An event-triggered asynchronous electroencephalogram acquisition system and method

Abstract

The application discloses an event-triggering mechanism-based asynchronous electroencephalogram acquisition system and method, wherein a multi-channel electroencephalogram signal is directly received at an input end, an event-triggering sensing module is connected with an output end of an event feature conditioning module, a high-precision time sequence marking module is controlled by the output end of the event-triggering sensing module, an enabling end of an asynchronous electroencephalogram signal acquisition module is connected with the output end of the event-triggering sensing module, and an input end of the asynchronous electroencephalogram signal acquisition module receives the multi-channel electroencephalogram signal. The application adopts the event-triggering mechanism-based asynchronous electroencephalogram acquisition system and method, is designed based on natural asynchronous activity rules of the brain, and can non-forcedly and synchronously acquire, and more truly reflects the excitation and conduction sequence between brain regions; through a hardware-level event-triggering unit, event response can be accurately captured in real time, and the application far exceeds a traditional synchronous system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electroencephalogram signal acquisition and perception, and particularly relates to an asynchronous electroencephalogram acquisition system and method based on an event triggering mechanism. BACKGROUND

[0002] Existing electroencephalogram signal acquisition technologies are generally based on a synchronous acquisition mechanism, that is, continuous sampling of full-brain electroencephalogram signals at fixed time intervals in order to capture neural responses after stimulation. However, this method cannot effectively reveal the natural asynchronous neural activity characteristics of the brain. The neural responses of different brain regions have significant asynchronous and region-specific characteristics when receiving external stimuli or processing internal information. The electroencephalogram synchronous acquisition method has the following defects and deficiencies:

[0003] Time alignment deviation: the neural responses of different brain regions have individualized delays and excitation timing, and the synchronous mechanism cannot accurately capture this real timing structure. Redundant sampling and resource waste: fixed frequency sampling results in a large amount of redundant data at non-critical moments, occupying computing and storage resources. Difficulty in adapting to high timing accuracy research: the identification of functional brain diseases such as depression and epilepsy relies on fine brain region excitation sequence analysis, and the traditional method cannot support such needs. Hardware response lag: the response speed of traditional acquisition devices cannot be accurately synchronized with instantaneous electroencephalogram events, limiting real-time performance and perception sensitivity. Lack of timing accuracy support for disease identification: brain functional diseases such as depression and epilepsy have close relationships between brain electrical characteristics and brain region excitation sequences, and the traditional synchronous method cannot extract such key timing characteristics.

[0004] At present, although some studies attempt to use event-related potentials (ERP) to analyze the electroencephalogram responses after specific stimulation, they still rely on fixed time window sampling and belong to the quasi-synchronous paradigm, and cannot achieve true asynchronous acquisition and high timing accuracy perception. Therefore, it is urgent to propose a new event-oriented electroencephalogram acquisition method that can more truly, efficiently and accurately reflect the timing nature of brain activity. SUMMARY

[0005] The present application aims to provide an asynchronous electroencephalogram acquisition system and method based on an event triggering mechanism, which is designed based on the natural asynchronous activity rules of the brain, and can more truly reflect the excitation and conduction sequence between brain regions through non-mandatory synchronous acquisition. Through a hardware-level event triggering unit, the event response can be accurately captured in real time, far exceeding traditional synchronous systems.

[0006] The application provides an event-triggering mechanism-based asynchronous electroencephalogram acquisition system and method, which comprises an event induction module, a multi-channel electroencephalogram signal, an event feature conditioning module, an event trigger sensing module, a high-precision time sequence marking module and an asynchronous electroencephalogram signal acquisition module, the event feature conditioning module directly receives the multi-channel electroencephalogram signal at an input end, the event trigger sensing module is connected with the output end of the event feature conditioning module, and the high-precision time sequence marking module is controlled by the output end of the event trigger sensing module; the enable end of the asynchronous electroencephalogram signal acquisition module is connected with the output end of the event trigger sensing module, and the input end of the asynchronous electroencephalogram signal acquisition module receives the multi-channel electroencephalogram signal.

[0007] Preferably, the event induction module comprises audio stimulation protocols with different frequencies, intensities and rhythms.

[0008] Preferably, the event feature conditioning module comprises an impedance matching circuit, a filter circuit, a low-noise differential operational amplifier and a direct current servo circuit based on a negative feedback technology.

[0009] Preferably, the event trigger sensing module is provided with an asynchronous chip.

[0010] Preferably, the asynchronous electroencephalogram signal acquisition module dynamically sets a sampling window according to the event type and historical reaction time sequence.

[0011] Preferably, a method of the event-triggering mechanism-based asynchronous electroencephalogram acquisition system comprises the following steps.

[0012] Step S1: generating an audio stimulation protocol through the event induction module to induce a human body to generate a neural response event;

[0013] Step S2: collecting a multi-channel electroencephalogram signal generated due to the neural response event through an electrode;

[0014] Step S3: the event feature conditioning module performs impedance matching, filtering, amplification and direct current bias elimination on the multi-channel electroencephalogram signal; after the multi-channel electroencephalogram signal of different brain regions is strengthened by the event trigger feature through the event feature conditioning module, the signal enters the event trigger sensing module for feature matching;

[0015] Step S4: when the event trigger sensing module matches a trigger feature to a threshold value, an enable signal is sent to the time sequence marking module and the acquisition module;

[0016] Step S5: the acquisition module starts to collect a target brain region signal and dynamically sets a sampling window;

[0017] Step S6: the time sequence marking module records a time stamp and binds the time stamp with collected data, audio stimulation information and a brain region number.

[0018] Preferably, in step S5, the dynamic setting of the sampling window comprises automatically setting the window length according to the event type and correcting the sampling start time point according to the historical response delay.

[0019] Therefore, the application adopts the above-mentioned event-triggering mechanism-based asynchronous electroencephalogram acquisition system and method, which is designed based on the natural asynchronous activity law of the brain, non-forcedly synchronously acquires, and more truly reflects the excitation and conduction sequence between brain regions; through the hardware-level event triggering unit, the event response can be accurately captured in real time, far exceeding the traditional synchronous system.

[0020] The technical solutions of the application will be further described in detail below with reference to the drawings and embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0021] Fig. 1 FIG. 1 is a schematic diagram of the overall system of the event-triggering mechanism-based asynchronous electroencephalogram acquisition system and method of the application;

[0022] Fig. 2 FIG. 1 is a schematic diagram of the overall system of the event-triggering mechanism-based asynchronous electroencephalogram acquisition system and method of the application; DETAILED DESCRIPTION

[0023] The technical solutions of the application will be further described in detail below with reference to the drawings and embodiments.

[0024] Unless otherwise defined, the technical terms or scientific terms used in the application shall have the usual meanings understood by those skilled in the art to which the application belongs.

[0025] The terms "first", "second", and similar terms used in the application do not represent any order, number, or importance, but are only used to distinguish different components. The terms "include" or "contain" and similar terms mean that the elements or objects before the terms cover the elements or objects listed after the terms and their equivalents, without excluding other elements or objects. The terms "connect" or "connected" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms "up", "down", "left", "right", and the like are only used to represent relative positional relationships, and when the absolute positions of the described objects change, the relative positional relationships may also change accordingly.

[0026] Embodiment One

[0027] As Figs. 1-2As shown, the application is an event-triggering mechanism-based asynchronous electroencephalogram acquisition system and method, which comprises an event induction module, a multi-channel electroencephalogram signal, an event feature conditioning module, an event-triggering perception module, a high-precision timing labeling module, and an asynchronous electroencephalogram signal acquisition module. The event induction module comprises audio stimulation protocols of different frequencies, intensities, and rhythms.

[0028] The event feature conditioning module directly receives the multi-channel electroencephalogram signal at the input end. The event feature conditioning module comprises an impedance matching circuit, a filter circuit, a low-noise differential operational amplifier, and a direct current servo circuit based on negative feedback technology. The event-triggering perception module is connected to the output end of the event feature conditioning module at the input end and is used to extract trigger features and generate an enable signal. The event feature conditioning module integrates the impedance matching circuit, the filter circuit, and the low-noise differential operational amplifier, can realize denoising, amplification of the original trigger event signal, and strengthening of the event trigger features, and enhances the sensitivity of the event feature matching unit in the event-triggering perception module to the trigger event. After the original electroencephalogram signals of different brain regions are strengthened by the event feature conditioning module, the event trigger features are entered into the event-triggering perception module for feature matching.

[0029] The high-precision timing labeling module is controlled by the output end of the event-triggering perception module. The event feature conditioning module and the event-triggering perception module are used to monitor the changes in the electroencephalogram signal in real time and extract key trigger features, such as specific frequency band transitions, instantaneous phase transformations, and waveform mutations. The event-triggering perception module is provided with an asynchronous chip, specific trigger events are designed according to the characteristics of the electroencephalogram signals induced by different audio and video emotional inductions, and thus the individualized event trigger function is realized. When the event feature matching unit in the event-triggering perception module perceives that the event trigger features meet the preset values (the feature threshold is determined by the specific event trigger features selected), the enable signal is generated by the pulse generator. The start of the electroencephalogram signal acquisition of the corresponding analog-to-digital converter channel in the asynchronous electroencephalogram signal acquisition module is activated. At the same time, the high-precision timing labeling module records the current time point to complete the high-precision timing labeling.

[0030] The enable end of the asynchronous electroencephalogram signal acquisition module is connected to the output end of the event-triggering perception module, and the input end of the asynchronous electroencephalogram signal acquisition module receives the multi-channel electroencephalogram signal. The asynchronous electroencephalogram signal acquisition module dynamically sets the sampling window according to the event type and the historical reaction timing.

[0031] All the collected data in the high-precision timing labeling module are bound with the event trigger timestamp, the audio stimulation information, and the brain region number to form a structured electroencephalogram data set with high time resolution. After the trigger event is identified, the asynchronous electroencephalogram signal acquisition module starts the sampling process of the corresponding brain region and automatically sets the sampling window according to the event type and the historical reaction timing to complete the non-fixed time point and region-oriented high-precision acquisition.

[0032] The specific method comprises the following steps:

[0033] Step S1, generating an audio stimulation protocol by an event induction module to induce a human body to generate a neural response event.

[0034] Step S2, collecting multi-channel electroencephalogram signals generated due to the neural response event by electrodes.

[0035] Step S3, an event feature conditioning module performs impedance matching, filtering, amplification and direct current bias elimination on the multi-channel electroencephalogram signals. After the multi-channel electroencephalogram signals of different brain regions are strengthened by the event feature conditioning module, the event triggered features enter an event triggered perception module for feature matching.

[0036] Step S4, the event triggered perception module sends an enable signal to a time sequence marking module and a collection module when the trigger feature matching threshold is met.

[0037] Step S5, the collection module starts target brain region signal collection and dynamically sets a sampling window. In step S5, dynamically setting the sampling window comprises automatically setting a window length according to the event type and correcting a sampling start time point according to a historical response delay.

[0038] Step S6, the time sequence marking module records a time stamp and binds it with collected data, audio stimulation information and brain region numbers.

[0039] Therefore, the application adopts the above-mentioned asynchronous electroencephalogram collection system and method based on an event triggered mechanism, is designed based on the natural asynchronous activity law of the brain, and performs non-forced synchronous collection, so as to more truly reflect the excitation and conduction sequence between brain regions; through a hardware level event triggering unit, the event response can be captured in real time and accurately, which is far superior to a traditional synchronous system; only when the event is triggered, the collection is activated, so that invalid data and energy consumption are significantly reduced, and the system is suitable for deployment in a mobile device or a long-term monitoring scene.

[0040] The above embodiment is only used to illustrate the technical solutions of the application but not to limit the application. Although the application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the application can be modified or replaced equivalently, and these modifications or replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the application.

Claims

1. An asynchronous EEG acquisition system based on an event-triggered mechanism, characterized in that, It includes an event induction module, a multi-channel EEG signal module, an event feature conditioning module, an event trigger perception module, a high-precision timing labeling module, and an asynchronous EEG signal acquisition module. The event feature conditioning module directly receives multi-channel EEG signals at its input end. The event trigger perception module is connected to the output end of the event feature conditioning module at its input end. The high-precision timing labeling module is controlled by the output end of the event trigger perception module. The enable terminal of the asynchronous EEG signal acquisition module is connected to the output terminal of the event-triggered perception module, and the input terminal of the asynchronous EEG signal acquisition module receives multi-channel EEG signals. The event triggering sensing module is equipped with an asynchronous chip. When the event feature matching unit in the event triggering sensing module senses that the event triggering feature meets the preset value, it controls the pulse generator to generate an enable signal. The high-precision timing marking module records the current time point to complete the high-precision timing marking.

2. The asynchronous EEG acquisition system based on an event-triggered mechanism according to claim 1, characterized in that, The event-triggered module includes audio stimulus protocols with different frequencies, intensities, and rhythms.

3. The asynchronous EEG acquisition system based on an event-triggered mechanism according to claim 1, characterized in that, The event feature conditioning module includes an impedance matching circuit, a filter circuit, a low-noise differential operational amplifier, and a DC servo circuit based on negative feedback technology.

4. The asynchronous EEG acquisition system based on an event-triggered mechanism according to claim 1, characterized in that, The asynchronous EEG signal acquisition module dynamically sets the sampling window based on the event type and historical reaction sequence.

5. A method for an asynchronous EEG acquisition system based on an event-triggered mechanism as described in any one of claims 1-4, characterized in that, Includes the following steps: Step S1: Generate an audio stimulus protocol through the event triggering module to induce a neural response event in the human body; Step S2: Acquire multi-channel electroencephalogram (EEG) signals generated by the neural response event using electrodes; Step S3: The event feature conditioning module performs impedance matching, filtering, amplification, and DC bias elimination on the multi-channel EEG signals; after the multi-channel EEG signals from different brain regions are enhanced with event triggering features by the event feature conditioning module, they enter the event triggering perception module for feature matching. Step S4: When the event triggering perception module triggers the feature matching threshold, it sends an enable signal to the timing marking module and the acquisition module. Step S5: The acquisition module starts acquiring signals from the target brain region and dynamically sets the sampling window; Step S6: The time-series marking module records the timestamp and binds it to the collected data, audio stimulus information, and brain region number.

6. The method of an asynchronous EEG acquisition system based on an event-triggered mechanism according to claim 5, characterized in that, In step S5, dynamically setting the sampling window includes automatically setting the window duration based on the event type and correcting the sampling start time based on historical response delays.

Images