Literature DB >> 17827657

An EEG-based real-time cortical rhythmic activity monitoring system.

Chang-Hwan Im1, Han-Jeong Hwang, Huije Che, Seunghwan Lee.   

Abstract

In the present study, we introduce an electroencephalography (EEG)-based, real-time, cortical rhythmic activity monitoring system which can monitor spatiotemporal changes of cortical rhythmic activity on a subject's cortical surface, not on the subject's scalp surface, with a high temporal resolution. In the monitoring system, a frequency domain inverse operator is preliminarily constructed, considering the subject's anatomical information and sensor configurations, and then the spectral current power at each cortical vertex is calculated for the Fourier transforms of successive sections of continuous data, when a particular frequency band is given. A preliminary offline simulation study using four sets of artifact-free, eye-closed, resting EEG data acquired from two dementia patients and two normal subjects demonstrates that spatiotemporal changes of cortical rhythmic activity can be monitored at the cortical level with a maximal delay time of about 200 ms, when 18 channel EEG data are analyzed under a Pentium4 3.4 GHz environment. The first pilot system is applied to two human experiments-(1) cortical alpha rhythm changes induced by opening and closing eyes and (2) cortical mu rhythm changes originated from the arm movements-and demonstrated the feasibility of the developed system.

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Year:  2007        PMID: 17827657     DOI: 10.1088/0967-3334/28/9/011

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  4 in total

1.  An EEG-based real-time cortical functional connectivity imaging system.

Authors:  Han-Jeong Hwang; Kyung-Hwan Kim; Young-Jin Jung; Do-Won Kim; Yong-Ho Lee; Chang-Hwan Im
Journal:  Med Biol Eng Comput       Date:  2011-06-24       Impact factor: 2.602

2.  Noninvasive Brain-Computer Interfaces Based on Sensorimotor Rhythms.

Authors:  Bin He; Bryan Baxter; Bradley J Edelman; Christopher C Cline; Wendy Ye
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2015-05-20       Impact factor: 10.961

3.  Portable wireless neurofeedback system of EEG alpha rhythm enhances memory.

Authors:  Ting-Ying Wei; Da-Wei Chang; You-De Liu; Chen-Wei Liu; Chung-Ping Young; Sheng-Fu Liang; Fu-Zen Shaw
Journal:  Biomed Eng Online       Date:  2017-11-13       Impact factor: 2.819

Review 4.  Hybrid Brain-Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review.

Authors:  Keum-Shik Hong; Muhammad Jawad Khan
Journal:  Front Neurorobot       Date:  2017-07-24       Impact factor: 2.650

  4 in total

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