Brain-like awakening system and method driven by non-invasive brain-computer interface

Abstract

The invention discloses a brain-like awakening system and method driven by a non-invasive brain-computer interface. The brain-like awakening system comprises a signal acquisition module, a multi-modal fusion module, a state judgment module, a feedback adjustment module, a user portrait module and the like. The system integrates electroencephalogram, physiology and eye movement data, identifies attention or fatigue state in real time, and implements personalized feedback intervention to realize closed-loop nerve regulation and control. The method is suitable for cognitive training, psychological recovery and motion activation, and has the advantages of non-invasiveness, high adaptability, real-time feedback and the like.

Description

[0001]

Technical Field

[0002]

Background Art

[0003]

Summary of the Invention

Description of the Drawings

[0004] Figure 1 It is the functional module structure diagram of the system of the present invention;

[0005] Figure 2 It is the flow chart of the brain - like arousal method;

[0006] Figure 3 It is the structure diagram of a typical application scenario.

[0007]

Technical Solution

[0008] 1. Signal acquisition module: including non - invasive electroencephalogram devices, physiological monitoring devices (such as heart rate belts or wearable HRV devices), and eye trackers;

[0009] 2. Multi - modal fusion module: extracting and fusing the above signals, including α / β ratio, θ power, HRV fluctuation index, eye movement fixation duration, etc.;

[0010] 3. Arousal determination module: determining whether the current brain state is in a state of low attention, fatigue or insufficient alertness based on training data or rule logic;

[0011] 4. Feedback regulation module: according to the arousal determination result, calling a preset feedback method (such as rhythmic visual flicker, audio beat or tactile signal) for rapid intervention;

[0012] 5. Data recording and user profiling module: Continuously track the intervention effect, establish a personalized neural response model, and achieve dynamic adjustment of rhythm and plan.

[0013]

Beneficial effects

[0014] 1. Implement a non-invasive, low-latency, closed-loop brain arousal regulation system;

[0015] 2. Multimodal physiological signal fusion significantly improves the accuracy and robustness of brain state determination;

[0016] 3. Can be extended to fields such as educational attention regulation, pre-sports competition activation, medical rehabilitation training, and cognitive disorder intervention.

[0017]

Example

Claims

1. A non-invasive brain-computer interface-driven brain-like arousal system, characterized in that, The system includes: · A signal acquisition module, including a non-invasive electroencephalogram device, an HRV / heart rate monitoring device, and an eye movement tracking device; · A multimodal fusion module, which extracts and fuses features of the above signals and outputs a unified processed evidence index. · A state determination module, which determines whether the user is in a fatigued, insufficiently awake, or distracted state based on the fused features; · A feedback adjustment module, which calls preset visual, audio, or rhythmic perception output methods according to the determination result; · A user grouping and model update module, which makes personalized selections and adaptive adjustments according to user responses or positive evaluations.

2. The system according to claim 1, wherein the signal acquisition module includes an EEG electroencephalogram acquisition unit for acquiring the alpha / beta wave ratio and spatial distribution characteristics of the user.

3. The system according to claim 1, wherein the signal acquisition module further includes an HRV / heart rate monitoring unit for acquiring heart rate variability indexes such as SDNN and RMSSD.

4. The system according to claim 1, wherein the signal acquisition module further includes an eye movement tracking unit for acquiring behavioral data such as the user's fixation points, eye movement, and blinking.

5. The system according to claim 1, wherein the output of the feedback adjustment module includes one or more perception signals, including rhythmic flashing lights, repeated audio, or vibration signals, to relieve the fatigued state or improve the efficiency of entering the state.

6. The system according to claim 1, wherein the user grouping module cooperates with a set of user effect indicators (such as fatigue recovery speed, reaction time, display effectiveness, HRV recovery rate, etc.) to perform user classification and update of personalized adjustment strategies.

7. The system according to claim 1, wherein the state determination module trains a reusable rule logic model or a machine learning type for classifying and determining the user's current neural awakening state.

8. The system according to claim 1c wherein the application scenarios of the system include application systems such as education and training, sports migration, mental recovery, or quality monitoring, and can be connected to a series of unified application components or software platforms.

9. The system according to claim 1, wherein the signal acquisition, analysis, and output devices are interconnected via the Internet or BLE and can perform local system calls or remote collaboration.

10. The system according to claim 1, wherein the data center is also equipped with interface devices for accessing and extending functions such as data acquisition, evaluation, and personalized analysis.

11. The system according to claim 1, wherein the feedback adjustment module is wirelessly connected to a wearable output device, and the output device includes augmented reality glasses, a smart bracelet, or a vibration patch.

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