Implementation of Phase-tagged SSVEP-based BCI using Comb Filter

碩士 === 國立中央大學 === 電機工程研究所碩士在職專班 === 98 === This thesis mainly designs as a brain computer interface (BCI) system for electroencephalogram (EEG) of steady state visual evoked potential (SSVEP). Since users gaze at different spatially separated flash channels (FCs) in order to induce visual evoked sig...

Full description

Bibliographic Details
Main Authors: Chih-I Sun, 孫智億
Other Authors: Po-Lei Lee
Format: Others
Language:zh-TW
Published: 2010
Online Access:http://ndltd.ncl.edu.tw/handle/78899891124360931981
id ndltd-TW-098NCU05441003
record_format oai_dc
spelling ndltd-TW-098NCU054410032016-04-20T04:17:48Z http://ndltd.ncl.edu.tw/handle/78899891124360931981 Implementation of Phase-tagged SSVEP-based BCI using Comb Filter 使用梳狀濾波器於相位編碼之穩態視覺誘發電位腦波人機介面 Chih-I Sun 孫智億 碩士 國立中央大學 電機工程研究所碩士在職專班 98 This thesis mainly designs as a brain computer interface (BCI) system for electroencephalogram (EEG) of steady state visual evoked potential (SSVEP). Since users gaze at different spatially separated flash channels (FCs) in order to induce visual evoked signals, the BCI provides four fixed frequency but different phase encoding in the flickering source. The Algorithm uses comb filter in the digital filter easy to implement, keep main frequency and harmonic, and can reduce noise. In order to recognize the command mapping to the gazed FC can be sent out to achieve control purposes, the current design uses event correlation to achieve identify distinct flickering sequences among different FCs. The implementation method is designed the analog EEG capture amplifier and micro control unit(MCU), in order to establish a low cost, small size and fast to recognize BCI system. In this thesis, we have built an four-FC system. The command information transfer ratio(ITR) and detected accuracy are 31.02 bits/min and 91.64%, respectively. Po-Lei Lee 李柏磊 2010 學位論文 ; thesis 57 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 國立中央大學 === 電機工程研究所碩士在職專班 === 98 === This thesis mainly designs as a brain computer interface (BCI) system for electroencephalogram (EEG) of steady state visual evoked potential (SSVEP). Since users gaze at different spatially separated flash channels (FCs) in order to induce visual evoked signals, the BCI provides four fixed frequency but different phase encoding in the flickering source. The Algorithm uses comb filter in the digital filter easy to implement, keep main frequency and harmonic, and can reduce noise. In order to recognize the command mapping to the gazed FC can be sent out to achieve control purposes, the current design uses event correlation to achieve identify distinct flickering sequences among different FCs. The implementation method is designed the analog EEG capture amplifier and micro control unit(MCU), in order to establish a low cost, small size and fast to recognize BCI system. In this thesis, we have built an four-FC system. The command information transfer ratio(ITR) and detected accuracy are 31.02 bits/min and 91.64%, respectively.
author2 Po-Lei Lee
author_facet Po-Lei Lee
Chih-I Sun
孫智億
author Chih-I Sun
孫智億
spellingShingle Chih-I Sun
孫智億
Implementation of Phase-tagged SSVEP-based BCI using Comb Filter
author_sort Chih-I Sun
title Implementation of Phase-tagged SSVEP-based BCI using Comb Filter
title_short Implementation of Phase-tagged SSVEP-based BCI using Comb Filter
title_full Implementation of Phase-tagged SSVEP-based BCI using Comb Filter
title_fullStr Implementation of Phase-tagged SSVEP-based BCI using Comb Filter
title_full_unstemmed Implementation of Phase-tagged SSVEP-based BCI using Comb Filter
title_sort implementation of phase-tagged ssvep-based bci using comb filter
publishDate 2010
url http://ndltd.ncl.edu.tw/handle/78899891124360931981
work_keys_str_mv AT chihisun implementationofphasetaggedssvepbasedbciusingcombfilter
AT sūnzhìyì implementationofphasetaggedssvepbasedbciusingcombfilter
AT chihisun shǐyòngshūzhuànglǜbōqìyúxiāngwèibiānmǎzhīwěntàishìjuéyòufādiànwèinǎobōrénjījièmiàn
AT sūnzhìyì shǐyòngshūzhuànglǜbōqìyúxiāngwèibiānmǎzhīwěntàishìjuéyòufādiànwèinǎobōrénjījièmiàn
_version_ 1718228235910643712