Sensory enhancement system based on brain-computer interface

Abstract

The invention discloses a sensory enhancement system based on a brain-computer interface, and the system comprises a sensory information database which is used for storing various types of sensory information data; the enhancement confirmation module is used for the user to input information needing to be enhanced; the information matching module is used for matching corresponding sensory information data from the sensory information database according to the information which is input by the user and needs to be enhanced; the signal processing module is used for processing the sensory information data matched by the information matching module to obtain corresponding stimulation signals; and the brain-computer interface module is used for stimulating the cerebral cortex of the user according to the stimulation signal processed by the signal processing module. According to the sensory enhancement system based on the brain-computer interface, input and output of sensory information are achieved by directly stimulating the cerebral cortex, and therefore the sensory experience of human beings is enhanced or expanded.

Description

Technical Field

[0001] The present invention specifically relates to a sensory enhancement system based on brain-computer interface. Background Art

[0002] With the rapid development of neuroscience and brain-computer interface technology, the way humans interact with machines is undergoing profound changes. Traditional sensory experience is limited by human biological structure, while brain-computer interface technology provides us with an unprecedented way to directly stimulate the cerebral cortex to input and output sensory information, thereby enhancing or expanding human sensory capabilities.

[0003] At present, the application of brain-computer interface technology in sensory enhancement is still in its infancy. Existing research has mainly focused on restoring damaged sensory functions, such as restoring vision and hearing through brain-computer interfaces, while research on sensory enhancement is relatively rare. In addition, most existing sensory enhancement technologies rely on external devices, such as virtual reality (VR) and augmented reality (AR). Although these technologies can provide rich sensory experiences, they cannot directly stimulate the cerebral cortex, so their sensory enhancement effects are limited. Summary of the invention

[0004] The present invention provides a sensory enhancement system based on a brain-computer interface to solve the above-mentioned technical problems, and specifically adopts the following technical solutions:

[0005] A sensory enhancement system based on brain-computer interface, comprising:

[0006] A sensory information database, used to store various types of sensory information data;

[0007] Enhancement confirmation module, used for users to input information that needs to be enhanced;

[0008] An information matching module, used for matching corresponding sensory information data from the sensory information database according to the information to be enhanced input by the user;

[0009] A signal processing module, used for processing the sensory information data matched by the information matching module to obtain a corresponding stimulation signal;

[0010] The brain-computer interface module is used to stimulate the user's cerebral cortex according to the stimulation signal obtained by the signal processing module.

[0011] Furthermore, the brain-computer interface module uses electroencephalogram technology or non-invasive transcranial magnetic stimulation technology to stimulate the user's cerebral cortex.

[0012] Furthermore, the signal processing module comprises:

[0013] A feature extraction unit, used to extract features of sensory information data;

[0014] The signal conversion unit is used to convert the extracted features into electrical signals suitable for cerebral cortex stimulation.

[0015] Furthermore, the enhancement confirmation module is a touch display screen, and the touch display screen receives a touch operation output by a user to confirm the information that needs to be enhanced.

[0016] Furthermore, the enhanced confirmation module also includes:

[0017] A voice receiving unit, used to receive a user's voice command;

[0018] The voice analysis unit is used to analyze the voice command to identify the user's information that needs to be enhanced.

[0019] Furthermore, the brain-computer interface module is also used to collect brain activity signals of the user;

[0020] The enhanced confirmation module also includes:

[0021] The signal recognition unit is used to recognize the information that the user needs to enhance based on the brain activity signal collected by the brain-computer interface module.

[0022] Furthermore, the signal recognition unit comprises:

[0023] A signal processing subunit, used to process the brain activity signals collected by the brain-computer interface module;

[0024] A feature extraction subunit, used to extract features of brain activity signals;

[0025] The classification subunit classifies and identifies the features extracted by the feature extraction subunit based on the trained neural network model to obtain the enhanced sensory type selected by the user.

[0026] Furthermore, the sensory enhancement system based on brain-computer interface also includes:

[0027] A monitoring module, used to determine the current state of the user based on the brain activity signal collected by the brain-computer interface module;

[0028] The control module is used to stop the stimulation operation of the brain-computer interface module when the monitoring module detects that the user is in a risky state.

[0029] Furthermore, the sensory enhancement system based on brain-computer interface also includes:

[0030] A feedback module, used for providing user feedback on stimulation status;

[0031] The adjustment module is used to adjust the brain-computer interface module based on the user's feedback information, and the brain-computer interface module adaptively adjusts the stimulation strategy according to the adjustment result of the adjustment module.

[0032] Furthermore, the sensory type includes visual type, auditory type, tactile type, olfactory type and taste type.

[0033] The benefit of the present invention lies in that the provided brain-computer interface-based sensory enhancement system realizes the input and output of sensory information by directly stimulating the cerebral cortex, thereby enhancing or expanding the human sensory experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0035] Figure 1 It is a schematic diagram of the sensory enhancement system based on brain-computer interface of the present application. DETAILED DESCRIPTION

[0036] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0037] like Figure 1 A sensory enhancement system based on brain-computer interface is shown, comprising: a sensory information database, an enhancement confirmation module, an information matching module, a signal processing module and a brain-computer interface module.

[0038] Among them, the sensory information database is used to store multiple types of sensory information data. Sensory types include visual type, auditory type, tactile type, olfactory type and taste type, and different sensory types further include different subtypes. For example, the visual type also includes red, yellow, etc. It can be understood that the sensory information database is an important part of the system and is used to store various sensory information data. The sensory information database of the present application can support the storage and query of multiple sensory information data through a reasonable data structure design, thereby achieving efficient retrieval and matching. At the same time, the database can also be continuously updated and improved as needed to adapt to the needs and changes of different users. In addition, the sensory information database can also adopt distributed storage technology to improve data security and access efficiency. The data in the database can be protected by encryption technology to ensure that user privacy is not leaked. At the same time, the database can also support concurrent access by multiple users to meet the needs of large-scale application scenarios. In order to improve the retrieval speed of data, the database can also use indexing technology and caching mechanism to further optimize system performance.

[0039] The enhancement confirmation module is used for the user to input the information to be enhanced. The information matching module is used for matching the corresponding sensory information data from the sensory information database according to the selection information input by the user.

[0040] In an embodiment of the present application, the enhancement confirmation module is a touch screen, and the touch screen receives the touch operation output by the user to confirm the information that needs to be enhanced. For example, the user can choose to enhance the red vision through the touch operation, and the information matching module matches the sensory information data corresponding to the enhanced red vision from the sensory information database. The information matching module is based on a related algorithm and can accurately extract the features of the sensory information data and convert it into electrical signals. The design of the algorithm needs to be combined with the structural and functional characteristics of the cerebral cortex, as well as the differences and complexity of different sensory information data.

[0041] The signal processing module is used to process the sensory information data matched by the information matching module to obtain the corresponding stimulation signal. Specifically, the stimulation signal is an electrical signal. The brain-computer interface module is used to stimulate the user's cerebral cortex according to the stimulation signal processed by the signal processing module to achieve the input and output of sensory information. The design of the signal processing module needs to fully consider the stability and security of the signal to ensure that the generated stimulation signal can accurately reflect the user's sensory needs. The brain-computer interface module uses advanced neural stimulation technology to ensure the accurate transmission and effective effect of the stimulation signal. In order to improve the reliability of the system, the signal processing module can also add signal filtering and noise suppression functions to ensure that the generated stimulation signal is pure and interference-free.

[0042] As a preferred embodiment, the enhanced confirmation module also includes: a voice receiving unit and a voice analysis unit. The voice receiving unit is used to receive the user's voice instructions. The voice analysis unit is used to analyze the voice instructions to identify the information that the user needs to enhance. In this way, the user can not only input instructions through the touch screen, but also output selection instructions through voice control. The voice receiving unit can adopt high-sensitivity microphone array technology to ensure that the user's voice instructions can be accurately captured even in a noisy environment. The voice analysis unit combines natural language processing technology to recognize multiple languages ​​and dialects to meet the needs of different users. In order to improve the accuracy of voice recognition, the voice analysis unit can also combine contextual information and the user's historical instructions to provide more intelligent recognition results.

[0043] It is understandable that the brain-computer interface module can use electroencephalography (EEG) or non-invasive transcranial magnetic stimulation (TMS) technology to stimulate the user's cerebral cortex. Electroencephalography (EEG) can monitor the user's brain activity in real time to ensure the accurate transmission of stimulation signals. Non-invasive transcranial magnetic stimulation (TMS) technology stimulates the cerebral cortex through magnetic fields, which is painless and non-invasive and suitable for long-term use. In order to improve the stimulation effect, the brain-computer interface module can also combine a variety of stimulation technologies and dynamically adjust according to the specific needs of the user.

[0044] In an embodiment of the present application, the signal processing module includes: a feature extraction unit and a signal conversion unit.

[0045] Among them, the feature extraction unit is used to extract the features of the sensory information data. The signal conversion unit is used to convert the extracted features into electrical signals suitable for cerebral cortex stimulation. The feature extraction unit can use advanced signal processing algorithms, such as wavelet transform or Fourier transform, to ensure that the extracted features can accurately reflect the essence of the sensory information data. The signal conversion unit converts the digital signal into an analog electrical signal suitable for cerebral cortex stimulation through digital-to-analog conversion technology. In order to improve the accuracy of signal conversion, the signal conversion unit can also use a high-resolution digital-to-analog converter to ensure that the generated stimulation signal has high fidelity.

[0046] In an embodiment of the present application, the brain-computer interface module is also used to collect brain activity signals of the user. The enhanced confirmation module also includes: a signal recognition unit. The signal recognition unit is used to identify information that needs to be enhanced based on the brain activity signals collected by the brain-computer interface module. The brain-computer interface module collects the user's brain activity signals through high-precision sensors to ensure the accuracy and real-time nature of the data. The signal recognition unit combines advanced pattern recognition technology to extract useful information from complex brain activity signals. In order to improve the accuracy of recognition, the signal recognition unit can also be combined with deep learning technology to optimize the recognition model by training a large amount of EEG signal data.

[0047] Specifically, the signal recognition unit includes: a signal processing subunit, a feature extraction subunit and a classification subunit. The signal processing subunit is used to process the brain activity signal collected by the brain-computer interface module. The feature extraction subunit is used to extract the features of the brain activity signal. The classification subunit classifies and identifies the features extracted by the feature extraction subunit based on the trained neural network model to obtain the enhanced sensory type selected by the user. The signal processing subunit can use filtering and noise reduction technology to ensure the purity of the brain activity signal. The feature extraction subunit extracts the most representative features through techniques such as principal component analysis (PCA) or independent component analysis (ICA). The classification subunit classifies and identifies the features through deep learning models such as convolutional neural networks (CNN) or recurrent neural networks (RNN) to ensure the accuracy of the recognition results.

[0048] In the implementation of the present application, the design of the enhanced confirmation module fully considers the convenience and accuracy of user operation. Users can input instructions in a variety of ways, such as touch, voice or EEG signals, to ensure that different user groups can easily use the system. The information matching module uses an efficient algorithm to achieve fast matching, ensuring that users can obtain the desired sensory enhancement effect in real time. In order to improve the accuracy of matching, the information matching module can also combine the user's personalized preferences and historical data to provide more accurate matching results.

[0049] In an embodiment of the present application, the sensory enhancement system based on brain-computer interface further includes: a monitoring module and a control module.

[0050] The monitoring module is used to determine the user's current state based on the brain activity signals collected by the brain-computer interface module. The control module is used to stop the stimulation operation of the brain-computer interface module when the monitoring module detects that the user is in a risky state. In this way, the safety of the system can be further improved to avoid harm to the user. The monitoring module can promptly detect the user's abnormal state, such as fatigue, anxiety or discomfort, by analyzing the user's brain activity signals in real time. The control module ensures the user's safety by automatically stopping the stimulation operation or adjusting the stimulation intensity. In order to improve the accuracy of monitoring, the monitoring module can also combine the user's physiological data, such as heart rate, blood pressure, etc., for comprehensive judgment.

[0051] In an embodiment of the present application, the sensory enhancement system based on the brain-computer interface also includes: a feedback module and an adjustment module. The feedback module is used for users to feedback the stimulation state. The adjustment module is used to adjust the brain-computer interface module based on the user's feedback information, and the brain-computer interface module adaptively adjusts the stimulation strategy according to the adjustment result of the adjustment module. The feedback module can collect user feedback information in a variety of ways, such as questionnaires, physiological indicator monitoring or real-time feedback buttons. The adjustment module dynamically adjusts the intensity, frequency and duration of the stimulation signal according to the user's feedback information to ensure that the user obtains the best sensory enhancement effect. In order to improve the level of intelligence of the adjustment, the adjustment module can also be combined with reinforcement learning technology to improve user satisfaction by continuously optimizing the stimulation strategy.

[0052] In summary, the sensory enhancement system based on brain-computer interface of this application can achieve efficient and accurate sensory enhancement effects through the collaborative work of multiple modules. The design of the system fully considers the user's convenience of operation, data security and usage safety to ensure that users can get the best sensory experience. At the same time, the system is also highly scalable and adaptable, and can be continuously optimized and upgraded according to user needs and technological development.

[0053] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the above embodiments do not limit the present invention in any form, and any technical solution obtained by equivalent replacement or equivalent transformation falls within the protection scope of the present invention.

Claims

1. A sensory enhancement system based on brain-computer interface, characterized in that: Include: A sensory information database, used to store various types of sensory information data; Enhancement confirmation module, used for users to input information that needs to be enhanced; An information matching module, used for matching corresponding sensory information data from the sensory information database according to the information to be enhanced input by the user; A signal processing module, used for processing the sensory information data matched by the information matching module to obtain a corresponding stimulation signal; The brain-computer interface module is used to stimulate the user's cerebral cortex according to the stimulation signal obtained by the signal processing module.

2. The sensory enhancement system based on brain-computer interface according to claim 1 is characterized in that: The brain-computer interface module uses electroencephalogram technology or non-invasive transcranial magnetic stimulation technology to stimulate the user's cerebral cortex.

3. The sensory enhancement system based on brain-computer interface according to claim 2 is characterized in that: The signal processing module comprises: A feature extraction unit, used to extract features of sensory information data; The signal conversion unit is used to convert the extracted features into electrical signals suitable for cerebral cortex stimulation.

4. The sensory enhancement system based on brain-computer interface according to claim 1, characterized in that: The enhancement confirmation module is a touch display screen, and the touch display screen receives a touch operation output by a user to confirm the information that needs to be enhanced.

5. The sensory enhancement system based on brain-computer interface according to claim 4 is characterized in that: The enhanced confirmation module also includes: A voice receiving unit, used to receive a user's voice command; The voice analysis unit is used to analyze the voice command to identify the user's information that needs to be enhanced.

6. The sensory enhancement system based on brain-computer interface according to claim 5 is characterized in that: The brain-computer interface module is also used to collect brain activity signals of the user; The enhanced confirmation module also includes: The signal recognition unit is used to recognize the information that the user needs to enhance based on the brain activity signal collected by the brain-computer interface module.

7. The sensory enhancement system based on brain-computer interface according to claim 6 is characterized in that: The signal recognition unit comprises: A signal processing subunit, used to process the brain activity signals collected by the brain-computer interface module; A feature extraction subunit, used to extract features of brain activity signals; The classification subunit classifies and identifies the features extracted by the feature extraction subunit based on the trained neural network model to obtain the enhanced sensory type selected by the user.

8. The sensory enhancement system based on brain-computer interface according to claim 1, characterized in that: The sensory enhancement system based on brain-computer interface also includes: A monitoring module, used to determine the current state of the user based on the brain activity signal collected by the brain-computer interface module; The control module is used to stop the stimulation operation of the brain-computer interface module when the monitoring module detects that the user is in a risky state.

9. The sensory enhancement system based on brain-computer interface according to claim 1, characterized in that: The sensory enhancement system based on brain-computer interface also includes: A feedback module, used for providing user feedback on stimulation status; The adjustment module is used to adjust the brain-computer interface module based on the user's feedback information, and the brain-computer interface module adaptively adjusts the stimulation strategy according to the adjustment result of the adjustment module.

10. The sensory enhancement system based on brain-computer interface according to claim 1, characterized in that: Sensory types include visual type, auditory type, tactile type, olfactory type and taste type.

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