CN116350174A

CN116350174A - Brain-computer interface device and information acquisition method

Info

Publication number: CN116350174A
Application number: CN202111620144.3A
Authority: CN
Inventors: 陆晓风; 李良川
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2021-12-27
Filing date: 2021-12-27
Publication date: 2023-06-30
Also published as: WO2023125478A1

Abstract

The embodiment of the application discloses a brain-computer interface device and an information acquisition method, and relates to the field of Internet of things, wherein the brain-computer interface comprises a light source, a time domain delay module, a wavelength-dependent light splitting module, a sensing network and a sensing front end; the light source is used for providing a wide-spectrum pulse light array, the time domain delay module is used for converting the wide-spectrum pulse light array into a multi-wave pulse light array, the wavelength related light splitting module is used for decomposing the multi-wave pulse light array into a sparse pulse light array, the sensing network is used for sending the sparse pulse light array to a sensing point at the front end of the sensing network, and the front end of the sensing network is used for sending the sparse pulse light array to a target brain through the sensing point so as to acquire sensing information, so that detection light with different wavelengths is obtained through using the wide-spectrum pulse light and the time domain delay technology, a plurality of light sources are not needed, and a corresponding wavelength control module is not needed to be added, thereby realizing high spatial resolution of a brain-computer interface on the basis of ensuring small integration of the brain-computer interface.

Description

Brain-computer interface device and information acquisition method

Technical Field

The embodiment of the application relates to the field of Internet of things, in particular to a brain-computer interface device and an information acquisition method.

Background

Brain-computer interface (Brain-Computer Interface, BCI) has become an important enabling technology for the intelligent world in the future in recent years. For example, in the meta-universe concept, brain-computer interfaces become an important component of its technology group.

The temporal resolution and the spatial resolution are main technical indexes of the BCI. In non-invasive brain machines, the implementation of the functional near infrared technology (functional near infrared, fNIR) has better temporal resolution but insufficient spatial resolution. The fmri is typically responsible for sensing of the local brain area using a set of near infrared emitting and receiving sensors, with several infrared receiving points placed around one infrared emitting point. Part of infrared light which is transmitted through the skull and enters the brain is scattered by brain tissues and reversely emitted, and is received by a photoelectric detector. In order to improve the spatial resolution, infrared lasers with different wavelengths can be used at each infrared emission end, and parallel sensing communication channels are formed between different sensor points.

However, each sensor point in the above scheme uses a different wavelength, which requires a wavelength control mechanism in the system, and if the laser wavelength or the temperature wavelength control is strictly controlled and selected, the implementation cost of the system increases dramatically with the increase of the number of sensor points, and the host of the system is huge in scale.

Disclosure of Invention

The embodiment of the application provides a brain-computer interface device which is used for realizing high spatial resolution of a brain-computer interface on the basis of ensuring small integration of the brain-computer interface. The embodiment of the application also provides a corresponding information acquisition method.

The first aspect of the application provides a brain-computer interface device, which comprises a light source, a time domain delay module, a wavelength-dependent light splitting module, a sensing network and a sensing front end; the light source is used for providing sensing detection light, the sensing detection light comprises a plurality of broad-spectrum pulse light columns, the repetition frequency of the plurality of broad-spectrum pulse light columns is a first repetition frequency, and each broad-spectrum pulse light column consists of a plurality of pulse lights with different wavelengths; the time domain delay module is used for converting a plurality of broad-spectrum pulse light columns into a plurality of multi-wave pulse light columns, each multi-wave pulse light column comprises a plurality of pulse lights with different wavelengths, the repetition frequency of the pulse lights with different wavelengths is a second repetition frequency, the second repetition frequency is N times of the first repetition frequency, and N is the wavelength category number of the pulse lights with different wavelengths; the wavelength correlation light splitting module is used for decomposing a plurality of multi-wave pulse light columns into N sparse pulse light columns, each sparse pulse light column comprises a plurality of pulse lights with the same wavelength, and the repetition frequency of the pulse lights with the same wavelength is a first repetition frequency; the sensing network is used for transmitting N sparse pulse light columns to N sensing points at the front end of the sensing network; the sensing front end is used for sending N sparse pulse light columns to the target brain through N sensing points so as to acquire sensing information.

The light source in the application is a broad-spectrum pulse light source, the time domain delay module can be an optical fiber delay line, a dispersion module or a dispersion waveguide, the wavelength-related light splitting module is a light splitter, and the sensing network is a passive optical fiber network (passive optical network, PON).

The brain-computer interface device in the application adopts a functional infrared technology (fNIR), and the fNIR has better time resolution but insufficient spatial resolution. The method and the device are based on the wavelength division-time division multiplexing technology, adopt a point-to-multipoint PON network architecture, greatly improve the spatial density of the sensing point layout, improve the spatial resolution of fNIR and reduce the device cost.

The brain-computer interface device comprises a light source, a time domain delay module, a wavelength-dependent light splitting module, a sensing network and a sensing front end; the light source is used for providing a wide-spectrum pulse light array, the time domain delay module is used for converting the wide-spectrum pulse light array into a multi-wave pulse light array, the wavelength related light splitting module is used for decomposing the multi-wave pulse light array into a sparse pulse light array, the sensing network is used for sending the sparse pulse light array to a sensing point at the front end of the sensing network, and the front end of the sensing network is used for sending the sparse pulse light array to a target brain through the sensing point so as to acquire sensing information, so that detection light with different wavelengths is obtained through using the wide-spectrum pulse light and the time domain delay technology, a plurality of light sources are not needed, and a corresponding wavelength control module is not needed to be added, thereby realizing high spatial resolution of a brain-computer interface on the basis of ensuring small integration of the brain-computer interface.

In a possible implementation manner of the first aspect, the brain-computer interface device further includes a signal processing module, where the signal processing module is configured to convert the sensing information into sensing data.

In the possible implementation manner, the signal processing module is further arranged in the brain-computer interface device and is used for processing the sensing information collected by the sensing front end, so that the feasibility of the scheme is improved.

In a possible implementation manner of the first aspect, the sensing information is a sensing optical signal, and the signal processing module includes a photoelectric detection unit, an analog-to-digital conversion unit and a data processing unit; the photoelectric detection unit is used for converting the sensing optical signal into a sensing electric signal; the analog-to-digital conversion unit is used for converting the sensing electric signal into a sensing digital signal; the data processing unit is used for converting the sensing digital signals into sensing data.

In the possible implementation manner, the signal processing module comprises various processing units, and can convert the sensing signals into the sensing data which can be processed by other equipment, so that the feasibility of the scheme is improved.

In a possible implementation manner of the first aspect, the sensing front end is further configured to acquire an brain wave signal of the target brain, the analog-to-digital conversion unit includes a high-speed analog-to-digital conversion subunit and a low-speed analog-to-digital conversion subunit, the high-speed conversion subunit is configured to convert the sensing electric signal into a first sensing digital signal, the low-speed analog-to-digital conversion subunit is configured to convert the brain wave signal into a second sensing digital signal, and the data processing unit is specifically configured to convert the first sensing digital signal and the second sensing digital signal into sensing data.

In the possible implementation mode, the sensing front end not only provides sensing signals, but also provides brain wave signals, so that signals of two different modes are provided, and the processing precision of the sensing signals and the recognition capability of complex signal modes are improved.

In a possible implementation manner of the first aspect, the sensing front end further includes an electrode unit, and the electrode unit is configured to acquire brain wave signals of the target brain.

In the possible implementation mode, the sensing front end acquires brain wave signals through the electrode unit, so that the feasibility of the scheme is improved.

In a possible implementation manner of the first aspect, the low-speed analog-to-digital conversion subunit is connected to a sensing network, and a material of the sensing network and a material of the sensing front end are conductive materials.

In the possible implementation mode, the sensing front end directly acquires brain wave signals through the sensing network, so that the small-size integration of the brain-computer interface device is improved.

In a possible implementation manner of the first aspect, the wavelength-dependent optical splitting module includes an optical signal monitoring unit, where the optical signal monitoring unit is configured to send optical signal information of the N sparse pulse optical trains to the signal processing module, and the signal processing module is configured to adjust sensing probe light provided by the light source according to the optical signal information.

In the possible implementation manner, a feedback mechanism is arranged for the light source, so that the filtering characteristic of the wavelength-dependent light splitting module can be adapted, the output power of the light source is stabilized, and the detection accuracy of the brain-computer interface device is improved.

In a possible implementation manner of the first aspect, the brain-computer interface device further includes a data transmission module, where the data transmission module is configured to send the sensing data to the host computer.

In the possible implementation manner, the data transmission module is also arranged in the brain-computer interface device, is a wireless communication module and is used for sending the sensing data to the upper computer so as to further process the sensing data by the upper computer, thereby improving the realizability of the scheme.

In a possible implementation manner of the first aspect, the brain-computer interface device further includes an optical amplifier, and the optical amplifier is configured to enhance optical power of the broad spectrum pulse light train.

In the possible implementation manner, the optical amplifier is further arranged in the brain-computer interface device, so that the optical power of the broad-spectrum pulse light array is enhanced, and the detection accuracy of the brain-computer interface device is improved.

In a possible implementation manner of the first aspect, the sensing front end includes an optical fiber interface, the optical fiber interface is configured to receive N sparse pulse light columns, and an irradiation direction of the optical fiber interface and the N sparse pulse light columns are parallel.

In the possible implementation mode, the optical fiber interface is parallel to the irradiation directions of the N sparse pulse light columns, the layout structure is simple, and the structural mechanical stability of the brain-computer interface device is improved.

In a possible implementation manner of the first aspect, the sensing front end further includes a beam steering unit, and the beam steering unit is configured to change an irradiation direction of the N sparse pulse light trains.

In the possible implementation manner, the irradiation directions of the optical fiber interface and the N sparse pulse light columns are not parallel, so that the integration of the external structure of the sensing front end and the brain-computer interface device is simplified, and the layout of the optical fibers of the sensing network is simplified.

In a possible implementation manner of the first aspect, the sensing front end includes a skin contact, and a contact surface of the skin contact and the target brain is a spherical surface, a hemispherical surface or a smooth curved surface.

In the possible implementation manner, the contact surface of the skin contact and the target brain is a spherical surface, a semi-spherical surface or a smooth curved surface, so that the use experience of a user is enhanced.

In one possible implementation of the first aspect, the material of the skin contact is a flexible material.

In this possible implementation, the material of the skin contact is a flexible material, further enhancing the user experience.

A second aspect of the present application provides an information acquisition method applied to the brain-computer interface device in the first aspect or any one of the possible implementation manners of the first aspect, the method including: controlling a light source to provide sensing detection light, wherein the sensing detection light comprises a plurality of broad-spectrum pulse light columns, the repetition frequency of the plurality of broad-spectrum pulse light columns is a first repetition frequency, and each broad-spectrum pulse light column consists of a plurality of pulse lights with different wavelengths; the time domain delay module is controlled to convert a plurality of broad spectrum pulse light columns into a plurality of multi-wave pulse light columns, each multi-wave pulse light column comprises a plurality of pulse lights with different wavelengths, the repetition frequency of the pulse lights with different wavelengths is a second repetition frequency, the second repetition frequency is N times of the first repetition frequency, and N is the wavelength category number of the pulse lights with different wavelengths; the method comprises the steps that a wavelength-dependent light splitting module is controlled to split a plurality of multi-wave pulse light columns into N sparse pulse light columns, each sparse pulse light column comprises a plurality of pulse lights with the same wavelength, and the repetition frequency of the pulse lights with the same wavelength is a first repetition frequency; the method comprises the steps that a sensing network is controlled to send N sparse pulse light columns to N sensing points at the front end of sensing; and controlling the sensing front end to send N sparse pulse light columns to the target brain through N sensing points so as to acquire sensing information.

In the embodiment of the application, the brain-computer interface comprises a light source, a time domain delay module, a wavelength-dependent light splitting module, a sensing network and a sensing front end; the light source is used for providing a wide-spectrum pulse light array, the time domain delay module is used for converting the wide-spectrum pulse light array into a multi-wave pulse light array, the wavelength related light splitting module is used for decomposing the multi-wave pulse light array into a sparse pulse light array, the sensing network is used for sending the sparse pulse light array to a sensing point at the front end of the sensing network, and the front end of the sensing network is used for sending the sparse pulse light array to a target brain through the sensing point so as to acquire sensing information, so that detection light with different wavelengths is obtained through using the wide-spectrum pulse light and the time domain delay technology, a plurality of light sources are not needed, and a corresponding wavelength control module is not needed to be added, thereby realizing high spatial resolution of a brain-computer interface on the basis of ensuring small integration of the brain-computer interface.

Drawings

FIG. 1 is a schematic diagram of an embodiment of a brain-computer interface device according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a plurality of broad spectrum pulse trains according to an embodiment of the present disclosure;

FIG. 3 is a schematic diagram of a plurality of multi-wave pulse trains according to an embodiment of the present disclosure;

fig. 4 is a schematic diagram of a plurality of sparse pulse trains according to an embodiment of the present disclosure;

FIG. 5 is a schematic view of another embodiment of a brain-computer interface device according to an embodiment of the present application;

FIG. 6 is a schematic diagram of a sensing optical signal according to an embodiment of the present disclosure;

FIG. 7 is a schematic diagram of another embodiment of a brain-computer interface device according to an embodiment of the present application;

FIG. 8 is a schematic diagram of another embodiment of a brain-computer interface device according to an embodiment of the present application;

FIG. 9 is a schematic diagram of another embodiment of a brain-computer interface device according to an embodiment of the present application;

FIG. 10 is a schematic view of an embodiment of a sensor front end structure according to an embodiment of the present application;

FIG. 11 is a schematic view of another embodiment of a sensor front end structure provided in an embodiment of the present application;

fig. 12 is a schematic diagram of an embodiment of an information obtaining method according to an embodiment of the present application.

Detailed Description

Embodiments of the present application will now be described with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some, but not all embodiments of the present application. As a person of ordinary skill in the art can know, with the development of technology and the appearance of new scenes, the technical solutions provided in the embodiments of the present application are applicable to similar technical problems.

The terms first, second and the like in the description and in the claims of the present application and in the above-described figures, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

The word "exemplary" is used herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

In addition, numerous specific details are set forth in the following detailed description in order to provide a better understanding of the present application. It will be understood by those skilled in the art that the present application may be practiced without some of these specific details. In some instances, methods, means, elements, and circuits have not been described in detail as not to unnecessarily obscure the present application.

The embodiment of the application provides a brain-computer interface device which is used for realizing high spatial resolution of a brain-computer interface on the basis of ensuring small integration of the brain-computer interface. The embodiment of the application also provides a corresponding information acquisition method. The following will describe in detail.

Concepts related to the embodiments of the present application are explained below:

brain-computer interfaces are a deep development of Human-machine interface technology (Human-Computer Interface, HCI). The traditional man-machine interaction technology needs to be realized by means of media layer software and hardware, such as a computer display screen, a visual interface, a mouse and the like. The brain-computer interface realizes understanding of brain consciousness by directly detecting brain activities, and realizes intervention and even participation in brain activities by bioengineering means such as optogenetic means, brain electrodes and the like. The non-invasive brain-computer interface refers to a brain-computer sensing mode in which brain-signal sensing devices are arranged on the scalp and unexpected areas and any surgical operation is avoided. A typical non-invasive brain-computer architecture such as brain-wave sensing, i.e., the acquisition of brain waves by electrical means, and the acquisition of brain activity information by analysis of brain wave patterns.

Near infrared imaging (NIR) technology is now widely used for neuron imaging. The developed functional infrared technology (fNIR) based on the above can detect the activity of neurons and is widely applied to non-invasive brain-computer interfaces. fNIR is the medium of blood oxygen protein in blood to obtain information of brain nerve activity, and specifically, oxygen is needed to be consumed for the activity of human brain neurons. While oxygen in the blood is carried by the blood oxygen proteins. Thus, the higher the degree of cortical activity, the greater the blood oxygen consumption in this region, and the higher the hemoglobin (oxyhemoglobin HbO and deoxyhemoglobin HbR) concentration. Meanwhile, the concentration of hemoglobin, i.e., heme concentration, determines the absorbance of near infrared light, i.e., the ratio of incident to scattered NIR light power. Thus, by detecting the incident NIR light power and the scattered light power through brain tissue surrounding the incident electricity, the degree of activity of the cortex of the localized brain region can be analyzed.

The brain-computer interface device and the information acquisition method provided in the embodiments of the present application are described in detail below in conjunction with the above explanation of the concepts of the brain-computer interface and the fnr, respectively.

As shown in fig. 1, an embodiment of a brain-computer interface device provided in the present application includes: the system comprises a light source 100, a time domain delay module 200, a wavelength-dependent light splitting module 300, a sensing network 400 and a sensing front end 500.

Specifically, the light source 100 is configured to provide sensing probe light, where the sensing probe light includes a plurality of broad spectrum pulse light columns, and a repetition frequency of the plurality of broad spectrum pulse light columns is a first repetition frequency, and each broad spectrum pulse light column is composed of a plurality of pulse lights with different wavelengths; the time domain delay module 200 is configured to convert a plurality of broad spectrum pulse light columns into a plurality of multi-wave pulse light columns, where each multi-wave pulse light column includes a plurality of pulse lights with different wavelengths, the repetition frequency of the plurality of pulse lights with different wavelengths is a second repetition frequency, the second repetition frequency is N times the first repetition frequency, and N is the number of wavelength types of the plurality of pulse lights with different wavelengths; the wavelength-dependent spectroscopic module 300 is configured to decompose a plurality of multi-wave pulse light trains into N sparse pulse light trains, where each sparse pulse light train includes a plurality of pulse lights with the same wavelength, and a repetition frequency of the plurality of pulse lights with the same wavelength is a first repetition frequency; the sensing network 400 is configured to send N sparse pulse light columns to N sensing points of the sensing front end 500; the sensing front end 500 is configured to transmit N sparse pulse trains to the target brain 600 through N sensing points to obtain sensing information.

Optionally, in this embodiment, the light source 100 is a broad-spectrum pulse light source, specifically, a Kerr light comb, a mode-locked laser or other broad-spectrum light comb, as shown in fig. 2, the sensing probe light provided by the light source 100 includes a plurality of broad-spectrum pulse light columns, where the repetition frequency of the plurality of broad-spectrum pulse light columns is 1/T of the first repetition frequency, that is, the time interval for generating each broad-spectrum pulse light column by the light source 100 is T, and in addition, each broad-spectrum pulse light column is composed of a plurality of pulse lights with different wavelengths, that is, composed of discrete N wavelength components, where N is the number of kinds of wavelength components, and adjacent intervals of different wavelengths are equal.

Alternatively, the time domain delay module 200 in the embodiment of the present application may be an optical fiber delay line, a dispersion module, a dispersion waveguide, or the like, and in the embodiment of the present application, an optical fiber delay line with a specific length and a specific dispersion coefficient is used as the time domain delay module 200. The sensing probe light generated by the light source 100 is transmitted to the time domain delay module 200, the plurality of broad spectrum pulse light columns are separated through the time domain delay module 200 by dispersion, that is, the propagation speed of the light signals with different wavelengths in the dispersive medium is different, so that the light signal separation occurs, the pulse light columns with different wavelengths which are staggered in time are formed, that is, a plurality of multi-wave pulse light columns are formed, as shown in fig. 3, each multi-wave pulse light column comprises a plurality of pulse lights with different wavelengths, the repetition frequency of the pulse lights with different wavelengths is the second repetition frequency, the second repetition frequency is N times the first repetition frequency, that is, the second repetition frequency is N/T, the time interval of the pulse lights with different wavelengths generated by the time domain delay module 200 is T/N, the N kinds of the pulse lights with different wavelengths are the number of the pulse lights with different wavelengths, and the N kinds of the wavelengths alternately occur in sequence.

Optionally, in this embodiment of the present application, the wavelength-related optical splitting module 300 is an optical splitter, specifically, a wavelength-division Demultiplexer (DEMUX), and the multiple multi-wavelength pulse optical columns generated by the time-domain delay module 200 are transmitted to the wavelength-related optical splitting module 300, as shown in fig. 4, where the wavelength-related optical splitting module 300 splits the multiple multi-wavelength pulse optical columns into N sparse pulse optical columns, where each sparse pulse optical column includes multiple pulse lights with the same wavelength, and the repetition frequency of the multiple pulse lights with the same wavelength is 1/T of the first repetition frequency, that is, the time interval of each pulse light with the same wavelength generated by the wavelength-related optical splitting module 300 is T.

Optionally, in this embodiment of the present application, the sensing network 400 is a passive optical network (passive optical network, PON), N sparse pulse light columns generated by the wavelength-related optical splitting module 300 are transmitted to the sensing network 400, N optical paths exist in the sensing network 400, optionally, the optical paths are formed by optical fibers, specifically, a printed polymer waveguide or other optical waveguides, the sensing front end 500 includes N sensing points, each branch light of the sensing front end 500 is connected to a sensing point of the sensing front end 500, the sensing network 400 sends the N sparse pulse light columns to the N sensing points of the sensing front end 500 through the N optical paths, that is, the optical signals transmitted on each optical path are all of the same wavelength, and the formed time intervals of the pulse light are T, for the N optical paths, the time intervals of the pulse light formation between each other are sequentially different by T/N. Finally, the sensing front end 500 sends N sparse pulse light columns to the target brain 600 through N sensing points, the N sparse pulse light columns pass through the skull and each layer of tissue of the target brain 600 and are scattered by the cerebral cortex to form scattered light, the scattered light carries information of the brain nerve activity degree of the brain region near the sensing points, namely sensing information, particularly blood oxygen saturation intensity information, and the sensing front end 500 collects the sensing information, so that information of the target brain 600 is obtained.

Optionally, the sensing points include a light emitting end and a light receiving end, where the light emitting end and the light receiving end are both used as an independent sensing point, and the light emitting end and the light receiving end are in one-to-one correspondence, that is, the sensing front end 500 includes 2N sensing points altogether, where the light emitting end is used for sending sparse pulse light columns, and the light receiving end is used for collecting scattered light carrying sensing information.

Optionally, the light source 100, the time domain delay module 200, the wavelength-dependent optical splitting module 300, the sensing network 400 and the sensing front end 500 are all connected by optical fibers to conduct optical signals.

For example, n=4, each broad spectrum pulse train is composed of discrete 4 wavelength components, the second repetition frequency is 4/T, the time interval for generating the pulse light of each different wavelength by the time domain delay module 200 is T/4, the number of wavelength types of the pulse light of the plurality of different wavelengths is 4, the wavelength-dependent spectroscopy module 300 decomposes the plurality of multi-wave pulse trains into 4 sparse pulse trains, the sensing network 400 has 4 optical paths, and the sensing front end 500 includes 4 sensing points.

As shown in fig. 5, another embodiment of a brain-computer interface device provided in the present application includes: the device comprises a light source 100, a time domain delay module 200, a wavelength-dependent light splitting module 300, a sensing network 400, a sensing front end 500 and a signal processing module 700.

The signal processing module 700 includes a photoelectric detection unit 710, an analog-to-digital conversion unit 720, and a data processing unit 730, where the signal processing module 700 is configured to convert sensing information into sensing data. Specifically, the sensing information is a sensing optical signal, and the photoelectric detection unit 710 is configured to convert the sensing optical signal into a sensing electrical signal; the analog-to-digital conversion unit 720 is used for converting the sensing electric signal into a sensing digital signal; the data processing unit 730 is used for converting the sensing digital signal into sensing data.

More specifically, the optical receiving end 520 of the sensing point collects scattered light carrying sensing information, that is, sensing optical signals, and then sends the scattered light to the photoelectric detection unit 710 through the sensing network 400, where the wavelength division demultiplexer and the PON can be integrated into a PON (time and wavelength division multiplexed PON, TWDM-PON) system based on time division and wavelength division multiplexing, that is, the PON transmitting end 410, and the PON transmitting end 410 are connected with the N light emitting ends 510 through N optical paths, so as to implement point-to-multipoint networking, the sensing network 400 and the wavelength division Multiplexer (MUX) are integrated into the PON receiving end 420, and the PON receiving end 420 is connected with the N optical receiving ends 520 through N optical paths, that is, the sensing network 400 includes 2N optical paths, the MUX collects the sensing optical signals returned by the N optical paths, and reforms a broad-spectrum pulse optical train with a time interval of T/N, as shown in fig. 6, and each branch carries dynamic sensing information, so that the pulse optical trains have different pulse intensities. Optionally, the photo detector 710 is a Photodiode (PD), the PD converts a broad spectrum pulse light column into a sensing electric signal, optionally, the analog-to-digital converter 720 is an analog-to-digital conversion (ADC), the ADC has a sampling rate of N/T, the sensing electric signal is converted into a sensing digital signal at a sampling frequency of N/T, an amplifying circuit is optionally disposed between the analog-to-digital converter 720 and the photo detector 710, the amplifying circuit is used for amplifying the sensing electric signal, finally, the data processing unit 730 converts the sensing digital signal into sensing data, optionally, the data processing unit 730 is a digital signal processing unit (digital signal process, DSP), the DSP analyzes the light intensity of each sensing point through an algorithm, extracts the brain region activity intensities of different space and time points through combining with the prior spatial information of the sensing point and combining with an artificial intelligence system and an expert system, and the like, and abstracts the brain activity mode.

Optionally, the brain-computer interface device further comprises an optical amplifier, wherein the optical amplifier is arranged between the time domain delay module and the wavelength-dependent light splitting module, and is used for enhancing the optical power of the broad-spectrum pulse light column, and the optical amplifier is an optical fiber amplifier or a semiconductor optical amplifier and the like.

Alternatively, as shown in fig. 7, in an embodiment, the PON transmitting end and the PON receiving end of the sensing network may be integrally multiplexed into a transceiver 430 of a PON network, and any wavelength division multiplexer or wavelength division demultiplexer having optical reciprocity is used. Meanwhile, on the basis, the light emitting end and the light receiving end of the sensing front end are also reconstructed into a structure integrating receiving and transmitting, namely, each sensing point has the functions of the light emitting end and the light receiving end, namely, the sensing network 400 comprises N optical paths, the sensing front end 500 comprises N sensing points, and the PON receiving and transmitting end 430 is connected with the N sensing points through the N optical paths.

Further, the wavelength-dependent optical splitting module 300 includes an optical signal monitoring unit 310, where the optical signal monitoring unit 310 is configured to send optical signal information of N sparse pulse optical trains to the signal processing module 730, and the signal processing module 730 is configured to adjust sensing probe light provided by the light source 100 according to the optical signal information, thereby forming a feedback mechanism, and adapting a filtering characteristic of the wavelength-dependent optical splitting module 300 and stabilizing output power of the light source. The brain-computer interface device further comprises a data transmission module 900, wherein the data transmission module 900 is used for sending the sensing data to the upper computer, and optionally, the data transmission module 900 is a wireless communication module, and the wireless communication module is used for uploading the original data, the preprocessed data, the state information and the like acquired by the brain-computer interface device to the upper computer, and simultaneously downloading control signals, the pre-training model, the equipment parameters and the like from the upper computer.

Optionally, in an embodiment, as shown in fig. 8 and fig. 9, the sensing front end 500 is further configured to acquire brain wave signals of the target brain, the analog-to-digital conversion unit 720 includes a high-speed analog-to-digital conversion subunit 721 and a low-speed analog-to-digital conversion subunit 722, the high-speed conversion subunit 721 is configured to convert the sensing electric signals into first sensing digital signals, the low-speed analog-to-digital conversion subunit 722 is configured to convert the brain wave signals into second sensing digital signals, and the data processing unit 730 is specifically configured to convert the first sensing digital signals and the second sensing digital signals into sensing data, so as to implement multi-mode signals, thereby improving processing accuracy of the signals, improving recognition capability of complex signal modes, and so on. The first sensing digital signal and the second sensing digital signal are multiplexed into a set of data processing unit 730, and the data processing unit 730 only regards the signal inputs of different channels as signals of different modalities. Optionally, the data processing unit 730 includes an independent or joint preprocessing module for each mode signal. Optionally, the signal processing module 700 further includes a central processing unit 740, where the central processing unit 740 is configured to: adjusting the wavelength and wavelength interval of the light source 100; adjusting the gain of the optical amplifier 800; adjusting the spectral characteristics of the wavelength-dependent spectroscopy module 300 to match the spectral characteristics of the light source; a transimpedance amplifier mode controlling the photodetection unit 710; is responsible for synchronization of multi-mode signals; analyzing information and data of the upper computer; signal processing parameters and super parameters, calculation and configuration, etc.

Specifically, there may be various ways to obtain brain wave signals, and the following descriptions respectively apply:

1. by means of an electrode unit:

as shown in fig. 8, the sensing front end 500 further includes an electrode unit 530, and the electrode unit 530 is used to acquire brain wave signals of the target brain 600. Specifically, the electrode units 530 are connected to the low-speed analog-to-digital conversion subunit 722 through wires, optionally, the low-speed analog-to-digital conversion subunit 722 is specifically an ADC array, each ADC corresponds to one wire, each wire corresponds to one electrode unit 530, each electrode unit 530 is used for forming an electroencephalogram channel to collect brain wave signals, and the low-speed analog-to-digital conversion subunit 722 samples the collected analog signals, i.e. brain wave signals, into digital signals, i.e. second sensing digital signals.

2. Through the sensing network:

as shown in fig. 9, the low-speed analog-to-digital conversion subunit 722 is connected to the sensing network 400, and specifically may be connected by a wire, where the wire corresponds to each optical path of the sensing network 400 one by one, and the material of the sensing network 400 and the material of the sensing front end 500 are conductive materials, that is, each optical path of the sensing network 400 and the sensing front end 500 are conductive, and optionally, conductive polymers are used to make optical fibers or optical fiber cladding layers of each optical path of the sensing front end 500 and the sensing network 400. Optionally, the cpu 740 is integrated inside the signal processing module 700, and the photodetection unit 710 is integrated outside the signal processing module 700 as a unit that the cpu 740 needs to adjust.

In addition, as shown in fig. 10 and 11, for the structure of the sensing front end, the sensing front end includes an optical fiber interface 503, a beam space modulation unit 504, a skin contact 505, a sleeve 502, and the like, where the optical fiber interface 503 is configured to receive N sparse pulse light columns through the optical fiber 501, a contact surface between the skin contact 505 and a target brain is a spherical surface, a semi-spherical surface, or a smooth curved surface, optionally, a material of the skin contact 505 is a flexible material, or may be a flexible conductive material, and the sensing front end has various layouts, optionally, as shown in fig. 10, the optical fiber 501 coincides with a sensing light direction, that is, an irradiation direction of the optical fiber interface 503 and the N sparse pulse light columns is parallel. Optionally, as shown in fig. 11, the optical fiber 501 is not coincident with the sensing direction, where the sensing front end further includes a beam steering unit 506, and the beam steering unit 506 is configured to change the irradiation directions of the N sparse pulse light columns, for example, the optical fiber interface 503 is perpendicular to the irradiation directions of the N sparse pulse light columns.

Optionally, the brain-computer interface device further comprises a skeleton as a support of the device, optionally, the skeleton is a hard skeleton or a flexible elastic wearable fabric as a skeleton.

As shown in fig. 12, an embodiment of an information obtaining method provided in the present application includes:

1201. the control light source provides sensing probe light.

The sensing detection light comprises a plurality of broad spectrum pulse light columns, the repetition frequency of the plurality of broad spectrum pulse light columns is a first repetition frequency, and each broad spectrum pulse light column consists of a plurality of pulse lights with different wavelengths;

1202. the time domain delay module is controlled to convert the plurality of broad spectrum pulse light columns into a plurality of multi-wave pulse light columns.

Each multi-wave pulse light array comprises a plurality of pulse lights with different wavelengths, the repetition frequency of the pulse lights with different wavelengths is a second repetition frequency which is N times of the first repetition frequency, and N is the wavelength category number of the pulse lights with different wavelengths;

1203. the control wavelength correlation light splitting module is used for decomposing the plurality of multi-wave pulse light columns into N sparse pulse light columns.

Each sparse pulse light column comprises a plurality of pulse lights with the same wavelength, and the repetition frequency of the pulse lights with the same wavelength is a first repetition frequency;

1204. and controlling the sensing network to send the N sparse pulse light columns to N sensing points at the front end of the sensing.

1205. And controlling the sensing front end to send N sparse pulse light columns to the target brain through N sensing points so as to acquire sensing information.

Optionally, the execution subject of the information acquisition method is a central processing unit in the brain-computer interface device. The specific implementation of the information obtaining method provided in the embodiment of the present application may refer to the description of the embodiment section of the brain-computer interface device in the foregoing embodiment, and the embodiment of the present application is not repeated.

In the embodiment of the application, the wide-spectrum pulse light array is provided by controlling the light source, the time domain delay module is controlled to convert the wide-spectrum pulse light array into the multi-wave pulse light array, the wavelength related light splitting module is controlled to decompose the multi-wave pulse light array into the sparse pulse light array, the sensing network is controlled to send the sparse pulse light array to the sensing point at the sensing front end, and the sensing front end is controlled to send the sparse pulse light array to the target brain through the sensing point so as to acquire sensing information, so that detection light with different wavelengths is obtained by using the wide-spectrum pulse light and the time domain delay technology, a plurality of light sources are not required, and a corresponding wavelength control module is not required to be added, thereby realizing high spatial resolution of the brain-computer interface on the basis of ensuring small integration of the brain-computer interface.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.

In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (RAM, random access memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

Claims

1. The brain-computer interface device is characterized by comprising a light source, a time domain delay module, a wavelength-dependent light splitting module, a sensing network and a sensing front end;

the light source is used for providing sensing detection light, the sensing detection light comprises a plurality of broad spectrum pulse light columns, the repetition frequency of the plurality of broad spectrum pulse light columns is a first repetition frequency, and each broad spectrum pulse light column consists of a plurality of pulse lights with different wavelengths;

the time domain delay module is configured to convert the plurality of broad spectrum pulse light columns into a plurality of multi-wave pulse light columns, where each multi-wave pulse light column includes a plurality of pulse lights with different wavelengths, a repetition frequency of the plurality of pulse lights with different wavelengths is a second repetition frequency, the second repetition frequency is N times the first repetition frequency, and N is a wavelength category number of the plurality of pulse lights with different wavelengths;

the wavelength-dependent light splitting module is configured to split the multiple multi-wave pulse light trains into N sparse pulse light trains, where each sparse pulse light train includes multiple pulse lights with the same wavelength, and a repetition frequency of the multiple pulse lights with the same wavelength is the first repetition frequency;

the sensing network is used for sending the N sparse pulse light columns to N sensing points at the front end of the sensing;

the sensing front end is used for sending the N sparse pulse light columns to a target brain through the N sensing points so as to acquire sensing information.

2. The brain-computer interface device according to claim 1, further comprising a signal processing module for converting the sensory information into sensory data.

3. The brain-computer interface device according to claim 2, wherein the sensing information is a sensing optical signal, and the signal processing module comprises a photoelectric detection unit, an analog-to-digital conversion unit and a data processing unit;

the photoelectric detection unit is used for converting the sensing optical signal into a sensing electric signal;

the analog-to-digital conversion unit is used for converting the sensing electric signal into a sensing digital signal;

the data processing unit is used for converting the sensing digital signals into sensing data.

4. The brain-computer interface device according to claim 3, wherein the sensing front end is further configured to acquire brain wave signals of the target brain, the analog-to-digital conversion unit includes a high-speed analog-to-digital conversion subunit and a low-speed analog-to-digital conversion subunit, the high-speed conversion subunit is configured to convert the sensing electric signals into first sensing digital signals, the low-speed analog-to-digital conversion subunit is configured to convert the brain wave signals into second sensing digital signals, and the data processing unit is specifically configured to convert the first sensing digital signals and the second sensing digital signals into the sensing data.

5. The brain-computer interface device according to claim 4, wherein the sensing front end further comprises an electrode unit for acquiring brain wave signals of the target brain.

6. The brain-computer interface device according to claim 4, wherein the low-speed analog-to-digital conversion subunit is connected to the sensing network, and the sensing network and the sensing front end are made of conductive materials.

7. The brain-computer interface device according to any one of claims 2 to 6, wherein the wavelength-dependent spectroscopic module includes an optical signal monitoring unit for transmitting optical signal information of the N sparse pulse light trains to the signal processing module, and the signal processing module is configured to adjust sensing probe light provided by the light source according to the optical signal information.

8. The brain-computer interface device according to any one of claims 2-6, further comprising a data transmission module for transmitting the sensing data to an upper computer.

9. The brain-computer interface device according to any one of claims 1-6, further comprising an optical amplifier for enhancing the optical power of the broad spectrum pulse train.

10. The brain-computer interface device according to any one of claims 1 to 6, wherein the sensing front end includes an optical fiber interface for receiving the N sparse pulse light trains, the optical fiber interface being parallel to an irradiation direction of the N sparse pulse light trains.

11. The brain-computer interface device according to claim 10, wherein the sensing front end further comprises a beam steering unit for changing an irradiation direction of the N sparse pulse light trains.

12. The brain-computer interface device according to any one of claims 1-6, wherein the sensing front end includes a skin contact, and a contact surface of the skin contact with the target brain is a spherical surface, a hemispherical surface, or a smooth curved surface.

13. The brain-computer interface device according to claim 12, wherein the material of the skin contact is a flexible material.

14. An information acquisition method applied to the brain-computer interface device according to any one of claims 1 to 13, characterized in that the method comprises:

controlling the light source to provide sensing detection light, wherein the sensing detection light comprises a plurality of broad spectrum pulse light columns, the repetition frequency of the plurality of broad spectrum pulse light columns is a first repetition frequency, and each broad spectrum pulse light column consists of a plurality of pulse lights with different wavelengths;

controlling the time domain delay module to convert the plurality of broad spectrum pulse light columns into a plurality of multi-wave pulse light columns, wherein each multi-wave pulse light column comprises a plurality of pulse lights with different wavelengths, the repetition frequency of the plurality of pulse lights with different wavelengths is a second repetition frequency which is N times of the first repetition frequency, and N is the wavelength category number of the plurality of pulse lights with different wavelengths;

the wavelength-dependent light splitting module is controlled to split the plurality of multi-wave pulse light columns into N sparse pulse light columns, each sparse pulse light column comprises a plurality of pulse lights with the same wavelength, and the repetition frequency of the plurality of pulse lights with the same wavelength is the first repetition frequency;

controlling the sensing network to send the N sparse pulse light columns to N sensing points at the front end of the sensing network;

and controlling the sensing front end to send the N sparse pulse light columns to a target brain through the N sensing points so as to acquire sensing information.