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Eye movement data-based electroencephalogram experiment evaluation system and method

A data and eye movement technology, applied in the field of information processing, can solve problems such as consuming computing time, achieve the effect of simple difficulty, improve prediction accuracy, and increase the participation of subjects

Active Publication Date: 2017-10-17
上海零唯一思科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

It is based on dynamic programming, which can effectively reduce the search time, but for a large number of sample data, O(n 2 ) time complexity still consumes a lot of computing time

Method used

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  • Eye movement data-based electroencephalogram experiment evaluation system and method
  • Eye movement data-based electroencephalogram experiment evaluation system and method
  • Eye movement data-based electroencephalogram experiment evaluation system and method

Examples

Experimental program
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Embodiment 1

[0031] Such as figure 1 As shown, the present embodiment collects the eye movement data of the object through the SMI iView ETG eye tracker, uses the BeGaze software to extract the eye movement data, and generates a distance matrix through the distance matrix module according to the fixation point in the eye movement data; then through the participation detection module and The emotion recognition module draws the result.

[0032] Such as image 3 As shown, this example was carried out in a strictly controlled experimental environment. The experiment is carried out in an independent and soundproof room. The indoor lighting is controlled by the lighting system to ensure that the light intensity is moderate and constant, and the room temperature is maintained at a comfortable temperature by the air conditioning system.

[0033]In this embodiment, 10 subjects were tested to participate in the emotion recognition experiment and wear an eye tracker to collect eye movement data. A...

Embodiment 2

[0038] This embodiment adopts the same environment and the same eye movement data collection equipment as in Embodiment 1. In addition, this embodiment uses the ESI NeuroScan system to collect EEG. The EEG cap has 64 electrodes, and the electrode distribution conforms to the internationally unified 10-20 system standard. Two of the leads are not used, so a total of 62 leads are collected. The sampling frequency of EEG cap is 1000Hz.

[0039] In this embodiment, 26 subjects were tested to test their participation in the emotion recognition experiment and wear an eye tracker to collect eye movement data. During the experiment, the degree of seriousness of the subjects was unknown. Using the method of the present invention, the object data is divided into serious and non-serious categories. Use the EEG-based emotion recognition method to calculate the accuracy of each person's emotion recognition. Among them, the average emotion recognition accuracy of all subjects was 68.52%,...

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Abstract

The invention discloses an eye movement data-based electroencephalogram experiment evaluation system and method. The method comprises the following steps of: acquiring eye movement data of an object through an eye tracker, and establishing a time-space model according to a point of regard in the eye movement data; calculating a similarity between sequences by using a dynamic time wrapping algorithm fast technology, establishing a distance matrix, carrying out outlier detection through a density-based clustering algorithm, and carrying out quantitative sorting by adoption of a learning, sorting and training model according to a clustering result so as to obtain a participation degree of the object. According to the system and method, the experiment participation degrees of objects can be objectively and quantitatively evaluated, so as to form feedbacks for experiments and models and then ensure the data quality and improve the model prediction accuracy. According to the system and method, quantitative evaluation is carried out on the experiment participation degrees of the objects, and quantitative feedbacks of emotion recognition experiment are constructed.

Description

technical field [0001] The present invention relates to a technology in the field of information processing, in particular to an eye movement data-based EEG experiment evaluation system and method. Background technique [0002] Machine learning is a science of artificial intelligence. The main research object of this field is artificial intelligence, especially how to improve the performance of specific algorithms in experience learning. Machine learning can be divided into: 1. Supervised learning; 2. Unsupervised learning; 3. Semi-supervised learning; 4. Enhanced learning. Today's supervised learning has relatively mature applications in various fields. However, the dependence of supervised learning on sample labels limits its further development: inaccurate labels, excessive sample bases, and excessive cost of given labels may affect supervision. learning accuracy. On the contrary, semi-supervised learning, unsupervised learning, and enhanced learning are closer to human...

Claims

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Application Information

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IPC IPC(8): G06F19/00G06K9/62
CPCG06F18/23G06F18/2411
Inventor 吕宝粮郑伟龙石振锋周畅
Owner 上海零唯一思科技有限公司
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