CN111571619A - Life assisting system and method based on SSVEP brain-controlled mechanical arm grabbing - Google Patents
Life assisting system and method based on SSVEP brain-controlled mechanical arm grabbing Download PDFInfo
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- CN111571619A CN111571619A CN202010310189.XA CN202010310189A CN111571619A CN 111571619 A CN111571619 A CN 111571619A CN 202010310189 A CN202010310189 A CN 202010310189A CN 111571619 A CN111571619 A CN 111571619A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J13/00—Controls for manipulators
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J13/00—Controls for manipulators
- B25J13/08—Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
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Abstract
The invention discloses a life auxiliary system and method based on SSVEP brain-controlled mechanical arm grabbing. The method of the invention comprises the following steps: the brain wave cap is used for assisting a user to wear the brain wave cap firstly by a professional, then the intention expression interface of the computer end is opened, when the intention expression interface has stimulation and flicker, the user watches the corresponding block on the intention expression interface according to the requirement of the user, the brain wave cap collects brain wave signals of the user at the moment and transmits the brain wave signals to the SSVEP decoding unit of the computer end, decoding is carried out through preprocessing and an FBCCA algorithm, the decoding result is converted into a control instruction and is sent to the mechanical arm, the mechanical arm executes the control instruction, corresponding articles are grabbed according to a planned path, and therefore the purpose of assisting the daily life of the user is achieved, and particularly, the brain wave cap is more convenient and safer for.
Description
Technical Field
The invention designs a life auxiliary system and a life auxiliary method based on SSVEP (Steady-State visual evoked Potentials) brain-controlled mechanical arm grabbing for old people and disabled people, wherein the system comprises an electroencephalogram cap, a computer, an intention expression interface, an SSVEP decoding unit and a mechanical arm, so that the old people and the disabled people are assisted to grab required articles independently under the condition of no help of people, the daily life is assisted, the problem of inconvenient life is solved, and the life quality is improved.
Background
According to 2019, 8500 million disabled people exist in China, and 4400 million disabled and semi-disabled old people exist. Many of them require auxiliary implements. The auxiliary appliance is a product for compensating and replacing human body functions, and is a means for helping disabled persons and old persons to improve life quality and enhance social participation ability. The number of disabled people in China is large, and the obstacles caused by the disabilities can cause various difficulties in the lives of the disabled people, including worse health conditions, lower education receptivity, worse economic participation, higher poverty loss rate, higher dependence and the like. Participation in normal life is the biggest challenge, especially for special populations with speech communication impairment and loss of physical mobility. Therefore, developing a brain-controlled mechanical arm system capable of assisting the daily life of the elderly or the disabled, especially for the people with physical disabilities, improving the quality of life and the active participation ability of the people, and solving the problem of inconvenient life is necessary, and becomes a technical problem to be solved urgently.
Disclosure of Invention
In order to solve the problems in the prior art, the invention aims to overcome the defects in the prior art and provide a life assisting system and method based on SSVEP brain-controlled mechanical arm grabbing, the basic principle is that each block on an intention expression interface represents a specific article, the blocks flicker with different frequencies, a user watches the corresponding block representing the article on the intention expression interface according to the requirement of the user, namely the article to be grabbed, an electroencephalogram cap collects electroencephalogram signals of the user at the moment and transmits the electroencephalogram signals to an SSVEP decoding unit at the computer end in a wired or wireless mode to perform filtering and typical correlation analysis of an FBCCA filter set. The frequency corresponding to the brain potential induced by the visual stimulation of the user is decoded, the object which the user wants to grab is known by finding the block corresponding to the intention expression interface through the frequency, and then the computer sends an instruction to control the mechanical arm to grab the corresponding object, so that the operation of assisting the old and the disabled to grab the required object is realized.
In order to achieve the purpose of the invention, the invention adopts the following technical scheme:
a life auxiliary system based on SSVEP brain control mechanical arm grabbing comprises an electroencephalogram cap, a computer, an intention expression interface, an SSVEP decoding unit and a mechanical arm, wherein the electroencephalogram cap is connected with the computer in a wired or wireless mode, the computer comprises the intention expression interface and the SSVEP decoding unit, and the mechanical arm is connected with the computer in a wired connection mode; the electroencephalogram cap is used for helping a user wear the electroencephalogram cap, an intention expression interface of a computer end is opened, when the intention expression interface has stimulation and flicker, the user watches corresponding blocks on the intention expression interface according to the requirement of the user, the electroencephalogram cap collects electroencephalogram signals of the user at the moment and transmits the electroencephalogram signals to an SSVEP decoding unit of the computer end, the signals are decoded through a pretreatment and filter bank typical correlation analysis FBCCA algorithm, decoding results are converted into control instructions and sent to a mechanical arm, the mechanical arm executes the control instructions, and corresponding articles are grabbed according to a planned path.
As the preferred technical scheme of the invention, the brain electricity cap adopts a Borikang 24-lead dry electrode cap, and brain electricity signal collection can be carried out on the scalp of a user without beating brain electricity cream. The system is connected with a computer in a wired serial port communication mode or in a wireless Bluetooth mode; the computer comprises an intention expression interface and an SSVEP decoding unit; the mechanical arm adopts Kinova6 axle bionic mechanical arm, and the mechanical arm is connected with the computer through wired mode.
As a preferred technical solution of the present invention, the intention expression interface includes 12 blocks, and the 12 blocks represent 12 instructions: 1 part of apple, 1 part of banana, 1 part of green tea, orange, cola, 2 parts of apple, 2 parts of banana, mineral water, orange, seven happiness, cancellation and confirmation; the user watches the needed article firstly, then watches the cancellation or confirmation block, and after the confirmation block is excited, the mechanical arm executes the action of grabbing the article.
As a preferable technical scheme of the invention, the SSVEP decoding unit firstly preprocesses, namely filters, an electroencephalogram signal of a user, then adopts typical correlation analysis of an FBCCA filter bank, and finally decodes and identifies an instruction which the user wants to send, thereby realizing that the brain of the user controls a mechanical arm to grab a corresponding article.
As the preferred technical scheme of the invention, the mechanical arm carries out path planning by a forward and reverse kinematics principle, and avoids the phenomenon of blockage by adopting continuous trajectory planning.
A life auxiliary method based on SSVEP brain-controlled mechanical arm grabbing adopts the life auxiliary system based on SSVEP brain-controlled mechanical arm grabbing to operate, and comprises the following operation steps:
1) the professional helps the user wear the electroencephalogram cap;
2) opening an intention expression interface;
3) when the intention expression interface appears stimulating and flickering, the user watches the corresponding block according to the requirement; meanwhile, the electroencephalogram cap collects electroencephalogram signals and transmits the electroencephalogram signals to the SSVEP decoding unit at the computer end in a wired or wireless mode;
4) the SSVEP decoding unit decodes through an FBCCA algorithm;
5) the SSVEP decoding unit sends a control command to the mechanical arm after decoding through the FBCCA algorithm;
6) and the mechanical arm grabs the corresponding article according to the planned path.
As a preferred technical solution of the present invention, in the step 2), the designed intention expression interface comprises 12 blocks, wherein the 12 blocks represent 12 instructions, apple 1, banana 1, green tea, orange, cola, apple 2, banana 2, mineral water, orange, qixi, cancel and confirm.
As a preferred technical solution of the present invention, in the step 3), the user first watches the corresponding block of the desired item in the intention expression interface, and then watches the cancel or confirm block. During the watching period, the electroencephalogram signals are transmitted to the SSVEP decoding unit at the computer end for processing in a wired or wireless mode.
As a preferable technical solution of the present invention, in the step 4), the SSVEP decoding unit performs preprocessing, i.e., filtering, on the electroencephalogram signal of the user, performs typical correlation analysis on the FBCCA filter bank, and decodes and identifies an instruction that the user wants to send, so as to implement an operation that the user brain controls the mechanical arm to grab a corresponding item.
As a preferred technical solution of the present invention, the step of decoding the electroencephalogram signal by the FBCCA algorithm in the step 5) is as follows:
5-1) carrying out filter bank analysis, and decomposing the SSVEP electroencephalogram signals through a plurality of different pass bands of the filter to obtain sub-band signals passing through each sub-band of the filter;
5-2) carrying out correlation analysis on each sub-band component obtained by filtering and a standard sine and cosine reference signal;
5-3) the frequency corresponding to the maximum correlation is the identification result; and according to the algorithm recognition result, after the confirmation block is judged to be excited, sending a control command to the mechanical arm, and executing the action of grabbing the article by the mechanical arm.
Compared with the prior art, the invention has the following obvious and prominent substantive characteristics and remarkable advantages:
1. the invention adopts the brain-computer interface technology, establishes a channel between the brain of a user and a computer or other electronic equipment, does not depend on peripheral nerves and muscle tissues, and realizes that the brain controls external equipment; SSVEP steady state visual evoked potential is one of brain-computer interface technology, the brain is induced to generate different frequency potentials through visual stimulation with different frequencies, electroencephalogram signals are collected and processed by an electroencephalogram cap, the corresponding visual stimulation frequency is decoded, the intention of a user is decoded, and then a control command is output to control the motion of a mechanical arm, namely, the operation that the user controls the mechanical arm through the brain is realized;
2. the scalp electroencephalogram paste is convenient to use, and complex scalp electroencephalogram paste is not needed; a more humanized interactive interface can enable a user to clearly express the intention of the user; mechanical arms for grabbing articles are expanded, and the old and the disabled are assisted to grab the articles needed by the old and the disabled without help of people;
3. the system of the invention is easy to expand, realizes more functions, and has simple operation method and low cost.
Drawings
FIG. 1 is a block diagram of the system architecture of the present invention.
FIG. 2 is a general experimental flow chart of the present invention.
FIG. 3 is a flowchart of a computer program according to the present invention.
Fig. 4 is an intention expression interface stimulation screen of the present invention.
FIG. 5 is an intention expression interface feedback screen of the present invention.
Detailed Description
The above-described scheme is further illustrated below with reference to specific embodiments, which are detailed below:
the first embodiment is as follows:
in this embodiment, as shown in fig. 1, a life assisting system based on SSVEP brain-controlled mechanical arm grabbing comprises an electroencephalogram cap 1, a computer 2, an intention expression interface 3, an SSVEP decoding unit 4 and a mechanical arm 5, wherein the electroencephalogram cap 1 is connected with the computer 2 in a wired or wireless manner, the computer 2 includes the intention expression interface 3 and the SSVEP decoding unit 4, and the mechanical arm 5 is connected with the computer 2 in a wired manner; the electroencephalogram cap is characterized in that a professional helps a user to wear the electroencephalogram cap 1, the intention expression interface 3 of the computer 2 is opened, when the intention expression interface 3 flickers in a stimulating mode, the user watches corresponding blocks on the intention expression interface 3 according to own needs, the electroencephalogram cap 1 collects electroencephalograms of the user at the moment and transmits the electroencephalograms to the SSVEP decoding unit 4 of the computer 2, the users decode through a pretreatment and filter bank typical correlation analysis FBCCA algorithm, decoding results are converted into control instructions and sent to the mechanical arm 5, the mechanical arm 5 executes the control instructions, and corresponding articles are grabbed according to a planned path.
Example two:
this embodiment is substantially the same as the first embodiment, and is characterized in that:
in this embodiment, the intention expression interface 3 includes 12 blocks, and 12 blocks represent 12 instructions: 1 part of apple, 1 part of banana, 1 part of green tea, orange, cola, 2 parts of apple, 2 parts of banana, mineral water, orange, seven happiness, cancellation and confirmation; the user watches the needed article firstly, then watches the cancellation or confirmation block, and after the confirmation block is excited, the mechanical arm executes the action of grabbing the article.
The SSVEP decoding unit 4 firstly preprocesses, namely filters, an electroencephalogram signal of a user, then adopts typical correlation analysis of an FBCCA filter bank, and finally decodes and identifies an instruction which the user wants to send, so that the user brain controls the mechanical arm 5 to grab a corresponding article.
The mechanical arm 5 performs path planning by a forward and reverse kinematics principle, and avoids the stuck phenomenon by adopting continuous trajectory planning.
EXAMPLE III
This embodiment is substantially the same as the previous embodiment, and is characterized in that:
in this embodiment, as shown in fig. 2, a life assisting method based on SSVEP brain-controlled mechanical arm grabbing is performed by using the life assisting system based on SSVEP brain-controlled mechanical arm grabbing in the foregoing embodiment, and the operation steps are as follows:
1) the cap 1 collects electroencephalogram signals and transmits the electroencephalogram signals to the SSVEP decoding unit 4 at the computer 2 end in a wired or wireless mode;
4) the SSVEP decoding unit 4 decodes through the FBCCA algorithm;
5) after the SSVEP decoding unit 4 decodes the signals through the FBCCA algorithm, a control command is sent to the mechanical arm 5;
6) the mechanical arm 5 grabs the corresponding article according to the planned path.
Example four
This embodiment is substantially the same as the previous embodiment, and is characterized in that:
in this embodiment, as shown in fig. 1, a life assisting system and method based on SSVEP brain-controlled mechanical arm grabbing includes an electroencephalogram cap, a computer, an intention expression interface, an SSVEP decoding unit, and a mechanical arm. The brain electricity cap adopts the briukan 24-lead dry electrode cap, and the user scalp can be used for collecting brain electricity signals without beating brain electricity cream. The dry electrode cap amplifies the acquired microvolt level electroencephalogram signals, and converts the electroencephalogram analog signals into digital signals through A/D (analog to digital) conversion, wherein the sampling rate is 250 Hz. The device can be connected with a computer in a wired serial port communication mode and can also be connected with the computer in a wireless Bluetooth mode; the computer comprises an intention expression interface and an SSVEP decoding unit; the intent expression interface is for user interaction; the SSVEP decoding unit is used for preprocessing, namely filtering, electroencephalograms of a user, performing typical correlation analysis on an FBCCA filter bank, and decoding and identifying instructions which the user wants to send; the mechanical arm is a Kinova 6-axis bionic mechanical arm and is connected with a computer in a wired mode; the operation steps are as follows: firstly, a professional helps a user to wear the electroencephalogram cap, then the intention expression interface of the computer end is opened, when the intention expression interface has stimulation and flicker, the user watches the corresponding block on the intention expression interface according to the requirement of the user, the electroencephalogram cap collects electroencephalogram signals of the user at the moment, the electroencephalogram signals are transmitted to the SSVEP decoding unit of the computer end to be decoded through the FBCCA algorithm, the decoding result is converted into a control instruction and sent to the mechanical arm, and the mechanical arm executes the control instruction to capture the corresponding article.
As shown in fig. 2, an experimental process of a life assisting system and method based on SSVEP brain-controlled mechanical arm grasping: firstly, a professional helps a user to wear the Borykang 24-lead dry electrode cap, then an intention expression interface at the computer end is opened, when the intention expression interface is stimulated to flicker, the user watches the corresponding block on the intention expression interface according to the requirement of the user, the electroencephalogram cap collects the electroencephalogram signals of the user at the moment, the electroencephalogram signals are transmitted to an SSVEP decoding unit at the computer end in a wired or wireless mode to be decoded, after the decoding is successful, a control instruction is sent to a Kinova 6-axis bionic mechanical arm, and the mechanical arm executes the control instruction to grab the corresponding article.
As shown in fig. 3, a computer-side program flow of the life assisting system and method based on SSVEP brain-controlled mechanical arm grabbing is divided into two parts, namely, an SSVEP decoding unit and an intention expression interface. The SSVEP decoding unit is referred to herein as a processor and the intended expression interface is a stimulator. The electroencephalogram signals are collected by the electroencephalogram cap and then sent to a processor (SSVEP decoding unit) at the computer end, and the processor and the stimulator interact data through TCP/IP communication.
Processor (SSVEP decode unit) program flow:
1) initializing each electroencephalogram parameter, acquiring frequency of electroencephalogram data, extracting a data channel and processing time of data.
2) And initializing a mechanical arm communication interface, establishing communication with the mechanical arm, and conveniently sending control information.
3) TCP/IP communication is established to provide a transmission data channel for the stimulator.
4) And receiving the electroencephalogram cap electroencephalogram signals, carrying out filtering and typical correlation analysis of an FBCCA filter bank, and decoding the frequency of the block watched by the user.
5) And sending the data obtained by the processing to the stimulator.
6) And sending the data obtained by processing to the mechanical arm, and grabbing the article by the mechanical arm.
Stimulator (intent expression interface) program flow:
1) connecting TCP/IP generated by a processor program to receive data processed by a processor
2) Initializing stimulation normal form interface parameters, interface size and interface frequency parameters
3) Drawing an exciting paradigm interface, i.e. drawing an interface requiring a mechanical arm to grab an article
4) Stimulation paradigm interface producing stimulation signals
5) The receiving processor processes the obtained data
6) Stimulus interface displays processed results
The stimulator generates an intention expression interface, a user generates corresponding electroencephalogram signals through an stimulation paradigm of the intention expression interface, the electroencephalogram signals are collected and transmitted to the processor through an electroencephalogram cap, an SSVEP decoding unit in the processor decodes and analyzes the electroencephalogram signals, the electroencephalogram signals are finally sent to the stimulator, the intention expression interface displays processing results, control signals are sent to the mechanical arm, and finally the mechanical arm grabs needed articles.
As shown in fig. 4, a life assisting system and method based on SSVEP brain-controlled mechanical arm grabbing intends to express stimulator interface, where the interface includes 12 blocks, and 12 blocks represent 12 instructions, apple 1, banana 1, green tea, orange, cola, apple 2, banana 2, mineral water, orange, seven happiness, cancellation and confirmation. The 12 blocks correspond to 12 flicker frequencies, 9, 9.25, 9.5, 9.75, 10.25, 10.5, 10.75, 11, 11.25, 11.5, 11.75 and 12 Hz. The frequency of different blocks is different, according to the SSVEP steady-state vision induction principle, a user watches different blocks, namely watches different frequency signals, the brain generates different electroencephalogram signals, and the intention of the user can be known by decoding the electroencephalogram signals.
The electroencephalogram decoding adopts an FBCCA (Filter bank correlation analysis) algorithm, the method is an improvement on the CCA (Filter bank correlation analysis) algorithm, and a Filter bank is added on the basis of the CCA, so that electroencephalogram signal harmonic components which are not fully utilized in the traditional CCA algorithm are utilized, and the algorithm precision is improved. And (3) algorithm decoding:
1) constructing N band-pass filters, wherein all the band-pass filters cover all the band-pass frequencies as much as possible;
2) suppose that the order is solved for frequency fkThe maximum correlation coefficient of the signal of (a) with the EEG signal X. Respectively introducing the EEG data into N different band-pass filters to obtain N groups of data after the data pass through the band-pass filters;
3) solving a maximum correlation coefficient of a reference signal formed by each group of data and standard sine and cosine by using a CCA algorithm to obtain N phase relation numbers;
4) according to the formula w (n) ═ ae-bn+ c solving harmonic weight and substituting the result into formula
Solving the sum of the weights as frequency fkWith the maximum correlation coefficient p of the EEG signal Xk；
5) Respectively substituting the reference signals with 12 frequencies into the steps 2) to 4), finding the maximum correlation coefficient, wherein the corresponding frequency is the frequency of the SSVEP signal, and obtaining the identification result;
as shown in fig. 5, a life assisting system and method based on SSVEP brain-controlled mechanical arm grabbing intends to express an interface feedback picture. If the user wants to grab the apple 2, the user firstly watches the 6 th block (apple 2) on the interface when the user generates the stimulus flicker on the intention expression interface, and when the feedback appears on the interface, the apple 2 is displayed above the interface. When the stimulation flicker appears again on the intention expression interface, the last block (confirmation) on the interface is watched, and when the feedback appears on the interface, the grabbing is displayed above the interface, so that one grabbing instruction output is completed. After the interface is grabbed, the computer sends a control command to the mechanical arm, and the mechanical arm grabs the corresponding article.
In the grabbing process of the mechanical arm, in order to achieve a better grabbing effect, the mechanical arm does not touch a target object in the grabbing process, and a pre-grabbing pose is set. And setting the position as 10cm in the Z-axis negative direction of the grabbing pose. Because the pre-grabbing pose is set, two sections of tracks exist in the grabbing process.
1) From starting position to pre-capture pose
2) From a pre-grab pose to a grab pose
Because each planned path is from an initial speed 0 to a final speed 0, if two sections of trajectories are directly combined, frequent pause occurs in the motion process, and thus the problem of trajectory re-planning is involved.
First, the two movements are planned separately. After combining the two planned track points, calling an interface of an IPTP time optimization algorithm, replanning the information of the speed, the acceleration, the time and the like of the new track, and calling and executing continuous motion after the planning is finished.
In summary, the life assisting system and method based on the SSVEP brain-controlled mechanical arm grabbing in the above embodiments of the present invention includes an electroencephalogram cap 1, a computer 2, an intention expression interface 3, an SSVEP decoding unit 4, and a mechanical arm 5. The method of the invention comprises the following steps: firstly, a professional helps a user to wear the electroencephalogram cap 1, then the intention expression interface 3 at the computer 2 end is opened, when the intention expression interface 3 has stimulation and flicker, the user watches the corresponding block on the intention expression interface 3 according to the requirement of the user, the electroencephalogram cap 1 collects the electroencephalogram signals of the user at the moment and transmits the electroencephalogram signals to the SSVEP decoding unit 4 at the computer 2 end, the signals are decoded through preprocessing and FBCCA (Filter bank registration analysis) algorithm, the decoding result is converted into a control instruction and is sent to the mechanical arm 5, the mechanical arm 5 executes the control instruction, and the corresponding objects are grabbed according to a planned path, so that the purpose of assisting the daily life of the user is achieved, and particularly, more convenience and safety in life for the elderly and the disabled are achieved.
The embodiments of the present invention have been described above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes and modifications can be made according to the purpose of the invention, and all changes, modifications, substitutions, combinations or simplifications made according to the spirit and principle of the technical solution of the present invention shall be equivalent substitution ways, so long as the purpose of the present invention is met, and the protection scope of the present invention shall be covered as long as the technical principle and inventive concept of the life support system and method based on the SSVEP brain-controlled mechanical arm grasping of the present invention are not departed.
Claims (6)
1. The utility model provides a life auxiliary system based on SSVEP brain control arm snatchs, includes brain electricity cap (1), computer (2), intention expression interface (3), SSVEP decoding unit (4) and arm (5), its characterized in that: the electroencephalogram cap (1) is connected with a computer (2) in a wired or wireless mode, the computer (2) comprises an intention expression interface (3) and an SSVEP decoding unit (4), and the mechanical arm (5) is connected with the computer (2) in a wired mode; the electroencephalogram cap is worn by a professional to help a user, an intention expression interface (3) at the end of a computer (2) is opened, when stimulation flicker occurs on the intention expression interface (3), the user watches corresponding blocks on the intention expression interface (3) according to own requirements, electroencephalogram signals of the user at the moment are collected by the electroencephalogram cap (1), an SSVEP decoding unit (4) at the end of the computer (2) is transmitted, decoding is carried out through a typical correlation analysis FBCCA algorithm of a preprocessing and filter bank, a decoding result is converted into a control command and is sent to a mechanical arm (5), the mechanical arm (5) executes the control command, and corresponding articles are captured according to a planned path.
2. The life assisting system based on SSVEP brain-controlled mechanical arm grabbing of claim 1, wherein: the intention expression interface (3) comprises 12 blocks, wherein the 12 blocks represent 12 instructions: 1 part of apple, 1 part of banana, 1 part of green tea, orange, cola, 2 parts of apple, 2 parts of banana, mineral water, orange, seven happiness, cancellation and confirmation; the user watches the needed article firstly, then watches the cancellation or confirmation block, and after the confirmation block is excited, the mechanical arm executes the action of grabbing the article.
3. The life assisting system based on SSVEP brain-controlled mechanical arm grabbing of claim 1, wherein: the SSVEP decoding unit (4) firstly preprocesses the electroencephalogram signals of the user, namely filtering, then adopts typical correlation analysis of an FBCCA filter bank, and finally decodes and identifies the instruction which the user wants to send, thereby realizing the operation that the user brain controls the mechanical arm (5) to grab the corresponding article.
4. The life assisting system based on SSVEP brain-controlled mechanical arm grabbing of claim 1, wherein: the mechanical arm (5) carries out path planning through a forward and reverse kinematics principle, and avoids the phenomenon of blockage by adopting continuous trajectory planning.
5. A life assisting method based on SSVEP brain-controlled mechanical arm grabbing is operated by adopting the life assisting system based on SSVEP brain-controlled mechanical arm grabbing of claim 1, and is characterized by comprising the following operation steps:
1) the professional helps the user to wear the electroencephalogram cap (1);
2) opening an intention expression interface (3);
3) when the intention expression interface (3) appears stimulating and flickering, the user watches the corresponding block according to the requirement of the user; meanwhile, the electroencephalogram cap (1) collects electroencephalogram signals and transmits the electroencephalogram signals to the SSVEP decoding unit (4) at the computer (2) end in a wired or wireless mode;
4) the SSVEP decoding unit (4) decodes through an FBCCA algorithm;
5) the SSVEP decoding unit (4) sends a control command to the mechanical arm (5) after decoding through the FBCCA algorithm;
6) the mechanical arm (5) grabs corresponding articles according to the planned path.
6. The life assisting method based on SSVEP brain-controlled mechanical arm grabbing of claim 5, wherein the life assisting method comprises the following steps: the steps of the FBCCA algorithm in step 4) are as follows:
4-1) carrying out filter bank analysis, and decomposing the SSVEP electroencephalogram signals through a plurality of different pass bands of the filter to obtain sub-band signals passing through each sub-band of the filter;
4-2) carrying out correlation analysis on each sub-band component obtained by filtering and a standard sine and cosine reference signal;
4-3) the frequency corresponding to the maximum correlation is the identification result.
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| CN113359991A (en) * | 2021-06-10 | 2021-09-07 | 西安交通大学 | Intelligent brain-controlled mechanical arm auxiliary feeding system and method for disabled people |
| CN114146283A (en) * | 2021-08-26 | 2022-03-08 | 上海大学 | Attention training system and method based on target detection and SSVEP |
| CN114209343A (en) * | 2021-04-29 | 2022-03-22 | 上海大学 | Portable attention training system and method based on AR and SSVEP |
| CN117718962A (en) * | 2023-12-21 | 2024-03-19 | 太原理工大学 | Multi-task-oriented brain-control composite robot control system and method |
| CN118163115A (en) * | 2024-05-09 | 2024-06-11 | 安徽大学 | Robot control method based on SSVEP-MI and face key point detection fusion |
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