A non-contact intelligent glasses blinking control method, device, equipment and medium

Abstract

This invention relates to a non-contact smart glasses blink control method, device, equipment, and medium. The method involves real-time synchronous acquisition of the wearer's eye movement characteristic parameters, periorbital muscle activity characteristic parameters, and head posture movement characteristic parameters; fusing these parameters to extract signal change characteristic parameters representing the user's blinking intention; dynamically identifying specific blinking action patterns performed by the user using a preset pattern recognition algorithm based on the extracted signal change characteristic parameters; generating corresponding control commands based on the identified specific blinking action patterns; and executing the control commands to manipulate the smart glasses' predetermined functions, thereby achieving precise control of the smart glasses for full-function natural interaction, including taking photos, recording videos, making calls, and adjusting parameters.

Description

Technical Field

[0001] This invention relates to the field of smart wearable device technology, and in particular to a non-contact smart glasses blink control method, device, equipment and medium. Background Technology

[0002] With the rapid development of smart glasses, existing interaction technologies face severe challenges. Traditional head movement control, such as nodding or shaking, is easily affected by turbulence in motion scenarios, leading to a high rate of false triggers. Voice control suffers a significant drop in recognition rate in noisy environments and poses a risk of privacy leaks in public places. Mainstream blink detection solutions also have limitations: camera-based image analysis is computationally complex and power-consuming, making continuous operation difficult; while electromyography (EMG) sensors require close contact with the skin, resulting in poor comfort during long-term wear. Furthermore, a single interaction logic cannot simultaneously support multiple scenarios such as taking photos, recording videos, making calls, and adjusting parameters, leading to a fragmented user experience and severely restricting the practicality and widespread adoption of smart glasses. Summary of the Invention

[0003] The main objective of this invention is to provide a non-contact smart glasses blink control method, device, equipment, and medium, which achieves the goal of precise control of smart glasses for taking photos, recording videos, making calls, and adjusting parameters through blinking actions with high anti-interference and no privacy leakage.

[0004] To achieve the above objectives, the present invention provides a non-contact smart glasses blink control method, comprising the following steps:

[0005] Real-time synchronous collection of the wearer's eye movement characteristics, periorbital muscle activity characteristics, and head posture movement characteristics;

[0006] The collected eye movement feature parameters, periorbital muscle activity feature parameters, and head posture movement feature parameters are fused to extract signal change feature parameters that represent the user's blinking intention.

[0007] Based on the extracted signal change feature parameters, a preset pattern recognition algorithm is used to dynamically identify specific blinking action patterns performed by the user.

[0008] Based on the identified specific blinking pattern, corresponding control commands are generated;

[0009] The control commands are executed to operate the predetermined functions of the smart glasses.

[0010] Furthermore, the steps of real-time synchronously collecting the wearer's eye movement feature parameters, periocular muscle activity feature parameters, and head posture movement feature parameters include:

[0011] By using a dual-wavelength infrared sensor located at the nose pad of the smart glasses, the infrared reflection light difference signal of the eyelid opening and closing speed and amplitude is collected in real time as the eye movement feature parameter.

[0012] A capacitive pressure sensor array located on the inner side of the temple is used to collect non-contact pressure fluctuation signals caused by the contraction of the orbicularis oculi muscle in real time as characteristic parameters of the periocular muscle activity.

[0013] The smart glasses use a built-in six-axis gyroscope sensor to collect real-time changes in the three-dimensional angle of the head as the head posture motion characteristic parameters.

[0014] The data acquisition timing of the dual-wavelength infrared sensor, the capacitive pressure sensor array, and the six-axis gyroscope sensor is synchronously controlled by the main control board.

[0015] Further, the step of fusing the collected eye movement feature parameters, periocular muscle activity feature parameters, and head posture movement feature parameters to extract signal change feature parameters representing the user's blinking intention includes:

[0016] The head motion state is determined based on the head posture motion characteristic parameters: if the change in head angle exceeds the vibration threshold, the current data is marked as disturbed.

[0017] The eye movement feature parameters and the periocular muscle activity feature parameters are aligned on the time axis to calculate the correlation strength between eyelid closure events and pressure fluctuations.

[0018] By combining head motion state markers and correlation strength, interference data is filtered out and the temporal characteristics of valid blinking actions are output, which constitute the signal change characteristic parameters.

[0019] Further, the steps of filtering out interfering data and outputting the temporal features of valid blinking actions include:

[0020] When the head posture motion feature parameters exceed the vibration threshold, all feature parameters within the current time window are discarded.

[0021] When the eye movement feature parameters show eyelid closure but no associated periorbital muscle activity feature parameters are detected, it is determined to be an invalid blinking action;

[0022] Extract the timestamp sequence, pressure peak, and duration of the validated valid blinking actions to form the temporal features of valid blinking actions.

[0023] Further, based on the extracted signal change feature parameters, the step of dynamically identifying a specific blinking action pattern performed by the user using a preset pattern recognition algorithm includes:

[0024] The first action pattern is detected. Within a preset first time window, two valid blinking actions are detected consecutively, and the pressure fluctuation signal conforms to the first frequency range. The first action pattern constitutes a specific blinking action pattern.

[0025] The second action pattern is detected if three valid blinking actions are detected continuously within a preset second time window and the pressure fluctuation signal conforms to the second frequency range. The second action pattern constitutes one of the specific blinking action patterns.

[0026] The third action mode is detected, and the pressure fluctuation signal in the third frequency range is continuously detected. At the same time, the head posture movement characteristic parameters remain static for more than a preset time. The third action mode constitutes one of the specific blinking action modes.

[0027] The first action mode, the second action mode, or the third action mode is matched based on the real-time extracted signal change feature parameters.

[0028] Further, the step of generating corresponding control commands based on the identified specific blinking pattern includes:

[0029] When the first action pattern is matched, a basic function instruction is generated to trigger the basic function;

[0030] When the second action mode is matched, an audio / video recording start / stop command is generated;

[0031] When the third action mode is matched, parameter adjustment instructions for the system are generated.

[0032] Further, the step of executing the control commands to operate the predetermined functions of the smart glasses includes:

[0033] The basic function commands are transmitted to the camera module to take a picture; or to the audio module to answer a phone call.

[0034] The audio and video recording start / stop command is transmitted to the camera module and audio module to execute the start / stop operation of recording or audio recording;

[0035] The parameter adjustment command is transmitted to the audio module to adjust the volume, or to the camera module to adjust the focus.

[0036] During operation, the smart glasses output status prompts via LED indicator lights.

[0037] The present invention also provides a non-contact smart glasses blink control device, comprising:

[0038] The parameter acquisition module is used to collect the wearer's eye movement feature parameters, periorbital muscle activity feature parameters, and head posture movement feature parameters in real time.

[0039] The feature extraction module is used to fuse the collected eye movement feature parameters, periorbital muscle activity feature parameters, and head posture movement feature parameters to extract signal change feature parameters that represent the user's blinking intention.

[0040] The pattern recognition module is used to dynamically identify specific blinking action patterns performed by the user based on the extracted signal change feature parameters and using a preset pattern recognition algorithm.

[0041] The instruction generation module is used to generate corresponding control instructions based on the identified specific blinking action pattern;

[0042] The instruction execution module is used to execute the control instructions and operate the predetermined functions of the smart glasses.

[0043] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described non-contact smart glasses blink control method.

[0044] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described non-contact smart glasses blink control method.

[0045] The non-contact smart glasses blink control method, device, equipment, and medium provided by this invention have the following beneficial effects: This invention solves the problems of strong light and motion interference by combining a dual-wavelength infrared sensor with a gyroscope dynamic threshold filtering. At the same time, it uses a non-contact capacitive pressure array to accurately capture eye muscle activity, taking into account both environmental robustness and wearing comfort. Pure physical blink control eliminates privacy concerns by eliminating the need for voice input. With multi-level action modes (single, continuous, long duration), it seamlessly supports full-function operations such as taking photos, recording videos, making calls, and adjusting parameters, allowing users to interact intuitively without learning. Lightweight temporal feature extraction and direct hardware-level command connection significantly reduce power consumption, breaking through the energy efficiency bottleneck of micro wearable devices. Users can also customize action parameters and function mappings through an APP to flexibly adapt to different physiological habits, greatly expanding the applicability to special groups and providing a natural interaction paradigm for smart glasses that is available in all scenarios with zero learning cost. Attached Figure Description

[0046] Figure 1 This is a flowchart illustrating a non-contact smart glasses blink control method according to an embodiment of the present invention.

[0047] Figure 2This is a structural block diagram of a non-contact smart glasses blink control device according to an embodiment of the present invention;

[0048] Figure 3 This is a schematic block diagram of the structure of a computer device according to an embodiment of the present invention.

[0049] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0051] Reference Figure 1 The diagram below illustrates a non-contact smart glasses blink control method proposed in this invention, comprising the following steps:

[0052] S1 collects the wearer's eye movement feature parameters, periorbital muscle activity feature parameters, and head posture movement feature parameters in real time and synchronously.

[0053] S2, the collected eye movement feature parameters, periorbital muscle activity feature parameters and head posture movement feature parameters are fused to extract signal change feature parameters that represent the user's blinking intention;

[0054] S3. Based on the extracted signal change feature parameters, a preset pattern recognition algorithm is used to dynamically identify the specific blinking action pattern performed by the user.

[0055] S4, Generate corresponding control commands based on the identified specific blinking action pattern;

[0056] S5, execute the control command to operate the predetermined functions of the smart glasses.

[0057] In one embodiment, for step S1,

[0058] The steps for real-time synchronous collection of the wearer's eye movement feature parameters, periocular muscle activity feature parameters, and head posture movement feature parameters include:

[0059] By using a dual-wavelength infrared sensor located at the nose pad of the smart glasses, the infrared reflection light difference signal of the eyelid opening and closing speed and amplitude is collected in real time as the eye movement feature parameter.

[0060] A capacitive pressure sensor array located on the inner side of the temple is used to collect non-contact pressure fluctuation signals caused by the contraction of the orbicularis oculi muscle in real time as characteristic parameters of the periocular muscle activity.

[0061] The smart glasses use a built-in six-axis gyroscope sensor to collect real-time changes in the three-dimensional angle of the head as the head posture motion characteristic parameters.

[0062] The data acquisition timing of the dual-wavelength infrared sensor, the capacitive pressure sensor array, and the six-axis gyroscope sensor is synchronously controlled by the main control board.

[0063] In practice, parameter acquisition is achieved through multi-sensor collaboration. Eye movement detection utilizes a dual-wavelength infrared sensor (940nm + 850nm) located at the nose pad. Ambient light interference is eliminated by calculating the intensity difference between the two reflected light bands, and the eyelid opening and closing speed and amplitude are output in real time. The formula for eyelid opening and closing speed is: v = Δd / Δt, with a displacement change Δd accuracy of ±0.1mm and a time interval Δt = 1ms; the formula for amplitude is: A = 0.5 × ∫|I 850 (t)-I 940 (t)|dt, where the integration interval is a single blink cycle. Periorbital muscle activity detection uses an 8-channel capacitive pressure sensor array on the inner side of the temple to capture micro-pressure fluctuations caused by orbicularis oculi muscle contraction (non-contact). The pressure signal is weighted and fused by channels: P(t)=w1C1(t)+w2C2(t)+...+w8C8(t) (weights w are allocated according to anatomical position, ∑w=1), detection range 0.1-5N, accuracy ±0.02N. Head posture detection is performed using a six-axis gyroscope, outputting the three-dimensional angle change Δθ=(θ x ,θ y ,θ z The synchronization mechanism is triggered by the main control board hardware, controlling three types of sensors to synchronously acquire data at a 1ms cycle (40MHz crystal oscillator clock source, deviation <0.1ms) to solve the physiological signal delay problem (eyelid-muscle contraction delay 15-50ms) and ensure data timing alignment. Step S1 solves the three major problems of environmental interference, motion-induced accidental touch, and signal inaccuracy in existing technologies through dual-wavelength differential anti-light interference, capacitive array non-contact detection, gyroscope dynamic threshold filtering, and hardware-level synchronization control, providing a highly reliable data foundation for subsequent fusion processing. The sensor layout strictly follows ergonomics (nose pad / inner temple) to ensure wearing comfort.

[0064] In one embodiment, for step S2,

[0065] The steps of fusing the collected eye movement feature parameters, periocular muscle activity feature parameters, and head posture movement feature parameters to extract signal change feature parameters representing the user's blinking intention include:

[0066] The head motion state is determined based on the head posture motion characteristic parameters: if the change in head angle exceeds the vibration threshold, the current data is marked as disturbed.

[0067] The eye movement feature parameters and the periocular muscle activity feature parameters are aligned on the time axis to calculate the correlation strength between eyelid closure events and pressure fluctuations.

[0068] By combining head motion state markers and correlation strength, interference data is filtered out and the temporal characteristics of valid blinking actions are output, which constitute the signal change characteristic parameters.

[0069] In practical implementation, signal fusion processing achieves highly robust feature extraction through a three-level anti-interference mechanism. Head motion interference is blocked based on the three-dimensional angle change θ output by the six-axis gyroscope. x ,θ y ,θ z Calculate the overall rotational speed When R ≥ 5° / s (vibration threshold calibrated by exercise testing), all data within the current 20ms time window are discarded to prevent false triggering during walking / running and other scenarios. For physiological signal correlation verification, the eyelid closure event collected by the dual-wavelength infrared sensor and the muscle pressure fluctuation signal collected by the capacitive pressure sensor are aligned on the time axis, and the correlation coefficient Corr = Cov(E,P) / (σ) is calculated using a sliding window. E ×σ P When the correlation coefficient Corr < 0.7 (the physiological correlation threshold verified by experiments), it is judged as an invalid blink (such as involuntary eyelid closure caused by wind). Valid features are extracted, retaining only the blinking actions that have passed the above verification, and extracting their key temporal features, including timestamp sequences (eyelid closure start / peak / end time points), pressure peak (maximum pressure value of the capacitive array, reflecting the blinking force), and duration (duration from the start to the end of closure), which constitute signal change feature parameters representing the user's true intention.

[0070] In one embodiment, the step of filtering out interfering data and outputting the temporal characteristics of valid blinking actions includes:

[0071] When the head posture motion feature parameters exceed the vibration threshold, all feature parameters within the current time window are discarded.

[0072] When the eye movement feature parameters show eyelid closure but no associated periorbital muscle activity feature parameters are detected, it is determined to be an invalid blinking action;

[0073] Extract the timestamp sequence, pressure peak, and duration of the validated valid blinking actions to form the temporal features of valid blinking actions.

[0074] In practical implementation, a three-tiered defense mechanism ensures the reliability of the features. The first is motion interference hard blocking: when the six-axis gyroscope detects a head rotation velocity R ≥ 5° / s (a threshold calibrated using 5000 sets of motion data), all data within the current 20ms time window is immediately discarded, completely eliminating false triggers caused by walking, running, or vehicle bumps. The second is physiological consistency verification: if the dual-wavelength infrared sensor detects eyelid closure (amplitude A > threshold A),... th However, if the capacitive pressure sensor fails to detect associated muscle activity synchronously (pressure fluctuation ΔP < 0.1N or correlation coefficient < 0.7), it is judged as an invalid blink (such as strong wind stimulation or random eyelid tremor); high signal-to-noise ratio feature extraction: for valid blinking actions that pass verification, three temporal features are accurately extracted, including the timestamp sequence (closing start t). start Peak value t peak End of t end Peak pressure P ax (Reflects blinking force, unit N), duration T = t end -t start (Unit: ms) constitutes the anti-interference time-series feature vector.

[0075] In one embodiment, for step S3,

[0076] Based on the extracted signal change feature parameters, and using a preset pattern recognition algorithm, the steps for dynamically identifying specific blinking patterns performed by the user include:

[0077] The first action pattern is detected. Within a preset first time window, two valid blinking actions are detected consecutively, and the pressure fluctuation signal conforms to the first frequency range. The first action pattern constitutes a specific blinking action pattern.

[0078] The second action pattern is detected if three valid blinking actions are detected continuously within a preset second time window and the pressure fluctuation signal conforms to the second frequency range. The second action pattern constitutes one of the specific blinking action patterns.

[0079] The third action mode is detected, and the pressure fluctuation signal in the third frequency range is continuously detected. At the same time, the head posture movement characteristic parameters remain static for more than a preset time. The third action mode constitutes one of the specific blinking action modes.

[0080] The first action mode, the second action mode, or the third action mode is matched based on the real-time extracted signal change feature parameters.

[0081] In practical implementation, accurate intent recognition is achieved through multi-level action pattern matching. The first action pattern (basic operation) detects two consecutive valid blinks within a 300ms time window (adjustable range 200-500ms), with pressure fluctuation frequency within the 2-4Hz range (physiological blink frequency). This first action pattern is mapped to basic functions such as taking photos / answering phone calls. The second action pattern (start / stop control) detects three consecutive valid blinks within a 500ms time window (adjustable range 400-800ms), with pressure fluctuation frequency within the 3-5Hz range. This second action pattern is designed to avoid confusion with a single blink (natural blink frequency 1-6Hz) and is specifically used for starting / stopping video / audio recording. The third action pattern (parameter adjustment) continuously detects 1-2Hz pressure fluctuations (low-frequency muscle contraction), while the gyroscope data remains stationary for 200ms (overall head rotation speed <2° / s). This combined condition prevents accidental touches and is used for volume / focus adjustment, with a measured environmental interference suppression ratio of 35dB. The time-series features (t) extracted in step S2 start t peak t end P ax The input is a finite state machine (T), which calculates the continuity of the action: if the interval between the end timestamp of the nth blink and the start timestamp of the (n+1)th blink is less than the action mode time window (e.g., 300ms for the first mode), it is determined to be a continuous action; otherwise, it is determined to be a discontinuous action. Step S3 eliminates involuntary muscle tremors (<1Hz) by constraining the pressure fluctuation frequency (e.g., 2-4Hz) and eliminates slow blinks (the average blinking time for the elderly is 400ms) by constraining the time window (e.g., 300ms), thus solving the problem of misidentification in traditional schemes; the third mode requires "low-frequency pressure fluctuation + head stillness", avoiding false triggers caused by the user speaking or chewing (facial movements can generate 0.5-3Hz pressure noise). Furthermore, users can adjust mode parameters through the app to match their individual habits. They can redefine the time window, such as changing the first mode window from 300ms to 400ms (to suit elderly users who blink slowly) or reset the frequency range, such as changing the third mode pressure frequency from 1-2Hz to 0.8-1.5Hz (to suit patients with myasthenia gravis) or remap the function, such as binding the second action mode (three blinks) to "start recording" instead of the default recording.

[0082] In one embodiment, for step S4,

[0083] The step of generating corresponding control commands based on the identified specific blinking pattern includes:

[0084] When the first action pattern is matched, a basic function instruction is generated to trigger the basic function;

[0085] When the second action mode is matched, an audio / video recording start / stop command is generated;

[0086] When the third action mode is matched, parameter adjustment instructions for the system are generated.

[0087] In practical implementation, precise control is achieved through action mode-function mapping, generating three types of core commands. Basic function command generation: When matching the first action mode (two blinks within 300ms + 2-4Hz pressure fluctuation), an instantaneous trigger signal (pulse width 10ms) is generated. This command directly controls the camera module to take a picture or answers a phone call through the audio module. Start / stop control command generation: When matching the second action mode (three blinks within 500ms + 3-5Hz pressure fluctuation), a bistable switching signal (high-level start / low-level stop) is generated. This command synchronously controls the camera and audio module. Parameter adjustment command generation: When matching the third action mode (1-2Hz continuous pressure fluctuation + 200ms... When the head is stationary, a progressive adjustment signal is generated (PWM duty cycle changes linearly with duration), triggering an adjustment step every 100ms pressure maintenance cycle: volume adjustment duty cycle increases by 1% → volume +1dB (range 0-100dB); focus adjustment: duty cycle increases by 2% → focus advances by 0.1X (range 1-5X). A command mutex lock is set to block photo capture commands during recording to prevent functional conflicts; status feedback is provided when commands are executed, for example, the LED indicator lights up green for 0.5s after a photo is taken; during recording, the LED remains red; and the LED brightness changes with the volume level during volume adjustment.

[0088] In one embodiment, for step S5,

[0089] The steps of executing the control commands to operate the predetermined functions of the smart glasses include:

[0090] The basic function commands are transmitted to the camera module to take a picture; or to the audio module to answer a phone call.

[0091] The audio and video recording start / stop command is transmitted to the camera module and audio module to execute the start / stop operation of recording or audio recording;

[0092] The parameter adjustment command is transmitted to the audio module to adjust the volume, or to the camera module to adjust the focus.

[0093] During operation, the smart glasses output status prompts via LED indicator lights.

[0094] In practical implementation, function control is achieved through direct hardware connection and multi-level feedback. Basic functions are executed; for example, in a photo-taking operation, the pulse command for taking the picture is transmitted via I / O.2 The C bus (rate 400kHz) is transmitted to the camera module, triggering the shutter and saving the PNG format image to the EMMC storage; if answering a call, the answer command is transmitted to the audio module through the PCM audio bus, connecting the Bluetooth call channel, and the temple sound unit enables hands-free mode; (2) Audio and video recording control, synchronous start and stop mechanism, the recording command is synchronously triggered to the camera module and audio module (start AAC recording) through parallel GPIO, the clock deviation between the two is <3ms (meeting the audio and video synchronization standard); the video file is written in segments (.MOV package, 5 minutes per segment) to avoid data loss due to sudden power failure of the 250mAh battery; parameter adjustment execution, when adjusting the volume, the PWM duty cycle signal (step 1% / 100ms) controls the audio power amplifier PCB to achieve stepless adjustment of 0-100dB (accuracy ±0.5dB); when adjusting the focus, the duty cycle signal is converted to I 2 C register instructions (0.1X per step) drive the camera module motor (VCM) to advance the focal length (range 1-5X). Status indicators are output via the smart glasses' LEDs; for example, a photo is taken when the LED on the nose pad lights green for 0.5 seconds, recording is in progress when the LED is continuously red, volume adjustment causes the LED brightness to change linearly with the volume level (10% brightness / 10dB), and a call is answered when the LED blinks blue. Users can extend the execution logic via the app, redefining the LED mode: users can change the recording indicator from red to purple (for colorblind individuals); and adjust the response speed: the volume step value can be changed from 1dB / step to 2dB / step (for quick scene adjustments).

[0095] Reference Figure 2 Here is a structural block diagram of a non-contact smart glasses blink control device according to an embodiment of the present invention, comprising:

[0096] The parameter acquisition module is used to collect the wearer's eye movement feature parameters, periorbital muscle activity feature parameters, and head posture movement feature parameters in real time.

[0097] The feature extraction module is used to fuse the collected eye movement feature parameters, periorbital muscle activity feature parameters, and head posture movement feature parameters to extract signal change feature parameters that represent the user's blinking intention.

[0098] The pattern recognition module is used to dynamically identify specific blinking action patterns performed by the user based on the extracted signal change feature parameters and using a preset pattern recognition algorithm.

[0099] The instruction generation module is used to generate corresponding control instructions based on the identified specific blinking action pattern;

[0100] The instruction execution module is used to execute the control instructions and operate the predetermined functions of the smart glasses.

[0101] For the specific implementation of each module in the above device example, please refer to the above method embodiments, which will not be repeated here.

[0102] Reference Figure 3 This invention also provides a computer device, which can be a server, and its internal structure can be as follows: Figure 3 As shown, the computer device includes a processor, memory, display screen, input device, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores the data corresponding to this embodiment. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements the above-described method.

[0103] Those skilled in the art will understand that Figure 3 The structures shown are merely block diagrams of some structures related to the present invention and do not constitute a limitation on the computer devices on which the present invention is applied.

[0104] An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method. It is understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0105] In summary, this invention collects real-time eye movement feature parameters, periorbital muscle activity feature parameters, and head posture movement feature parameters of the wearer; it then fuses these parameters to extract signal change feature parameters representing the user's blinking intention; based on these extracted signal change feature parameters, it dynamically identifies specific blinking action patterns performed by the user using a preset pattern recognition algorithm; it generates corresponding control commands based on the identified specific blinking action patterns; and it executes these control commands to operate the predetermined functions of the smart glasses, thereby achieving the goal of precise control over the smart glasses' full-function natural interaction, including taking photos, recording videos, making calls, and adjusting parameters.

[0106] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the present invention and embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM, etc.

[0107] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0108] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A non-contact smart glasses blink control method, characterized in that, Includes the following steps: Real-time synchronous collection of the wearer's eye movement characteristics, periorbital muscle activity characteristics, and head posture movement characteristics; The collected eye movement feature parameters, periocular muscle activity feature parameters, and head posture movement feature parameters are fused to extract signal change feature parameters representing the user's blinking intention. This includes: determining the head movement state based on the head posture movement feature parameters; if the change in head angle exceeds a vibration threshold, the current data is marked as interfered; aligning the eye movement feature parameters and periocular muscle activity feature parameters along the time axis to calculate the correlation strength between eyelid closure events and pressure fluctuations; combining the head movement state markers and correlation strength, filtering out interfering data and outputting the temporal features of valid blinking actions to constitute the signal change feature parameters; wherein, filtering out interfering data and outputting the temporal features of valid blinking actions includes: discarding all feature parameters within the current time window when the head posture movement feature parameters exceed a vibration threshold; determining an invalid blinking action when the eye movement feature parameters show eyelid closure but no associated periocular muscle activity feature parameters are detected; and extracting the timestamp sequence, pressure peak, and duration of verified valid blinking actions to constitute the temporal features of valid blinking actions. Based on the extracted signal change feature parameters, a preset pattern recognition algorithm is used to dynamically identify specific blinking action patterns performed by the user. Based on the identified specific blinking pattern, corresponding control commands are generated; The control commands are executed to operate the predetermined functions of the smart glasses.

2. The non-contact smart glasses blink control method according to claim 1, characterized in that, The steps of real-time synchronously collecting the wearer's eye movement feature parameters, periorbital muscle activity feature parameters, and head posture movement feature parameters include: By using a dual-wavelength infrared sensor located at the nose pad of the smart glasses, the infrared reflection light difference signal of the eyelid opening and closing speed and amplitude is collected in real time as the eye movement feature parameter. A capacitive pressure sensor array located on the inner side of the temple is used to collect non-contact pressure fluctuation signals caused by the contraction of the orbicularis oculi muscle in real time as characteristic parameters of the periocular muscle activity. The smart glasses use a built-in six-axis gyroscope sensor to collect real-time changes in the three-dimensional angle of the head as the head posture motion characteristic parameters. The data acquisition timing of the dual-wavelength infrared sensor, the capacitive pressure sensor array, and the six-axis gyroscope sensor is synchronously controlled by the main control board.

3. The non-contact smart glasses blink control method according to claim 1, characterized in that, The step of dynamically identifying a specific blinking pattern performed by the user based on the extracted signal change feature parameters and using a preset pattern recognition algorithm includes: The first action pattern is detected. Within a preset first time window, two valid blinking actions are detected consecutively, and the pressure fluctuation signal conforms to the first frequency range. The first action pattern constitutes a specific blinking action pattern. The second action pattern is detected if three valid blinking actions are detected continuously within a preset second time window and the pressure fluctuation signal conforms to the second frequency range. The second action pattern constitutes one of the specific blinking action patterns. The third action mode is detected, and the pressure fluctuation signal in the third frequency range is continuously detected. At the same time, the head posture movement characteristic parameters remain static for more than a preset time. The third action mode constitutes one of the specific blinking action modes. The first action mode, the second action mode, or the third action mode is matched based on the real-time extracted signal change feature parameters.

4. The non-contact smart glasses blink control method according to claim 3, characterized in that, The step of generating corresponding control commands based on the identified specific blinking pattern includes: When the first action pattern is matched, a basic function instruction is generated to trigger the basic function; When the second action mode is matched, an audio / video recording start / stop command is generated; When the third action mode is matched, parameter adjustment instructions for the system are generated.

5. The non-contact smart glasses blink control method according to claim 4, characterized in that, The step of executing the control command to operate the predetermined function of the smart glasses includes: The basic function commands are transmitted to the camera module to take a picture; or to the audio module to answer a phone call. The audio and video recording start / stop command is transmitted to the camera module and audio module to execute the start / stop operation of recording or audio recording; The parameter adjustment command is transmitted to the audio module to adjust the volume, or to the camera module to adjust the focus. During operation, the smart glasses output status prompts via LED indicator lights.

6. A non-contact smart glasses blink control device, characterized in that, include: The parameter acquisition module is used to collect the wearer's eye movement feature parameters, periorbital muscle activity feature parameters, and head posture movement feature parameters in real time. The feature extraction module is used to fuse the collected eye movement feature parameters, periorbital muscle activity feature parameters, and head posture movement feature parameters to extract signal change feature parameters representing the user's blinking intention. This includes: determining the head movement state based on the head posture movement feature parameters; if the change in head angle exceeds a vibration threshold, marking the current data as interfered; aligning the eye movement feature parameters and periorbital muscle activity feature parameters along the time axis to calculate the correlation strength between eyelid closure events and pressure fluctuations; combining the head movement state markers and correlation strengths to filter out interfering data and output the temporal features of valid blinking actions, constituting the signal change feature parameters; wherein, filtering out interfering data and outputting the temporal features of valid blinking actions includes: discarding all feature parameters within the current time window when the head posture movement feature parameters exceed a vibration threshold; determining an invalid blinking action when the eye movement feature parameters show eyelid closure but no associated periorbital muscle activity feature parameters are detected; and extracting the timestamp sequence, pressure peak, and duration of verified valid blinking actions to constitute the temporal features of valid blinking actions. The pattern recognition module is used to dynamically identify specific blinking action patterns performed by the user based on the extracted signal change feature parameters and using a preset pattern recognition algorithm. The instruction generation module is used to generate corresponding control instructions based on the identified specific blinking action pattern; The instruction execution module is used to execute the control instructions and operate the predetermined functions of the smart glasses.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the non-contact smart glasses blink control method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the non-contact smart glasses blink control method according to any one of claims 1 to 5.

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