Electroencephalogram signal acquisition control method and device, human factor intelligent control method and system based on brain-computer interface, edge computing equipment and medium

Abstract

The invention discloses an electroencephalogram signal acquisition control method and device, a human factor intelligent control method and system based on a brain-computer interface, edge computing equipment and a medium. Acquiring current wearing parameters between the electroencephalogram signal acquisition electrode and the testee; on the basis of the current wearing parameters, determining the comfort degree of wearing the electroencephalogram signal acquisition electrode by the testee; based on the comfort level, the electroencephalogram signal acquisition electrode is controlled to move so as to adjust the wearing tightness of the electroencephalogram signal acquisition electrode. And controlling the controlled terminal to execute the target operation based on the collected electroencephalogram signal.

Description

Technical Field

[0001] The present invention relates to technical fields such as human factors engineering and brain-computer interface, and in particular to a method and device for controlling electroencephalogram (EEG) signal acquisition, a human factors intelligent control method and system based on brain-computer interface, and edge computing equipment and media. Background Art

[0002] Brain Computer Interface (BCI) is a revolutionary human-computer interaction technology. Its mechanism of action is to bypass peripheral nerves and muscles and directly establish a new communication and control channel between the brain and external devices. It can capture brain signals and convert them into electrical signals to achieve information transmission and control. When studying EEG signals, it is usually necessary to wear an EEG cap to obtain EEG data, analyze the acquired EEG information, extract relevant instructions, and control the controlled terminal.

[0003] When the subjects of the related technology wear the EEG cap, they do not consider that the comfort of wearing the EEG cap will affect the psychological state of the subjects and the changes in thermal sensation, so that the EEG information collected by the EEG cap cannot accurately reflect the EEG activity of the subjects in the natural state, thereby affecting the control effect of the controlled terminal. Summary of the invention

[0004] The embodiments of the present invention are intended to solve at least one of the technical problems in the related art to a certain extent. To this end, one object of the present invention is to propose a method and device for controlling EEG signal acquisition, a human factors intelligent control method and system based on brain-computer interface, and an edge computing device and medium.

[0005] An embodiment of the present invention provides an EEG signal acquisition control method, which includes: in the process of acquiring the EEG signal of the subject through the EEG signal acquisition electrode, obtaining the current wearing parameters between the EEG signal acquisition electrode and the subject; based on the current wearing parameters, determining the comfort of the subject wearing the EEG signal acquisition electrode; based on the comfort, controlling the movement of the EEG signal acquisition electrode to adjust the wearing tightness of the EEG signal acquisition electrode.

[0006] Exemplarily, based on current wearing parameters, determining the comfort level of the subject wearing the EEG signal collection electrodes includes: based on current wearing parameters and feedback data from the subject, determining the comfort level of the subject wearing the EEG signal collection electrodes.

[0007] Exemplarily, the feedback data includes the historical wearing time when the subject's comfort level when wearing the EEG signal acquisition electrodes is lower than a preset comfort level, and the current wearing parameters include the current wearing time and the current somatosensory parameters; based on the current wearing parameters and the subject's feedback data, the comfort level of the subject wearing the EEG signal acquisition electrodes is determined, including: determining the consistency parameters of the current wearing time and the historical wearing time; using the consistency parameters as a reference, determining the comfort level of the subject wearing the EEG signal acquisition electrodes based on the current somatosensory parameters.

[0008] Exemplarily, based on the comfort level, the movement of the EEG signal acquisition electrodes is controlled, including: when the comfort level is lower than a preset comfort level, the movement of the EEG signal acquisition electrodes is controlled with reference to preset wearing parameters so that the wearing parameters between the EEG signal acquisition electrodes and the subject are the preset wearing parameters.

[0009] Exemplarily, the current wearing parameters include pressure parameters; controlling the movement of the EEG signal acquisition electrodes includes: controlling the movement of the EEG signal acquisition electrodes with reference to the real-time wearing parameters, wherein the real-time wearing parameters include real-time pressure parameters, so that the change trend of the real-time pressure parameters in the process of controlling the movement of the EEG signal acquisition electrodes is a preset trend, and the preset trend includes pressure decreasing, increasing, and decreasing in sequence.

[0010] Exemplarily, the EEG signal acquisition control method further includes: acquiring the EEG signal of the subject through the EEG signal acquisition electrode when the updated wearing parameters between the EEG signal acquisition electrode and the subject meet preset conditions.

[0011] Another embodiment of the present invention provides an EEG signal acquisition method, which includes: in the process of acquiring the EEG signal of the subject through the EEG signal acquisition electrodes, obtaining the current wearing parameters between the EEG signal acquisition electrodes and the subject; based on the current wearing parameters, determining the comfort of the subject wearing the EEG signal acquisition electrodes; based on the comfort, controlling the movement of the EEG signal acquisition electrodes to adjust the wearing tightness of the EEG signal acquisition electrodes; when the updated wearing parameters between the EEG signal acquisition electrodes and the subject meet preset conditions, acquiring the EEG signal of the subject through the EEG signal acquisition electrodes.

[0012] Another embodiment of the present invention provides a human factors intelligent control method based on brain-computer interface, and the human factors intelligent control method based on brain-computer interface includes: in the process of collecting EEG signals of the subject through EEG signal collection electrodes, using the above-mentioned EEG signal collection control method to collect EEG signals; based on the collected EEG signals, controlling the controlled terminal to perform the target operation.

[0013] Another embodiment of the present invention provides an EEG signal acquisition control device, which includes: an EEG signal acquisition electrode, configured to collect the EEG signal of the subject; a driving device, connected to the EEG signal acquisition electrode, configured to drive the EEG signal acquisition electrode to move; a sensor, configured to obtain current wearing parameters between the EEG signal acquisition electrode and the subject during the process of collecting the EEG signal of the subject through the EEG signal acquisition electrode; a data processing unit, configured to determine the comfort of the subject wearing the EEG signal acquisition electrode based on the current wearing parameters, and based on the comfort, control the driving device to drive the EEG signal acquisition electrode to move so as to adjust the wearing tightness of the EEG signal acquisition electrode.

[0014] Exemplarily, the sensor is integrated into the EEG signal acquisition electrode, and the sensor includes at least one of a pressure sensor and a temperature sensor.

[0015] Exemplarily, the EEG signal acquisition control device also includes a collector, an EEG signal data cable, a wearing parameter data cable, and a driving data cable, wherein the EEG signal data cable connects the collector and the EEG signal acquisition electrode, the wearing parameter data cable connects the sensor and the collector, and the driving data cable connects the driving device and the collector.

[0016] Exemplarily, the EEG signal acquisition electrodes, the driving device, and the sensor are integrated into a wearable device.

[0017] Another embodiment of the present invention provides an EEG signal acquisition system, which includes: an EEG signal acquisition electrode, configured to collect EEG signals of a subject; a driving device, connected to the EEG signal acquisition electrode, configured to drive the EEG signal acquisition electrode to move; a sensor, configured to obtain current wearing parameters between the EEG signal acquisition electrode and the subject during the process of collecting the EEG signals of the subject through the EEG signal acquisition electrode; a data processing unit, configured to determine the comfort of the subject wearing the EEG signal acquisition electrode based on the current wearing parameters, and based on the comfort, control the driving device to drive the EEG signal acquisition electrode to move to adjust the wearing tightness of the EEG signal acquisition electrode, and control the EEG signal acquisition electrode to collect the EEG signal of the subject when the updated wearing parameters between the EEG signal acquisition electrode and the subject meet preset conditions.

[0018] Another embodiment of the present invention provides a human factors intelligent control system based on brain-computer interface, and the human factors intelligent control system based on brain-computer interface includes: any of the above-mentioned EEG signal acquisition and control devices; a controlled terminal, configured to receive control instructions and perform target operations based on the control instructions; an EEG interface control unit, used to generate control instructions for controlling the controlled terminal based on the collected EEG signals.

[0019] Another embodiment of the present invention provides an edge computing device, including a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the method of any of the above-mentioned embodiments when executing the computer program; and / or, the edge computing device includes any of the above-mentioned EEG signal acquisition and control devices or human factors intelligent control systems based on brain-computer interfaces.

[0020] Another embodiment of the present invention provides a program product, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method of any of the above embodiments are implemented.

[0021] An embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method of any one of the above embodiments are implemented.

[0022] In the above implementation, the EEG signal acquisition control method includes: in the process of acquiring the EEG signal of the subject through the EEG signal acquisition electrode, obtaining the current wearing parameters between the EEG signal acquisition electrode and the subject; based on the current wearing parameters, determining the comfort of the subject wearing the EEG signal acquisition electrode; based on the comfort, controlling the movement of the EEG signal acquisition electrode to adjust the wearing tightness of the EEG signal acquisition electrode. The above method determines the comfort of the subject wearing the EEG signal acquisition electrode by acquiring the current wearing parameters between the EEG signal acquisition electrode and the subject, thereby controlling the movement of the EEG signal acquisition electrode to adjust the wearing tightness of the EEG signal acquisition electrode. The method intelligently adjusts the tightness of the electrode cap according to the actual acquired wearing parameters, which can reduce the discomfort caused by the subject wearing the EEG collector for a long time, and can be applied to any experimental environment that requires long-term wearing, thereby improving the signal quality of the collected EEG.

[0023] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flow chart of the EEG signal acquisition control method provided by an embodiment of the present invention;

[0025] Figure 2 A flow chart of an electroencephalogram signal acquisition method provided by another embodiment of the present invention;

[0026] Figure 3 A flow chart of a human factors intelligent control method based on a brain-computer interface provided by another embodiment of the present invention;

[0027] Figure 4 A schematic diagram of the structure of an electroencephalogram signal acquisition control device provided in another embodiment of the present invention;

[0028] Figure 5 A schematic diagram of the structure of an electroencephalogram signal acquisition control device provided in another embodiment of the present invention;

[0029] Figure 6 A schematic diagram of the structure of a human factors intelligent control system based on a brain-computer interface provided by another embodiment of the present invention;

[0030] Figure 7 A block diagram of an electroencephalogram signal acquisition control device provided in another embodiment of the present invention;

[0031] Figure 8 A block diagram of an electroencephalogram signal acquisition device provided in another embodiment of the present invention;

[0032] Fig. 9 A block diagram of a human factors intelligent control device based on a brain-computer interface provided by another embodiment of the present invention;

[0033] Fig.10 A block diagram of an edge computing device provided for another embodiment of the present invention. DETAILED DESCRIPTION

[0034] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0035] Brain Computer Interface (BCI) is a revolutionary human-computer interaction technology. Its mechanism of action is to bypass peripheral nerves and muscles and directly establish a new communication and control channel between the brain and external devices. It can capture brain signals and convert them into electrical signals to achieve information transmission and control. When studying EEG signals, it is usually necessary to wear an EEG cap to obtain EEG data, analyze the acquired EEG information, extract relevant instructions, and control the controlled terminal.

[0036] Related technology When the subjects wore the EEG cap, they did not consider that the comfort of wearing the EEG cap would affect the psychological state of the subjects and the change of thermal sensation. For example, wearing an uncomfortable EEG cap would cause the subjects to feel uncomfortable or anxious. This change of psychological state may affect the activity pattern of the brain, thereby affecting the EEG signal. Or the discomfort may increase the alertness or stress response of the brain, which may be reflected in the EEG waves, such as increasing the activity of beta waves; in addition, the EEG cap will affect the thermal sensation of the subjects, especially when conducting thermal comfort research. If the EEG cap causes the subjects to feel overheated or too cold, this change in thermal sensation may affect the EEG signal, because thermal comfort is correlated with the relative power of the EEG band. Studies have shown that in a hotter environment, the relative power of the delta band will increase, while in a more comfortable environment, the relative power of the alpha band will be higher. The above-mentioned effects that may be caused by the discomfort of wearing the EEG cap may eventually lead to deviations in the experimental results. An uncomfortable EEG cap may cause the experimental data to fail to accurately reflect the EEG activity of the subjects in a natural state, thereby affecting the validity and reliability of the experimental results. Therefore, ensuring the comfort of the EEG cap is crucial to obtaining accurate and reliable EEG signal measurements.

[0037] Classification of EEG signals: Delta wave, with a frequency range of 0.5-4Hz. It usually appears in the deep sleep stage, that is, the slow wave sleep period. For example, infants will have more Delta wave activity during sleep. This brain wave has a higher amplitude and is a slow wave rhythm, which means that the brain is in a deep state of relaxation or unconsciousness. Theta wave, with a frequency between 4-8Hz. It is common in childhood and also appears in meditation or light sleep stages of adults. For example, when a person is having a relaxing daydream or is in a state of half-sleep, theta waves may be recorded on the EEG. It reflects a state of the brain that is relatively relaxed but still has certain conscious activities. Alpha wave, with a frequency range of 8-13Hz. When a person is in a quiet, closed-eye, relaxed state, alpha waves dominate the EEG signals. For example, when you close your eyes and rest in a quiet environment, your brain will produce more obvious alpha waves. This type of brain wave indicates that the brain is in a relatively quiet, awake but not in a state of intense thinking. It is a typical rhythm of the brain when it is resting. Beta wave, with a frequency of about 13-30Hz. It is related to the brain's active thinking, concentration, and mental tension. For example, when you are solving a complex math problem or engaging in a heated debate, the brain will produce a large number of beta waves, which indicates that the brain is in a highly active cognitive processing process. Gamma wave, with a frequency greater than 30Hz, is a high-frequency brain wave. It is usually related to the brain's advanced cognitive functions, such as information integration in perception, cognition, learning, and memory. For example, gamma waves may appear when the brain processes multiple sensory information at the same time and performs complex information processing.

[0038] To this end, an embodiment of the present invention provides an EEG signal acquisition control method, which determines the comfort of the subject wearing the EEG signal acquisition electrode by acquiring the current wearing parameters between the EEG signal acquisition electrode and the subject, thereby controlling the movement of the EEG signal acquisition electrode to adjust the wearing tightness of the EEG signal acquisition electrode. This method intelligently adjusts the tightness of the electrode cap according to the actually acquired wearing parameters, which can reduce the discomfort caused by the subject wearing the EEG collector for a long time. It can be applicable to any experimental environment that requires long-term wearing, and improves the signal quality of the collected EEG.

[0039] Figure 1 This is a flow chart of the EEG signal acquisition control method provided in an embodiment of the present invention.

[0040] like Figure 1 As shown, the EEG signal acquisition control method 100 includes steps S110 to S130.

[0041] Step S110, in the process of collecting the EEG signal of the subject through the EEG signal collecting electrode, obtaining the current wearing parameters between the EEG signal collecting electrode and the subject.

[0042] Exemplarily, in addition to electroencephalography (EEG) signals, the acquisition control of other signals may also be applicable to the method of an embodiment of the present invention. Other signals may include, for example, electrodermal activity (EDA), pulse signals (Photoplethysmographic, PPG), functional near-infrared spectroscopy (FNIRS), or nine-axis signals, such as accelerometer signals (ACC), gyroscope signals (GYRO), and magnetometer signals (MAG).

[0043] Step S120, based on the current wearing parameters, determining the comfort level of the subject wearing the EEG signal collection electrodes.

[0044] Exemplarily, the current wearing parameters include data such as the tightness, temperature, pressure, and wearing time of the EEG signal collection electrodes worn by the user, and the comfort of wearing the EEG signal collection electrodes includes data such as whether the tightness and temperature of the EEG signal collection electrodes are appropriate.

[0045] Step S130, based on the comfort level, controlling the movement of the EEG signal collection electrodes to adjust the wearing tightness of the EEG signal collection electrodes.

[0046] For example, the user provides feedback to the software based on the comfort of wearing the EEG signal collection electrodes, and the software issues control instructions to adjust the movement of the EEG signal collection electrodes, thereby changing the wearing tightness of the EEG signal collection electrodes. The software can be an artificial intelligence model loaded on a personal computer (PC), such as software AI (Artificial Intelligence).

[0047] In the above embodiment, the comfort level of the subject wearing the EEG signal acquisition electrode is determined by acquiring the current wearing parameters between the EEG signal acquisition electrode and the subject, thereby controlling the movement of the EEG signal acquisition electrode to adjust the wearing tightness of the EEG signal acquisition electrode. This method intelligently adjusts the tightness of the EEG signal acquisition electrode according to the actually acquired wearing parameters, which can reduce the discomfort caused by the subject wearing the electrode for a long time. It can be applied to any experimental environment that requires long-term wearing, and improves the signal quality of the collected EEG.

[0048] Based on the current wearing parameters, the comfort level of the subject wearing the EEG signal collection electrodes is determined, including: based on the current wearing parameters and the subject's feedback data, the comfort level of the subject wearing the EEG signal collection electrodes is determined.

[0049] Exemplarily, the feedback data includes the historical wearing time when the subject's comfort level when wearing the EEG signal acquisition electrodes is lower than a preset comfort level, and the current wearing parameters include the current wearing time and the current somatosensory parameters; based on the current wearing parameters and the subject's feedback data, the comfort level of the subject wearing the EEG signal acquisition electrodes is determined, including: determining the consistency parameters of the current wearing time and the historical wearing time; using the consistency parameters as a reference, determining the comfort level of the subject wearing the EEG signal acquisition electrodes based on the current somatosensory parameters.

[0050] For example, when the subject wears the EEG signal acquisition electrode and the comfort level is lower than the preset comfort level, the software system will feedback data, and the software system will record the wearing time to store multiple historical records. When the subject wears the EEG signal acquisition electrode, the software system will query the historical wearing time that is consistent with the current wearing time based on the current wearing time and the current somatosensory parameters (such as temperature and pressure), and determine the comfort level of the subject wearing the EEG signal acquisition electrode based on the current wearing parameters.

[0051] For example, when the subject felt uncomfortable wearing the EEG signal acquisition electrodes in the past (for example, the comfort level was lower than the preset comfort level), the subject could provide feedback on the wearing time (historical wearing time) of the EEG signal acquisition electrodes and the historical somatosensory temperature (temperature, pressure data, etc.) corresponding to the wearing time, and input the historical wearing time and temperature and pressure data into the AI ​​software to train the AI ​​model. When the subject wears the EEG signal acquisition electrodes again in the future, the current wearing time and the current somatosensory parameters are sent to the AI ​​software, and the AI ​​software predicts the current comfort level based on the current wearing time and the current somatosensory parameters. When the AI ​​software makes a comfort prediction, if the consistency parameters of the current wearing time and the historical wearing time indicate that the current wearing time and the historical wearing time are similar, it indicates that the probability of discomfort is high. Therefore, the probability of discomfort can be increased when further predicting comfort based on the current somatosensory parameters.

[0052] In the above embodiment, when determining the comfort level of the subject wearing the EEG signal collection electrodes, the subject's previous records are combined for analysis, and the comfort level analysis is combined with the current somatosensory parameters, which increases the reliability of the comfort level and provides the subject with a better wearing experience.

[0053] Based on the comfort level, the movement of the EEG signal collection electrodes is controlled, including: when the comfort level is lower than a preset comfort level, the movement of the EEG signal collection electrodes is controlled with reference to preset wearing parameters so that the wearing parameters between the EEG signal collection electrodes and the subject are the preset wearing parameters.

[0054] Exemplarily, the current wearing parameters include pressure parameters; controlling the movement of the EEG signal acquisition electrodes includes: controlling the movement of the EEG signal acquisition electrodes with reference to the real-time wearing parameters, wherein the real-time wearing parameters include real-time pressure parameters, so that the change trend of the real-time pressure parameters in the process of controlling the movement of the EEG signal acquisition electrodes is a preset trend, and the preset trend includes pressure decreasing, increasing, and decreasing in sequence.

[0055] For example, when the comfort level is lower than the preset comfort level, adjustments are made according to the preset wearing parameters based on the real-time wearing parameter data. When adjusting the pressure of the EEG signal collection electrode, adjustments are made according to the preset trend of decreasing, increasing, and decreasing the pressure in sequence.

[0056] In the above embodiment, when adjusting the pressure of the EEG signal acquisition electrode, periodic adjustments are performed according to a preset trend of pressure reduction, increase, and reduction in sequence, to avoid a one-time direct reduction or increase in pressure that causes excessive pressure changes and affects the EEG signal. This can reduce the impact of pressure changes on the EEG signal and improve the quality of EEG signal acquisition.

[0057] The EEG signal acquisition control method also includes: when the updated wearing parameters between the EEG signal acquisition electrode and the subject meet the preset conditions, the EEG signal of the subject is acquired through the EEG signal acquisition electrode.

[0058] Exemplarily, the preset conditions refer to performing a comfort analysis on the updated wearing parameters (such as pressure and temperature) between the EEG signal acquisition electrodes and the subject, and if the resulting comfort is higher than the preset comfort, the wearing parameters at this time meet the preset conditions.

[0059] Figure 2 This is a flow chart of an EEG signal acquisition method provided in another embodiment of the present invention.

[0060] like Figure 2 As shown, the EEG signal collection method 200 includes steps S210 to S240.

[0061] Step S210, in the process of collecting physiological signals of the subject through the EEG signal collection electrodes, obtaining current wearing parameters between the EEG signal collection electrodes and the subject.

[0062] Step S220, based on the current wearing parameters, determining the comfort level of the subject wearing the EEG signal collection electrodes.

[0063] Step S230: Based on the comfort level, the movement of the EEG signal collection electrode is controlled to adjust the wearing tightness of the EEG signal collection electrode.

[0064] Step S240, when the updated wearing parameters between the EEG signal collection electrode and the subject meet the preset conditions, the EEG signal of the subject is collected through the EEG signal collection electrode.

[0065] Exemplarily, the preset conditions refer to performing a comfort analysis on the updated wearing parameters (such as pressure and temperature) between the EEG signal acquisition electrodes and the subject, and if the resulting comfort is higher than the preset comfort, the wearing parameters at this time meet the preset conditions.

[0066] In the above embodiment, the comfort level of wearing the EEG signal acquisition electrode is obtained based on the wearing parameters, and the movement of the EEG signal acquisition electrode is controlled based on the comfort level. When the wearing parameters between the EEG signal acquisition electrode and the subject meet preset conditions, the EEG signal of the subject is collected, and the quality of the EEG acquisition signal is improved by intelligent adjustment of the wearing parameters.

[0067] In another example, for the wearing parameters between the EEG signal acquisition electrodes and the subject, the wearing parameters can be obtained in real time or at regular intervals for comfort judgment, or when the real-time acquired EEG signals fluctuate greatly (this indicates that the EEG signals may be inaccurate due to uncomfortable wearing), the wearing parameters can be obtained for comfort judgment. When the preset comfort level is not met, the drive adjustment is performed in time until the updated wearing parameters meet the preset comfort level. After the updated wearing parameters meet the preset comfort level, the EEG signal acquisition electrodes are used to collect the subject's updated (i.e., more accurate) EEG signals, so that the collected updated EEG signals are more accurate.

[0068] Figure 3 A flow chart of a human factors intelligent control method based on a brain-computer interface provided in another embodiment of the present invention.

[0069] like Figure 3 As shown, the human factors intelligent control method 300 based on brain-computer interface includes steps S310 to S320.

[0070] Step S310, collecting the EEG signals of the subject during the process of collecting the EEG signals of the subject through the EEG signal collecting electrodes.

[0071] Among them, any of the above-mentioned EEG signal acquisition control methods can be used to acquire the EEG signal of the subject.

[0072] Step S320: Based on the collected EEG signal, control the controlled terminal to perform the target operation.

[0073] Exemplarily, the controlled terminal includes, for example, a robotic arm, a drone, a car, etc. The control method may be to connect a wireless controller via USB, and control the controlled terminal via a wireless signal sent by the wireless controller.

[0074] In the above embodiment, the comfort of wearing the EEG signal acquisition electrode is obtained based on the wearing parameters, and the movement of the EEG signal acquisition electrode is controlled based on the comfort. When the wearing parameters between the EEG signal acquisition electrode and the subject meet the preset conditions, the EEG signal of the subject is collected, and based on the collected EEG signal, the controlled terminal is controlled to perform the target operation, and the quality of the EEG acquisition signal of the subject is improved, thereby improving the intelligent control effect based on BCI. And for the wearing parameters between the EEG signal acquisition electrode and the subject, the wearing parameters can be obtained in real time or at intervals for comfort judgment, or when the real-time collected EEG signal fluctuates greatly (this indicates that the EEG signal may be inaccurate due to uncomfortable wearing), the active wearing parameters are used for comfort judgment. When the preset comfort is not met, the drive adjustment is carried out in time until the updated wearing parameters meet the preset comfort. After the updated wearing parameters meet the preset comfort, the EEG signal of the subject after the update (i.e., more accurate) is collected through the EEG signal acquisition electrode, so that the collected updated EEG signal is more accurate, thereby achieving better control of the controlled terminal.

[0075] Figure 4 This is a schematic structural diagram of an EEG signal acquisition and control device provided in another embodiment of the present invention.

[0076] The EEG signal acquisition control device includes: an EEG signal acquisition electrode, which is configured to acquire the EEG signal of the subject; a driving device, which is connected to the EEG signal acquisition electrode and is configured to drive the EEG signal acquisition electrode to move; a sensor, which is configured to obtain the current wearing parameters between the EEG signal acquisition electrode and the subject during the process of acquiring the EEG signal of the subject through the EEG signal acquisition electrode; a data processing unit, which is configured to determine the comfort of the subject wearing the EEG signal acquisition electrode based on the current wearing parameters, and based on the comfort, control the driving device to drive the EEG signal acquisition electrode to move so as to adjust the wearing tightness of the EEG signal acquisition electrode.

[0077] For example, Figure 4 As shown, the EEG signal acquisition electrode includes the electrode in the figure, and the electrode contains a pressure sensor and a temperature sensor inside, which are used to collect the EEG signal of the subject and the current wearing parameters; the driving device includes the motor in the figure. Among them, the motor and the electrode are integrated in the electrode cap, and the subject needs to wear the electrode cap when using the EEG signal acquisition electrode to collect EEG signals.

[0078] The EEG signal acquisition control device also includes a collector, an EEG signal data line, a wearing parameter data line, and a driving data line, wherein the EEG signal data line connects the collector and the EEG signal acquisition electrode, the wearing parameter data line connects the sensor and the collector, and the driving data line connects the driving device and the collector. The sensor is integrated in the EEG signal acquisition electrode, and the sensor includes at least one of a pressure sensor and a temperature sensor.

[0079] For example, Figure 4 As shown in the figure, the G electrode connection line includes the right leg drive line, which is mainly used to shield some common mode interference from the front end of the hardware; the R electrode connection line is also the - line, which is the reference signal in the EEG data line; the + line is the single-conductor data line in the entire multi-conductor EEG signal, which is the data line that actually collects the signal. The EEG signal collection process collects the V+- voltage signal.

[0080] The right leg drive line is connected to the right leg drive circuit, which amplifies the common-mode signal collected from the electrode in an inverted manner and then feeds the inverted signal back to the human body through the right leg electrode (G electrode). In this way, the common-mode interference signal is offset or greatly weakened on the human body, thereby shielding the common-mode interference from the hardware front end and improving the quality of EEG signal collection.

[0081] Common mode interference is an interference signal that appears simultaneously on two electrodes (such as the reference electrode and the measurement electrode) of the signal input during the EEG signal acquisition process. The magnitude and phase of this interference signal are basically the same on the two electrodes, for example, the power frequency (50Hz or 60Hz) electromagnetic field generated by surrounding power equipment (such as power sockets, motors, etc.).

[0082] For example, Figure 4 The medium pressure and temperature data line includes a wearing parameter data line, which is used to connect the sensor inside the electrode and the collector. The drive data line includes a motor control line, which is used to connect the motor and the collector. The EEG signal data line includes an EEG data line, which is used to connect the EEG signal collection electrode and the collector. The collector obtains EEG signals by contacting the electrode with the scalp. The storage module inside the collector can temporarily store the collected EEG signal data. The amplifier in the collector can amplify these weak signals for subsequent processing and analysis. When the PC needs to process digital signals, the built-in analog-to-digital converter (ADC) of the collector can convert analog EEG signals into digital signals, and transmit the processed digital EEG signals to the PC through wired (such as USB, Ethernet and other interfaces) or wireless (such as Bluetooth, Wi-Fi, etc.) communication methods.

[0083] Figure 5This is a schematic structural diagram of an EEG signal acquisition and control device provided in another embodiment of the present invention.

[0084] like Figure 5 As shown, the EEG signal acquisition control device includes: an EEG signal acquisition electrode, which is configured to acquire the EEG signal of the subject; a driving device, which is connected to the EEG signal acquisition electrode and is configured to drive the EEG signal acquisition electrode to move; a sensor, which is configured to obtain the current wearing parameters between the EEG signal acquisition electrode and the subject in the process of acquiring the EEG signal of the subject through the EEG signal acquisition electrode; a data processing unit, which is configured to determine the comfort of the subject wearing the EEG signal acquisition electrode based on the current wearing parameters, and based on the comfort, control the driving device to drive the EEG signal acquisition electrode to move to adjust the wearing tightness of the EEG signal acquisition electrode, and control the EEG signal acquisition electrode to acquire the EEG signal of the subject when the updated wearing parameters between the EEG signal acquisition electrode and the subject meet the preset conditions. Among them, the EEG signal acquisition electrode, the driving device, and the sensor are integrated in the wearable device.

[0085] For example, Figure 5 As shown, the EEG signal acquisition electrodes, driving device, and sensor are integrated in the EEG cap (i.e., the wearable device), and the data processing unit includes Figure 5 The software AI is loaded on the PC. When the subjects are collecting EEG signal data, they wear the EEG cap to make the electrodes fully contact with the head skin, collect EEG signals through the EEG data line, and at the same time, the pressure and temperature data lines will also collect pressure and temperature data at a certain frequency. The frequency will be much lower than the frequency of the EEG signal, because these two signals are only for better control of the motor. Then the data is sent to the software AI on the PC wirelessly. The software AI analyzes the comfort of the subject through the temperature and pressure information of the contact surface between the electrode and the skin. If it is the same subject, the software AI will also store the subject's record information. The record information combined with the real-time temperature and pressure of the current experiment can more accurately analyze the comfort. Then the software AI obtains the appropriate control motor instructions based on the comfort and returns them to the EEG acquisition control end.

[0086] The whole control process will be slow, for example, the cycle of low pressure → high pressure → low pressure may take at least one minute, which can reduce the impact of pressure changes on EEG signals. Although slow changes will cause baseline drift, the pressure data is retained in the database, and the software can filter out the baseline in the EEG signal based on the pressure data afterwards.

[0087] Baseline drift refers to the phenomenon that the baseline of the EEG signal (i.e. the zero-level reference line of the signal) slowly deviates up and down, which is not caused by the characteristics of the EEG signal itself. Under normal circumstances, the EEG signal fluctuates with a relatively stable baseline as a reference, and baseline drift makes the entire signal waveform look like it is on a "moving platform".

[0088] Figure 6 A schematic diagram of the structure of a human factors intelligent control system based on a brain-computer interface provided in another embodiment of the present invention.

[0089] The human factors intelligent control system based on brain-computer interface includes: any of the above-mentioned EEG signal acquisition and control devices; a controlled terminal, configured to receive control instructions and perform target operations based on the control instructions; and a brain-computer interface control unit, used to generate control instructions for controlling the controlled terminal based on the acquired EEG signals.

[0090] For example, Figure 6 As shown, the data processing unit includes the system software (i.e., the software AI in the figure) loaded on the PC, and the communication between the software and the peripheral devices is realized through USB. The system software can analyze the EEG signal in real time, extract the instructions in the signal, and send the instructions to the controlled end through USB. The controlled end includes any device that can receive instructions, such as: a robotic arm, a drone, a car, etc. Figure 6 The controlled end includes the car.

[0091] In the embodiment of the present invention, the EEG collector can be used in any experimental environment that requires long-term wearing, and can reduce the discomfort caused by the subject wearing the EEG collector for a long time, thereby indirectly improving the signal quality of the EEG. In the application scenario of EEG control, while ensuring the signal quality, the acquisition system also helps to improve the subject's attention during the experiment, making EEG control more accurate.

[0092] Figure 7 This is a block diagram of an EEG signal acquisition control device provided in another embodiment of the present invention.

[0093] The embodiment of the present invention provides an electroencephalogram signal acquisition control device 700, see Figure 7 The EEG signal acquisition control device 700 includes: a first acquisition module 710 , a first determination module 720 , and a first control module 730 .

[0094] Exemplarily, the first acquisition module 710 is used to acquire current wearing parameters between the EEG signal acquisition electrodes and the subject during the process of acquiring the EEG signal of the subject through the EEG signal acquisition electrodes.

[0095] Exemplarily, the first determination module 720 is used to determine the comfort level of the subject wearing the EEG signal acquisition electrodes based on the current wearing parameters.

[0096] Exemplarily, the first control module 730 is used to control the movement of the EEG signal collection electrode based on the comfort level to adjust the wearing tightness of the EEG signal collection electrode.

[0097] It can be understood that for the specific description of the EEG signal acquisition control device 700, reference can be made to the description of the EEG signal acquisition control method above, which will not be repeated here.

[0098] Figure 8 This is a block diagram of an EEG signal acquisition device provided in another embodiment of the present invention.

[0099] The embodiment of the present invention provides an electroencephalogram signal acquisition device 800, see Figure 8 The EEG signal acquisition device 800 includes: a second acquisition module 810 , a second determination module 820 , a second control module 830 , and a first acquisition module 840 .

[0100] Exemplarily, the second acquisition module 810 is used to acquire current wearing parameters between the EEG signal acquisition electrodes and the subject during the process of acquiring the EEG signal of the subject through the EEG signal acquisition electrodes.

[0101] Exemplarily, the second determination module 820 is used to determine the comfort level of the subject wearing the EEG signal acquisition electrodes based on the current wearing parameters.

[0102] Exemplarily, the second control module 830 is used to control the movement of the EEG signal collection electrode based on the comfort level to adjust the wearing tightness of the EEG signal collection electrode.

[0103] Exemplarily, the first acquisition module 840 is used to acquire the EEG signal of the subject through the EEG signal acquisition electrode when the updated wearing parameters between the EEG signal acquisition electrode and the subject meet preset conditions.

[0104] It can be understood that for the specific description of the EEG signal acquisition device 800, reference can be made to the description of the EEG signal acquisition method above, which will not be repeated here.

[0105] Fig. 9 A block diagram of a human factors intelligent control device based on a brain-computer interface provided in another embodiment of the present invention.

[0106] The embodiment of the present invention provides a human factors intelligent control device 900 based on a brain-computer interface, see Fig. 9The human factors intelligent control device 900 based on brain-computer interface includes: a third acquisition module 910, a third determination module 920, a third control module 930, a second acquisition module 940, and a fourth control module 950.

[0107] Exemplarily, the third acquisition module 910 is used to acquire current wearing parameters between the EEG signal acquisition electrodes and the subject during the process of acquiring the EEG signal of the subject through the EEG signal acquisition electrodes.

[0108] Exemplarily, the third determination module 920 is used to determine the comfort level of the subject wearing the EEG signal acquisition electrodes based on the current wearing parameters.

[0109] Exemplarily, the third control module 930 is used to control the movement of the EEG signal collection electrode based on the comfort level to adjust the wearing tightness of the EEG signal collection electrode.

[0110] Exemplarily, the second acquisition module 940 is used to acquire the EEG signal of the subject through the EEG signal acquisition electrode when the updated wearing parameters between the EEG signal acquisition electrode and the subject meet preset conditions.

[0111] Exemplarily, the fourth control module 950 is used to control the controlled terminal to perform a target operation based on the collected EEG signal.

[0112] It can be understood that for the specific description of the human factors intelligent control device 900 based on brain-computer interface, reference can be made to the description of the human factors intelligent control method based on brain-computer interface in the above text, and no further details will be given here.

[0113] Fig.10 A block diagram of an edge computing device provided for another embodiment of the present invention.

[0114] like Fig.10 As shown, the edge computing device of this embodiment includes a processor 1001 and a memory 1002, wherein the memory 1002 stores programs or instructions that can be run on the processor 1001, and when the programs or instructions are executed by the processor 1001, the above-mentioned EEG signal acquisition control method is implemented, or the edge computing device can execute the above-mentioned EEG signal acquisition method, or the edge computing device can execute the above-mentioned human factors intelligent control method based on brain-computer interface, or the edge computing device integrates the above-mentioned EEG signal acquisition control device, or the edge computing device integrates the above-mentioned EEG signal acquisition system, or the edge computing device integrates the above-mentioned human factors intelligent control system based on brain-computer interface.

[0115] An embodiment of the present invention provides a program product on which a computer program is stored. When the computer program is executed by a processor, the steps of the method of any of the above embodiments are implemented.

[0116] An embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method of any one of the above embodiments are implemented.

[0117] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of the present invention, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0118] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0119] In the description of the present invention, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In the present invention, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0120] In the description of the present invention, it is to be understood that the terms “center”, “longitudinal”, “lateral”, “length”, “width”, “thickness”, “up”, “down”, “front”, “back”, “left”, “right”, “vertical”, “horizontal”, “top”, “bottom”, “inside”, “outside”, “clockwise”, “counterclockwise”, “axial”, “radial”, “circumferential”, etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0121] In addition, the terms "first", "second", etc. used in the embodiments of the present invention are only used for descriptive purposes and should not be understood as indicating or implying relative importance, or implicitly indicating the number of technical features indicated in the present embodiment. Therefore, the features defined by the terms "first", "second", etc. in the embodiments of the present invention can explicitly or implicitly indicate that the embodiment includes at least one of the features. In the description of the present invention, the word "multiple" means at least two or two or more, such as two, three, four, etc., unless otherwise clearly and specifically defined in the embodiments.

[0122] In the present invention, unless otherwise clearly specified or limited in the embodiments, the terms "installed", "connected", "connected" and "fixed" etc. in the embodiments should be understood in a broad sense. For example, the connection can be a fixed connection, a detachable connection, or an integrated connection. It can be understood that it can also be a mechanical connection, an electrical connection, etc.; of course, it can also be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal connection of two elements, or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific implementation situation.

[0123] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0124] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for collecting and controlling electroencephalogram signals, characterized in that: The method comprises: In the process of collecting the EEG signal of the subject through the EEG signal collecting electrode, obtaining the current wearing parameters between the EEG signal collecting electrode and the subject; Based on the current wearing parameters, determining the comfort level of the subject wearing the EEG signal collection electrodes; Based on the comfort level, the movement of the EEG signal collection electrode is controlled to adjust the wearing tightness of the EEG signal collection electrode.

2. The method according to claim 1, characterized in that Determining the comfort level of the subject wearing the EEG signal acquisition electrodes based on the current wearing parameters includes: determining the comfort level of the subject wearing the EEG signal acquisition electrodes based on the current wearing parameters and feedback data from the subject.

3. The method according to claim 2, characterized in that The feedback data includes a historical wearing time during which the subject's comfort level when wearing the electroencephalogram signal acquisition electrode is lower than a preset comfort level, and the current wearing parameters include a current wearing time and a current somatosensory parameter; and determining the comfort level of the subject wearing the electroencephalogram signal acquisition electrode based on the current wearing parameters and the subject's feedback data includes: Determine a consistency parameter between the current wearing time and the historical wearing time; The consistency parameter is used as a reference, and based on the current somatosensory parameter, the comfort level of the subject wearing the EEG signal collection electrode is determined.

4. The method according to any one of claims 1 to 3, characterized in that: The step of controlling the movement of the electroencephalogram signal acquisition electrode based on the comfort level includes: When the comfort level is lower than a preset comfort level, the movement of the EEG signal acquisition electrode is controlled with reference to the preset wearing parameters so that the wearing parameters between the EEG signal acquisition electrode and the subject are the preset wearing parameters.

5. The method according to any one of claims 1 to 3, characterized in that: The current wearing parameter includes a pressure parameter; and the controlling the movement of the EEG signal acquisition electrode includes: The movement of the EEG signal acquisition electrode is controlled with reference to the real-time wearing parameters, wherein the real-time wearing parameters include real-time pressure parameters, so that the change trend of the real-time pressure parameters in the process of controlling the movement of the EEG signal acquisition electrode is a preset trend, and the preset trend includes pressure decreasing, increasing, and decreasing in sequence.

6. The method according to any one of claims 1 to 3, characterized in that: The method further comprises: When the updated wearing parameters between the electroencephalogram signal collecting electrode and the subject meet the preset conditions, the electroencephalogram signal of the subject is collected through the electroencephalogram signal collecting electrode.

7. A human factors intelligent control method based on brain-computer interface, characterized in that: The method comprises: In the process of collecting the EEG signals of the subject through the EEG signal collection electrodes, the EEG signals are collected by using the EEG signal collection control method as described in any one of claims 1 to 6; Based on the collected EEG signals, the controlled terminal is controlled to perform the target operation.

8. An electroencephalogram signal acquisition and control device, characterized in that: The device comprises: The EEG signal collecting electrodes are configured to collect EEG signals of the subject; A driving device, connected to the EEG signal collecting electrode, configured to drive the EEG signal collecting electrode to move; The sensor is configured to obtain current wearing parameters between the EEG signal collection electrode and the subject during the process of collecting the EEG signal of the subject through the EEG signal collection electrode; The data processing unit is configured to determine the comfort level of the subject wearing the EEG signal acquisition electrode based on the current wearing parameters, and based on the comfort level, control the driving device to drive the EEG signal acquisition electrode to move so as to adjust the wearing tightness of the EEG signal acquisition electrode.

9. The device according to claim 8, characterized in that The sensor is integrated in the EEG signal acquisition electrode, and the sensor includes at least one of a pressure sensor and a temperature sensor.

10. The device according to claim 8 or 9, characterized in that The device also includes a collector, an EEG signal data line, a wearing parameter data line, and a driving data line, wherein the EEG signal data line connects the collector and the EEG signal collecting electrode, the wearing parameter data line connects the sensor and the collector, and the driving data line connects the driving device and the collector.

11. The device according to claim 10, characterized in that The electroencephalogram signal acquisition electrode, the driving device, and the sensor are integrated in a wearable device.

12. A human factors intelligent control system based on brain-computer interface, characterized in that: The system comprises: The electroencephalogram signal acquisition and control device as described in any one of claims 8 to 11; The controlled terminal is configured to receive the control instruction and perform the target operation based on the control instruction; A brain-computer interface control unit is used to generate control instructions for controlling the controlled terminal based on the collected EEG signals.

13. An edge computing device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method described in any one of claims 1-7 are implemented; and / or, the edge computing device includes the EEG signal acquisition and control device described in any one of claims 8-11 or the human factors intelligent control system based on the brain-computer interface described in claim 12.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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