor located at the starting point of the motion track; during the automatic reset operation, when the starting position sensor detects that the target assembly has returned to the starting point, the second processing module controls the drive assembly to stop.

8. A control system for a linear machine, characterized in that, The system, applied to the linear actuator of claim 1, is deployed on a desktop execution unit and wirelessly communicates with a wearable sensing unit, characterized in that the system comprises: A wireless data receiving module is used to receive characteristic parameters that characterize the intensity of the user's electromyographic signals, sent by the sensing unit. The user status calibration and modeling module is used to establish a personalized user model that includes a start threshold and a stop threshold based on the feature parameters. The training mode management module is used to select between at least two modes: continuous training mode and cyclic training mode. And a core control decision module, which is configured to compare the feature parameters received in real time with the thresholds in the model, and generate drive commands for controlling the movement of a target assembly based on the comparison results and the selected training mode, the drive commands including forward, stop and reset.

9. A control method for a linear machine, characterized in that, Applied to the linear machine of claim 1, the method is executed by a desktop execution unit in a distributed vision training device, characterized in that the method includes the following steps: Through a wireless communication link, real-time characteristic parameters representing the intensity of the user's electromyographic signals are received from a wearable sensing unit. When the received real-time feature parameters are higher than a preset start threshold, a sight assembly is driven forward. When the received real-time feature parameters are higher than a preset start threshold, a sight assembly is driven forward. If the training mode is continuous training mode, then the movement of the target assembly is stopped; If the training mode is a loop training mode, the target assembly is driven to return from its current position to a training starting point.

10. The method according to claim 9, characterized in that, The method further includes: When driving the target assembly forward, the moving speed of the target assembly is adjusted in real time according to the value of the real-time feature parameter; In addition, before training begins, a calibration step is performed, which includes automatically setting the start threshold and the stop threshold based on characteristic parameters of the user in a relaxed and focused state.

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