CN117481667A

CN117481667A - Electroencephalogram signal acquisition system

Info

Publication number: CN117481667A
Application number: CN202311389372.3A
Authority: CN
Inventors: 陈骥驰; 崔育国; 钱程; 何恩球
Original assignee: Shenyang University of Technology
Current assignee: Shenyang University of Technology
Priority date: 2023-10-24
Filing date: 2023-10-24
Publication date: 2024-02-02

Abstract

The invention discloses an electroencephalogram signal acquisition system, which comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for measuring the electrical activity of the brain through brain electrodes to obtain an electroencephalogram signal; the amplification module is used for amplifying and enhancing the brain electrical signals through the amplifier; the conversion module is used for converting the amplified and enhanced brain electrical signals into digital forms to obtain brain electrical signal data; the processing module is used for monitoring the brain electrical activity in real time according to the brain electrical signal data, and carrying out data processing, feature extraction, time domain and frequency domain analysis to obtain an analysis result; and the storage module is used for classifying and storing the analysis results so as to store the analysis results for a long time and retrieve the analysis results later. The brain-computer interface classifying method and the brain-computer interface classifying device can classify according to different application purposes of the brain-computer signals, so that the brain activities are researched, the brain diseases are diagnosed, the sleep is monitored, the brain-computer interface is researched and the like, and related personnel can conveniently call the brain-computer signal data in real time.

Description

Electroencephalogram signal acquisition system

Technical Field

The invention belongs to the field of electroencephalogram signal acquisition, and particularly relates to an electroencephalogram signal acquisition system.

Background

The informatization development of the medical technology makes the medical technology more advanced, and the development of the medical technology makes the diagnosis and treatment of diseases more accurate, convenient and quick. Brain electrical signals are spontaneous potential activities generated by brain neuron activities and always exist, and are important bioelectric signals. The brain electrical signal not only can provide diagnosis basis for some brain diseases, but also can be used for assisting the research of brain activities, monitoring sleep, researching brain-computer interfaces and the like. Therefore, the acquisition of the brain electrical signals is very important. However, no acquisition system and device capable of integrating the purposes of the electroencephalogram signals exist at present. Therefore, there is an urgent need for such a device and system to achieve multiple functions in one machine, and to realize different interaction studies across fields.

Disclosure of Invention

In order to achieve the above object, the present invention provides the following solutions: an electroencephalogram signal acquisition system comprising:

the acquisition module is used for measuring the electrical activity of the brain through brain electrodes to obtain brain electrical signals;

the amplifying module is connected with the acquisition module and is used for amplifying and enhancing the electroencephalogram signals through an amplifier;

the conversion module is connected with the amplification module and used for converting the amplified and enhanced brain electrical signals into digital forms to obtain brain electrical signal data;

the processing module is connected with the conversion module and is used for monitoring the brain electrical activity in real time according to the brain electrical signal data and carrying out data processing, feature extraction, time domain and frequency domain analysis to obtain an analysis result;

and the storage module is connected with the processing module and used for classifying and storing the analysis results so as to store for a long time and retrieve later.

Preferably, the brain electrode comprises a collecting electrode and a reference electrode;

the acquisition electrode is used for measuring brain electrical signals;

the reference electrode is arranged on the scalp and far away from the brain, is used for relatively measuring the activity of the brain electrical signals and provides a reference potential for the acquisition electrode.

Preferably, the collecting electrode comprises an electrode main body, an electrode head, a connecting wire and a connector;

the electrode body is made of conductive materials, particularly metals or other materials with good conductivity, and at least comprises silver, silver/silver chloride and brass;

the electrode head is round or flat and is used for contacting with the scalp, and the electrode head is provided with holes and is used for connecting the collecting electrode to the scalp through conductive adhesive;

the connecting wire is an insulated wire and is used for transmitting the recorded brain electrical signals to the brain electrical signal amplifier or the recording equipment;

the connector is arranged at the tail end of the connecting wire and is used for connecting the acquisition electrode with an amplifier or a recording device.

Preferably, the brain electrode further comprises a fixing device, conductive adhesive and a marking unit;

the fixing device is used for ensuring that the electrode is kept fixed on the scalp safely during the collection period and preventing the electrode from moving or loosening;

the conductive adhesive is used for being smeared on the electrode head so as to ensure good electric conduction and reduce resistance;

the marking unit is used for marking the position and the direction of the electrode and ensuring the consistent placement of the electrode.

Preferably, the electrode type of the brain electrode comprises a surface electrode, a depth electrode, a cerebral cortex electrode, an intracranial electrode, a brain stem electrode, an eye electrode, a muscle electrode and a heart electrode;

the surface electrode comprises a sticking electrode, a silver chloride/silver electrode and a cap electrode.

Preferably, the amplifier comprises a pre-amplifier and a main amplifier;

the preamplifier is arranged near the acquisition electrode and is used for immediately amplifying the brain electrical signal and reducing noise interference in signal transmission;

the main amplifier is used for further increasing the amplitude of the signal and has adjustable gain so as to adapt to different signal strengths and experimental requirements.

Preferably, the conversion module comprises a filter and an analog-to-digital converter;

the filter is used for filtering to reserve the interested brain electrical frequency range and remove unnecessary frequency component interference;

analog-to-digital converters (ADCs) are used to convert amplified and filtered analog signals to digital signals for processing and storage by a computer or data acquisition system.

Preferably, the processing module comprises an event marking unit, a feature extraction unit, a time domain analysis unit, a frequency domain analysis unit, a statistical analysis unit and a visualization unit;

the event marking unit is used for recording the time point of a specific event, correlating the electroencephalogram signal with the specific event through event marking, and then analyzing the event-related potential;

the characteristic extraction unit is used for extracting useful characteristics from the electroencephalogram signal data, wherein the characteristics comprise amplitude, frequency, phase and energy;

the time domain analysis unit is used for researching the amplitude and waveform of the electroencephalogram signal and searching the potential difference of a specific event;

the frequency domain analysis unit is used for converting the electroencephalogram signals into spectrograms to study the signal activities in different frequency ranges;

the visualization unit is used for visualizing the analysis result in a graph or chart form and helping researchers and other people understand the data.

Preferably, the storage module comprises a storage unit, a classification unit and a security management unit;

the storage unit is used for storing the electroencephalogram signals, the characteristic data, the marking data and the data storage of the electroencephalogram signals;

the classification unit is used for dividing the electroencephalogram signal data according to different application purposes of the electroencephalogram signal;

the security management unit is used for carrying out data management and backup, setting version control and access authority of the data, and ensuring the backup and security of the data.

Preferably, the data storage adopts a database system or a file system for data storage management, so that the safety and retrievability of the data are ensured.

Compared with the prior art, the invention has the following advantages and technical effects:

the electroencephalogram signal acquisition system can be classified according to different application purposes of the electroencephalogram signals, so as to perform interactive application of research on brain activities, diagnosis of brain diseases, monitoring of sleep, research on brain-computer interfaces and the like. The electroencephalogram data is used for analyzing the frequency spectrum of the brain waves, identifying Event Related Potential (ERP), monitoring epileptic activities, exploring cognitive functions and the like according to different purposes, so that related personnel can conveniently call the electroencephalogram data in real time.

The electroencephalogram signal acquisition system can be interactively applied in the fields of research, medical treatment, technology and psychology, and can intelligently schedule electroencephalogram signal data required by different researchers in real time. Is helpful for understanding brain function, improving medical diagnosis and treatment, developing brain-computer interface technology, improving user experience and emotion recognition, and providing important brain activity information for researchers and medical professionals.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application, illustrate and explain the application and are not to be construed as limiting the application. In the drawings:

fig. 1 is a schematic diagram of a system structure according to an embodiment of the present invention.

Detailed Description

It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.

As shown in fig. 1, the electroencephalogram signal acquisition system provided by the invention comprises,

the amplifying module is connected with the acquisition module and used for amplifying and enhancing the brain electrical signals through the amplifier;

the conversion module is connected with the amplification module and used for converting the amplified and enhanced electroencephalogram signals into digital forms to obtain electroencephalogram signal data;

the processing module is connected with the conversion module and used for monitoring the brain electrical activity in real time according to the brain electrical signal data and carrying out data processing, feature extraction, time domain and frequency domain analysis to obtain an analysis result;

the storage module is connected with the processing module and used for classifying and storing the analysis results so as to store the analysis results for a long time and retrieve the analysis results later.

Further, the brain electrode comprises a collecting electrode and a reference electrode;

the acquisition electrode is used for measuring brain electrical signals;

the brain electrode comprises an electrode main body, an electrode head, a connecting wire, a connector, a fixing device, conductive adhesive and a marking unit. These parts work together to enable the brain electrical signals to be recorded and transmitted accurately and reliably.

The body of the brain electrode is made of an electrically conductive material, in particular metal or other material with good electrical conductivity, such as silver, silver/silver chloride, brass, etc.

One end of the brain electrode has a smaller rounded or flattened head for contact with the scalp. The brain electrode head has tiny holes for connecting the electrodes to the scalp through conductive glue. The shape and size of the electrode head will vary depending on the type and application of the electrode.

The connecting wire of the brain electrode is an insulated wire and is used for transmitting the recorded brain electrical signals to the brain electrical signal amplifier or the recording equipment. The connection lines are typically flexible, insulated to avoid signal interference or shock risks. The terminal of the connection wire is attached with a connector to connect the electrode with an amplifier or recording device.

The brain electrode also includes a securing means, such as a headband, glue or elastic band, to ensure that the electrode remains securely fixed to the scalp during harvesting, preventing movement or loosening.

For the wet contact electrode, the conductive adhesive is further included, and the conductive adhesive is smeared on the electrode head to ensure good electric conduction and reduce resistance, so that the clear electroencephalogram signal can be obtained.

The brain electrode also includes a system of specific markers for identifying the position and orientation of the electrode to ensure consistent placement of the electrode.

The reference electrode works as follows:

establishing a reference potential: the main task of the reference electrode is to establish a reference potential in order to measure the acquired brain electrical signals with respect to this reference. This is because the electroencephalogram signal is typically a weak bioelectric signal, and its measurement requires a reference of known potential.

Stability and low noise: the reference electrode is typically placed in a fixed position on the scalp to ensure its stability. It should remain in a constant position and not be disturbed by head movements or other factors. Furthermore, the reference electrode should have a low noise characteristic to avoid introducing disturbances in the signal measurement.

Conductance: the reference electrode must have good conductivity characteristics to ensure that the potential is faithfully transferred. Typically, the reference electrode uses a skin friendly material, such as a silver/silver chloride electrode, to ensure good electrical conductivity.

Differential measurement: in electroencephalogram acquisition, the potential difference between an electroencephalogram electrode and a reference electrode is a measured signal. Thus, the electroencephalogram signal acquisition system will measure the potential difference between the electroencephalogram electrode and the reference electrode, rather than the absolute potential.

Common mode noise reduction: the location and nature of the reference electrode helps to reduce the effects of common mode noise. Common mode noise is any external disturbance that affects both the brain electrical signal and the reference electrode. By placing the reference electrode at a fixed location, the effects of common mode noise can be reduced.

In summary, the working of the reference electrode in the acquisition of an electroencephalogram signal involves establishing a stable reference potential for measuring the potential difference of the electroencephalogram signal relative to the reference. It has good conductivity characteristics and low noise to ensure accurate measurement of brain electrical signals and should be placed in a fixed position to reduce the effects of common mode noise. This helps to obtain a clear and reliable record of the brain electrical signals.

Further optimizing the protocol, the brain electrode types in this embodiment include, but are not limited to, surface electrodes, depth electrodes, cerebral cortex electrodes, intracranial electrodes, brainstem electrodes, ocular electrodes, muscle electrodes, cardiac electrodes. Wherein,

the surface electrode is placed on the scalp and a conductive adhesive is used to ensure good contact. The surface electrode may be further classified into a paste electrode, a silver chloride/silver electrode, and a cap electrode.

The adhesive electrode is used for disposable use, is attached with a self-adhesive bottom and is easy to place and remove.

Silver chloride/silver electrodes can provide good signal quality for long term monitoring or research.

The cap electrode embeds the electrode in a cap, which can be quickly placed on the head for use in electroencephalogram (EEG) studies.

Depth electrodes are electrodes implanted into the brain for monitoring electrical activity in specific brain regions, such as preoperative localization of epilepsy and study of brain disease.

The cerebral cortex electrode is directly implanted into cerebral cortex for brain-machine interface and brain electric stimulation therapy.

Intracranial electrodes are located intracranially but do not enter the cerebral cortex for monitoring seizures, brain surgery and research.

Brainstem electrodes are used to monitor electrical activity in brain stem regions and conduct research and diagnosis.

The ocular electrodes are used to monitor eye movement in order to correct Electrooculogram (EOG) data.

Myoelectrodes are used to monitor muscle activity, typically for Electromyography (EMG) studies.

The cardiac electrodes are used to record Electrocardiogram (ECG) signals for cardiac monitoring or to remove electrocardiographic interference in some electroencephalographic studies.

Electroencephalogram (EEG) is an electrophysiological record of human brain neural activity. During the acquisition process, the electroencephalogram signals are usually very weak and need to be amplified for analysis and research. The following is the basic steps of the amplification process of electroencephalogram signal acquisition:

further, the amplifier comprises a pre-amplifier and a main amplifier;

the brain electrical signals are typically very weak and need to be amplified to be effectively detected and recorded. The signal is passed from the electrodes on the scalp to the amplifier, typically with a pre-amplifier and a main amplifier on the harvester. The pre-amplifier is used to increase the amplitude of the signal in real time to reduce noise interference in signal transmission. The main amplifier further increases the amplitude of the signal and has an adjustable gain to accommodate different signal strengths and experimental requirements.

The pre-amplifier is arranged near the electrode, and the pre-amplifier is used for amplifying the brain electrical signal immediately before the brain electrical signal enters the main amplifier, so that the interference suffered by the signal when transmitted in a long cable can be reduced, and the signal-to-noise ratio can be improved.

The signal output by the pre-amplifier is transferred to the main amplifier. The main amplifier is a high gain, low noise amplifier for further amplifying the brain electrical signal. The main amplifier has different gain settings and can be adjusted according to experimental requirements.

Further, the conversion module comprises a filter and an analog-to-digital converter;

the amplified signal contains components of various frequencies, including noise from other than the brain electrical signal. Thus removing unwanted frequency components using filters. Common filters include a low pass filter for removing high frequency noise and a high pass filter for removing low frequency noise. The filtering is performed by a filter to preserve the electroencephalogram frequency range of interest while removing interference.

Maintaining the quality of the signal throughout the amplification process is critical. Proper amplifier and filter selection, good electrode attachment and conductive paste use, and minimization of system interference (e.g., electromagnetic interference) are key factors to ensure electroencephalogram signal quality.

The processing module comprises an event marking unit, a feature extraction unit, a time domain analysis unit, a frequency domain analysis unit, a statistic analysis unit and a visualization unit;

wherein the event marking unit is used for recording the time point of a specific event, such as stimulus presentation, behavior response or other important events. The Event markers can help correlate the electroencephalogram signals with specific events for Event-related potential (Event-Related Potentials, ERPs) analysis.

The feature extraction unit is used for extracting useful features from the electroencephalogram data so as to carry out subsequent analysis. Features include amplitude, frequency, phase, energy, etc. Patterns and events in the electroencephalogram signal are identified based on these features.

The time domain analysis unit is used for researching the amplitude and waveform of the brain electrical signal to find the potential difference of specific events, including calculating ERPs, such as P300, N200, etc., so as to know the response of the brain to specific stimulus or task.

The frequency domain analysis unit is used for converting the electroencephalogram signals into spectrograms so as to study signal activities in different frequency ranges, and specifically comprises Fourier transformation, power spectral density analysis, coherence analysis and the like.

The time-frequency domain analysis combines time domain and frequency domain analysis, and studies how the frequency components of the signal change with time by wavelet transform, hilbert-yellow transform, and the like. Common methods include.

The statistical analysis unit is used for determining whether significant differences exist between the electroencephalogram signals under different conditions, including t-test, variance analysis, non-parameter test and the like, and a multivariate statistical method.

The visualization unit is used for visualizing the analysis result in the form of graphs or charts to help researchers and other people understand data, and the visualized charts comprise brain topography charts, spectrograms, heat charts and the like.

Further, the storage module comprises a storage unit, a classification unit and a security management unit;

the storage unit is used for storing the electroencephalogram signals, the characteristic data, the marking data and the electroencephalogram signal data;

the data storage adopts a database system or a file system to carry out data storage management, so that the safety and retrievability of the data are ensured.

the safety management unit is used for carrying out data management and backup, setting version control and access authority of the data, and ensuring the backup and safety of the data.

Further, according to an optimized scheme, the electroencephalogram signal acquisition system can be used for classifying according to different application purposes of the electroencephalogram signal, so that application such as research of brain activities, diagnosis of brain diseases, monitoring of sleep, research of brain-computer interfaces and the like can be performed. The electroencephalogram data is used for analyzing the frequency spectrum of the brain waves, identifying Event Related Potential (ERP), monitoring epileptic activities, exploring cognitive functions and the like according to different purposes, so that related personnel can conveniently call the electroencephalogram data in real time.

Further optimizing scheme, the electroencephalogram signal acquisition system of the embodiment can be applied to:

neuroscience study: for understanding the structure and function of the brain. Researchers study brain functions such as cognitive processes, perception, emotion, thinking, and memory by analyzing electroencephalograms (EEG).

Clinical diagnosis: the healthcare field uses brain electrical signal acquisition systems to help diagnose various neurological and brain diseases such as epilepsy, stroke, parkinson's disease, concussions and sleep disorders. EEG can also be used to monitor anesthesia status and brain death.

Sleep study: the electroencephalogram signal acquisition system of the present embodiment can be used for researching and diagnosing sleep disorders such as insomnia, sleep apnea syndrome and various sleep disorders. Sleep quality and architecture are assessed by monitoring brain electrical activity during sleep.

Brain-computer interface: the electroencephalogram signal acquisition system of the embodiment is a key component of brain-computer interface (BCI) technology. BCI allows people to use brain electrical signals to control external devices such as computers, wheelchairs, prostheses and communication devices, and is of great importance to disabled people.

Psychological study: the electroencephalogram signal acquisition system of the present embodiment uses the electroencephalogram signal acquisition system in psychological study to study psychological processes such as emotion, attention, learning, and memory.

Sports science: the electroencephalogram signal acquisition system of the embodiment can be used for researching motion control, coordination and kinematics, and is helpful for understanding how the brain regulates and controls muscle activities.

Emotion recognition: based on the electroencephalogram signal acquisition system of the present embodiment, the EEG is used to detect and identify the emotional state of a person, such as anxiety, excitement, fatigue, and the like. This has applications in advertising, user experience research, and emotion recognition technology.

Cognitive neuroscience: based on the electroencephalogram signal acquisition system of the embodiment, how the brain processes information, makes decisions and executes cognitive tasks can be explored. This is important for understanding learning, memory and decision making processes.

The basic process of the electroencephalogram signal acquisition system of the embodiment for acquiring the electroencephalogram signal is as follows:

1. preparation: some preparation work is required before the acquisition of an electroencephalogram signal is started. This includes washing the scalp of the subject to remove dirt, grease and keratin from the scalp to ensure good contact of the electrodes. If the hair is too long, it may be necessary to cut the hair short or to use conductive glue to hold the electrodes tightly.

2. Placing an electrode: the electrodes are placed on the scalp of the subject. The electrodes are brought into close contact with the scalp by means of electrically conductive gel (a conductive gel or paste substance) to ensure good electrical signal transmission.

3. Electrode layout: the layout of the electrodes may vary according to experimental or clinical needs. Typically, a set of electrode arrays is used to cover different areas of the scalp to record activity in a particular brain region.

4. Reference electrode: in electroencephalogram acquisition, one or more reference electrodes are selected for relatively measuring the activity of an electroencephalogram. The reference electrode is typically placed on the scalp, away from the brain, for measurements with respect to the other electrodes.

5. Signal amplification and filtering: the raw signal acquired is typically very weak and requires amplification by an amplifier, while the signal may be filtered to remove some unwanted frequency components such as muscle movement or power disturbances.

6. Data acquisition and recording: the amplified signal is digitized and recorded by a computer. Data acquisition is typically performed at a sampling rate of hundreds of times per second.

7. Experiments or tasks are performed: during signal acquisition, the subject may need to perform a particular experiment or task in order to record the brain electrical activity under a particular condition.

8. Data processing and analysis: the acquired brain electrical data may be subjected to subsequent data processing and analysis, including denoising, feature extraction, event correlation analysis, etc., to extract useful information therefrom.

In general, the electroencephalogram signal acquisition system of the embodiment can be interactively applied in the fields of research, medical treatment, technology and psychology, and can intelligently schedule electroencephalogram signal data required by different researchers in real time. Is helpful for understanding brain function, improving medical diagnosis and treatment, developing brain-computer interface technology, improving user experience and emotion recognition, and providing important brain activity information for researchers and medical professionals.

The foregoing is merely a preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily conceivable by those skilled in the art within the technical scope of the present application should be covered in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. An electroencephalogram signal acquisition system, characterized by comprising:

2. The electroencephalogram signal acquisition system according to claim 1, wherein,

the brain electrode comprises a collecting electrode and a reference electrode;

the acquisition electrode is used for measuring brain electrical signals;

3. The electroencephalogram signal acquisition system according to claim 2, wherein,

the collecting electrode comprises an electrode main body, an electrode head, a connecting wire and a connector;

4. The electroencephalogram signal acquisition system according to claim 1, wherein,

the brain electrode also comprises a fixing device, conductive adhesive and a marking unit;

5. The electroencephalogram signal acquisition system according to claim 1, wherein,

the electrode types of the brain electrode comprise surface electrodes, depth electrodes, cerebral cortex electrodes, intracranial electrodes, brain stem electrodes, eye electrodes, muscle electrodes and heart electrodes;

6. The electroencephalogram signal acquisition system according to claim 1, wherein,

the amplifier comprises a pre-amplifier and a main amplifier;

7. The electroencephalogram signal acquisition system according to claim 1, wherein,

the conversion module comprises a filter and an analog-to-digital converter;

8. The electroencephalogram signal acquisition system according to claim 1, wherein,

9. The electroencephalogram signal acquisition system according to claim 1, wherein,

the storage module comprises a storage unit, a classification unit and a safety management unit;

10. The electroencephalogram signal acquisition system according to claim 9, wherein,