Transcranial electrical stimulation device and system based on multimodal data

Abstract

The present application discloses a transcranial electrical stimulation device and system based on multimodal data, the device comprising: an analog front-end module, an ADC acquisition module, a blood oxygen detection module, a control module, a transcranial electrical stimulation module, and an acquisition and stimulation integrated module. A preset stimulation scheme is obtained through the control module, and the preset stimulation scheme is adjusted according to a third EEG signal, pulse data, and blood oxygen data of a target object to obtain a target stimulation scheme, and a target control instruction corresponding to the target stimulation scheme is determined; the target control instruction is transmitted to the transcranial electrical stimulation module, and the transcranial electrical stimulation module controls the acquisition and stimulation integrated module to perform transcranial electrical stimulation on the target object according to the target control instruction, so as to improve the stimulation effect of transcranial electrical stimulation on the target object. By adopting the embodiments of the present application, the stability of tES stimulation therapy is improved.

Description

Technical Field

[0001] The present application relates to the field of medical technology, and in particular to a transcranial electrical stimulation device and system based on multimodal data. Background Art

[0002] Transcranial electric stimulation (tES) is a non-invasive, economical, and well-tolerated central nervous system regulation technology that aims to stimulate the cerebral cortex by applying specific patterns of microcurrent to affect neural activity in specific brain areas.

[0003] Currently, when performing tES stimulation, clinicians usually choose the corresponding stimulation plan based on the observed treatment effects and accumulated experience. However, the effect of tES stimulation varies with the brain state, and the brain state changes dynamically. If the stimulation plan is not formulated in combination with the subject's EEG signals, blood oxygen data and other modal information, it may result in good stimulation effects at some times and poor effects at other times, and the stability of the treatment cannot be guaranteed.

[0004] Therefore, the issue of how to improve the stability of tES stimulation therapy needs to be addressed urgently. Summary of the invention

[0005] The embodiments of the present application provide a transcranial electrical stimulation device and system based on multimodal data, which improves the stability of tES stimulation therapy by formulating a stimulation plan by combining the subject's EEG signals, blood oxygen data and other modal information.

[0006] In a first aspect, an embodiment of the present application provides a transcranial electrical stimulation device based on multimodal data, including: an analog front-end module, an ADC acquisition module, a blood oxygen detection module, a control module, a transcranial electrical stimulation module, and an acquisition and stimulation integrated module, wherein:

[0007] The first end of the analog front-end module is connected to the first end of the integrated acquisition and stimulation module, and the second end of the analog front-end module is connected to the first end of the ADC acquisition module; the second end of the ADC acquisition module is connected to the first end of the control module, and the second end of the control module is connected to the second end of the transcranial electrical stimulation module; the first end of the transcranial electrical stimulation module is connected to the second end of the integrated acquisition and stimulation module; the third end of the control module is connected to the blood oxygen detection module;

[0008] The analog front-end module is used to collect a first EEG signal of the target object through the integrated collection and stimulation module within a first preset time period, and filter and amplify the first EEG signal to obtain a second EEG signal; the second EEG signal is an analog signal;

[0009] The ADC acquisition module is used to convert the second EEG signal into a digital signal to obtain a third EEG signal, and transmit the third EEG signal to the control module; the third EEG signal is a digital signal;

[0010] The blood oxygen detection module is used to monitor the pulse wave and blood oxygen of the target object in real time within the first preset time period, obtain pulse data and blood oxygen data, and transmit the pulse data and the blood oxygen data to the control module;

[0011] The control module is used to obtain a preset stimulation scheme, adjust the preset stimulation scheme according to the third EEG signal, the pulse data and the blood oxygen data to obtain a target stimulation scheme; determine a target control instruction corresponding to the target stimulation scheme; and transmit the target control instruction to the transcranial electrical stimulation module;

[0012] The transcranial electrical stimulation module is used to control the integrated acquisition and stimulation module to perform transcranial electrical stimulation on the target object using the target stimulation scheme within a second preset time period according to the target control instruction, so as to enhance the stimulation effect of transcranial electrical stimulation on the target object; the start time of the second preset time period is later than the end time of the first preset time period.

[0013] In a second aspect, an embodiment of the present application provides a transcranial electrical stimulation system based on multimodal data, the system comprising a transcranial electrical stimulation device based on multimodal data as described in any one of the first aspects.

[0014] It can be seen that by implementing the transcranial electrical stimulation device based on multimodal data provided by an embodiment of the present invention, multimodal data such as EEG signals, pulse data, blood oxygen data, etc. of the target object are first collected, and then the preset stimulation scheme is obtained through the control module, and the preset stimulation scheme is adjusted according to the third EEG signal, pulse data and blood oxygen data to obtain the target stimulation scheme, and the target control instruction corresponding to the target stimulation scheme is determined; the target control instruction is transmitted to the transcranial electrical stimulation module, and the transcranial electrical stimulation module controls the acquisition and stimulation integration module according to the target control instruction to perform transcranial electrical stimulation on the target object using the target stimulation scheme to enhance the stimulation effect of transcranial electrical stimulation on the target object. These multimodal data provide physiological information of the target object from different angles, and the stimulation parameters of the transcranial electrical stimulation module are adjusted according to the physiological information, which can ensure that the stimulation therapy is carried out within a safe and effective range, thereby improving the stability of tES stimulation therapy. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the background technology, the drawings required for use in the embodiments of the present application or the background technology will be described below.

[0016] Figure 1 is a structural block diagram of a transcranial electrical stimulation device based on multimodal data provided in an embodiment of the present application;

[0017] Figure 2 is a structural block diagram of an analog front-end circuit provided in an embodiment of the present application;

[0018] Figure 3 is a circuit diagram of an analog front-end circuit provided in an embodiment of the present application;

[0019] Figure 4 is a circuit diagram of a right leg driving circuit provided in an embodiment of the present application;

[0020] Figure 5 This is a circuit diagram of an active electrode integrating target acquisition and stimulation provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0022] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0023] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0024] The following is an explanation of some professional terms involved in this application:

[0025] 10-20 system: It is an internationally accepted standard system for placing EEG electrodes. The 10-20 system provides a standardized method for collecting EEG signals, making the EEG data collected by different laboratories and researchers comparable. No matter where the EEG experiment is conducted, as long as the 10-20 system is used to place the electrodes, the consistency and repeatability of the data can be ensured.

[0026] ADC acquisition module: also known as analog-to-digital conversion acquisition module, its main function is to convert analog signals into digital signals for processing and analysis by digital systems. In many electronic devices and systems, actual physical signals (such as temperature, pressure, sound, light intensity, etc.) usually exist in the form of analog signals. However, digital processors (such as microcontrollers, digital signal processors, etc.) can only process digital signals. The ADC acquisition module plays the role of building a bridge between the analog world and the digital world.

[0027] tES: The Chinese name is transcranial electrical stimulation. It is a non-invasive neuromodulation technology that increases or decreases the excitability of neurons by applying weak electric current to the cerebral cortex through scalp electrodes, thereby achieving the purpose of regulation.

[0028] EEG signal: It is the reflection of electrophysiological signal generated by brain neuron activity on the surface of scalp or inside the skull.

[0029] Neurons in the brain generate weak currents when transmitting and processing information, and the sum of these currents forms EEG signals. EEG signals are usually collected by placing electrodes on the scalp to record changes in the brain's electrical activity in different states.

[0030] Stimulation parameters: In this application, stimulation parameters refer to various variables used to describe and control the tES process. Different stimulation parameters will have different effects on the stimulation effect, for example, stimulation current intensity, stimulation time, stimulation frequency, etc., which are not limited here.

[0031] Stimulation protocol: In this application, a stimulation protocol refers to a combination of a series of parameters and operating methods for transcranial electrical stimulation developed to achieve specific therapeutic or research purposes. For example, using 1 mA of direct current to stimulate the brain through an active electrode for 5 minutes is a stimulation protocol.

[0032] See also Figure 1 , Figure 1 1 is a structural block diagram of a transcranial electrical stimulation device 100 based on multimodal data provided in an embodiment of the present application; the transcranial electrical stimulation device 100 based on multimodal data includes: an analog front-end module 101, an ADC acquisition module 102, a blood oxygen detection module 103, a control module 104, a transcranial electrical stimulation module 105, and an acquisition and stimulation integration module 106, wherein:

[0033] The first end of the analog front-end module 101 is connected to the first end of the integrated collection and stimulation module 106, and the second end of the analog front-end module 101 is connected to the first end of the ADC collection module 102; the second end of the ADC collection module 102 is connected to the first end of the control module 104, and the second end of the control module 104 is connected to the second end of the transcranial electrical stimulation module 105; the first end of the transcranial electrical stimulation module 105 is connected to the second end of the integrated collection and stimulation module 106; the third end of the control module 104 is connected to the blood oxygen detection module 103;

[0034] The analog front-end module 101 is used to collect a first EEG signal of the target object through the collection and stimulation integration module 106 within a first preset time period, and filter and amplify the first EEG signal to obtain a second EEG signal; the second EEG signal is an analog signal;

[0035] Specifically, the electrodes in the integrated acquisition and stimulation module 106 can be placed at specific positions on the scalp to cover different brain areas according to the international standard 10-20 system or other specific EEG acquisition schemes. Then, the first EEG signal of the target object can be acquired through the integrated acquisition and stimulation module 106, and the first EEG signal can be transmitted to the analog front-end module 101, which filters and amplifies the first EEG signal to obtain a second EEG signal.

[0036] Optionally, in the aspect of collecting the first EEG signal of the target object through the integrated collection and stimulation module 106, the analog front end module 101 is specifically used for:

[0037] A1. Obtaining the electrode positions corresponding to the n integrated collection and stimulation active electrodes in the integrated collection and stimulation module 106 to obtain n electrode positions; each integrated collection and stimulation active electrode corresponds to one electrode position;

[0038] A2. Obtaining the historical data collected by the integrated collection and stimulation module 106;

[0039] A3, determining the collection data of the n integrated collection and stimulation active electrodes according to the historical collection data, and obtaining n collection data; each integrated collection and stimulation active electrode corresponds to one collection data;

[0040] A4. Determine a first data quality parameter corresponding to each of the n collected data to obtain n first data quality parameters;

[0041] A5. Determine the optimization factor corresponding to each of the n electrode positions to obtain n optimization factors;

[0042] A6. Adjust corresponding first data quality parameters among the n first data quality parameters according to the n optimization factors to obtain n second data quality parameters;

[0043] A7, determining the number m of collection electrodes corresponding to the preset required EEG data volume; m is a positive integer less than n;

[0044] A8. Determine the priority order corresponding to the n second data quality parameters to obtain a target priority order; the larger the second data quality parameter, the higher the priority order;

[0045] A9. Selecting m integrated collection and stimulation active electrodes from the n integrated collection and stimulation active electrodes according to the target priority order;

[0046] A10. Collect the EEG signal of the target object through the m integrated collection and stimulation active electrodes to obtain the first EEG signal.

[0047] In the embodiment of the present application, the data quality parameter is an indicator used to measure and evaluate the data quality. It is used to indicate the quality of the data, and its value range can be 0~10; the larger the data quality parameter, the better the quality of the collected data; the required amount of EEG data can be preset or defaulted in advance, and the required amount of EEG data can be the minimum amount of data required to analyze the brain state of the target object.

[0048] In a specific embodiment, the electrode positions corresponding to n integrated acquisition and stimulation active electrodes can be analyzed according to the 10-20 system to obtain n electrode positions; then, the historical acquisition data corresponding to the integrated acquisition and stimulation module 106 can be obtained. Specifically, the historical acquisition data refers to the data collected by the integrated acquisition and stimulation module 106 in the past period of time (for example, one week, one month, etc.), and the historical acquisition data can be queried from the database of the transcranial electrical stimulation device 100 based on multimodal data to obtain the historical acquisition data; then, the acquisition data of the n integrated acquisition and stimulation active electrodes can be determined according to the historical acquisition data to obtain n acquisition data. Specifically, each integrated acquisition and stimulation active electrode can correspond to a unique electrode identifier, and the electrode identifiers of the n integrated acquisition and stimulation active electrodes are obtained to obtain n electrode identifiers, and the acquisition data is searched from the historical acquisition data according to the n electrode identifiers to obtain n acquisition data.

[0049] Next, the first data quality parameter corresponding to each of the n collected data can be determined to obtain n first data quality parameters; then, the optimization factor corresponding to each of the n electrode positions can be determined to obtain n optimization factors. Specifically, a mapping relationship between a preset electrode position and an optimization factor can be pre-stored, and n optimization factors corresponding to the n electrode positions can be determined based on the mapping relationship. The value range of the optimization factor can be -0.12~0.12; then, the corresponding first data quality parameter in the n first data quality parameters can be adjusted according to the n optimization factors. The specific calculation formula is as follows:

[0050] The second data quality parameter a=the first data quality parameter a×(1+optimization factor a);

[0051] Among them, the first data quality parameter a is any first data quality parameter among the n first data quality parameters, and the optimization factor a is the optimization factor corresponding to the first data quality parameter a among the n optimization factors; the second data quality parameter a is one of the n second data quality parameters; by calculating n times according to the above formula, n second data quality parameters can be obtained; then, the number m of acquisition electrodes corresponding to the preset required EEG data volume can be determined, specifically, the mapping relationship between the preset EEG data volume and the number of acquisition electrodes can be pre-stored, and the number m of acquisition electrodes corresponding to the required EEG data volume can be determined based on the mapping relationship; the n second data quality parameters are sorted according to their sizes to obtain the target priority order; then, the top m acquisition and stimulation integrated active electrodes can be selected from the n acquisition and stimulation integrated active electrodes according to the target priority order; the EEG signal of the target object is collected by the m acquisition and stimulation integrated active electrodes to obtain the first EEG signal.

[0052] In this way, by obtaining n electrode positions corresponding to n integrated acquisition and stimulation active electrodes in the integrated acquisition and stimulation module 106; obtaining historical acquisition data corresponding to the integrated acquisition and stimulation module 106; determining n acquisition data corresponding to n integrated acquisition and stimulation active electrodes according to the historical acquisition data; determining n first data quality parameters corresponding to the n acquisition data; determining n optimization factors corresponding to the n electrode positions; adjusting the n first data quality parameters according to the n optimization factors to obtain n second data quality parameters; determining the number m of acquisition electrodes corresponding to the preset required EEG data volume; determining the priority order corresponding to the n second data quality parameters, to the target priority order; m integrated acquisition and stimulation active electrodes are selected from the n integrated acquisition and stimulation active electrodes according to the target priority order; the EEG signal of the target object is acquired through the m integrated acquisition and stimulation active electrodes to obtain a first EEG signal. On the one hand, by determining the first data quality parameter corresponding to each integrated acquisition and stimulation active electrode, the quality of the data collected by each electrode can be quantitatively evaluated to provide data support for subsequent operations; on the other hand, by screening out the best quality electrodes for acquisition, the quality of the collected data can be guaranteed to be good, thus avoiding the waste of time and resources in processing a large amount of low-quality data and improving the efficiency of data acquisition and analysis.

[0053] Optionally, in determining the first data quality parameter corresponding to each of the n collected data to obtain n first data quality parameters, the analog front-end module 101 is specifically used for:

[0054] B1. Acquire target acquisition data and target electrode; the target acquisition data is any one of the n acquisition data; the target electrode is the electrode corresponding to the target acquisition data in the m integrated acquisition and stimulation active electrodes;

[0055] B2. determining a target signal-to-noise ratio corresponding to the target acquisition data;

[0056] B3, determining a reference data quality parameter corresponding to the target signal-to-noise ratio;

[0057] B4, obtaining a target sampling rate corresponding to the target electrode;

[0058] B5. Obtain the maximum data value and the minimum data value in the target collected data;

[0059] B6. Determine the difference between the maximum data value and the minimum data value to obtain a target difference;

[0060] B7. Determine a first influence coefficient corresponding to the target sampling rate;

[0061] B8. Determine a second influence coefficient corresponding to the target difference;

[0062] B9. Determine a first data quality parameter corresponding to the target acquisition data according to the first influence coefficient, the second influence coefficient and the reference data quality parameter.

[0063] In an embodiment of the present application, target acquisition data can be obtained from n acquisition data, and then, the target electrode identifier corresponding to the target stimulation data can be obtained, and the target electrode can be determined according to the target electrode identifier; then, the target signal-to-noise ratio corresponding to the target acquisition data can be determined. Specifically, the valid data interval of the EEG signal can be first obtained, and the data in the valid data interval is the valid signal, and the data not in the valid data interval is the noise signal. The effective signal power and noise power in the target acquisition data are calculated according to the valid data interval, and then, the effective signal power and noise power are calculated according to the signal-to-noise ratio calculation formula to obtain the target signal-to-noise ratio; then, the reference data quality parameters corresponding to the target signal-to-noise ratio can be determined. Specifically, the mapping relationship between the preset signal-to-noise ratio and the data quality parameter can be pre-stored, and the reference data quality parameters corresponding to the target signal-to-noise ratio can be determined based on the mapping relationship.

[0064] Next, the target sampling rate corresponding to the target electrode can be obtained. Specifically, the instruction manual of the target electrode can be queried to find the target sampling rate from the instruction manual; then, the maximum data value and the minimum data value in the target acquisition data can be obtained; further, the difference between the maximum data value and the minimum data value can be calculated to obtain the target difference; the first influence coefficient corresponding to the target sampling rate can be determined. Specifically, the mapping relationship between the preset sampling rate and the influence coefficient can be pre-stored, and the first influence coefficient corresponding to the target sampling rate can be determined based on the mapping relationship; the second influence coefficient corresponding to the target difference can be determined. Specifically, the mapping relationship between the preset difference and the influence coefficient can be pre-stored, and the second influence coefficient corresponding to the target difference can be determined based on the mapping relationship; the value range of the influence coefficient can be -0.2~0.2; finally, the first data quality parameter corresponding to the target acquisition data can be determined based on the first influence coefficient, the second influence coefficient and the reference data quality parameter. The specific calculation formula is as follows:

[0065] The first data quality parameter = reference data quality parameter × (1 + first influence coefficient) × (1 + second influence coefficient).

[0066] In this way, by acquiring the target acquisition data and the target electrode; determining the target signal-to-noise ratio corresponding to the target acquisition data; determining the reference data quality parameter corresponding to the target signal-to-noise ratio; acquiring the target sampling rate corresponding to the target electrode; acquiring the maximum data value and the minimum data value in the target acquisition data; determining the difference between the maximum data value and the minimum data value to obtain the target difference; determining the first influence coefficient corresponding to the target sampling rate; determining the second influence coefficient corresponding to the target difference; determining the first data quality parameter corresponding to the target acquisition data based on the first influence coefficient, the second influence coefficient and the reference data quality parameter, by determining multiple factors such as the target signal-to-noise ratio, the reference data quality parameter, the target sampling rate, the target difference and the corresponding influence coefficient, the quality of the target acquisition data can be comprehensively evaluated from different angles, which is more comprehensive and accurate than evaluation based on a single indicator alone.

[0067] Optionally, the analog front-end module 101 includes an analog front-end circuit 200, see Figure 2 , Figure 2 It is a structural block diagram of an analog front-end circuit 200 provided in an embodiment of the present application; the analog front-end circuit 200 includes a first amplifier circuit 11 and a second amplifier circuit 12; the first amplifier circuit 11 is connected to the second amplifier circuit 12; specifically, the first end of the first amplifier circuit 11 can be connected to the first end of the second amplifier circuit 12, and the second end of the first amplifier circuit 11 can be connected to the second end of the second amplifier circuit 12.

[0068] See also Figure 3 , Figure 3 is a circuit diagram of an analog front-end circuit 200 provided in an embodiment of the present application; Figure 3 As shown, the first amplifier circuit 11 includes: a first operational amplifier A1, a second operational amplifier A2, a first resistor R1, a second resistor R2, a third resistor R3, a fourth resistor R4, and a first capacitor C1; wherein:

[0069] The non-inverting input terminal of the first operational amplifier A1 is used to receive the positive terminal signal V of the first differential voltage. i+ The non-inverting input terminal of the second operational amplifier A2 is used to receive the negative terminal signal V of the first differential voltage i- The inverting input terminal of the first operational amplifier A1 is respectively connected to the first end of the first resistor R1 and the first end of the third resistor R3; the output terminal of the first operational amplifier A1 is respectively connected to the second end of the first resistor R1 and the first end of the first capacitor C1; the second end of the third resistor R3 is respectively connected to the first end of the second resistor R2 and the inverting input terminal of the second operational amplifier A2; the second end of the second resistor R2 is respectively connected to the output terminal of the second operational amplifier A2, the second end of the fourth resistor R4, and the first end of the second amplifier circuit 12; the first end of the fourth resistor R4 is respectively connected to the second end of the first capacitor C1 and the second end of the second amplifier circuit 12;

[0070] The first differential voltage is the voltage collected by the integrated collection and stimulation module 106 .

[0071] In a specific embodiment, the analog front-end circuit 200 acquires the signal by acquiring the differential voltage between the in-phase input terminal and the inverting input terminal of the operational amplifier. This method can effectively suppress common-mode interference. Common-mode interference refers to the interference signal acting on two input terminals at the same time. Through differential input, the influence of common-mode interference on the two input terminals will be greatly weakened, thereby improving the quality of the signal.

[0072] Among them, the first operational amplifier A1 and the second operational amplifier A2 are both gain amplifiers, and the first resistor R1, the second resistor R2, and the third resistor R3 are used to control the amplification factor of the first amplifier circuit 11. After the input signal passes through the first amplifier circuit 11, the signal amplitude is initially improved.

[0073] The first capacitor C1 and the fourth resistor R4 control the integral time constant, that is, the high-pass filter cutoff frequency. The high-pass filter cutoff frequency can be set to 0.2 Hz, which is used to remove low-frequency drift and baseline noise in the input signal. For example, due to changes in the contact resistance between the electrode and the scalp, human body movement, etc., there may be low-frequency drift in the EEG signal. The high-pass filter can effectively remove these low-frequency interferences and highlight useful signal components.

[0074] Optional, such as Figure 3 As shown, the second amplifier circuit 12 includes: a third operational amplifier A3, a fourth operational amplifier A4, a fifth resistor R5, a sixth resistor R6, a seventh resistor R7, an eighth resistor R8, a ninth resistor R9, a second capacitor C2, a third capacitor C3, and a fourth capacitor C4, wherein:

[0075] The non-inverting input terminal of the third operational amplifier A3 serves as the first terminal of the second amplifier circuit 12; the inverting input terminal of the third operational amplifier A3 is respectively connected to the first terminal of the fifth resistor R5, the first terminal of the ninth resistor R9, and the first terminal of the second capacitor C2; the output terminal of the third operational amplifier A3 is respectively connected to the second terminal of the fifth resistor R5, the second terminal of the second capacitor C2, and the first terminal of the seventh resistor R7; the second terminal of the ninth resistor R9 is respectively connected to the first terminal of the third capacitor C3, the first terminal of the sixth resistor R6, and the inverting input terminal of the fourth operational amplifier A4; the non-inverting input terminal of the fourth operational amplifier A4 serves as the second terminal of the second amplifier circuit 12; the output terminal of the fourth operational amplifier A4 is respectively connected to the second terminal of the sixth resistor R6, the second terminal of the third capacitor C3, and the first terminal of the eighth resistor R8; the second terminal of the eighth resistor R8 is connected to the second terminal of the fourth capacitor C4; the second terminal of the seventh resistor R7 is connected to the first terminal of the fourth capacitor C4; the first terminal of the fourth capacitor C4 is used to output the positive terminal signal V of the second differential voltageO+ The second end of the fourth capacitor C4 is used to output the negative end signal V of the second differential voltage. O- ;

[0076] The second differential voltage is a voltage obtained by processing the first differential voltage by the analog front-end circuit 200 .

[0077] In a specific embodiment, the third operational amplifier A3 and the fourth operational amplifier A4 are both gain amplifiers, and the fifth resistor R5, the sixth resistor R6, and the ninth resistor R9 are used to control the amplification factor of the second amplifier circuit 12. By setting these resistors to a suitable ratio, the overall amplification factor of the first amplifier circuit 11 and the second amplifier circuit 12 can be made 5 times.

[0078] The seventh resistor R7, the eighth resistor R8, and the fourth capacitor C4 form a differential passive first-order low-pass filter, and its cut-off frequency can be set to 100 Hz. The second capacitor C2 and the third capacitor C3 add an integral structure to the second amplifier circuit 12, and together with the following differential passive first-order low-pass filter, form a second-order anti-aliasing low-pass filter.

[0079] Among them, the tolerances of various components in the analog front-end circuit 200 are set as follows: the tolerances of the fourth resistor R4, the seventh resistor R7, and the eighth resistor R8 are all set to ±1%, and the tolerances of other resistors are all set to 1‰; the tolerances of all capacitors in the analog front-end circuit 200 are set to ±10%; Monte Carlo simulation analysis is performed on the above-mentioned analog front-end circuit 200, and the simulation results show that in the worst case (that is, the parameters of various components are in the most unfavorable combination), the common mode rejection ratio of the analog front-end circuit 200 is approximately 110dB, which is fully capable of meeting daily use.

[0080] The ADC acquisition module 102 is used to convert the second EEG signal into a digital signal to obtain a third EEG signal, and transmit the third EEG signal to the control module 104; the third EEG signal is a digital signal;

[0081] The blood oxygen detection module 103 is used to monitor the pulse wave and blood oxygen of the target object in real time within a first preset time period, obtain pulse data and blood oxygen data, and transmit the pulse data and blood oxygen data to the control module 104;

[0082] The control module 104 is used to obtain a preset stimulation scheme, adjust the preset stimulation scheme according to the third EEG signal, the pulse data and the blood oxygen data, and obtain a target stimulation scheme; determine a target control instruction corresponding to the target stimulation scheme; and transmit the target control instruction to the transcranial electrical stimulation module 105;

[0083] In the embodiment of the present application, the preset stimulation scheme can be preset or defaulted in advance.

[0084] In a specific embodiment, the control module 104 is used to obtain a preset stimulation scheme. Specifically, the preset stimulation scheme can be a stimulation scheme designed by a target doctor based on the target object's medical information, wherein the target doctor is a doctor who treats the target object; then, the preset stimulation scheme can be adjusted according to the third EEG signal, pulse data, and blood oxygen data to obtain a target stimulation scheme; determine the target control instruction corresponding to the target stimulation scheme, specifically, the mapping relationship between the preset stimulation scheme and the control instruction can be pre-stored, and the target control instruction corresponding to the preset stimulation scheme is determined based on the mapping relationship; then, the target control instruction can be transmitted to the transcranial electrical stimulation module 105 to control the transcranial electrical stimulation module 105 to stimulate the target object according to the target control instruction.

[0085] Optionally, the preset stimulation scheme includes: a preset stimulation current intensity and a preset stimulation duration. In adjusting the preset stimulation scheme according to the third EEG signal, the pulse data and the blood oxygen data to obtain a target stimulation scheme, the control module 104 is specifically used to:

[0086] C1. extracting a characteristic signal from the third EEG signal to obtain a target characteristic signal;

[0087] C2. determining a reference brain activity corresponding to the target characteristic signal;

[0088] C3. determining the heart rate variability corresponding to the pulse data according to the reference brain activity and the blood oxygen data to obtain a target heart rate variability;

[0089] C4. Determine the adjustment coefficient corresponding to the target heart rate variability to obtain the target adjustment coefficient;

[0090] C5. adjusting the preset stimulation current intensity and the preset stimulation duration according to the target adjustment coefficient to obtain a target stimulation current intensity and a target stimulation duration;

[0091] C6. Determine the target stimulation scheme according to the target stimulation current intensity and the target stimulation duration.

[0092] In the embodiment of the present application, the target characteristic signal may include at least one of the following: α wave, β wave, θ wave, δ wave, etc., which are not limited here; heart rate variability refers to the change in the difference between successive heartbeat cycles, which reflects the ability of the cardiac autonomic nervous system to regulate the heart rhythm.

[0093] In a specific embodiment, a characteristic signal in the third EEG signal can be extracted to obtain a target characteristic signal. For example, the target characteristic signal may be an alpha wave. Fourier transform may be used to convert the third EEG signal from the time domain to the frequency domain. In the frequency domain, the energy distribution of different frequency components may be intuitively observed. By analyzing the frequency domain signal, the energy size in the range of 8Hz to 13Hz may be determined, thereby extracting the characteristic signal of the alpha wave. Then, a reference brain activity corresponding to the target characteristic signal may be determined. Specifically, a mapping relationship between a preset characteristic signal and brain activity may be pre-stored, and a reference brain activity corresponding to the target characteristic signal may be determined based on the mapping relationship. Then, the heart rate variability corresponding to the pulse data may be determined based on the reference brain activity and blood oxygen data to obtain the target heart rate variability.

[0094] Further, the adjustment coefficient corresponding to the target heart rate variability can be determined to obtain the target adjustment coefficient. For example, a mapping relationship between a preset heart rate variability and an adjustment coefficient can be pre-stored, and the target adjustment coefficient corresponding to the target heart rate variability can be determined based on the mapping relationship. The value range of the target adjustment coefficient can be -0.3~0.3; then, the preset stimulation current intensity and the preset stimulation duration can be adjusted according to the target adjustment coefficient. The specific calculation formula is as follows:

[0095] Target stimulation current intensity = preset stimulation current intensity × (1 + target adjustment coefficient);

[0096] Target stimulation duration = preset stimulation duration × (1 + target adjustment coefficient);

[0097] According to the above formula, the target stimulation current intensity and the target stimulation duration can be obtained; then, the target stimulation scheme can be determined according to the target stimulation current intensity and the target stimulation duration.

[0098] In this way, by extracting the target characteristic signal from the third EEG signal; determining the reference brain activity corresponding to the target characteristic signal; determining the target heart rate variability corresponding to the pulse data based on the reference brain activity and blood oxygen data; determining the target adjustment coefficient corresponding to the target heart rate variability; adjusting the preset stimulation current intensity and the preset stimulation duration according to the target adjustment coefficient to obtain the target stimulation current intensity and the target stimulation duration; determining the target stimulation scheme based on the target stimulation current intensity and the target stimulation duration, determining the target adjustment coefficient based on the target heart rate variability, and adjusting the preset stimulation current intensity and the preset stimulation duration. This dynamic adjustment method can be optimized according to the individual's real-time physiological state, avoiding the inadaptability and risks that may be caused by fixed parameters, thereby improving the safety of transcranial electrical stimulation.

[0099] Optionally, in determining the heart rate variability corresponding to the pulse data according to the reference brain activity and the blood oxygen data to obtain the target heart rate variability, the control module 104 is specifically used to:

[0100] D1. Determine a target pulse waveform corresponding to the pulse data;

[0101] D2. Determine the peak value in the target pulse waveform to obtain j peak values ​​and j peak times; j is an integer greater than 1; each peak value corresponds to a peak time;

[0102] D3, calculating the time interval between every two adjacent peak values ​​among the j peak values, and obtaining j-1 time intervals;

[0103] D4, arranging the j-1 time intervals in time order to obtain a RR interval sequence;

[0104] D5. Analyze the RR interval sequence according to a preset analysis method to obtain a reference heart rate variability;

[0105] D6. Determine the target blood oxygen saturation corresponding to the blood oxygen data;

[0106] D7. Determine a target adjustment factor corresponding to the target blood oxygen saturation;

[0107] D8. Optimizing the reference brain activity according to the target adjustment factor to obtain a target brain activity;

[0108] D9, determining a target interference factor corresponding to the target brain activity;

[0109] D10. Adjust the reference heart rate variability according to the target interference factor to obtain the target heart rate variability.

[0110] In the embodiment of the present application, the RR interval sequence refers to a sequence composed of the time intervals between the peak values ​​of the R waves in two adjacent heartbeats; the preset analysis method can be one of the following: standard deviation method, root mean square error method, frequency domain analysis method, etc., which is not limited here.

[0111] In a specific embodiment, a target pulse waveform corresponding to the pulse data can be determined. Specifically, the pulse data can be sampled at equal time intervals to obtain multiple pulse values ​​and their corresponding pulse times. Then, curve fitting can be performed based on the multiple pulse values ​​and their corresponding pulse times to obtain the target pulse waveform. Next, the peak value in the target pulse waveform can be determined to obtain j peak values ​​and j peak times. Specifically, a differential method can be used to obtain j peak values ​​and j peak times. For example, the first-order difference and second-order difference of the target pulse waveform are calculated. The first-order difference can reflect the change in the slope of the waveform, and the second-order difference can reflect the change in curvature. When the first-order difference of a point changes from positive to negative and the second-order difference is less than zero, the point is judged to be a peak, and the pulse value and pulse time of the point, that is, the peak value and peak time, are recorded.

[0112] Next, the time interval between every two adjacent peak values ​​among the j peak values ​​can be calculated to obtain j-1 time intervals; then, the j-1 time intervals can be arranged in the time order of the peak values ​​to obtain the RR interval sequence; then, the RR interval sequence can be analyzed according to a preset analysis method to obtain a reference heart rate variability. Specifically, the preset analysis method can be a standard deviation method to calculate the target standard deviation of the RR interval sequence, and then, the reference heart rate variability is determined according to the target standard deviation. For example, a mapping relationship between a preset standard deviation and heart rate variability can be pre-stored, and a reference corresponding to the target standard deviation can be determined based on the mapping relationship. Heart rate variability; then, the target blood oxygen saturation corresponding to the blood oxygen data can be determined. Specifically, the blood oxygen data can contain multiple blood oxygen saturations, and the average of the multiple blood oxygen saturations can be calculated, and the average value is used as the target blood oxygen saturation; then, the target adjustment factor corresponding to the target blood oxygen saturation can be determined. Specifically, the mapping relationship between the preset blood oxygen saturation and the adjustment factor can be pre-stored, and the target adjustment factor corresponding to the target blood oxygen saturation is determined based on the mapping relationship. The value range of the target adjustment factor can be -0.1~0.1; then, the reference brain activity can be optimized according to the target adjustment factor. The specific calculation formula is as follows:

[0113] Target brain activity = reference brain activity × (1 + target adjustment factor);

[0114] According to the above formula, the target brain activity can be obtained; then, the target interference factor corresponding to the target brain activity can be determined. For example, a preset mapping relationship between brain activity and interference factor can be stored in advance, and the target interference factor corresponding to the target brain activity can be determined based on the mapping relationship. The value range of the target interference factor can be -0.5~0.5; finally, the reference heart rate variability can be adjusted according to the target interference factor. The specific calculation formula is as follows:

[0115] Target heart rate variability = reference heart rate variability × (1 + target interference factor);

[0116] The target heart rate variability can be obtained according to the above formula.

[0117] In this way, by determining the target pulse waveform corresponding to the pulse data; determining the peak value in the target pulse waveform to obtain j peak values ​​and j peak times; calculating the time interval between every two adjacent peak values ​​in the j peak values ​​to obtain j-1 time intervals; arranging the j-1 time intervals in chronological order to obtain the RR interval sequence; analyzing the RR interval sequence according to a preset analysis method to obtain a reference heart rate variability; determining the target blood oxygen saturation corresponding to the blood oxygen data; determining the target adjustment factor corresponding to the target blood oxygen saturation; optimizing the reference brain activity according to the target adjustment factor to obtain the target brain activity; determining the target interference factor corresponding to the target brain activity; adjusting the reference heart rate variability according to the target interference factor to obtain the target heart rate variability, and determining the target adjustment factor corresponding to the target blood oxygen saturation, the reference brain activity can be optimized according to the individual's blood oxygen situation. The blood oxygen saturation levels of different people may be different. By optimizing the brain activity in a targeted manner, it is possible to better adapt to individual differences, thereby improving the accuracy of the target brain activity.

[0118] Among them, the transcranial electrical stimulation module 105 is used to control the acquisition and stimulation integration module 106 to adopt a target stimulation scheme to perform transcranial electrical stimulation on the target object within a second preset time period according to the target control instruction, so as to enhance the stimulation effect of transcranial electrical stimulation on the target object; the starting time of the second preset time period is later than the ending time of the first preset time period.

[0119] Optionally, the device further comprises a right leg driving module 107, see Figure 4 , Figure 4 : is a circuit diagram of a right leg driving circuit 400 provided in an embodiment of the present application; the right leg driving module 107 is connected to the fourth end of the control module 104; the right leg driving module 107 includes a right leg driving circuit 400, and the right leg driving circuit 400 includes: a tenth resistor R10, an eleventh resistor R11, a twelfth resistor R12, a fifth operational amplifier A5, a sixth operational amplifier A6, and a fifth capacitor C5, wherein:

[0120] The first end of the tenth resistor R10 is connected to a preset common electrode Ecom, and the preset common electrode is set at a preset leg position of the target object. The second end of the tenth resistor R10 is respectively connected to the first end of the fifth capacitor C5, the first end of the eleventh resistor R11, and the output end of the fifth operational amplifier A5; the inverting input end of the fifth operational amplifier A5 is respectively connected to the second end of the fifth capacitor C5, the second end of the eleventh resistor R11, and the first end of the twelfth resistor R12, and the non-inverting input end of the fifth operational amplifier A5 is connected to a preset reference source Vref; the second end of the twelfth resistor R12 is respectively connected to the output end of the sixth operational amplifier A6 and the inverting input end of the sixth operational amplifier A6, and the non-inverting input end of the sixth operational amplifier A6 is connected to the reference end Eref of the preset instrument amplifier;

[0121] The right leg driving module 107 is used to extract the first common-mode voltage in the voltage signal collected by the integrated collection and stimulation module 106, reversely amplify the first common-mode voltage to obtain a second common-mode voltage, and feed the second common-mode voltage back to the target object, and suppress the common-mode voltage in the target object through the second common-mode voltage to improve the common-mode rejection ratio.

[0122] In the embodiment of the present application, the preset instrument amplifier, the preset reference source Vref, and the preset common electrode Ecom can be preset or defaulted in advance.

[0123] In a specific embodiment, the sixth operational amplifier A6 is a voltage follower to increase input impedance; in the case of low frequency, the fifth operational amplifier A5, the eleventh resistor R11, and the twelfth resistor R12 form an inverting amplifier with a gain of -R11 / R12, amplifying the common mode noise in the voltage signal and injecting it into the target object in reverse phase; the fifth capacitor C5 and the inverting amplifier together form a low-pass filter with a cutoff frequency of 1 / (2×π×R11×C5), and the fifth capacitor C5 not only limits the bandwidth of the inverting amplifier, but also improves the stability of the circuit. The tenth resistor R10 is a current limiting voltage, and its function is to ensure that the current flowing through the human body of the fifth operational amplifier A5 is within a safe range when it is saturated, but it should be noted that the existence of the tenth resistor R10 will also weaken the function of the right leg driving circuit 400.

[0124] Optionally, the integrated acquisition and stimulation module 106 includes n integrated acquisition and stimulation active electrodes, where n is an integer greater than 1; each integrated acquisition and stimulation active electrode corresponds to a working mode, and the working mode includes a stimulation mode or an acquisition mode. Figure 5 , Figure 5is a circuit diagram of a target acquisition stimulation integrated active electrode 500 provided in an embodiment of the present application, wherein the target acquisition stimulation integrated active electrode 500 is any one of n acquisition stimulation integrated active electrodes; Figure 5 As shown:

[0125] The target acquisition and stimulation integrated active electrode 500 comprises: a seventh operational amplifier A7, an eighth operational amplifier A8, a first analog switch S1, a second analog switch S2, a stimulation circuit 502, and an acquisition circuit 501. The target acquisition and stimulation integrated active electrode 500 is any one of a plurality of acquisition and stimulation integrated active electrodes;

[0126] The first end of the first analog switch S1 is connected to the first end of the second analog switch S2, the second end of the first analog switch S1 is connected to the non-inverting input end of the seventh operational amplifier A7, and the third end of the first analog switch S1 is connected to the inverting input end of the seventh operational amplifier A7; the output end of the seventh operational amplifier A7 is respectively connected to the acquisition circuit 501 and the non-inverting input end of the eighth operational amplifier A8, and the output end of the eighth operational amplifier A8 is connected to the second end of the second analog switch S2; the third end of the second analog switch S2 is connected to the stimulation circuit 502; the inverting input end of the eighth operational amplifier A8 can be grounded.

[0127] The target acquisition and stimulation integrated active electrode 500 is used to enter a corresponding working mode according to the switch states of the first analog switch S1 and the second analog switch S2. The working mode includes a stimulation mode or an acquisition mode.

[0128] In a specific embodiment, the stimulation circuit 502 is used to electrically stimulate the target object, the acquisition circuit 501 is used to acquire the EEG signal of the target object, and the seventh operational amplifier A7 and the first analog switch S1 constitute the electrode assembly 503. Figure 5 As shown, the cable design of the target acquisition and stimulation integrated active electrode 500 uses five cables, namely, a power line Vcc, a control line Ctr, an acquisition line Acq, a stimulation line Sti, and a ground line Gnd, as a bus of an integrated electrode.

[0129] The power line Vcc is used to provide working power for the entire target acquisition and stimulation integrated active electrode 500. Ensure that the acquisition circuit 501, the stimulation circuit 502, and the analog switch and other parts can operate normally. The control line Ctr is used to transmit control signals to control various operation modes of the target acquisition and stimulation integrated active electrode 500, for example, to control the on and off of the first analog switch S1 or the second analog switch S2 to determine whether to perform signal acquisition or stimulation output; the acquisition line Acq is used to transmit physiological signals (for example, EEG signals) from the target object to the acquisition circuit 501 for processing.

[0130] Among them, the stimulation line Sti is used to transmit the stimulation signal from the stimulation circuit 502 to the electrode assembly 503, and the target object is subjected to transcranial electrical stimulation through the electrode assembly 503. The stimulation line Sti can carry a current or voltage signal of a specific intensity, frequency and waveform, and act on the target tissue or organ through the electrode to achieve the purpose of treating, studying or regulating physiological functions. For example, in transcranial direct current stimulation, the stimulation line transmits a constant direct current to the scalp electrode, changes the membrane potential of brain neurons, and thus regulates the brain's neural activity. The ground line Gnd is grounded.

[0131] Optionally, entering a corresponding working mode according to the switch states of the first analog switch S1 and the second analog switch S2 includes:

[0132] When the first end of the first analog switch S1 is connected to the third end of the first analog switch S1, and the first end of the second analog switch S2 is connected to the second end of the second analog switch S2, the working mode of the target acquisition stimulation integrated active electrode 500 is the acquisition mode;

[0133] When the first end of the first analog switch S1 is connected to the second end of the first analog switch S1, and the first end of the second analog switch S2 is connected to the third end of the second analog switch S2, the working mode of the target acquisition and stimulation integrated active electrode 500 is the stimulation mode.

[0134] It can be seen that by implementing the transcranial electrical stimulation device based on multimodal data provided by an embodiment of the present invention, multimodal data such as EEG signals, pulse data, blood oxygen data, etc. of the target object are first collected, and then the preset stimulation scheme is obtained through the control module, and the preset stimulation scheme is adjusted according to the third EEG signal, pulse data and blood oxygen data to obtain the target stimulation scheme, and the target control instruction corresponding to the target stimulation scheme is determined; the target control instruction is transmitted to the transcranial electrical stimulation module, and the transcranial electrical stimulation module controls the acquisition and stimulation integration module according to the target control instruction to perform transcranial electrical stimulation on the target object using the target stimulation scheme to enhance the stimulation effect of transcranial electrical stimulation on the target object. These multimodal data provide physiological information of the target object from different angles, and the stimulation parameters of the transcranial electrical stimulation module are adjusted according to the physiological information, which can ensure that the stimulation therapy is carried out within a safe and effective range, thereby improving the stability of tES stimulation therapy.

[0135] An embodiment of the present application also provides a transcranial electrical stimulation system based on multimodal data, the system comprising a transcranial electrical stimulation device based on multimodal data as described in any one of the above embodiments.

[0136] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0137] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0138] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0139] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0140] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0141] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the above-mentioned methods in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0142] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A transcranial electrical stimulation device based on multimodal data, characterized in that: The device comprises: an analog front-end module, an ADC acquisition module, a blood oxygen detection module, a control module, a transcranial electrical stimulation module, and an acquisition and stimulation integrated module, wherein: The first end of the analog front-end module is connected to the first end of the integrated acquisition and stimulation module, and the second end of the analog front-end module is connected to the first end of the ADC acquisition module; the second end of the ADC acquisition module is connected to the first end of the control module, and the second end of the control module is connected to the second end of the transcranial electrical stimulation module; the first end of the transcranial electrical stimulation module is connected to the second end of the integrated acquisition and stimulation module; the third end of the control module is connected to the blood oxygen detection module; The analog front-end module is used to collect a first EEG signal of the target object through the integrated collection and stimulation module within a first preset time period, and filter and amplify the first EEG signal to obtain a second EEG signal; the second EEG signal is an analog signal; The ADC acquisition module is used to convert the second EEG signal into a digital signal to obtain a third EEG signal, and transmit the third EEG signal to the control module; the third EEG signal is a digital signal; The blood oxygen detection module is used to monitor the pulse wave and blood oxygen of the target object in real time within the first preset time period, obtain pulse data and blood oxygen data, and transmit the pulse data and the blood oxygen data to the control module; The control module is used to obtain a preset stimulation scheme, adjust the preset stimulation scheme according to the third EEG signal, the pulse data and the blood oxygen data to obtain a target stimulation scheme; determine a target control instruction corresponding to the target stimulation scheme; and transmit the target control instruction to the transcranial electrical stimulation module; The transcranial electrical stimulation module is used to control the integrated acquisition and stimulation module to perform transcranial electrical stimulation on the target object using the target stimulation scheme according to the target control instruction within a second preset time period, so as to enhance the stimulation effect of transcranial electrical stimulation on the target object; the start time of the second preset time period is later than the end time of the first preset time period; The integrated acquisition and stimulation module includes n integrated acquisition and stimulation active electrodes, where n is an integer greater than 1; each integrated acquisition and stimulation active electrode corresponds to a working mode, and the working mode includes a stimulation mode or an acquisition mode; Wherein, in the aspect of collecting the first EEG signal of the target object through the integrated collection and stimulation module, the analog front-end module is specifically used for: Obtaining electrode positions corresponding to the n integrated collection and stimulation active electrodes in the integrated collection and stimulation module to obtain n electrode positions; each integrated collection and stimulation active electrode corresponds to one electrode position; Acquire the historical acquisition data corresponding to the acquisition and stimulation integration module; Determine the acquisition data of the n integrated acquisition and stimulation active electrodes according to the historical acquisition data to obtain n acquisition data; each integrated acquisition and stimulation active electrode corresponds to one acquisition data; Determine a first data quality parameter corresponding to each of the n collected data to obtain n first data quality parameters; Determine the optimization factor corresponding to each electrode position of the n electrode positions to obtain n optimization factors; Adjusting corresponding first data quality parameters among the n first data quality parameters according to the n optimization factors to obtain n second data quality parameters; Determine the number m of collection electrodes corresponding to the preset required amount of EEG data; m is a positive integer less than n; Determine the priority order corresponding to the n second data quality parameters to obtain a target priority order; the larger the second data quality parameter, the higher the priority order; Selecting m integrated collection and stimulation active electrodes from the n integrated collection and stimulation active electrodes according to the target priority order; Collecting the EEG signal of the target object through the m integrated collection and stimulation active electrodes to obtain the first EEG signal; Wherein, in determining the first data quality parameter corresponding to each of the n collected data to obtain n first data quality parameters, the analog front-end module is specifically used for: Acquire target acquisition data and target electrode; the target acquisition data is any one of the n acquisition data; the target electrode is the electrode corresponding to the target acquisition data in the n integrated acquisition and stimulation active electrodes; Determining a target signal-to-noise ratio corresponding to the target acquisition data; Determining a reference data quality parameter corresponding to the target signal-to-noise ratio; Obtaining a target sampling rate corresponding to the target electrode; Obtaining the maximum data value and the minimum data value in the target collected data; Determine a difference between the maximum data value and the minimum data value to obtain a target difference; Determine a first influence coefficient corresponding to the target sampling rate; Determining a second influence coefficient corresponding to the target difference; Determine a first data quality parameter corresponding to the target acquisition data according to the first influence coefficient, the second influence coefficient and the reference data quality parameter; Wherein, the preset stimulation scheme includes: a preset stimulation current intensity and a preset stimulation duration. In terms of adjusting the preset stimulation scheme according to the third EEG signal, the pulse data and the blood oxygen data to obtain a target stimulation scheme, the control module is specifically used to: Extracting a characteristic signal from the third EEG signal to obtain a target characteristic signal; Determining a reference brain activity corresponding to the target characteristic signal; determining the heart rate variability corresponding to the pulse data according to the reference brain activity and the blood oxygen data to obtain a target heart rate variability; Determining an adjustment coefficient corresponding to the target heart rate variability to obtain a target adjustment coefficient; Adjusting the preset stimulation current intensity and the preset stimulation duration according to the target adjustment coefficient to obtain a target stimulation current intensity and a target stimulation duration; Determining the target stimulation scheme according to the target stimulation current intensity and the target stimulation duration; Wherein, in determining the heart rate variability corresponding to the pulse data according to the reference brain activity and the blood oxygen data to obtain the target heart rate variability, the control module is specifically used for: determining a target pulse waveform corresponding to the pulse data; Determine the peak value in the target pulse waveform to obtain j peak values ​​and j peak times; j is an integer greater than 1; each peak value corresponds to a peak time; Calculate the time interval between every two adjacent peak values ​​of the j peak values ​​to obtain j-1 time intervals; Arrange the j-1 time intervals in time order to obtain a RR interval sequence; Analyze the RR interval sequence according to a preset analysis method to obtain a reference heart rate variability; Determining a target blood oxygen saturation corresponding to the blood oxygen data; Determining a target adjustment factor corresponding to the target blood oxygen saturation; Optimizing the reference brain activity according to the target adjustment factor to obtain a target brain activity; determining a target interference factor corresponding to the target brain activity; The reference heart rate variability is adjusted according to the target interference factor to obtain the target heart rate variability.

2. The device according to claim 1, characterized in that The analog front-end module includes an analog front-end circuit, which includes a first amplifier circuit and a second amplifier circuit; the first amplifier circuit is connected to the second amplifier circuit; the first amplifier circuit includes: a first operational amplifier, a second operational amplifier, a first resistor, a second resistor, a third resistor, a fourth resistor, and a first capacitor; wherein: The non-inverting input terminal of the first operational amplifier is used to receive the positive end signal of the first differential voltage; the non-inverting input terminal of the second operational amplifier is used to receive the negative end signal of the first differential voltage; the inverting input terminal of the first operational amplifier is respectively connected to the first end of the first resistor and the first end of the third resistor, and the output terminal of the first operational amplifier is respectively connected to the second end of the first resistor and the first end of the first capacitor; the second end of the third resistor is respectively connected to the first end of the second resistor and the inverting input terminal of the second operational amplifier; the second end of the second resistor is respectively connected to the output terminal of the second operational amplifier, the second end of the fourth resistor, and the first end of the second amplifier circuit; the first end of the fourth resistor is respectively connected to the second end of the first capacitor and the second end of the second amplifier circuit; The first differential voltage is the voltage collected by the integrated collection and stimulation module.

3. The device according to claim 2, characterized in that The second amplifier circuit includes: a third operational amplifier, a fourth operational amplifier, a fifth resistor, a sixth resistor, a seventh resistor, an eighth resistor, a ninth resistor, a second capacitor, a third capacitor, and a fourth capacitor, wherein: The non-inverting input terminal of the third operational amplifier serves as the first terminal of the second amplifier circuit; the inverting input terminal of the third operational amplifier is respectively connected to the first terminal of the fifth resistor, the first terminal of the ninth resistor, and the first terminal of the second capacitor; the output terminal of the third operational amplifier is respectively connected to the second terminal of the fifth resistor, the second terminal of the second capacitor, and the first terminal of the seventh resistor; the second terminal of the ninth resistor is respectively connected to the first terminal of the third capacitor, the first terminal of the sixth resistor, and the inverting input terminal of the fourth operational amplifier; the non-inverting input terminal of the fourth operational amplifier serves as the second terminal of the second amplifier circuit; the output terminal of the fourth operational amplifier is respectively connected to the second terminal of the sixth resistor, the second terminal of the third capacitor, and the first terminal of the eighth resistor; the second terminal of the eighth resistor is connected to the second terminal of the fourth capacitor; the second terminal of the seventh resistor is connected to the first terminal of the fourth capacitor; the first terminal of the fourth capacitor is used to output the positive terminal signal of the second differential voltage, and the second terminal of the fourth capacitor is used to output the negative terminal signal of the second differential voltage; The second differential voltage is a voltage obtained by processing the first differential voltage by the analog front-end circuit.

4. The device according to any one of claims 1 to 3, characterized in that: The device further includes a right leg driving module, which is connected to the fourth end of the control module; the right leg driving module includes a right leg driving circuit, which includes: a tenth resistor, an eleventh resistor, a twelfth resistor, a fifth operational amplifier, a sixth operational amplifier, and a fifth capacitor, wherein: The first end of the tenth resistor is connected to a preset common electrode, which is arranged at a preset leg position of the target object; the second end of the tenth resistor is respectively connected to the first end of the fifth capacitor, the first end of the eleventh resistor, and the output end of the fifth operational amplifier; the inverting input end of the fifth operational amplifier is respectively connected to the second end of the fifth capacitor, the second end of the eleventh resistor, and the first end of the twelfth resistor, and the non-inverting input end of the fifth operational amplifier is connected to a preset reference source; the second end of the twelfth resistor is respectively connected to the output end of the sixth operational amplifier and the inverting input end of the sixth operational amplifier, and the non-inverting input end of the sixth operational amplifier is connected to the reference end of a preset instrumentation amplifier; The right leg driving module is used to extract the first common-mode voltage in the voltage signal collected by the integrated collection and stimulation module, reversely amplify the first common-mode voltage to obtain a second common-mode voltage, and feed the second common-mode voltage back to the target object, and suppress the common-mode voltage in the target object through the second common-mode voltage to improve the common-mode rejection ratio.

5. A transcranial electrical stimulation system based on multimodal data, characterized in that: The system includes the transcranial electrical stimulation device based on multimodal data as described in any one of claims 1-4.

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