Feedback system based on motor imagery brain-computer interface

A motion imagery and feedback system technology, applied in the field of feedback system, can solve the problems of reducing the universality of the system and user experience, lack of instruction feedback paths, etc., and achieve considerable social and economic benefits.

Inactive Publication Date: 2016-04-06
TIANJIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] However, most of the current MI-BCI designs are an open-loop system, that is, there is only a one-way control path from the user's motor imagination to the command output, and there is no feedback path after the command output, which reduces the universality of the system and the user experience. to experience

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  • Feedback system based on motor imagery brain-computer interface
  • Feedback system based on motor imagery brain-computer interface
  • Feedback system based on motor imagery brain-computer interface

Examples

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Embodiment 1

[0032] The embodiment of the present invention provides a feedback system based on motor imagery brain-computer interface, the system is used to design the online experiment of user motor imagery feedback, build the EEG signal acquisition device required for the experiment, and then collect the operator's EEG signal data, store it and then perform certain preprocessing, feature extraction, classification and recognition, see figure 1 (a), the feedback system includes: a feedback module 1 , an EEG collector 2 , a wireless transmission module 3 and a terminal device 4 .

[0033] Feedback module 1, used to write feedback interface.

[0034] In actual implementation, the feedback interface can be written and designed under the Matlab platform, and parameters such as target tasks, number of imaginations, and other parameters can be set. The embodiment of the present invention does not limit the setting of the parameters, which can be set according to the needs in practical applica...

Embodiment 2

[0042] The scheme in embodiment 1 is described in detail below in conjunction with specific example, accompanying drawing, see below for details:

[0043] EEG collector 2 collects leads related to motion (14 channels in total, namely AF3, AF4, F3, F4, F7, F8, FC5, FC6, T7, T8, P7, P8, O1, O2, see figure 1 (b) EEG signal.

[0044] The terminal device 4 also includes an initial feedback module and an online feedback module, wherein the specific experimental process of the initial feedback module is as follows: figure 2 Shown:

[0045] 1) To collect real-time EEG without an initial model, the user first rests for 30s, and generates an initial judgment threshold based on the ERD energy value of the last 20s data;

[0046] 2) Enter the MI feedback interface training for 20s, and when the initial judgment threshold is reached, the target command feedback result will be output, otherwise the target command feedback will not be triggered;

[0047] That is, the operation feedback s...

Embodiment 3

[0060] Below in conjunction with specific example, calculation formula, the scheme in embodiment 1, 2 is described in detail, see the following for details:

[0061] 1. ERD energy feature calculation

[0062] For the processing of motor imagery ERD / ERS signals, power spectrum time-frequency analysis is usually used. Short-time Fourier analysis is one of the commonly used time-frequency analysis methods at present. It assumes that EEG signals have a certain degree of short-term stationarity, that is, is that the spectral distribution of the signal is invariant within a finite time window. In the case of no initial model in Example 2, the short-time Fourier transform is used to process the motor imagery EEG to obtain the real-time change of the ERD energy value, and compare it with the initial judgment threshold to determine whether to trigger the target command.

[0063] 2. Binary classification co-space model and support vector machine

[0064] When the data accumulation in ...

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Abstract

The invention discloses a feedback system based on a motor imagery brain-computer interface. The feedback system comprises a feedback module, an electroencephalogram collector, a wireless transmission module and a terminal device; the feedback module is used for compiling a feedback interface; the electroencephalogram collector is used for collecting an electroencephalogram signal associated with motion; the electroencephalogram signal is amplified and filtered by the electroencephalogram collector after scalp electrode detection and is transmitted to the terminal device by the wireless transmission module; and the terminal device is used for carrying out data processing on the electroencephalogram signal to extract a motor imagery characteristic signal, and the motor imagery characteristic signal is used for forming visual feedback after mode identification and controlling the feedback interface to form a closed loop control system. Compared with the traditional MI-BCI system, the feedback system disclosed by the invention better conforms to a normal thinking action control process and approaches to actual interactive application, thereby being expected to provide critical technological guarantee for novel MI-BCI. The feedback system disclosed by the invention can be applied to the fields of disabled rehabilitation, electronic entertainment, industrial control, aerospace engineering, etc.

Description

technical field [0001] The invention relates to the field of brain-computer interface, in particular to a feedback system based on motor imagery brain-computer interface. Background technique [0002] The definition of BCI (Brain-Computer Interface) given by the First International Conference on Brain-Computer Interface is: "BCI is a communication control system that does not depend on the normal output channels of peripheral nerves and muscles in the brain." Among the current research results , it mainly collects and analyzes human EEG signals in different states, and then uses certain engineering techniques to establish a direct communication and control channel between the human brain and computers or other electronic devices, thereby realizing a brand new Information exchange and control technology can provide a way for the disabled, especially those who have lost basic limb motor functions but have normal thinking, to communicate and control information with the outside...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F3/01G06K9/62
CPCG06F3/015G06F18/2411G06F3/01G06F18/00
Inventor 明东王仲朋陈龙顾斌王坤何峰綦宏志许敏鹏周鹏
Owner TIANJIN UNIV
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