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Research on Feature Extraction and Recognition Algorithm of EOG Signal

Author: WangJun
Tutor: WuXiaoPei
School: Anhui University
Course: Applied Computer Technology
Keywords: Human-Computer Interaction Eye electrical signal Endpoint detection Linear prediction coefficients Feature Extraction Pattern Recognition
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 145
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Abstract


Bio-electrical signal processing computer applications has become a major research focus. Based on the biological signals of the man-machine interaction (Human-Computer Interaction, HCI) system refers to establish a connection between the human body and a computer or other electronic device, by extracting human biological signals, and converted into corresponding control commands related to control interactive system of external equipment to complete the scheduled action. Has sparked a revolution in the way of traditional interactive system based on human-computer interaction bioelectric signals. EOG (Electro-oculogram, EOG) signal is a weak biological signals generated by eye movements, the signal can be affixed around the eye electrode recorded. Bioelectric signals, EOG signal has a higher amplitude, and waveform easy detection, treatment easily and other advantages, EOG-based human-computer interaction system is bound to have broad prospects for development. This paper studies EOG signal feature extraction and recognition algorithm, designed to obtain a set of efficient, portable characteristic parameters serve EOG signal pattern recognition. Based on this, the article to complete the following main work: 1. Acquisition and pre-processing of the experimental data: in a laboratory environment, designed EOG signal acquisition experimental and more than subjects for data collection, access to a large number of original EOG data . 2.EOG signal feature extraction: EOG characteristics extraction algorithm based on linear prediction (Linear Predictive Coding, LPC). I.e. the original EOG signal filtering, sub-frame, to calculate the short-term energy and endpoint detection preprocessing operation, extracting linear prediction (LPC) coefficients are used as the characteristic parameters of the EOG signal; order to obtain the information of the dynamic changes of the EOG signal, the algorithm further extraction of the first-order differential LPC coefficients and constitute a combination of characteristic parameters of the signal peak. 3.EOG signal pattern recognition algorithms: based BP algorithm of multi-layer feedforward network the saccade signal classification and BP network in key parameters determined by experiment. Finally, in MATLAB7.0 environment, design and complete the simulation experiment EOG signal pattern recognition, to verify the effectiveness of the mentioned characteristics recognition algorithm. Peripherals crosslinking: use of serial communication in VC 6.0 compiler platform, initially realized the line control external devices based on EOG signal. EOG signal acquisition and pre-processing of the article, feature extraction and pattern recognition software to implement part of the study and explore, completed the Design and Implementation of the external device control system based on the number of blinks, and for the further development of more efficient man-machine The interactive system to do the basic work. End part, a summary of the work done, and the future direction of the work put forward.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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