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EOG-based human body behavior identification system and method

A technology for identifying systems and behaviors. It is applied to pattern recognition, character and pattern recognition in signals, and input/output processes of data processing. It can solve problems such as difficulty in ensuring the correct rate of signal recognition.

Active Publication Date: 2017-03-15
ANHUI UNIVERSITY
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AI Technical Summary

Problems solved by technology

Although the above detection methods have achieved some success, they only recognize human behavior from the recognition of basic EOG units and the establishment of a simple code table based on timing, and it is difficult to guarantee the accuracy of signal recognition.

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  • EOG-based human body behavior identification system and method
  • EOG-based human body behavior identification system and method
  • EOG-based human body behavior identification system and method

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Embodiment Construction

[0064] The technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0065] A kind of human behavior recognition method based on EOG, its feature mainly comprises following module:

[0066] Module 1. Unit EOG signal recognition module: Through the analysis of the original multi-lead EOG signal, the judgment of the three behavioral states of reading, resting and writing is realized. The model includes multi-lead EOG signal acquisition, preprocessing and feature extraction and identification units based on signal average power, average frequency, and signal bandwidth parameters;

[0067] Module 2. Eye movement signal-behavior state relationship module: use the N-gram method to make statistics on a large number of unit EOG signal data, and calculate the transition probability between different behavior states, and obtain the context relationship between the states;

[0068] Modu...

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Abstract

The invention discloses a EOG-based human body behavior identification system and method. Firstly, an EOG signal recognition model based on Hjorth parameters is established and is used for achieving identification of original unit EOG signals; meanwhile, statistics is conducted on the context relations of different behavior states under a background task by using an N-gram method, and an eye movement signal-behavioral state relations model is established; finally, a most probable behavior state of a tested person is obtained by conducting comprehensive analysis and judgment on output results of the two models based on confidence parameters. The EOG-based human body behavior identification method has the advantages of being high in identification correction rate, strong in extensibility, good in application prospect and the like.

Description

technical field [0001] The present invention relates to a human behavior recognition system and method, in particular to an EOG-based human behavior recognition system and method. Background technique [0002] Human activity recognition (HAR) refers to the comprehensive analysis and recognition of the observed individual's action types, behavior patterns and other information, and the recognition results are described in natural language and other ways. Studies have shown that the eye movement pattern triggered by a person's specific activities can reveal his behavioral state to a large extent, such as: reading, writing, resting, etc., and this eye movement pattern can be tracked by eye movement. Therefore, the design and implementation of human behavior recognition algorithms based on eye movement information has become a new research hotspot. [0003] In recent years, electro-oculogram (EOG) has been proved to be one of the most effective tools for measuring eye movements...

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Application Information

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IPC IPC(8): A61B5/0496G06K9/00G06F3/01
CPCG06F3/013G06F3/015A61B5/398G06F2218/02G06F2218/08G06F2218/12
Inventor 吕钊张超陆雨吴小培周蚌艳张磊卫兵高湘萍
Owner ANHUI UNIVERSITY
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