Universal model of gesture action intention detection based on electroencephalogram signal

A technology of EEG signals and general models, applied in the computer field, can solve problems such as not proposed, time-consuming, and personal models that cannot meet the requirements of practical applications, so as to achieve the best experience, improve safety and driving experience.

Active Publication Date: 2018-11-23
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

Applying the brain-computer interface to distinguish the intention of gestures through the EEG signals when people make gestures, researchers have not yet proposed a related BCI-based gesture intention detection system, and the existing research models are based on A personal model, that is, a model for each person, this method is quite time-consuming in practical applications, as far as the current situation is concerned, the personal model is far from meeting the requirements of practical applications

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  • Universal model of gesture action intention detection based on electroencephalogram signal
  • Universal model of gesture action intention detection based on electroencephalogram signal
  • Universal model of gesture action intention detection based on electroencephalogram signal

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Embodiment Construction

[0017] The general model method for the true and false intention detection of gestures based on EEG signals described in the present invention is especially suitable for the application level, and those skilled in the art can combine it with various existing detection systems according to the foundation and principle of the present invention. Further extend or improve the performance of the model.

[0018] The basic principle of the present invention is that when there is a need to stop, the driver makes a stop gesture when encountering a pedestrian crossing the road; processing to detect true braking intention; when detecting true braking intention, the data of the same participant is not applied, but according to the similarity of EEG signals of different people under similar or the same environmental conditions and under the same stimulus Or synchronicity, use the data of multiple participants to build a general model through the convolutional neural network, which is appli...

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Abstract

The invention relates to a universal model of gesture action intention detection based on an electroencephalogram signal. Specifically, by processing the collected electroencephalogram signal, a universal model is constructed by a convolutional neural network method to detect whether a subject has an intention to perform a hand action. The model proposed by the invention is a universal model, which is different from a personal model in the previous work. The model does not train the electroencephalogram signal of a participant to directly participate in the test, the training data are from theother participants, and an experimenter obtains the accuracy of the model by analyzing the electroencephalogram signal. The invention belongs to the comprehensive application of the computer field, the vehicle design field, the human-computer interaction science, the psychology science, the cognitive neuroscience and the automatic control field.

Description

technical field [0001] The invention relates to a general model of gesture action intention detection based on electroencephalogram signals. Specifically, by processing the collected EEG signals, a general model is built through the method of convolutional neural network to realize the detection of whether the subjects intend to make gestures or not. The model proposed by the present invention is a general model, which is different from the personal model in the previous work. The model does not use the participants' EEG signals for training but directly participates in the test. The training data comes from other participants, experimenters The accuracy of the model is obtained by analyzing the EEG signal. The invention belongs to the comprehensive application of computer field, vehicle design field, human-computer interaction science, psychological science, cognitive neuroscience and automatic control field. Background technique [0002] In daily life, our gestures are m...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F3/01
CPCG06F3/015G06F3/017
Inventor 毕路拯王晓光王会康
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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