System for collecting electroencephalogram signals

Abstract

The utility model provides a system for collecting electroencephalogram signals, which relates to the technical field of electroencephalogram signal collection, and can improve signal range adaptability by arranging a preprocessing module at the front end of a filtering module, so that the signal can be better processed during filtering, and the filtering effect can be enhanced. According to the invention, offset or distortion caused by a direct current component in the filtering process is reduced, the calculated amount can be reduced, the filtering effect is improved, the response time is shortened, and the external power supply is detected in real time by arranging the power supply acquisition module. And the mains supply frequency is sent to the frequency adjustment unit to adjust the center frequency of the digital notch filter, so that the filtering module can better carry out notch filtering on the electroencephalogram signal when the mains supply frequency fluctuates, the influence of power grid fluctuation on the electroencephalogram signal is reduced, and the effect of improving the detection precision is achieved.

Description

Technical Field

[0001] The utility model relates to the technical field of electroencephalogram signal collection, in particular to a system for collecting electroencephalogram signals. Background Art

[0002] In the process of EEG signal collection, since human EEG signals are relatively weak and easily buried in various interference signals around the human body, multiple filtering operations are usually required to obtain separated EEG signals. The filtering effect is closely related to the quality of the EEG signals. Among various interference signals, power supply interference accounts for a considerable proportion. In the prior art, a notch filter is usually used to eliminate power supply interference. Since the mains frequency is generally 50Hz, the center frequency of the notch filter is also usually set to 50Hz. However, when the mains frequency fluctuates, the filtering effect of the notch filter will be reduced, causing greater interference to the collected EEG signals.

[0003] For example, Chinese patent publication No. CN212546961 discloses an EEG signal acquisition device that is resistant to external electromagnetic pulse interference. The device shields external electromagnetic pulse interference by providing a shielding driver and a shielding cover. Although this device can reduce external noise interference, it still cannot reduce internal interference caused by grid fluctuations, which is more obvious in areas where wind power and solar energy account for a high proportion, making it less applicable.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Utility Model Content

[0005] The purpose of the utility model is to provide a system for collecting electroencephalogram signals to solve the problems raised in the above-mentioned background technology.

[0006] In order to achieve the above purpose, the utility model provides the following technical solutions:

[0007] A system for collecting EEG signals, comprising a signal collection module, a power collection module, a preprocessing module, a filtering module, and a data analysis module;

[0008] The signal acquisition module includes an EEG cap and EEG acquisition electrodes, wherein the EEG cap is used to fix the EEG acquisition electrodes, and the EEG acquisition electrodes are electrically connected to the preprocessing module to collect EEG signals of the human body and send them to the preprocessing module;

[0009] The preprocessing module includes a signal amplifying unit and a data processing unit. The signal amplifying unit is electrically connected to the data processing unit and is used to amplify the EEG signal and send it to the data processing unit. The data processing unit is communicatively connected to the filtering module and is used to preprocess the amplified EEG signal to eliminate its DC component and baseline drift.

[0010] The power acquisition module is communicatively connected with the filter module and is used to acquire the mains frequency and mains voltage of the external power supply;

[0011] The filtering module includes a notch filter unit and a frequency adjustment unit. The notch filter unit is electrically connected to the data analysis module and is used to filter the preprocessed EEG signal and send the filtered EEG signal to the data analysis module for analysis. The frequency adjustment unit is communicatively connected to the power acquisition module and is used to adjust the center frequency of the notch filter unit according to the mains frequency.

[0012] The data analysis module includes a feature extraction unit and a signal analysis unit. The feature extraction unit is used to extract features from the filtered EEG signal, and the signal analysis unit is used to perform signal analysis on the extracted features.

[0013] Preferably, the data processing unit is provided with digital signal processing software, and the amplified EEG signal is preprocessed by de-averaging.

[0014] Preferably, the EEG signal acquisition system further includes a power supply module, which is used to connect to an external power supply and supply power to the entire EEG signal acquisition system, and the power acquisition module is arranged between the external power supply and the power supply module.

[0015] Preferably, the filtering module further includes a bandpass filtering unit, a low-pass filtering unit, and a high-pass filtering unit, which are used to highlight the target frequency band and reduce the influence of high-frequency noise and low-frequency noise.

[0016] Preferably, the system for collecting EEG signals further comprises an alarm module, which is communicatively connected to the signal analysis unit and is used for issuing an audible and visual alarm according to the analysis result of the signal analysis.

[0017] Preferably, the EEG collection electrode is a flexible electrode.

[0018] Compared with the prior art, the beneficial effects of the utility model are:

[0019] The utility model can improve the adaptability of the signal range by arranging a preprocessing module at the front end of the filtering module, so that it can be better processed during filtering, and can also enhance the filtering effect, reduce the offset or distortion caused by the DC component in the filtering process, and at the same time reduce the amount of calculation, thereby improving the filtering effect and reducing the response time. At the same time, by arranging a power acquisition module to perform real-time detection of the external power supply, and sending the AC power frequency to the frequency adjustment unit to adjust the center frequency of the digital notch filter, the filtering module can better perform notch filtering on the EEG signal when the AC power frequency fluctuates, reduce the impact of power grid fluctuations on the EEG signal, and improve the detection accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a schematic diagram of the module structure of the utility model;

[0021] Figure 2 This is a schematic diagram of the structure of the filter module of the utility model;

[0022] Figure 3 This is a connection diagram of the external power supply, power supply module and power acquisition module of the utility model. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0024] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0025] Example:

[0026] See also Figure 1 to Figure 3 , the utility model provides a technical solution:

[0027] A system for collecting electroencephalogram signals comprises a signal collection module, a power collection module, a preprocessing module, a filtering module and a data analysis module.

[0028] The signal acquisition module includes an EEG cap and EEG acquisition electrodes. The EEG cap is used to fix the EEG acquisition electrodes. The EEG acquisition electrodes are flexible electrodes, which are electrically connected to the preprocessing module through signal lines and are used to collect human EEG signals and send them to the preprocessing module. A shielding layer is provided on the outside of the EEG acquisition electrodes and the signal lines.

[0029] The preprocessing module includes a signal amplification unit and a data processing unit. The signal amplification unit is a signal amplifier for amplifying and processing the EEG signal and sending it to the data processing unit. The data processing unit is a digital integrated chip. In this embodiment, a microprocessor of the STM32F103 series can be used. The two are electrically connected. The data processing unit usually uses a PC computer for processing because it has a large amount of computational data. It is internally provided with digital signal processing software and is connected to the filter module for communication, which is used to preprocess the amplified EEG signal to eliminate its DC component and baseline drift. In this step, the digital signal processing software can use MATLAB, NumPy or SciPy libraries in Python, etc. These tools provide functions and tools that can de-mean the amplified EEG signal to reduce the DC component and baseline drift in the signal.

[0030] The preprocessing module is set at the front end of the filtering module for three reasons:

[0031] One is signal range adaptability: removing the DC component can adjust the range of the signal, making it easier to process before filtering. For example, if the DC component is large, the filter may need to adjust its gain to adapt to the range of the signal, while removing the DC component can make the signal range closer to the desired range.

[0032] The second is the filtering effect: removing the DC component can reduce the potential error in the filtering process. If there is a DC component in the signal and it is not removed before filtering, the filter may introduce some additional offset or distortion in the filtering process.

[0033] The third is to reduce the amount of calculation: removing the DC component before filtering can reduce the amount of calculation. If the DC component in the signal is large, then when filtering, the filter needs to handle a larger amplitude range, which may require more computing resources, making it more difficult to adjust the filter and taking longer to respond.

[0034] The system for collecting EEG signals also includes a power supply module, which is an integrated power supply for connecting an external power supply and powering the entire EEG signal collection system. The power acquisition module is a digital electric meter, which is arranged between the external power supply and the power supply module. The power acquisition module is communicatively connected to the filter module, and is used to collect the AC frequency and AC voltage of the external power supply.

[0035] The filtering module includes a notch filter unit and a frequency adjustment unit. The notch filter unit is a digital notch filter. The frequency adjustment unit is used to control the digital notch filter. The digital notch filter is electrically connected to the data analysis module, and is used to filter the preprocessed EEG signal and send the filtered EEG signal to the data analysis module for analysis. The frequency adjustment unit is communicatively connected to the power acquisition module, and is used to adjust the center frequency of the notch filter unit according to the mains frequency.

[0036] The filtering module also includes a bandpass filtering unit, a low-pass filtering unit, and a high-pass filtering unit, which are used to highlight the target frequency band and reduce the influence of high-frequency noise and low-frequency noise. Bandpass filtering is used to highlight the frequency components of interest to the user, such as alpha waves and beta waves in EEG signals. Commonly used frequency bands include alpha waves of 8-12Hz, beta waves of 12-30Hz, etc. Bandpass filtering can be achieved by using a digital filter (such as a Butterworth filter). Low-pass filtering is used to remove high-frequency noise and unnecessary high-frequency components, such as high-frequency noise caused by muscle movement. Commonly used low-pass filtering cutoff frequencies are usually between 30-50Hz. High-pass filtering is used to remove low-frequency noise and slow drift components, such as interference from breathing and heartbeat. Commonly used high-pass filtering cutoff frequencies are usually between 0.1-1Hz.

[0037] It can be seen that since the human body's EEG signals are relatively weak and easily interfered by other signals, multiple filtering operations targeting different targets are required. Preprocessing the EEG signals before filtering can improve the filtering effect and reduce the response time.

[0038] Among the noise sources of EEG signals, power supply interference is one of the most important ones, and a notch filter is needed to eliminate noise of a specific frequency. Since the mains frequency in my country is generally 50Hz, when designing the circuit, the center frequency of the notch filter is usually set to 50Hz to eliminate power supply interference. However, in some special cases, such as grid load fluctuations, power system failures, and renewable energy fluctuations, the mains frequency may also fluctuate, resulting in reduced filtering effect of the notch filter and greater interference to the collected EEG signals. Especially in areas where renewable energy accounts for a high proportion, sudden changes in wind speed or solar radiation may cause power fluctuations of wind turbines or solar power generation systems connected to the grid, thereby affecting the frequency of the mains. Therefore, by using the power acquisition module to detect the external power supply in real time and sending the mains frequency to the frequency adjustment unit, the center frequency of the digital notch filter is adjusted, which can better notch filter the EEG signal when the mains frequency fluctuates, reduce the impact of grid fluctuations on the EEG signal, and improve the detection accuracy.

[0039] The data analysis module includes a feature extraction unit and a signal analysis unit. The feature extraction unit is used to perform feature extraction on the filtered EEG signal, and the feature extraction includes time domain feature extraction, frequency domain feature extraction, spatial domain feature extraction, and complexity feature extraction. The signal analysis unit is used to perform signal analysis on the extracted features to compare the differences in EEG signals under different conditions, or to verify hypotheses, so as to explore whether the corresponding brain area has lesions and the extent of the lesions based on user experience and relevant medical knowledge.

[0040] The system for collecting EEG signals also includes an alarm module, which is communicatively connected to the signal analysis unit and is used to issue an audible and visual alarm according to the analysis results of the signal analysis. In this embodiment, the alarm module is implemented by a buzzer plus multiple groups of alarm lights. The alarm lights can be set to three groups of green, orange, and red to reflect the pathological conditions of the brain area. If there is no lesion, the green light will be on, if there is a slight lesion, the orange light will be on, the buzzer will sound intermittently, and if there is a severe lesion, the red light will be on, and the buzzer will sound for a long time to provide an obvious warning signal.

[0041] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0042] The above-mentioned embodiments only express several implementation methods of the utility model, and the description is relatively specific and detailed, but it cannot be understood as limiting the scope of the utility model patent. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the utility model, which all belong to the protection scope of the utility model. Therefore, the protection scope of the utility model patent shall be based on the attached claims.

Claims

1. A system for collecting electroencephalogram signals, characterized in that: It includes signal acquisition module, power acquisition module, pre-processing module, filtering module and data analysis module; The signal acquisition module includes an EEG cap and EEG acquisition electrodes, wherein the EEG cap is used to fix the EEG acquisition electrodes, and the EEG acquisition electrodes are electrically connected to the preprocessing module to collect EEG signals of the human body and send them to the preprocessing module; The preprocessing module includes a signal amplifying unit and a data processing unit. The signal amplifying unit is electrically connected to the data processing unit and is used to amplify the EEG signal and send it to the data processing unit. The data processing unit is communicatively connected to the filtering module and is used to preprocess the amplified EEG signal to eliminate its DC component and baseline drift. The power acquisition module is communicatively connected with the filter module and is used to acquire the mains frequency and mains voltage of the external power supply; The filtering module includes a notch filter unit and a frequency adjustment unit. The notch filter unit is electrically connected to the data analysis module and is used to filter the preprocessed EEG signal and send the filtered EEG signal to the data analysis module for analysis. The frequency adjustment unit is communicatively connected to the power acquisition module and is used to adjust the center frequency of the notch filter unit according to the mains frequency. The data analysis module includes a feature extraction unit and a signal analysis unit. The feature extraction unit is used to extract features from the filtered EEG signal, and the signal analysis unit is used to perform signal analysis on the extracted features.

2. A system for collecting electroencephalogram signals according to claim 1, characterized in that: The data processing unit is provided with digital signal processing software, and the amplified EEG signal is preprocessed by de-averaging.

3. The system for collecting electroencephalogram signals according to claim 1, characterized in that: The EEG signal acquisition system also includes a power supply module, which is used to connect to an external power supply and supply power to the entire EEG signal acquisition system. The power acquisition module is arranged between the external power supply and the power supply module.

4. The system for collecting EEG signals according to claim 1, characterized in that: The filtering module also includes a bandpass filtering unit, a low-pass filtering unit, and a high-pass filtering unit, which are used to highlight the target frequency band and reduce the influence of high-frequency noise and low-frequency noise.

5. The system for collecting EEG signals according to claim 1, characterized in that: The system for collecting EEG signals also includes an alarm module, which is communicatively connected to the signal analysis unit and is used to issue an audible and visual alarm according to the analysis results of the signal analysis.

6. The system for collecting EEG signals according to claim 1, characterized in that: The EEG collection electrodes are flexible electrodes.

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