Signal acquisition device, control method, electronic equipment and storage medium

Abstract

The invention discloses a signal acquisition device, a control method, electronic equipment and a storage medium. The device comprises an in-vivo machine, the first electrode is connected with the in-vivo machine and used for collecting cortical electroencephalogram signals; the second electrode is connected with the in-vivo machine and is used for collecting a single neuron action nerve peak potential signal; the third electrode is connected with the in-vivo machine and is used for collecting a stereotactic deep brain region electroencephalogram signal; wherein the in-vivo machine is used for feeding back a neural signal to an external main control device and receiving an electrode control signal of the external main control device, and the neural signal is acquired by the first electrode and / or the third electrode. The technical problem that in the prior art, cross-brain-region multi-mode neural signals are difficult to collect and process is solved.

Description

Technical Field

[0001] This invention relates to the field of brain-computer interface technology, and more specifically, to a signal acquisition device, control method, electronic device, and storage medium. Background Technology

[0002] In the field of Brain-Computer Interface (BCI), existing technologies primarily employ two invasive electrode recording methods: ECoG (Electrocorticography) and SPIKE (Peak Potential Electrodes) to acquire brain electrical signals. ECoG electrodes are typically placed on the surface of the cerebral cortex or under the dura mater to record the collective electrical activity of thousands of neurons in a localized area of ​​the cortex. Because they can cover a relatively large brain region, they are widely used in scenarios such as decoding motor intentions. However, ECoG electrodes have limited spatial resolution and cannot accurately record the activity of individual neurons, creating a bottleneck for achieving high-precision decoding of intentions. SPIKE electrodes, on the other hand, are implanted directly into brain tissue to record the action potentials of individual neurons. This signal can decode the contribution of a single neuron to motor intentions, thereby enabling high-precision control of peripherals such as robotic arms. However, the implantation depth and acquisition range of SPIKE electrodes are limited, covering only relatively localized brain regions. SEEG (Stereoelectroencephalography) electrodes can record electrical activity in deep brain regions such as the hippocampus and thalamus, which is crucial for monitoring and locating deep epileptic foci. However, the implantation sites of SEEG electrodes are fixed and singular, making it difficult to perform correlation analysis with signals from the cerebral cortex or superficial cortex, thus limiting research on neural circuits and the transmission mechanisms of epilepsy.

[0003] In fields such as motor rehabilitation, cognitive function monitoring and treatment, single-electrode recording methods cannot meet the requirements of covering the entire brain, providing high-precision signals, and adapting to diverse rehabilitation needs. Especially in the monitoring and treatment of brain diseases, current technologies lack effective technical pathways and cannot provide precise intervention when abnormal neural activity is detected. Therefore, existing technologies face technical challenges in acquiring and processing multimodal neural signals across brain regions.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides a signal acquisition device, control method, electronic device, and storage medium to at least solve the technical problem of difficulty in acquiring and processing multimodal neural signals across brain regions in the prior art.

[0006] According to one aspect of the present invention, a signal acquisition device is provided, comprising: an in vivo machine; a first electrode connected to the in vivo machine for acquiring cortical electroencephalogram (EEG) signals; a second electrode connected to the in vivo machine for acquiring single neuronal spike potential signals; and a third electrode connected to the in vivo machine for acquiring stereotactic deep brain region EEG signals; wherein the in vivo machine is used to feed back neural signals to an external main control device and receive electrode control signals from the external main control device, and the neural signals are acquired by the first electrode and / or the third electrode.

[0007] Optionally, the second electrode and the first electrode have an angle between them.

[0008] Optionally, the binding sites of the first electrode and the second electrode are eccentric structures.

[0009] Optionally, the binding region in the in vivo device that binds to the electrode has an equally divided structure.

[0010] According to another aspect of the present invention, a signal acquisition device control method is provided, comprising: acquiring neural signals of a subject acquired by a first electrode and a third electrode; determining the current state of the subject based on the neural signals; and controlling the working state of at least one of the first electrode, the second electrode, and the third electrode based on the current state.

[0011] Optionally, controlling the operating state of at least one of the first electrode, the second electrode, and the third electrode according to the current state includes: matching the current state with a preset control strategy lookup table to obtain a target control strategy, wherein the preset control strategy lookup table is used to characterize the correspondence between the current state and the control strategy; and controlling the operating state of at least one of the first electrode, the second electrode, and the third electrode according to the target control strategy.

[0012] Optionally, according to the target control strategy, controlling the working state of at least one of the first electrode, the second electrode, and the third electrode includes: in response to the current state being a first motor state, the target control strategy is to control the first electrode to work to acquire a first neural signal, wherein the first motor state is used to characterize the movement of the subject's first motor part, and the first neural signal is used to control the movement of the first motor part; in response to the current state changing from the first motor state to a second motor state, the target control strategy is to control the second electrode to work to acquire a second neural signal, wherein the second motor state is used to characterize the movement of the subject's second motor part, and the second neural signal is used to control the movement of the second motor part; wherein the fineness of the movement of the first motor part is less than the fineness of the movement of the second motor part.

[0013] Optionally, according to the target control strategy, controlling the working state of at least one of the first electrode, the second electrode, and the third electrode includes: responding to the current state being a first control state, the target control strategy is to control the first electrode to work to acquire a third neural signal, wherein the first control state is used to characterize the state in which the subject controls the large-range movement of the peripheral device, and the third neural signal is used to control the large-range movement of the peripheral device, wherein the large-range movement is a movement with a movement amplitude greater than a first preset movement amplitude; responding to the current state changing from the first control state to the second control state, the target control strategy is to control the second electrode to work to acquire a fourth neural signal, wherein the second control state is used to characterize the subject's small-range movement of the peripheral device, and the fourth neural signal is used to control the small-range movement of the peripheral device, wherein the small-range movement is a movement with a movement amplitude less than a second preset movement amplitude.

[0014] Optionally, according to the target control strategy, controlling the working state of at least one of the first electrode, the second electrode, and the third electrode includes: responding to the current state being a first preset mental state, the target control strategy is to control the third electrode to enter an electrical stimulation mode to periodically electrically stimulate deep nuclei and acquire monitoring neural signals through the first and third electrodes, wherein the first preset mental state is used to characterize the subject's abnormal emotional fluctuations and cognitive dysfunction; determining the process mental state during the electrical stimulation process based on the monitoring neural signals; responding to the process mental state being a second preset mental state, the target control strategy is to control the third electrode to exit the electrical stimulation mode, wherein the second preset mental state is used to characterize the subject's normal emotional fluctuations and normal cognitive function.

[0015] Optionally, controlling the working state of at least one of the first electrode, the second electrode, and the third electrode according to the current state includes: determining the brain functional area corresponding to the current state; determining the target controlled electrode from the first electrode, the second electrode, and the third electrode according to the brain functional area; and controlling the target controlled electrode to acquire target neural signals and to electrically stimulate the brain functional area according to the target neural signals.

[0016] According to another aspect of the present invention, an electronic device is also provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods of various embodiments of the present invention during runtime.

[0017] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is executed, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of the present invention.

[0018] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the methods of various embodiments of the present invention.

[0019] According to another aspect of the present invention, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods of various embodiments of the present invention.

[0020] According to another aspect of the present invention, a computer program is also provided, which, when executed by a processor, implements the methods of the various embodiments of the present invention.

[0021] In this embodiment of the invention, the signal acquisition device includes: an in vivo machine; a first electrode connected to the in vivo machine for acquiring cortical electroencephalogram (EEG) signals; a second electrode connected to the in vivo machine for acquiring single neuronal spike potential signals; and a third electrode connected to the in vivo machine for acquiring stereotactic deep brain region EEG signals. The in vivo machine is used to feed back neural signals to an external control device and receive electrode control signals from the external control device. The neural signals are acquired by the first electrode and / or the third electrode. This application achieves comprehensive coverage of the cerebral cortex, superficial cortical areas, and deep nuclei by integrating multimodal electrodes and the in vivo machine for signal acquisition. While optimizing signal acquisition, it dynamically adjusts the electrode working state to adapt to different rehabilitation stages and subject needs. This achieves the goal of efficient and accurate acquisition and processing of signals from different brain regions through the intelligent control of multimodal electrodes, the in vivo machine, and the external control device, thereby realizing comprehensive signal acquisition and personalized rehabilitation strategies. This solves the technical problem of difficulty in acquiring and processing multimodal neural signals across brain regions in the prior art. Attached Figure Description

[0022] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0023] Figure 1 This is a schematic diagram of the structure of a signal acquisition device according to an embodiment of the present invention;

[0024] Figure 2 This is an example diagram of a signal acquisition device implanted according to an embodiment of the present invention;

[0025] Figure 3 This is an example diagram of an electrode structure provided according to an embodiment of the present invention;

[0026] Figure 4This is another example diagram of an electrode structure provided according to an embodiment of the present invention;

[0027] Figure 5 This is an example diagram of an in vivo binding region provided by an embodiment of the present invention;

[0028] Figure 6 This is another example diagram of an in vivo binding region provided by an embodiment of the present invention;

[0029] Figure 7 This is a flowchart illustrating a signal acquisition device control method according to an embodiment of the present invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicating orientation or positional relationships are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention.

[0033] Figure 1This is a schematic diagram of the structure of a signal acquisition device according to an embodiment of the present invention, as shown below. Figure 1 As shown, the device consists of an in vivo machine 1; a first electrode 2, connected to the in vivo machine 1, used to collect cortical electroencephalogram (EEG) signals; a second electrode 3, connected to the in vivo machine 1, used to collect nerve spike potential signals of a single neuron; and a third electrode 4, connected to the in vivo machine 1, used to collect stereotactic deep brain region EEG signals. The in vivo machine 1 is used to feed back neural signals to an external main control device and receive electrode control signals from the external main control device. The neural signals are collected by the first electrode 2 and / or the third electrode 4.

[0034] Internal Unit 1: As the core of the entire signal acquisition device, Internal Unit 1 connects to the first electrode 2, the second electrode 3, and the third electrode 4 to complete the acquisition of multimodal signals. Simultaneously, Internal Unit 1 also receives electrode control signals sent by the external main control device, which are used to control the working state of the first electrode 2, the second electrode 3, and the third electrode 4.

[0035] Optionally, the external main control device has a built-in microprocessor and signal processing circuitry, capable of receiving, analyzing, and responding to cortical EEG and stereotactic deep brain region EEG signals from the first electrode 2 and the third electrode 4. Based on the signal characteristics and the subject's current rehabilitation stage, it intelligently adjusts the electrode's operating mode, including cortical EEG signal acquisition from the first electrode 2, single neuronal spike potential signal acquisition from the second electrode 3, and stereotactic deep brain region EEG signal acquisition from the third electrode 4. The external main control device sends electrode control signals to the in vivo machine 1, achieving intelligent control capabilities and flexibly switching between different EEG signals to achieve precise signal acquisition and efficient data processing.

[0036] The first electrode 2 is connected to the internal machine 1 and is used to collect cortical electroencephalogram (EEG) signals, i.e., electrical signals on the surface of the cerebral cortex. These signals are related to higher cognitive functions (learning, attention, decision-making, etc.), motor functions, language functions, and visual functions. By collecting data through the first electrode, macroscopic electrical activity information of brain functional areas can be obtained in a timely manner, providing a basis for subsequent signal analysis and rehabilitation strategy formulation. In addition, the first electrode 2 can also provide electrical stimulation to the cortex according to actual stimulation needs.

[0037] The second electrode 3 is also connected to the internal organ 1, but its purpose is to collect the spike potential signal of a single neuron, i.e., the SPIKE signal. The SPIKE signal can capture the firing activity of a single neuron, providing more detailed information than cortical EEG compared to the function of the first electrode 2, which is used to achieve fine motor control, decoding of higher cognitive functions, etc. The use of the second electrode 3 increases the dimension of signal acquisition. In addition, the second electrode 3 can also perform electrical stimulation at the single neuron level according to actual stimulation needs.

[0038] Third electrode 4: The third electrode 4 is connected to the in vivo machine 1 and is used to acquire stereotactic deep brain region electroencephalogram (SEEG) signals. SEEG signals can record the electrical activity of deep brain structures and are used to study the function of deep nuclei, monitor and treat deep brain diseases. The use of the third electrode 4 enables the signal acquisition capability of this embodiment to cover the entire brain, including the cortex and deep structures.

[0039] In this embodiment, the in vivo machine 1 can acquire multimodal neural signals and send them to an external main control device. The external main control device can analyze the neural signals and, based on the analysis results, send electrode control signals to control the working states of the first electrode, the second electrode 3, and the third electrode 4, thus achieving dynamic adjustment of signal acquisition. This dynamic adjustment method not only improves the efficiency and quality of signal acquisition but also reduces the power consumption of the device, enabling cross-brain region signal acquisition and the diversity of acquired signals. Through the multimodal signal acquisition function of the in vivo machine 1, this embodiment can achieve comprehensive monitoring of different functional areas and depths of the brain, providing subjects with personalized rehabilitation plans and disease management strategies, and improving the application effect and subject experience of brain-computer interfaces in the medical and rehabilitation fields.

[0040] In this embodiment of the invention, the signal acquisition device includes: an in vivo machine 1; a first electrode 2, connected to the in vivo machine 1, for acquiring cortical electroencephalogram (EEG) signals; a second electrode 3, connected to the in vivo machine 1, for acquiring single neuronal spike potential signals; and a third electrode 4, connected to the in vivo machine 1, for acquiring stereotactic deep brain region EEG signals. The in vivo machine is used to feed back neural signals to an external control device and receive electrode control signals from the external control device. The neural signals are acquired by the first electrode and / or the third electrode. This application, by integrating multimodal electrodes with the in vivo machine for signal acquisition, achieves comprehensive coverage of the cerebral cortex, superficial cortical areas, and deep nuclei. While optimizing signal acquisition, it dynamically adjusts the electrode working state to adapt to different rehabilitation stages and subject needs. This achieves the goal of efficient and accurate acquisition and processing of signals from different brain regions through the combination of multimodal electrodes and the in vivo machine, and intelligent control by the external control device, thereby realizing the comprehensiveness of signal acquisition and the personalization of rehabilitation strategies. Furthermore, it solves the technical problem of difficulty in acquiring and processing multimodal neural signals across brain regions in the prior art.

[0041] Optionally, in some embodiments of the present invention, as shown in the appendix Figure 1 The electrodes shown differ; the second electrode 3 can be a Utah electrode or a flexible microfilament electrode. The first electrode 2 can be a cortical EEG electrode, an interventional electrode, or an EEG electrode.

[0042] The Utah electrode is a microarray electrode with multiple tiny electrode pins used to acquire electrical activity signals from the cerebral cortex or superficial cortex, suitable for recording the spike potentials of single neurons. Due to its high-density pin design, the Utah electrode can provide high-resolution signal acquisition of localized brain regions, which is crucial for analyzing the brain's fine neural activity. In this embodiment, the Utah electrode can be selected as the second electrode 3 to provide basic data for subsequent signal processing and decoding.

[0043] Flexible microfilament electrodes are used to record action potential signals of neurons, that is, the brief potential changes when a neuron is excited. Flexible microfilament electrodes have extremely high temporal and spatial resolution, enabling precise capture of the firing events of individual neurons. In this embodiment, a flexible microfilament electrode can be selected as the second electrode 3 for precise acquisition of neural spike potential signals in the motor cortex or other key brain regions, enabling the interpretation and control of the subject's motor intentions.

[0044] Electrocorticometry (ECoG) electrodes are used to directly contact the surface of the cerebral cortex to collect macroscopic cortical electrical activity signals. Compared to scalp EEG electrodes, ECoG electrodes provide clearer signals with a higher signal-to-noise ratio, reflecting the average effect of large-area neural activity in the cerebral cortex. In this embodiment, an ECoG electrode can be used as the first electrode 2, capable of capturing a wide range of signals from the cerebral cortex, providing important information for understanding the overall state of the brain and developing rehabilitation strategies.

[0045] Based on the description of the above embodiments, the embodiments of this application can flexibly select the most suitable electrode type for signal acquisition according to the characteristics of different brain regions and the needs of the rehabilitation stage. This greatly improves the pertinence and effectiveness of signal acquisition and avoids the problems of signal ambiguity or insufficient acquisition that may be caused by general-purpose electrodes.

[0046] In practical applications, such as sports rehabilitation, the embodiments of this application can intelligently adjust the electrode type according to the rehabilitation stage of the subject. In the initial stage, electrocorticography (ECoG) electrodes can be used preferentially to collect cortical signals to control larger muscle groups. As the rehabilitation progresses, flexible microfilament electrodes or Utah electrodes are used to record single neuron activity to achieve control of fine motor skills, such as finger movement training. It is understood that, depending on the actual rehabilitation needs, ECOG electrodes, flexible microfilament electrodes, and Utah electrodes can be used alternately to collect neural signals or perform electrical stimulation.

[0047] This application embodiment achieves refined management and high-resolution capture of signals from the cerebral cortex by selecting the electrode types of the first electrode 2 and the second electrode 3, providing technical support for the formulation and implementation of personalized rehabilitation plans, significantly improving the application effect of brain-computer interfaces in motor rehabilitation, cognitive function recovery and other fields, ensuring the quality and diversity of signal acquisition, and meeting the specific needs of rehabilitation treatment at different stages.

[0048] Optionally, the second electrode 3 and the first electrode 2 have an included angle.

[0049] In this embodiment, the second electrode 3 and the first electrode 2 are designed with a certain angle between them. This angle design enables the acquisition of EEG signals from different brain regions or different types of EEG signals from the same brain region. For example, while the first electrode 2 acquires cortical signals, the second electrode 3 can also more accurately locate the action potential signal of the single neuron of interest. This design, based on innovative spatial layout, also ensures the complementarity of signal types.

[0050] Optionally, in some embodiments of the present invention, the angle between the second electrode 3 and the first electrode 2 is 0 degrees or 180 degrees, so as to realize signal acquisition at different depths within the same brain region and across brain regions.

[0051] For example, during the implantation of the signal acquisition device, the first electrode 2 is first placed above / below the cerebral cortex, above / below the dura mater, above / below the skull, or inside a cerebral blood vessel. Then, the second electrode 3 is inserted into the cerebral cortex or deeper at a pre-designed angle. This angle setting ensures that the first electrode 2 and the second electrode 3 accurately enter their respective predetermined brain regions. In actual operation, the first electrode 2 and the second electrode 3 work independently or simultaneously based on the electrode control signals received by the in vivo machine 1. The first electrode 2 acquires signals over a wide area of ​​the cortex, while the second electrode 3 focuses on the activity of a single neuron or a specific neural cluster, forming a multi-layered signal acquisition system in space.

[0052] Understandably, the angle design between the second electrode 3 and the first electrode 2 is more conducive to realizing cross-brain region implantation of electrodes and cross-brain region signal acquisition.

[0053] Optionally, the binding sites of the first electrode 2 and the second electrode 3 are eccentric structures.

[0054] In this embodiment, the binding sites of the first electrode 2 and the second electrode 3 adopt an eccentric structure design, meaning that the fixing points of the electrodes are outside the center point of the main body of the internal organ 1, forming an asymmetrical layout. This design ensures that the second electrode 3 is accurately positioned in a specific brain region below the first electrode 2 during implantation, enabling the acquisition of cortical signals and deep single neuron signals targeting the same brain region, achieving signal complementarity, and thus enabling more refined rehabilitation treatment plans. Simultaneously, the eccentric structure helps avoid direct contact between the binding areas of the two electrodes, reducing the risk of signal aliasing.

[0055] Reference Figure 2 , Figure 3 and Figure 4 Optionally, in some embodiments of the present invention, due to the eccentric design of the binding sites of the first electrode 2 and the second electrode 3, referring to Figure 2 The first electrode 2 and the second electrode 3 can be positioned vertically within the same region of the in vivo machine 1, allowing them to be implanted into the same brain functional area. Furthermore, the third electrode 4 is implanted and covers the longitudinal functional area of ​​the brain, enabling the recording of a large range of neural activity at a larger site while maintaining a low sampling rate for continuous acquisition. Figure 3 The first binding point 21 of the first electrode 2 is located off-center on one side of the electrode. Figure 4 The second binding site 31 of the second electrode 3 is located off-center on one side of the electrode. For example, the second electrode 3 is implanted in the motor function area, and the first electrode 2 is implanted in the dura mater above / below the dura mater, above / below the skull, above / below the cortex, or inside the cerebral blood vessels corresponding to the motor function area.

[0056] For example, ECoG signals have a lower sampling rate and lower implant power consumption. SPIKE signals have a higher sampling rate and higher implant power consumption. The subjects' motor rehabilitation strategy is to first rehabilitate large muscle groups in the early stages of stroke or hemiplegia, and then rehabilitate small muscle groups in the later stages. Rehabilitation of large muscle groups can be controlled by ECoG signals to control peripheral devices (pneumatic gloves, upper and lower limb exoskeletons). Later fine motor control does not use ECoG signals or ECoG signals are used to mobilize large muscle groups. For example, fine motor movements of the fingers are controlled by SPIKE signals to decode and control a robotic hand for motor rehabilitation. In addition, during the rehabilitation phase, ECoG signals and SPIKE signals can be used alternately according to rehabilitation needs. On the other hand, long-term acquisition of SPIKE signals by the implant increases the power consumption of the device, which can lead to a rise in device temperature. Therefore, time-sharing acquisition is performed (low-power ECoG for large muscle group rehabilitation, and high-sampling-rate SPIKE signals for fine motor rehabilitation). Specifically, 4*4 SPIKE electrodes are implanted in the motor functional area, and ECoG electrodes are then attached to the dura mater corresponding to this area, thereby realizing time-sharing acquisition and processing of EEG signals. While balancing power consumption, it avoids the risk of secondary implantation, resulting in higher system integration. Optionally, it offers 512 ECoG electrode sites and 512 SPIKE acquisition sites. Distinguishing between ECoG and SPIKE signals can be achieved through full-time signal acquisition and downsampling techniques, or the 512 ECoG electrode sites or 512 SPIKE sites can be acquired separately via hardware. Signal aliasing is avoided.

[0057] Optionally, the binding region 11 in the in vivo machine 1 that is bound to the electrode has an equally divided structure.

[0058] The binding region 11 refers to a specific part on the in vivo machine 1 that is connected to the electrode. In this embodiment, an equal division structure is adopted, which can evenly divide the binding region 11 into multiple parts, each part being used to bind a specific type of electrode. This design ensures a reasonable spatial layout between the electrodes, avoids physical interference between the electrodes, and enables the in vivo machine 1 to efficiently collect multimodal neural signals.

[0059] When implanted into the in vivo machine 1, a binding region 11 with an equally divided structure is designed, so that each electrode (first electrode 2, second electrode 3, and third electrode 4) can find its exclusive binding site on the in vivo machine 1. For example, refer to... Figure 5 and Figure 6 The feedthrough at the bottom of the in vivo unit 1 is designed as a binding structure that is divided into half or four equal parts, which makes it easy to arrange the electrode binding reasonably according to the electrode distribution pattern, such as left-right symmetrical binding or binding at a specific angle, so as to ensure the accuracy of signal acquisition and avoid signal aliasing.

[0060] This embodiment of the application designs the binding region 11, which binds to the electrodes in the in vivo machine 1, as an equally divided structure, achieving standardization of electrode binding and optimization of spatial layout. This design ensures that the signal acquisition device can efficiently and stably process signals from different brain regions and modalities, avoiding physical interference and signal aliasing during signal acquisition, and improving the purity and decodeability of signal acquisition. For applications requiring cross-brain region, multimodal signal acquisition, such as motor rehabilitation and epilepsy monitoring using advanced brain-computer interfaces, this feature can significantly improve the efficiency and quality of signal acquisition, providing subjects with more precise and personalized rehabilitation and treatment strategies.

[0061] According to an embodiment of the present invention, an embodiment of a control method for a signal processing acquisition device is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0062] Figure 7 This is a method according to an embodiment of the present invention, such as... Figure 7 As shown, the method includes the following steps:

[0063] Step S101: Acquire the neural signals of the subject using the first electrode and / or the third electrode.

[0064] First, neural signals from the subject are acquired using a first electrode and / or a third electrode. The first electrode is responsible for acquiring cortical electroencephalography (ECoG), while the third electrode is used to acquire stereotactic deep brain region electroencephalography (SEEG). In this embodiment of the invention, electrical activity information from the cerebral cortex and deep nuclei is collected in real time through the connection between the in vivo machine and the first and third electrodes. This enables multimodal signal acquisition across brain regions, providing fundamental data for subsequent analysis.

[0065] Step S102: Determine the subject's current state based on neural signals.

[0066] After collecting neural signals, the internal machine transmits these signals to an external control device. The external control device analyzes these neural signals to identify the subject's immediate brain state, including but not limited to motor intentions, cognitive function, and emotional state. This step utilizes pre-set signal processing and machine learning algorithms to predict the current state based on the input neural signals, extracting meaningful information from complex brain signals and providing a data foundation for the development of personalized rehabilitation strategies.

[0067] Optionally, the prediction of the current state can be made using a neural network model, which is constructed by collecting and labeling the subject data as a training dataset.

[0068] It should be noted that the neural signals collected in this application are information and data authorized by the user or fully authorized by all parties. The collection, use, processing, transmission, and other uses of the relevant data shall comply with relevant laws, regulations, and standards.

[0069] Step S103: Based on the current state, control the working state of at least one of the first electrode, the second electrode, and the third electrode.

[0070] Based on the current state determined in step S102, the internal machine receives electrode control signals sent by the external main control device and can intelligently adjust the working state of the electrodes. For example, when a subject's intention to move is detected, the second electrode (used to collect single-neuron nerve peak potential signals) is preferentially activated for high-precision motion decoding to achieve finer motion control. When changes in cognitive or emotional state are detected, the acquisition parameters of the first or third electrode may be adjusted accordingly, or even specific electrical stimulation patterns may be activated to optimize cognitive function or emotion management. This step demonstrates the dynamic response and personalized intervention capabilities of the present application embodiments to brain states, improving the device's intelligence level and application flexibility.

[0071] It should be noted that when the electrode control signal sent by the external master control device can intelligently adjust the working state of the electrode, the host computer can send the selected site code to the designated register of the in vivo machine through near field communication technology (Bluetooth, Wi-Fi, etc.). After receiving the instruction, the in vivo machine completes an initialization and controls the in vivo machine processor. The MCU completes the acquisition of the corresponding channel signal.

[0072] This embodiment of the application, through steps S101 to S103, enables real-time monitoring of neural signals in the cerebral cortex and deep nuclei, rapidly determining the subject's current brain state, and intelligently adjusting the electrode's working mode based on the state to achieve precise monitoring and personalized intervention of brain function. This process requires no additional manual intervention, reducing device power consumption and signal interference. It achieves the goal of efficient and precise acquisition and processing of signals from different brain regions through multimodal electrodes and in vivo intelligent control, thereby realizing comprehensive signal acquisition and personalized rehabilitation strategies. Furthermore, it solves the technical problem of difficulty in acquiring and processing multimodal neural signals across brain regions in existing technologies.

[0073] Optionally, controlling the operating state of at least one of the first electrode, the second electrode, and the third electrode according to the current state includes: matching the current state with a preset control strategy lookup table to obtain a target control strategy, wherein the preset control strategy lookup table is used to characterize the correspondence between the current state and the control strategy; and controlling the operating state of at least one of the first electrode, the second electrode, and the third electrode according to the target control strategy.

[0074] A pre-defined control strategy lookup table stores the mapping relationship between various brain states and corresponding electrode control strategies. For example, for motor states, the lookup table may include specific strategies for activating the second electrode (used to acquire single neuronal spike potential signals) to accurately locate and decode motor intentions; for depressive moods, the lookup table may guide the activation of the third electrode (used to acquire stereotactic deep brain region EEG signals) for monitoring and electrical stimulation intervention of deep nuclei.

[0075] After monitoring the subject's current state in real time, the internal or external decoding device queries a preset control strategy lookup table to find the most suitable control strategy, i.e., the target control strategy, based on the current state. This process, through the detailed classification and strategy definition in the lookup table, ensures that the adjustment of the electrode's working state is both rapid and precise, meeting the subject's actual needs.

[0076] Based on a target control strategy, the in vivo machine will adjust the operating state of the first, second, or third electrode. Guided by this strategy, one or more of the first, second, and third electrodes (electrode 2, electrode 3, and electrode 4) will be controlled to acquire signals, decreasing or increasing the acquisition frequency, or switching to a stimulation mode to intervene in brain activity. This flexibility in electrode control allows the device to take optimal measures in different states; for example, prioritizing SPIKE signal decoding during motor control phases, while focusing on ECoG or SEEG signal acquisition and analysis during cognitive or emotion monitoring.

[0077] This application embodiment achieves a high degree of automation and personalization in brain signal acquisition and intervention by establishing a preset control strategy comparison table and adjusting the working state of the electrodes in real time according to the current state. This significantly improves the device's user adaptability, ensuring that the most suitable and timely brain signal support or treatment methods are provided in various application scenarios, such as sports rehabilitation, emotion regulation, and cognitive function training, thereby enhancing the accuracy and effectiveness of brain-computer interface technology in regulating brain function.

[0078] Optionally, according to the target control strategy, controlling the working state of at least one of the first electrode, the second electrode, and the third electrode includes: in response to the current state being a first motor state, the target control strategy is to control the first electrode to work to acquire a first neural signal, wherein the first motor state is used to characterize the movement of the subject's first motor part, and the first neural signal is used to control the movement of the first motor part; in response to the current state changing from the first motor state to a second motor state, the target control strategy is to control the second electrode to work to acquire a second neural signal, wherein the second motor state is used to characterize the movement of the subject's second motor part, and the second neural signal is used to control the movement of the second motor part; wherein the fineness of the movement of the first motor part is less than the fineness of the movement of the second motor part.

[0079] For example, in the embodiments of this application, the first moving part can be a body part that performs a wide range of movements, such as the arm or thigh, and the second moving part can be a body part that performs a small range of movements, such as the hand, fingers, foot, or toes.

[0080] In this embodiment, the target control strategy is a strategy that adjusts the electrode working state according to the subject's current state (such as motor state). When the subject transitions from a first motor state (arm movement) to a second motor state (fine hand or finger movements), the device can intelligently switch from acquiring ECoG signals from the first electrode to acquiring SPIKE signals from the second electrode, ensuring that the signal type for motor control matches the fineness of the movement, thereby improving rehabilitation or control efficiency.

[0081] The first motor state specifically refers to the motor state of the subject's arm, such as waving or raising. The execution of these movements mainly relies on a wide range of activity in the cerebral cortex. The first neural signal is the ECoG signal captured by the first electrode and associated with the first motor state. It is used to decode the arm's movement intention and control peripheral devices, such as robotic arms or exoskeletons, to assist or enhance the arm's movement.

[0082] The second motor state refers to the fine motor state of the subject's hand, such as grasping and pinching. The execution of these actions involves deeper fine neural control of the brain. The second neural signal is the SPIKE signal recorded by the second electrode, which is closely related to the second motor state. It is used to decode the fine motor intention of the hand and control peripheral devices, such as robotic hands or fine exoskeletons, to achieve fine motor control and rehabilitation of the hand.

[0083] For example, a flexible microwire electrode (second electrode) is partially implanted into the motor cortex of the brain, and an ECoG electrode (first electrode) is placed on the brain surface or attached to the dura mater to collect ECoG signals from the functional areas above. When the subject completes the first step of the drinking action—raising the elbow or arm—the in vivo machine collects ECoG signals. Leveraging its low power consumption, the accompanying decoding algorithm controls external devices to move (or directly stimulate) large muscle groups, such as the biceps and triceps, to bring the hand closer to the cup. After completing this action, the acquisition system switches to collecting SPIKE signals, using the accompanying decoding algorithm to control a more precise hand exoskeleton to complete grasping or to stimulate hand muscles (various muscle groups in the hand) to complete grasping. At this point, system power consumption increases. After grasping, the acquisition system can switch back to ECoG signals, controlling a robotic arm to complete the upper arm and elbow movements, thus completing the drinking action. The time-sharing acquisition function can be switched using EEG beta waves over a certain period (100ms) or external sensors. Alternatively, specific EEG signals can be decoded, such as four imagined left hand movements as a switching indicator.

[0084] This application embodiment achieves intelligent recognition of different movement states and precise control of electrode operating states by implementing the technical features of "responding to the current state being a first movement state, the target control strategy is to control the first electrode to work to collect a first neural signal; and responding to the current state changing from the first movement state to a second movement state, the target control strategy is to control the second electrode to work to collect a second neural signal." Based on the control of the target control strategy, during gross arm movements, the first electrode can efficiently collect and decode ECoG signals to control arm movements; when the subject's movement needs shift to fine hand movements, the second electrode is activated to collect SPIKE signals, ensuring precise control of hand movements. This design not only optimizes the efficiency and quality of signal acquisition but also significantly improves the personalization and effectiveness of rehabilitation training, reduces unnecessary signal acquisition, thereby reducing the overall power consumption of the device and enhancing the user adaptability and clinical application value of the device. By intelligently switching electrode operating states, this application embodiment can provide the most suitable neural signal acquisition and movement control for different movement states.

[0085] Optionally, according to the target control strategy, controlling the working state of at least one of the first electrode, the second electrode, and the third electrode includes: responding to the current state being a first control state, the target control strategy is to control the first electrode to work to acquire a third neural signal, wherein the first control state is used to characterize the state in which the subject controls the large-range movement of the peripheral device, and the third neural signal is used to control the large-range movement of the peripheral device, wherein the large-range movement is a movement with a movement amplitude greater than a first preset movement amplitude; responding to the current state changing from the first control state to the second control state, the target control strategy is to control the second electrode to work to acquire a fourth neural signal, wherein the second control state is used to characterize the subject's small-range movement of the peripheral device, and the fourth neural signal is used to control the small-range movement of the peripheral device, wherein the small-range movement is a movement with a movement amplitude less than a second preset movement amplitude.

[0086] In this embodiment, the target control strategy is used to control the operation of the first electrode and the second electrode in response to the control state.

[0087] For example, the first preset motion amplitude and the second preset motion amplitude are used to characterize the amount of displacement that the peripheral device moves from the initial position to the target position.

[0088] The third and fourth neural signals are collected by the first and second electrodes, respectively, and they determine the behavior of the peripheral device based on the subject's current control needs. The third neural signal is mainly used to decode the peripheral device's large-range movements, while the fourth neural signal is used to decode the peripheral device's small-range movements.

[0089] The first control state refers to the stage where the subject controls the peripheral device's large-scale movements through their thoughts, such as the large-scale movement of a wheelchair or a robotic arm. The second control state refers to the need for commands to control the peripheral device's small-scale movements, such as controlling the wheelchair's pitch angle, the wheelchair's small-scale movement, or the robotic arm's gripping.

[0090] For example, in the first control state, when the subject attempts to control the direction and speed of the peripheral device's movement, this embodiment of the application responds to this state by activating and controlling the first electrode to collect third neural signals reflecting changes in the overall direction and speed of movement. The collected signals are decoded and converted into actual control commands for the peripheral device, enabling the regulation of a wide range of movements.

[0091] When the second control state occurs, it means that the subject's control needs shift to more specific, smaller-scale movements. The embodiments of this application accordingly adjust the target control strategy, controlling the second electrode to operate and collecting fourth neural signals. These signals can more accurately reflect the subject's intentions and control the peripheral device to perform fine motor actions.

[0092] For example, in a wheelchair control scenario, the intended direction of movement and speed changes are decoded via ECoG signals, and then fine-grained control of the movement is achieved through SPIKE signal decoding, enabling precise control of the movement position or the wheelchair's pitch angle. ECoG decoding determines the operating mode at a predetermined position, including vertical movement and the wheelchair's pitch angle. Different movement modes also require precise start and stop signals on a timescale coordinated with SPIKE signals.

[0093] This application's embodiments, by implementing the technical feature of "controlling the first electrode to acquire a third neural signal in response to a first control state; and controlling the second electrode to acquire a fourth neural signal in response to a second control state," can significantly improve the brain-computer interface's ability to interpret the subject's intentions and its flexibility in controlling peripheral devices. Specifically, this design enables the device to automatically select the most suitable signal acquisition type according to different control needs: in the first control state, the third neural signal acquired by the first electrode is used to efficiently control the peripheral device's wide-range movements; in the second control state, the fourth neural signal acquired by the second electrode is used to control the peripheral device's small-range movements. This intelligent signal acquisition and control strategy based on state recognition not only enhances the device's user adaptability but also ensures the accuracy of signal acquisition and decoding, thereby improving the precision and efficiency of peripheral device control and providing subjects with a more intuitive and natural brain-computer interaction experience.

[0094] Optionally, according to the target control strategy, controlling the working state of at least one of the first electrode, the second electrode, and the third electrode includes: responding to the current state being a first preset mental state, the target control strategy is to control the third electrode to enter an electrical stimulation mode to periodically electrically stimulate deep nuclei and acquire monitoring neural signals through the first and third electrodes, wherein the first preset mental state is used to characterize the subject's abnormal emotional fluctuations and cognitive dysfunction; determining the process mental state during the electrical stimulation process based on the monitoring neural signals; responding to the process mental state being a second preset mental state, the target control strategy is to control the third electrode to exit the electrical stimulation mode, wherein the second preset mental state is used to characterize the subject's normal emotional fluctuations and normal cognitive function.

[0095] In this embodiment, the target control strategy is used to control the working state of the first and third electrodes in response to mental state.

[0096] The first and second presupposed mental states define two different mental states of the brain. The first presupposed mental state indicates that the subject is experiencing abnormal emotional fluctuations accompanied by cognitive dysfunction, suggesting the need for intervention with electrical stimulation therapy, specifically periodic electrical stimulation. The second presupposed mental state, on the other hand, indicates that the subject's emotional fluctuations and cognitive function have returned to normal, allowing them to exit the periodic electrical stimulation mode.

[0097] When abnormal emotional fluctuations and cognitive decline are detected in the subjects, the embodiments of this application activate the third electrode to periodically electrically stimulate deep nuclei according to the target control strategy, while using the first and third electrodes to acquire monitoring neural signals for real-time evaluation of the effects and efficacy of electrical stimulation.

[0098] When determining the mental state during electrical stimulation based on monitored neural signals, the device analyzes the monitored neural signals acquired by the first and third electrodes to assess the impact of the electrical stimulation intervention on the subject's mental state in real time. Signal analysis can confirm whether the expected signs of cognitive and emotional improvement have occurred.

[0099] Once monitoring of neural signals indicates that the subject's emotional fluctuations and cognitive functions have returned to normal, the target control strategy of this application embodiment will instruct the third electrode electrical stimulation mode to cease periodic electrical stimulation, ensuring no over-intervention and marking the end of the treatment phase.

[0100] Optionally, in some embodiments of the present invention, the first electrode and the second motor may also be configured to electrically stimulate brain regions under command control.

[0101] For example, during the monitoring and treatment of diseases such as depression: SEEG signals are used to monitor deep nuclei (including the amygdala) for abnormal emotional fluctuations, including the type and range of emotions; ECoG signals are used to monitor whether cognitive function in the subject's cerebral cortex is affected; if only significant emotional fluctuations are found, but cognitive function is not yet affected, external reminders can be triggered to help the subject become aware of and adjust; if significant emotional fluctuations and cognitive function are detected, periodic electrical stimulation is applied to the deep nuclei; different types of stimulation patterns are obtained by decoding ECoG and SEEG signals; after the electrical stimulation begins, the electrical stimulation mode is exited after confirming a change in cognitive pattern through ECoG signal decoding, the intervention ends, and the monitoring mode is returned to.

[0102] It should be noted that the above-mentioned judgments on emotional abnormalities and whether cognitive functions are affected can be achieved by using neural network models for prediction or by comparing data with those of a normal state.

[0103] This application implements the technical feature of "responding to a first preset mental state, controlling the third electrode to enter an electrical stimulation mode to periodically electrically stimulate deep brain nuclei and acquiring monitoring neural signals through the first and third electrodes; subsequently determining the process mental state based on the monitoring neural signals; and controlling the third electrode to exit the electrical stimulation mode when the process mental state changes to a second preset mental state." This enables precise electrical stimulation intervention of deep brain nuclei when the subject experiences abnormal emotional fluctuations and cognitive impairment, while simultaneously monitoring neural signals in real time to assess the treatment effect. This technical feature can automatically adjust the activation and deactivation of the electrical stimulation mode according to the subject's mental state. The design of the above embodiment can improve the safety and personalization of treatment, ensure the timeliness and appropriateness of electrical stimulation intervention, avoid unnecessary stimulation, thereby reducing potential side effects and risks, and providing subjects with a more precise and gentle mental state regulation plan. In addition, the practice of dynamically adjusting the treatment strategy by monitoring neural signals also provides clinicians with real-time feedback, facilitating them to adjust the treatment plan according to the actual situation and enhancing the scientific basis of medical intervention. The implementation of this series of technological actions has independently promoted the innovation of non-pharmacological treatment methods in the field of mental health, providing new ideas and tools for the treatment of mood and cognitive disorders.

[0104] Optionally, controlling the working state of at least one of the first electrode, the second electrode, and the third electrode according to the current state includes: determining the brain functional area corresponding to the current state; determining the target controlled electrode from the first electrode, the second electrode, and the third electrode according to the brain functional area; and controlling the target controlled electrode to acquire target neural signals and to electrically stimulate the brain functional area according to the target neural signals.

[0105] Brain functional areas refer to regions of the brain responsible for specific functions or activities, such as the motor cortex and language areas. The neural activity patterns of different functional areas and the types of signals acquired by different electrodes vary significantly. Identifying the brain functional area corresponding to the current state is crucial for selecting the correct electrodes and signal acquisition methods.

[0106] In this embodiment, based on the brain functional area corresponding to the current state, one or more target controlled electrodes are determined from the first, second, and third electrodes to perform signal acquisition or electrical stimulation tasks. The selection of target controlled electrodes ensures the targeted and efficient operation of the electrodes.

[0107] Target neural signals refer to the electrical neural signals acquired by the target controlled electrodes that are directly related to the current state and brain functional areas. These signals may be ECoG signals, SPIKE signals, or SEEG signals, depending on the subject's specific state and the target functional area.

[0108] Electrical stimulation is a neuroscientific intervention that modulates neuronal activity by applying microcurrents to brain tissue. It can be used to treat or improve brain function, such as mood regulation and cognitive enhancement. The intensity, frequency, and duration of electrical stimulation need to be precisely controlled to ensure the safety and effectiveness of the intervention.

[0109] When the monitoring system identifies the subject's current state, such as being in the exercise rehabilitation stage or in an abnormal emotional state, the embodiments of this application can intelligently determine the brain functional area corresponding to this state, providing a location basis for subsequent steps.

[0110] Based on the identified brain functional areas, embodiments of this application further select the first, second, or third electrode most suitable for signal acquisition or electrical stimulation intervention in that functional area, i.e., determine the target controlled electrode, in order to achieve the most effective signal processing or therapeutic effect.

[0111] Finally, embodiments of this application instruct the controlled electrodes to operate, acquiring target neural signals related to the current state and brain functional areas. In some cases, these signals will be used to drive the electrical stimulation process to promote activity in brain functional areas or treat abnormal conditions.

[0112] For example, in one implementation scenario, ECoG electrodes cover transverse functional areas of the cerebral cortex (such as the motor cortex and prefrontal cortex), and SEEG electrodes cover longitudinal functional areas of the brain (such as the temporal lobe and deep nuclei). This allows for the recording of a wide range of neural activity at larger sites, with continuous acquisition maintained at a low sampling rate over a long period. The signals are used to determine the recorder's state (such as sleep, focused reading, movement, active communication with the outside world, etc.). By distinguishing different states, single-neuron recording electrodes at different locations are activated. For example, if fine hand motor control is required, single-neuron signal recording (SPIKE) in the hand motor cortex is activated for fine motor decoding, in conjunction with hand sensation. Microfiber electrode electrical stimulation of the sensory cortex provides fine tactile feedback; during focused reading, fine recording in the frontal lobe confirms reading efficiency and concentration, and combined with fine electrical stimulation of the frontal and temporal lobes, improves attention and memory, thus enhancing reading performance; during active communication with the outside world, the content of communication can be selected, and if it is similar to the transmission of visual information, visual memory and visual imagination can be directly awakened through imagination, and the signal can be directly sent to the other party, who then transmits the image through fine electrical stimulation of the visual area; combined with large-scale signal recording decoding of state and emotion, if prolonged depression or other emotional states occur, intervention and improvement can be achieved through electrical stimulation of deep nuclei.

[0113] This application implements the technical features of "determining the corresponding brain functional area based on the current state; identifying the target controlled electrode from the electrodes; controlling the target controlled electrode to collect target neural signals and performing electrical stimulation based on the target neural signals," enabling precise localization and individualized signal processing of the subject's brain functional area. This technology independently improves the targeting of signal acquisition and the personalization of electrical stimulation intervention, ensuring optimal electrode working state adjustment based on different brain states. By dynamically allocating electrode acquisition types and timely electrical stimulation, this application significantly enhances the applicability and effectiveness of brain-computer interfaces in fields such as neurorehabilitation and treatment of mental illnesses, providing more accurate neurophysiological data support for subsequent signal decoding and state improvement, thereby promoting the development of brain-computer interface technology towards greater intelligence and personalization. This series of technical operations not only improves the efficiency of signal acquisition and the accuracy of treatment but also reduces unnecessary electrode use, energy consumption, and potential biocompatibility issues, bringing a safer, more efficient, and personalized brain-computer interaction experience to the subject.

[0114] Embodiments of this application also provide an electronic device, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of the present invention during runtime.

[0115] Optionally, in this embodiment, the processor in the above-described electronic device can be configured to run an executable program to perform the following steps:

[0116] Step S101: Acquire the neural signals of the subject using the first electrode and / or the third electrode.

[0117] Step S102: Determine the subject's current state based on neural signals.

[0118] Step S103: Based on the current state, control the working state of at least one of the first electrode, the second electrode, and the third electrode.

[0119] Embodiments of this application also provide a computer-readable storage medium including a stored executable program, wherein, when the executable program is executed, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of the present invention.

[0120] Optionally, in this embodiment, the executable program can be configured to store an executable program for performing the following steps:

[0121] Step S101: Acquire the neural signals of the subject using the first electrode and / or the third electrode.

[0122] Step S102: Determine the subject's current state based on neural signals.

[0123] Step S103: Based on the current state, control the working state of at least one of the first electrode, the second electrode, and the third electrode.

[0124] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the methods of various embodiments of the present invention.

[0125] Optionally, in this embodiment, the computer program, when executed by the processor, performs the following steps:

[0126] Step S101: Acquire the neural signals of the subject using the first electrode and / or the third electrode.

[0127] Step S102: Determine the subject's current state based on neural signals.

[0128] Step S103: Based on the current state, control the working state of at least one of the first electrode, the second electrode, and the third electrode.

[0129] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium for storing a computer program that, when executed by a processor, implements the methods in various embodiments of the present invention.

[0130] Embodiments of this application also provide a computer program that, when executed by a processor, implements the methods described in the various embodiments of the present invention.

[0131] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0132] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0133] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0134] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0135] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, 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. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0136] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A signal acquisition device, characterized in that, include: Internal organs; The first electrode is connected to the in vivo machine and is used to collect cortical electroencephalogram (EEG) signals. The second electrode is connected to the in vivo machine and is used to collect the nerve spike potential signal of a single neuron. The third electrode is connected to the in vivo machine and is used to collect stereotactic deep brain region electroencephalogram (EEG) signals. The in vivo machine is used to feed back nerve signals to an external main control device and receive electrode control signals from the external main control device. The nerve signals are acquired by the first electrode and / or the third electrode.

2. The signal acquisition device according to claim 1, characterized in that, The second electrode and the first electrode have an angle between them.

3. The signal acquisition device according to claim 1, characterized in that, The bonding sites of the first electrode and the second electrode are eccentric structures.

4. The signal acquisition device according to claim 1, characterized in that, The binding area in the in vivo machine that is bound to the electrodes has an equally divided structure.

5. A control method for a signal acquisition device, characterized in that, The method applied to the signal acquisition device according to any one of claims 1 to 4 includes: Acquire neural signals from the subject using the first and / or third electrodes; Based on the neural signals, the subject's current state is determined; Based on the current state, control the operating state of at least one of the first electrode, the second electrode, and the third electrode.

6. The signal acquisition device control method according to claim 5, characterized in that, The step of controlling the operating state of at least one of the first electrode, the second electrode, and the third electrode according to the current state includes: The current state is matched with a preset control strategy lookup table to obtain the target control strategy, wherein the preset control strategy lookup table is used to characterize the correspondence between the current state and the control strategy. According to the target control strategy, the operating state of at least one of the first electrode, the second electrode, and the third electrode is controlled.

7. The signal acquisition device control method according to claim 6, characterized in that, The step of controlling the operating state of at least one of the first electrode, the second electrode, and the third electrode according to the target control strategy includes: In response to the current state being a first motor state, the target control strategy is to control the first electrode to work in order to collect a first neural signal, wherein the first motor state is used to characterize the movement of the subject's first motor part, and the first neural signal is used to control the movement of the first motor part; In response to the current state changing from the first motor state to the second motor state, the target control strategy is to control the second electrode to work to collect the second neural signal, wherein the second motor state is used to characterize the movement of the subject's second motor part, and the second neural signal is used to control the movement of the second motor part; The precision of the movement of the first moving part is less than that of the movement of the second moving part.

8. The signal acquisition device control method according to claim 6, characterized in that, The step of controlling the operating state of at least one of the first electrode, the second electrode, and the third electrode according to the target control strategy includes: In response to the current state being a first control state, the target control strategy is to control the first electrode to work in order to collect a third neural signal. The first control state is used to characterize the state in which the subject controls the wide range of motion of the peripheral device. The third neural signal is used to control the wide range of motion of the peripheral device. The wide range of motion is a motion with an amplitude greater than a first preset motion amplitude. In response to the change of the current state from the first control state to the second control state, the target control strategy is to control the second electrode to work to collect the fourth neural signal, wherein the second control state is used to characterize the subject's small-range movement of the peripheral device, and the fourth neural signal is used to control the small-range movement of the peripheral device, wherein the small-range movement is a movement with an amplitude smaller than a second preset movement amplitude.

9. The signal acquisition device control method according to claim 6, characterized in that, The step of controlling the operating state of at least one of the first electrode, the second electrode, and the third electrode according to the target control strategy includes: In response to the current state being a first preset mental state, the target control strategy is to control the third electrode to enter an electrical stimulation mode to periodically electrically stimulate deep nuclei and to acquire monitoring neural signals through the first electrode and the third electrode, wherein the first preset mental state is used to characterize the subject's abnormal emotional fluctuations and cognitive abnormalities. The mental state during the electrical stimulation process is determined based on the monitored neural signals. In response to the subject's mental state being a second preset mental state, the target control strategy is to control the third electrode to exit the electrical stimulation mode, wherein the second preset mental state is used to characterize that the subject's emotional fluctuations are normal and cognitive function is normal.

10. The signal acquisition device control method according to claim 6, characterized in that, The step of controlling the operating state of at least one of the first electrode, the second electrode, and the third electrode according to the current state includes: Based on the current state, determine the corresponding brain functional area; Based on the brain functional areas, the target controlled electrode is determined from the first electrode, the second electrode, and the third electrode; The target controlled electrode is controlled to acquire target neural signals and to electrically stimulate the brain functional area based on the target neural signals.

11. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 5 to 10.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the storage medium is located to perform the method according to any one of claims 5 to 10.

13. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 5 to 10.

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