The South China University of Technology

South China Brain-computer Interface Technology Co.

Yuanqing Li

Jing Jing Xiao

Zhijun Zhang

Shenghong He

Yongqian Huang

Jun Qu

Provided is a motion sickness intervention method based on mindfulness meditation and brain-computer interface. The method includes: collecting multi-channel/single-channel electroencephalographic (EEG) signals of the current user in real time; determining the motion sickness level from the multi-channel/single-channel EEG signals, where the motion sickness level includes a first level and a second level; and in response to the motion sickness level being the first level, performing a suspension operation; or in response to the motion sickness level being the second level, selecting a meditation feedback scenario and guiding the current user to meditate to alleviate motion sickness.

Motion sickness intervention method based on mindfulness meditation and brain-computer interface

Disclosed are a brain-computer interface based robotic arm self-assisting system and method. The system comprises a sensing layer, a decision-making layer and an execution layer. The sensing layer comprises an electroencephalogram acquisition and detection module and a visual identification and positioning module and is used for analyzing and identifying the intent of a user and identifying and locating positions of a corresponding cup and the user's mouth based on the user intent. The execution layer comprises a robotic arm control module that performs trajectory planning and control for a robotic arm based on an execution instruction received from a decision-making module. The decision-making layer comprises the decision-making module that is connected to the electroencephalogram acquisition and detection module, the visual identification and positioning module and the robotic arm control module to implement the acquisition and transmission of data of an electroencephalogram signal, a located position and a robotic arm status and the sending of the execution instruction for the robotic arm. The system combines the visual identification and positioning technology, a brain-computer interface and a robotic arm to facilitate paralyzed patients to drink water by themselves, improving the quality of life of the paralyzed patients.

Brain-computer interface based robotic arm self-assisting system and method

The present invention discloses an EOG-based method and apparatus for asynchronous character input, said method comprising the following steps: displaying a virtual keyboard having a total of N keys on a display, the virtual keyboard flickering in rounds, wherein in each round, all N keys randomly flicker once; when spelling, a user blinks after the flickering of a target key, so as to acquire electro-oculogram signals of the user in real-time; capturing electro-oculogram data within a time period following the flickering of a key from the acquired electro-oculogram signals, and using said electro-oculogram data as an original feature vector of the flickering key; N original feature vectors being generated in each cycle, an electro-oculogram identification method is called to identify the N original feature vectors, and outputting a certain result from 0 to N, wherein 0 indicates that a condition for character input is not met, and 1 to N correspond to the N keys on the virtual keyboard. The present invention ensures that blinking by a user may be detected normally, while at the same time effectively eliminating misjudgments of non-blinking signals, thus increasing the accuracy rate of character input.

EOG-based method and apparatus for asynchronous character input

A human-machine interaction method based on visual stimulations. The method can be applied to multiple new technical fields of display, which comprise but are not limited to the fields of virtual reality (VR), augmented reality (AR), mixed reality (MR), holographic projection and glasses-free 3D. The system consists of three parts: a human body biological collection apparatus, a software client for human-machine interaction and a display terminal. Input ports of the software client are connected to a human body physiological signal collection device (in a wired or wireless manner); a user wears the collection device, and communication ports of the client are respectively connected to communication ports of a display module by means of a multichannel communication module. Firstly, the system is initialized, and then starts to run based on a control method of visual stimulations (an object flicker or distortion). If a target is a text input target, an interface is switched to a text input interface, and texts are inputted by using a physiological signal detection algorithm for a human body. If the target is not a text input target, the type of information is determined by using a detection algorithm of a specific physiological signal and visual stimulation feedback information, so as to complete the interaction. Search and switching can be performed among text input boxes, selection options and multiple directories, and a bottom layer of the directories can be reached, so as to select a target.

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Guangzhou, China

Yuanqing Li