Multi-mode electroencephalogram and near-infrared brain function imaging signal integrated system

Abstract

The invention provides a multi-mode electroencephalogram and near-infrared brain function imaging signal integration system, and the system comprises an electroencephalogram collection unit which is disposed on the surface of a human body to collect a multi-lead electroencephalogram signal and transmit the multi-lead electroencephalogram signal to an electroencephalogram signal processing circuit; the electroencephalogram signal processing circuit is used for processing the multi-lead electroencephalogram signals and transmitting the multi-lead electroencephalogram signals to the digital-to-analog conversion circuit; the near-infrared acquisition unit comprises a plurality of groups of control circuits, a plurality of light emitting diodes and a plurality of groups of processing circuits which are combined to acquire multi-guide near-infrared signals; the near-infrared signal processing circuit is used for processing the acquired multi-guide near-infrared signals, performing round-robin switching on the multi-guide near-infrared signals and transmitting the multi-guide near-infrared signals to the digital-to-analog conversion circuit; the main control circuit unit is used for processing the multi-guide electroencephalogram signals and the multi-guide near-infrared signals of the digital signal type and sending generated processing results to an upper computer; the power supply module is used for supplying power. According to the invention, clock unification of collected multi-source signals can be ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of physiological information collection and detection, and in particular to a multi-channel electroencephalogram and multi-channel infrared signal integrated collection system. Background Art

[0002] Electroencephalogram (EEG) is an electrophysiological monitoring method for non-invasively recording brain electrical activity. It records the brain's spontaneous electrical activity over a period of time through multiple electrodes placed on the scalp. On the one hand, it is used clinically to diagnose epilepsy, sleep disorders, depth of anesthesia, coma, encephalopathy and brain death. On the other hand, it is used as a tool to provide brain activity information in the field of experimental psychology. It is also a brain imaging method and has been widely used in computational neuroscience. Functional near-infrared spectroscopy (fNIRS) is an emerging brain functional imaging technology that uses the penetrability and absorption of near-infrared light to penetrate tissues such as the scalp, muscles and skull, and record the intensity of near-infrared light absorbed. Neural activity induced by stimulation will increase blood flow to the activated brain area, resulting in an increase in blood volume. This phenomenon can be evaluated by the concentration of local oxyhemoglobin, deoxyhemoglobin or total hemoglobin. During cortical activation, the local oxygenated hemoglobin concentration (HbO) concentration increases and the deoxygenated hemoglobin (HBR) concentration decreases. We use near-infrared light from 650 to 950 nm for measurement. After measuring the light intensity, the stimulus presentation device is compared with the light intensity during no stimulation (baseline) and control stimulation. The change in brain area activation relative to the baseline is called the hemodynamic response, and there is a linear relationship between the hemodynamic function (the hemodynamic response after activation under ideal conditions, HRF) and the measured neural activity.

[0003] EEG and fNIRS have different signal sources, but they have good homogeneity and each has its own advantages. EEG is relatively cheap, has high temporal resolution, and has intuitive signals, which can accurately and in real time display the functional activity state of the brain in different cognitive activities; fNIRS is portable, noise-free, non-invasive, insensitive to the subject's movements, and has high spatial resolution, which can be used to study the advanced cognitive functions of the human brain.

[0004] However, in the prior art, the multi-channel EEG acquisition device and the multi-channel near-infrared acquisition device are usually two separate devices, and the information collected by the two devices is also processed by two unrelated main control circuit units. Therefore, the multi-channel EEG signals and multi-channel near-infrared signals collected by the combination of the two devices cannot achieve clock unification, that is, the information collected by the two devices may have a certain degree of misalignment in time correspondence, which affects the subsequent correlation analysis of the multi-channel EEG signals and the multi-channel near-infrared signals.

[0005] Therefore, how to provide a multimodal EEG and near-infrared brain functional imaging signal integration system that can ensure clock unification is a technical problem that needs to be solved urgently. Summary of the invention

[0006] In view of this, an embodiment of the present invention provides a multi-modal electroencephalogram and near-infrared brain functional imaging signal integration system to eliminate or improve one or more defects existing in the prior art.

[0007] The multimodal EEG and near-infrared brain function imaging signal integration system provided by the present invention comprises the following structure:

[0008] An electroencephalogram (EEG) acquisition device is used to acquire multi-channel EEG signals from the human body surface, where the acquired multi-channel EEG signals are analog signals;

[0009] An electroencephalogram signal processing circuit unit, used for performing signal processing on the received electroencephalogram signal;

[0010] A near-infrared acquisition device is used to acquire multi-channel near-infrared signals, where the type of the acquired multi-channel near-infrared signals is an analog signal;

[0011] A near-infrared signal processing circuit is used to process the collected multi-channel near-infrared signals;

[0012] A digital-to-analog conversion circuit unit, used for converting the processed analog signal type multi-channel EEG information and multi-channel near-infrared signal into a digital signal type multi-channel EEG signal and a digital signal type multi-channel near-infrared signal; and

[0013] The main control circuit unit is used to process the multi-channel EEG signals and multi-channel near-infrared signals of digital signal type in a unified clock manner, and send the generated processing results to the host computer.

[0014] In some embodiments of the present invention, the EEG signal processing circuit unit is used to perform high-pass filtering, low-pass filtering and amplification processing on the collected EEG signals, and use a multi-cut analog switch based on the EEG signals to perform round-robin switching on the processed EEG signals, so as to merge the processed multi-channel EEG signals and transmit them to the digital-to-analog conversion circuit unit.

[0015] In some embodiments of the present invention, a multi-channel EEG and a multi-channel near-infrared acquisition device simultaneously acquire corresponding EEG information and near-infrared information, and the spatial resolution of the multi-channel near-infrared acquisition device and the temporal resolution of the multi-channel EEG acquisition device complement each other, wherein the multi-channel EEG acquisition device detects the temporal resolution of a given stimulated cortex, and the multi-channel near-infrared acquisition device acquires the EEG information position information corresponding to the same moment collected by the multi-channel EEG acquisition device in the oxygen metabolism area of ​​neural activation.

[0016] In some embodiments of the present invention, the near-infrared collection device includes multiple groups of control circuits for controlling the on and off of red light and infrared light, multiple light-emitting diodes for detecting the light intensity of red light and infrared light, and multiple groups of processing circuits for collecting near-infrared signals through the light-emitting diodes. The combination of multiple groups of control circuits, multiple light-emitting diodes and multiple processing circuits is used to collect multi-channel near-infrared signals.

[0017] In some embodiments of the present invention, the near-infrared signal processing circuit is used to perform trans-impedance amplification and low-pass filtering on the collected multi-channel near-infrared signals, and use a multi-cut-one analog switch for the near-infrared signals to perform cyclic switching on the processed multi-channel near-infrared signals, so as to merge the processed multi-channel near-infrared signals and transmit them to the digital-to-analog conversion circuit.

[0018] In some embodiments of the present invention, the digital-to-analog conversion circuit unit is used to convert multi-channel EEG signals of analog signal type and multi-channel near-infrared signals of analog signal type into multi-channel EEG signals of digital signal type and multi-channel near-infrared signals of digital signal type, associate the multi-channel EEG signals of digital signal type and the multi-channel near-infrared signals through a daisy chain connection, and transmit them to the main control circuit unit based on the SPI transmission protocol.

[0019] In some embodiments of the present invention, the multi-channel EEG signals collected by the EEG acquisition device are an even number of multi-channel EEG signals, and the even number of multi-channel EEG signals are grouped according to set rules, and each group of EEG signals corresponds to a digital-to-analog conversion circuit.

[0020] In some embodiments of the present invention, the multiple groups of EEG signals are connected via a daisy chain.

[0021] In some embodiments of the present invention, the system also includes: a lead condition detection circuit, which is used to perform lead condition detection on each lead EEG signal in a round-robin manner before the EEG signal processing circuit performs high-pass filtering, low-pass filtering and amplification processing on the collected multi-lead EEG signals.

[0022] In some embodiments of the present invention, the near-infrared acquisition unit includes a path resistance amplifier, a second-order low-pass circuit, and a multi-to-one analog switch for near-infrared signals.

[0023] In some embodiments of the present invention, the main control circuit unit sends the generated processing result to the host computer via Bluetooth, wireless or wired communication.

[0024] In some embodiments of the present invention, the system further includes a power supply device, which includes an LDO power supply module and a BUCK power supply module. The LDO power supply module supplies power to a circuit that processes analog signals, and the BUCK power supply module supplies power to a circuit that processes digital signals.

[0025] The multimodal EEG and near-infrared brain function imaging signal integration system proposed in the present invention can collect multi-channel EEG signals based on the EEG acquisition unit, and optimize the collected signals through the EEG signal processing circuit, collect multi-channel near-infrared signals based on the near-infrared acquisition unit, and convert analog signal type multi-channel EEG signals and multi-channel near-infrared signals into digital signal type multi-channel EEG signals and multi-channel near-infrared signals through the near-infrared signal processing circuit based on the digital-to-analog conversion circuit, and uniformly process the digital signal type multi-channel EEG signals and multi-channel near-infrared signal clocks based on the daisy chain and the unified main control circuit unit, effectively avoiding the problem that the collected information may have a certain degree of misalignment in time correspondence due to the use of separate acquisition equipment, and facilitating the subsequent correlation analysis of the multi-channel EEG signals and multi-channel near-infrared signals.

[0026] Additional advantages, purposes, and features of the present invention will be described in part in the following description, and will become apparent to those skilled in the art after studying the following, or may be learned from the practice of the present invention. The purposes and other advantages of the present invention may be achieved and obtained by the structures specifically indicated in the specification and the accompanying drawings.

[0027] Those skilled in the art will appreciate that the objectives and advantages that can be achieved with the present invention are not limited to the above specific description, and the above and other objectives that can be achieved by the present invention will be more clearly understood from the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The drawings described herein are used to provide a further understanding of the present invention, constitute a part of the present application, and do not constitute a limitation of the present invention. In the drawings:

[0029] Figure 1 This is a structural diagram of a multimodal EEG and near-infrared brain functional imaging signal integration system in one embodiment of the present invention.

[0030] Figure 2Schematic diagram of the circuit structure of the EEG acquisition unit in one embodiment of the present invention.

[0031] Figure 3 Schematic diagram of the collection principle of the near-infrared collection unit.

[0032] Figure 4 Schematic diagram of the structure of a near-infrared acquisition and processing circuit in one embodiment of the present invention.

[0033] Figure 5 Schematic diagram of the principle of collecting 16-channel fNIRS signals through 10 channels in one embodiment of the present invention.

[0034] Figure 6 Schematic diagram of the feedback process of the processing result of the main control circuit unit in one embodiment of the present invention.

[0035] Figure 7 The figure is a schematic diagram of the circuit structure of an integrated data acquisition system in one embodiment of the present invention.

[0036] Figure 8 The figure is a schematic diagram of the circuit structure of an integrated data acquisition system including a power supply module in one embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments and the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0038] It should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, only structures and / or processing steps closely related to the solutions according to the present invention are shown in the accompanying drawings, while other details that are not closely related to the present invention are omitted.

[0039] It should be emphasized that the term “include / comprises” when used herein refers to the presence of features, elements, steps or components, but does not exclude the presence or addition of one or more other features, elements, steps or components.

[0040] It should also be noted that, unless otherwise specified, the term “connection” herein may refer not only to a direct connection but also to an indirect connection involving an intermediate.

[0041] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the accompanying drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

[0042] The sources of EEG and fNIRS signals are different, but they have good homogeneity and each has its own advantages. Among them, homogeneity refers to the tendency of individuals to interact and develop relationships with other similar people. EEG is low in price, high in time resolution, and intuitive in signal, and can accurately and real-time display the functional activity state of the brain in different cognitive activities; fNIRS is portable, noise-free, non-invasive, insensitive to the subject's movements, and has high spatial resolution, which can realize the study of the advanced cognitive functions of the human brain. The combination of the two can give full play to the advantages of both, and can accurately, comprehensively and real-time measure the activities of the brain in the cognitive process, and realize comprehensive and real-time brain imaging analysis, so as to be applied to cognitive activity research, brain function positioning, and state monitoring of emotions, cognitive load, alertness, and brain-computer interfaces. In particular, due to the daisy chain connection of multi-channel EEG signals and multi-channel near-infrared signals and the processing of the same main control chip (MCU chip), the clocks of the two source signals can be kept unified, which is convenient for the subsequent combination of the two multi-channel EEG signals and multi-channel near-infrared signals to analyze the characteristics.

[0043] In order to achieve the above-mentioned technical effects, the present invention provides a multimodal EEG and near-infrared brain functional imaging signal integration system. The EEG acquisition device and the near-infrared acquisition device complement each other in time resolution and spatial resolution, respectively, wherein the EEG acquisition device detects the time resolution of a given stimulated cortex, while the near-infrared acquisition device performs better positioning in the oxygen metabolism area of ​​neural activation. Modality is a form of expression of things, which is a description of a certain angle of things. Multimodality usually includes two or more modal forms, which means describing things from multiple perspectives.

[0044] Figure 1 This is a structural diagram of a multi-modal EEG and near-infrared brain function imaging signal integration system in one embodiment of the present invention. The device includes the following parts:

[0045] Structure 100: An electroencephalogram (EEG) acquisition device, used to acquire multi-channel EEG signals from the surface of a human body, wherein the acquired multi-channel EEG signals are analog signals.

[0046] In the specific implementation process, the multi-channel EEG signals collected in the EEG acquisition device are an even number of multi-channel EEG signals, and the even number of multi-channel EEG signals are grouped according to the set rules, and each group of EEG signals corresponds to a digital-to-analog conversion circuit. Among them, the setting rules for grouping multi-channel EEG signals can be based on the principle of equal division or can be divided according to different brain regions. For example, 16-channel EEG signals can be divided into 2 groups, each with 8 channels, or 16-channel EEG signals can be divided into 4 channels of the parietal lobe, 4 channels of the occipital lobe, and 8 channels of the central area. The setting rules listed above are only examples, and this solution is not limited to this.

[0047] Among them, the EEG acquisition unit contains multiple electrodes for collecting EEG signals, and the electrodes are close to the human brain to collect bioelectric signals. The number of leads in a multi-channel EEG usually refers to the number of electrodes for collecting EEG signals, and "multi-channel" corresponds to the number of electrodes placed. Traditional EEG uses only a few electrodes and can only collect partial EEG signals. Multi-channel EEG can collect EEG signals from multiple locations on the scalp, thereby providing clearer EEG images.

[0048] Structure 200: An electroencephalogram signal processing circuit unit, used for performing signal processing on the received electroencephalogram signal.

[0049] In the specific implementation process, the EEG signal processing circuit unit is used to perform high-pass filtering, low-pass filtering and amplification processing on the collected EEG signals, and use a multi-cut analog switch based on the EEG signals to perform round-robin switching on the processed EEG signals, so as to merge the processed multi-channel EEG signals and transmit them to the digital-to-analog conversion circuit unit.

[0050] For example, taking a 16-channel EEG signal processing circuit as an example, the processed multi-channel EEG signals can be switched in a round-robin manner through a 16-in-1 analog switch, or the 16-channel EEG signals can be divided into two groups, each with 8 channels, and the processed multi-channel EEG signals can be switched in a round-robin manner using an 8-in-1 analog switch, and the multi-channel EEG signals can be combined and transmitted to the digital-to-analog conversion circuit. The function of the 8-in-1 analog switch is to select eight analog signals and output them to a single analog output terminal. The 8-in-1 analog switch can be used to multiplex analog signals. For example, in a data acquisition system, it can be used to combine analog signals output by multiple sensors so that they can be input into a data acquisition card for acquisition.

[0051] Structure 300: A near-infrared acquisition device, used for acquiring multi-channel near-infrared signals, where the type of the acquired multi-channel near-infrared signals is an analog signal.

[0052] In the specific implementation process, the near-infrared acquisition device includes multiple groups of control circuits for controlling the on and off of red light and infrared light, multiple light-emitting diodes for detecting the light intensity of red light and infrared light, and multiple groups of processing circuits for collecting near-infrared signals through the light-emitting diodes. The combination of multiple groups of control circuits, multiple light-emitting diodes, and multiple processing circuits is used to collect multi-channel near-infrared signals. Among them, the combination of multiple control circuits, multiple light-emitting diodes, and multiple processing circuits is relatively diverse, and can be as follows: Figure 4 , Figure 5 The combined structure shown can also be a one-to-one simple structure, and the design here does not affect the creativity of this solution.

[0053] Structure 400: A near-infrared signal processing circuit, used for processing the collected multi-channel near-infrared signals.

[0054] In the specific implementation process, the near-infrared signal processing circuit is used to perform transimpedance amplification and low-pass filtering on the collected multi-channel near-infrared signals, and use a multi-cut-to-one analog switch for near-infrared signals to perform round-robin switching on the processed multi-channel near-infrared signals, so as to merge and transmit the processed multi-channel near-infrared signals to the digital-to-analog conversion circuit. Taking the collection of 16-channel near-infrared signals as an example, it can be controlled and implemented by a 10-cut-to-1 signal collection analog switch.

[0055] Structure 500: A digital-to-analog conversion circuit unit, used for converting the processed analog signal type multi-channel EEG information and multi-channel near-infrared signals into digital signal type multi-channel EEG signals and digital signal type multi-channel near-infrared signals.

[0056] During the specific implementation process, the digital-to-analog conversion circuit unit is used to convert multi-channel EEG signals of analog signal type and multi-channel near-infrared signals of analog signal type into multi-channel EEG signals of digital signal type and multi-channel near-infrared signals of digital signal type, associate the multi-channel EEG signals of digital signal type and the multi-channel near-infrared signals through a daisy chain connection, and transmit them to the main control circuit unit based on the SPI transmission protocol.

[0057] To explain it in layman's terms, the daisy chain can not only replace the function of the CAN line, but also contains a gateway function module in the daisy chain connection structure, which converts the daisy chain signal into the CAN line signal. The function of the digital-to-analog conversion circuit is to convert the analog signal into a digital signal. The analog signal changes continuously, while the digital signal is discrete. The digital-to-analog conversion circuit can convert the analog signal into a series of discrete digital values, which can be processed by computers or other digital devices. Analog to Digital Conventer means analog to digital converter.

[0058] Structure 600: A main control circuit unit, used for processing multi-channel EEG signals and multi-channel near-infrared signals of digital signal type in a unified clock manner, and sending the generated processing results to a host computer.

[0059] Among them, the clock unification feature is realized based on daisy chain series connection and a single MCU processing multi-source signals, which can effectively overcome the problem of inconsistent clocks in split devices, facilitate the correlation analysis of the two multi-channel EEG signals and multi-channel near-infrared signals in the subsequent analysis process, and associate the comprehensive performance of the EEG signals and near-infrared signals with the personnel and scenes associated with the acquisition equipment, so as to better use the EEG signals and near-infrared signals to identify the brain activities of people. The main control has a variety of ways to process multi-channel EEG signals and multi-channel near-infrared signals of digital signal type, including but not limited to merging multi-channel EEG signals and multi-channel near-infrared signals in the form of digital signals, combining signals from two sources, performing data cleaning, data preprocessing or data normalization on the signals from two sources, and drawing a line graph of digital signal changes over time based on the signals from two sources.

[0060] The multimodal EEG and near-infrared brain function imaging signal integration system proposed in the present invention can collect multi-channel EEG signals based on the EEG acquisition unit, and optimize the collected signals through the EEG signal processing circuit, collect multi-channel near-infrared signals based on the near-infrared acquisition unit, and convert the analog signal type multi-channel EEG signals and multi-channel near-infrared signals into digital signal type multi-channel EEG signals and multi-channel near-infrared signals based on the near-infrared signal processing circuit, and based on the digital-to-analog conversion circuit, the digital signal type multi-channel EEG signals and multi-channel near-infrared signals are processed in a unified clock based on the daisy chain and the unified main control circuit unit, effectively avoiding the problem that the collected information may have a certain degree of misalignment in time correspondence due to the use of separate acquisition equipment, facilitating the subsequent correlation analysis of the multi-channel EEG signals and the multi-channel near-infrared signals, and the multi-channel EEG and multi-channel infrared signal integration device can more comprehensively detect the activity of the cortex, the EEG acquisition system and the near-infrared acquisition system have better complementarity in time resolution and spatial resolution, the EEG acquisition system detects the time resolution of the given cortical stimulation, and the near-infrared is better positioned in the oxygen metabolism area of ​​neural activation.

[0061] The multi-channel EEG and multi-channel near-infrared acquisition devices simultaneously acquire corresponding EEG information and near-infrared information, and the spatial resolution of the multi-channel near-infrared acquisition device and the temporal resolution of the multi-channel EEG acquisition device complement each other, wherein the multi-channel EEG acquisition device detects the temporal resolution of a given stimulus cortex, and the multi-channel near-infrared acquisition device acquires the EEG information position information corresponding to the same moment collected by the multi-channel EEG acquisition device in the oxygen metabolism area of ​​neural activation.

[0062] In some embodiments of the present invention, the multi-channel EEG signal is a 16-channel EEG signal, and each 8-channel is a group, and the 16-channel EEG signal is divided into two groups, and each group of EEG signals corresponds to a digital-to-analog conversion circuit, and the specific type of the multi-cut-to-one analog switch for the EEG signal is a signal acquisition analog switch 8-cut-to-1. The digital-to-analog conversion circuit is used for analog-to-digital conversion of EEG signals and analog-to-digital conversion of fNIRS.

[0063] By adopting this embodiment, the processing pressure of the multi-cut-one analog switch can be dispersed, and the efficiency of merging and transmitting the processed multi-channel EEG signals can be guaranteed.

[0064] Furthermore, in the above embodiment, the multiple groups of EEG signals are connected via a daisy chain. Through the series connection of the daisy chain, multiple EEG signals can be combined together.

[0065] In some embodiments of the present invention, the device further includes: a lead condition detection circuit, which is used to perform a round-robin detection of the lead condition of each lead EEG signal before the EEG signal processing circuit performs high-pass filtering, low-pass filtering and amplification processing on the collected multi-lead EEG signals. The lead condition detection circuit includes a lead off detection channel analog switch 16 turned on to poll, and the corresponding detection circuit is a prior art and is not listed in detail here.

[0066] By adopting this embodiment, it is possible to check whether the electrodes used to collect EEG signals are in normal working condition based on the lead condition detection circuit, and then remind the user to process the abnormal electrodes to avoid the erroneous signals collected by the electrodes in abnormal working condition being collected and processed as normal signals, thereby interfering with normal judgment. The reminder can be given by turning the indicator light on and off.

[0067] In some embodiments of the present invention, the EEG signal processing circuit includes a high-pass filter, a low-pass filter, an amplifier circuit and a multi-cut analog switch for EEG signals. The multi-channel EEG signals after passing through the processing circuit can meet the requirements of subsequent processing.

[0068] In some embodiments of the present invention, the number of the control circuits is 4, the number of the light-emitting diodes and the number of the processing circuits are both 10, and a combination of multiple groups of the control circuits, multiple light-emitting diodes and multiple processing circuits is used to collect 16-channel near-infrared signals.

[0069] In some embodiments of the present invention, the near infrared acquisition unit includes a resistance amplifier, a second-order low-pass circuit and a multi-to-one analog switch for near infrared signals. The multi-channel near infrared signals after the processing circuit can meet the requirements of subsequent processing.

[0070] In some embodiments of the present invention, the main control circuit unit sends the generated processing results to the host computer via Bluetooth, wireless or wired communication. Figure 6 As shown, Figure 6 Schematic diagram of the feedback process of the processing result of the main control circuit unit in one embodiment of the present invention. This method is only an example, and the present solution is not limited to this.

[0071] In some embodiments of the present invention, Figure 1 As shown, the power supply module 700 includes an LDO power supply module and a BUCK power supply module, wherein the LDO power supply module supplies power to the circuit for processing analog signals, and the BUCK power supply module supplies power to the circuit for processing digital signals. In layman's terms, the LDO power supply module supplies power to the EEG acquisition unit, the EEG signal processing circuit, the near-infrared acquisition unit, and the near-infrared signal processing circuit, and the BUCK power supply module supplies power to the main control circuit unit. At the same time, the LDO power supply module and the BUCK power supply module simultaneously supply power to the digital-to-analog conversion circuit.

[0072] In some embodiments of the present invention, the frequency range of the infrared light is 650-950 nm.

[0073] In some other embodiments of the present invention, the multi-to-one analog switch used to implement polling access is also called a signal acquisition switching circuit, and the lead off detection channel analog switch 16-to-1 used for EEG signal lead off (lead status) detection is also called a signal lead off detection channel switching circuit.

[0074] Figure 2 FIG. 1 is a schematic diagram of the circuit structure of an EEG acquisition unit in an embodiment of the present invention. Figure 2 Take the example to explain the EEG acquisition unit and the EEG signal processing circuit. Specifically: EEG signals are grouped into 8 groups, namely EEG1, EEG2...EEG8. After being processed by analog circuits (high pass, low pass, amplification), the 8 leads are switched in a round-robin manner through analog switches, and the analog signals are transmitted to the next stage respectively. The other 8 leads, namely EEG9, EEG10...EEG16, are processed in the same way. Then, the circuit will perform a round-robin detection of the lead off condition of the EEG signal (i.e., the position and lead mode of the electrodes in the EEG) before processing the collected signal, and cut 16 through the signal acquisition analog switch.

[0075] Figure 3This is a schematic diagram of the collection principle of the near-infrared acquisition unit. The structure of the figure is a schematic diagram of the layered structure of the human brain, including the scalp, cerebrospinal fluid, skull, gray matter and white matter. S is the light source, that is, red light and infrared light. The arrow is the light path formed by the light emitted by the light source. The light passes through the light path and is received by the detector D. The detector D infers the concentration changes of deoxyhemoglobin and oxygen-carrying hemoglobin based on the intensity of the received light. The fNIRS measurement process is that the light source placed vertically on the scalp emits near-infrared light through the brain tissue, which is absorbed and scattered by the tissue and then emitted by the photodetector placed vertically on the scalp. The entire light path is "banana-shaped". The human brain tissue can be roughly divided into five layers of tissue: scalp, skull, cerebrospinal fluid, gray matter and white matter. In the near-infrared light in the 600-900nm band, the brain tissue is relatively transparent, and the light source can reach the gray matter and white matter layers to detect the concentration changes of hemoglobin. The detection depth is determined by the distance between the light source and the detector. According to the measurement principle, the fNIRS system can be mainly divided into three parts: the light source transmitting part, the photodetector receiving part and the data processing part. The function of the light source transmitting part is to emit low-power near-infrared light to the brain through a light-emitting diode (LED) or a laser diode (LD); the function of the photodetector receiving part is to receive the light intensity through a photodiode placed on the scalp and convert it into an electrical signal to be sent to the host computer for processing; the function of the data processing part is to process and analyze the collected electrical signals to obtain visible changes in HbO and Hb concentrations. Therefore, choosing a suitable system design method can effectively improve the system performance, have an important impact on the performance of the fNIRS system, and is of great significance to various studies based on fNIRS. The light source module is generally made of a light-emitting diode (LED) or a laser diode (LD). The function of the photodetector is to measure the intensity of the emitted light and convert it into an electrical signal for the data acquisition system to collect. Photodiodes (PD) are widely used in fNIRS systems, among which the most commonly used is silicon photodiodes (SiPD). Due to their good linearity and low cost, they are more suitable for rapid data acquisition.

[0076] Figure 4 This is a schematic diagram of the near-infrared acquisition and processing circuit structure in one embodiment of the present invention. In this embodiment, there are 10 groups of fNIRS signal processing circuits, but by controlling the on and off of red light and infrared, 16-lead fNIRS signal acquisition can be formed. After the red light and infrared enter the brain area, the PD detects the light intensity of the red light and infrared, and then infers the concentration changes of deoxyhemoglobin and oxygen-carrying hemoglobin. The PD converts the current signal into a voltage signal through a transimpedance amplifier, and then transmits it to the next stage after low-pass filtering. The system of multi-lead EEG and multi-lead near-infrared signals is not limited to 16-lead EEG and 16-lead near-infrared, and can be any derivative, which is not specifically limited here, and only 16 leads are taken as an example.

[0077] Figure 5 This is a schematic diagram of the principle of collecting 16-channel fNIRS signals through 10 channels in one embodiment of the present invention. Figure 5 and Figure 4 Correspondingly, PD1, PD2...PD10 are 10 channels, and the on and off are controlled by switching the signal acquisition analog switch 10 to 1. Figure 5 The 16 arrows in the figure represent the 16-channel fNIRS signals formed. This combination is only an example, and the specific combination can be added or reduced according to the actual situation.

[0078] Figure 7 This is a schematic diagram of the circuit structure of an integrated acquisition system in one embodiment of the present invention. The focus of this solution is to connect the multi-channel EEG signals and multi-channel near-infrared signals of the same target object (i.e., the subject) with the same multi-channel number in series through a daisy chain connection, and output the series connection result to a single microcontroller unit (MCU) for processing, so as to ensure the clock unification of the human factors signals from the two sources (multi-channel EEG signals and multi-channel near-infrared signals), so as to establish the correlation between the EEG signals and the near-infrared signals in the subsequent analysis process, and combine the EEG signals and the near-infrared signals to analyze the psychological activities of the target object, providing a new technical idea for human factors data collection and analysis.

[0079] Further, Figure 8 The working mode of the power supply module is shown in Figure 8 The schematic diagram of the circuit structure of an integrated acquisition system including a power supply module in one embodiment of the present invention. The power supply module in this embodiment includes a 3.0V output LDO (Low Dropout Voltage) power supply module and a 3.0V output BUCK power supply module, which respectively power the analog signal processing circuit and the digital signal processing circuit in the entire acquisition device. BUCK power supply is a DC-DC converter that can convert input voltage into an output voltage. The above voltage conditions are only examples, and the present invention is not limited thereto. The specific power supply voltage can be flexibly set according to the actual circuit conditions such as chip selection.

[0080] The multimodal EEG and near-infrared brain function imaging signal integration system proposed in the present invention can collect multi-channel EEG signals based on the EEG acquisition unit, and optimize the collected signals through the EEG signal processing circuit, collect multi-channel near-infrared signals based on the near-infrared acquisition unit, and convert the analog signal type multi-channel EEG signals and multi-channel near-infrared signals into digital signal type multi-channel EEG signals and multi-channel near-infrared signals based on the near-infrared signal processing circuit, and based on the digital-to-analog conversion circuit, the digital signal type multi-channel EEG signals and multi-channel near-infrared signals are processed in a unified clock based on the daisy chain and the unified main control circuit unit, effectively avoiding the problem that the collected information may have a certain degree of misalignment in time correspondence due to the use of separate acquisition equipment, facilitating the subsequent correlation analysis of the multi-channel EEG signals and the multi-channel near-infrared signals, and the multi-channel EEG and multi-channel infrared signal integration device can more comprehensively detect the activity of the cortex, the EEG acquisition system and the near-infrared acquisition system have better complementarity in time resolution and spatial resolution, the EEG acquisition system detects the time resolution of the given cortical stimulation, and the near-infrared is better positioned in the oxygen metabolism area of ​​neural activation.

[0081] The advantages of combining multi-channel EEG and multi-channel infrared signals, that is, performing clock-unified correlation analysis, are:

[0082] (1) It can achieve the complementarity of temporal resolution and spatial resolution;

[0083] (2) EEG and fNIRS reflect different aspects of underlying neuronal activity that are closely related and can provide complementary information;

[0084] (3) the ability to explore neurovascular coupling by acquiring electrical activity as well as hemodynamics in response to stimulation;

[0085] (4) Both technologies have a wide range of applications, from simple visual stimulation experiments to clinical monitoring, and can be used by a wide range of populations from infants to the elderly;

[0086] (5) Both EEG and fNIRS have the advantages of being relatively small and inexpensive and can be integrated into portable devices.

[0087] Furthermore, the EEG acquisition device based on neuronal activity detects brain activity by recording the spontaneous and rhythmic motor potential of nerves under the scalp. That is, when we only use EEG acquisition equipment, we can only see a signal change on the surface of the scalp. By adding a near-infrared acquisition device for synchronous acquisition, we can monitor the deep blood flow dynamics of the brain. When synchronously acquiring, we can monitor and analyze the epidermal potential and the blood flow dynamics at the same position. fNIRS (near-infrared acquisition device) mainly monitors the concentration changes of deoxyhemoglobin and oxygen-carrying hemoglobin in the brain region under experimental conditions. Therefore, EEG (electroencephalogram acquisition device) has high temporal resolution and low spatial resolution, while fNIRS has high spatial resolution and low temporal resolution. However, after combining and processing the data, more accurate EEG signals in the spatial domain and more accurate near-infrared information in the temporal domain can be obtained.

[0088] The combined use of the two can give full play to the advantages of both, and can accurately, comprehensively and in real time measure the brain's activities in the cognitive process, and realize comprehensive and real-time brain imaging analysis, which can be applied to cognitive activity research, brain function positioning, and emotion, cognitive load, alertness and other state monitoring, as well as brain-computer interfaces.

[0089] It should be understood by those skilled in the art that the exemplary components, systems and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software or a combination of the two. Whether it is performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present invention are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link via a data signal carried in a carrier.

[0090] It should be clear that the present invention is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present invention.

[0091] In the present invention, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with features of other embodiments or replace features of other embodiments.

[0092] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the embodiments of the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A multimodal EEG and near-infrared brain functional imaging signal integration system, characterized in that: The system includes: An electroencephalogram (EEG) acquisition device is used to acquire multi-channel EEG signals from the human body surface, where the acquired multi-channel EEG signals are analog signals; An electroencephalogram signal processing circuit unit, used for performing signal processing on the received electroencephalogram signal; A near-infrared acquisition device is used to acquire multi-channel near-infrared signals, where the type of the acquired multi-channel near-infrared signals is an analog signal; A near-infrared signal processing circuit is used to process the collected multi-channel near-infrared signals; A digital-to-analog conversion circuit unit, used for converting the processed analog signal type multi-channel EEG information and multi-channel near-infrared signal into a digital signal type multi-channel EEG signal and a digital signal type multi-channel near-infrared signal; and The main control circuit unit is used to process the multi-channel EEG signals and multi-channel near-infrared signals of digital signal type in a unified clock manner, and send the generated processing results to the host computer.

2. The integrated system according to claim 1, characterized in that: The EEG signal processing circuit unit is used to perform high-pass filtering, low-pass filtering and amplification processing on the collected EEG signals, and use a multi-cut analog switch based on the EEG signals to perform round-robin switching on the processed EEG signals, so as to merge the processed multi-channel EEG signals and transmit them to the digital-to-analog conversion circuit unit.

3. The integrated system according to claim 1, characterized in that: The near-infrared acquisition device includes multiple groups of control circuits for controlling the on and off of red light and infrared light, multiple light-emitting diodes for detecting the light intensity of red light and infrared light, and multiple groups of processing circuits for collecting near-infrared signals through the light-emitting diodes. The combination of multiple groups of control circuits, multiple light-emitting diodes and multiple processing circuits is used to collect multi-channel near-infrared signals.

4. The integrated system according to claim 1, characterized in that: The near-infrared signal processing circuit is used to perform transimpedance amplification and low-pass filtering on the collected multi-channel near-infrared signals, and use a multi-cut-one analog switch for the near-infrared signals to perform round-robin switching on the processed multi-channel near-infrared signals, so as to merge the processed multi-channel near-infrared signals and transmit them to the digital-to-analog conversion circuit.

5. The integrated system according to claim 1, characterized in that: The multi-channel EEG and multi-channel near-infrared acquisition devices simultaneously acquire corresponding EEG information and near-infrared information, and the spatial resolution of the multi-channel near-infrared acquisition device and the temporal resolution of the multi-channel EEG acquisition device complement each other, wherein the multi-channel EEG acquisition device detects the temporal resolution of a given stimulus cortex, and the multi-channel near-infrared acquisition device acquires the EEG information position information corresponding to the same moment collected by the multi-channel EEG acquisition device in the oxygen metabolism area of ​​neural activation.

6. The integrated system according to claim 1, characterized in that: The digital-to-analog conversion circuit unit is used to convert multi-channel EEG signals of analog signal type and multi-channel near-infrared signals of analog signal type into multi-channel EEG signals of digital signal type and multi-channel near-infrared signals of digital signal type, associate the multi-channel EEG signals of digital signal type and the multi-channel near-infrared signals through a daisy chain connection, and transmit them to the main control circuit unit based on the SPI transmission protocol.

7. The integrated system according to claim 1, characterized in that: The multi-channel EEG signals collected by the EEG collection device are an even number of multi-channel EEG signals, and the even number of multi-channel EEG signals are grouped according to a set rule, and each group of EEG signals corresponds to a digital-to-analog conversion circuit.

8. The integrated system according to claim 7, characterized in that: The multiple groups of EEG signals are connected via a daisy chain.

9. The integrated system according to claim 1, characterized in that: The system also includes: The lead condition detection circuit is used to perform round-robin detection on the lead condition of each lead EEG signal before the EEG signal processing circuit performs high-pass filtering, low-pass filtering and amplification processing on the collected multi-lead EEG signals.

10. The integrated system according to claim 1, characterized in that: The near-infrared acquisition unit comprises a path resistance amplifier, a second-order low-pass circuit and a multi-to-one analog switch for near-infrared signals.

11. The integrated system according to claim 1, characterized in that: The main control circuit unit sends the generated processing results to the host computer via Bluetooth, wireless or wired communication.

12. The integrated system according to claim 1, characterized in that: The system further includes a power supply device, which includes an LDO power supply module and a BUCK power supply module. The LDO power supply module supplies power to a circuit that processes analog signals, and the BUCK power supply module supplies power to a circuit that processes digital signals.

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