Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lin, Chin-Teng | en_US |
dc.contributor.author | Chen, Yu-Chieh | en_US |
dc.contributor.author | Huang, Teng-Yi | en_US |
dc.contributor.author | Chiu, Tien-Ting | en_US |
dc.contributor.author | Ko, Li-Wei | en_US |
dc.contributor.author | Liang, Sheng-Fu | en_US |
dc.contributor.author | Hsieh, Hung-Yi | en_US |
dc.contributor.author | Hsu, Shang-Hwa | en_US |
dc.contributor.author | Duann, Jeng-Ren | en_US |
dc.date.accessioned | 2014-12-08T15:12:13Z | - |
dc.date.available | 2014-12-08T15:12:13Z | - |
dc.date.issued | 2008-05-01 | en_US |
dc.identifier.issn | 0018-9294 | en_US |
dc.identifier.uri | http://dx.doi.org/10.1109/TBME.2008.918566 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/9373 | - |
dc.description.abstract | Biomedical signal monitoring systems have been rapidly advanced with electronic and information technologies in recent years. However, most of the existing physiological signal monitoring systems can only record the signals without the capability of automatic analysis. In this paper, we proposed a novel brain-computer interface (BCI) system that can acquire and analyze electroencephalogram (EEG) signals in real-time to monitor human physiological as well as cognitive states, and, in turn, provide warning signals to the users when needed. The BCI system consists of a four-channel biosignal acquisition/amplification module, a wireless transmission module, a dual-core signal processing unit, and a host system for display and storage. The embedded dual-core processing system with multitask scheduling capability was proposed to acquire and process the input EEG signals in real time. In addition, the wireless transmission module, which eliminates the inconvenience of wiring, can be switched between radio frequency (RF) and Bluetooth according to the transmission distance. Finally, the real-time EEG-based drowsiness monitoring and warning algorithms were implemented and integrated into the system to close the loop of the BCI system. The practical online testing demonstrates the feasibility of using the proposed system with the ability of real-time processing, automatic analysis, and online warning feedback in real-world operation and living environments. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | brain-computer interface (BCI) | en_US |
dc.subject | electroencephalogram (EEG) | en_US |
dc.subject | online | en_US |
dc.subject | drowsiness detection | en_US |
dc.subject | wireless | en_US |
dc.title | Development of wireless brain computer interface with embedded multitask scheduling and its application on real-time driver's drowsiness detection and warning | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/TBME.2008.918566 | en_US |
dc.identifier.journal | IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | en_US |
dc.citation.volume | 55 | en_US |
dc.citation.issue | 5 | en_US |
dc.citation.spage | 1582 | en_US |
dc.citation.epage | 1591 | en_US |
dc.contributor.department | 電控工程研究所 | zh_TW |
dc.contributor.department | 腦科學研究中心 | zh_TW |
dc.contributor.department | 工業工程與管理學系 | zh_TW |
dc.contributor.department | Institute of Electrical and Control Engineering | en_US |
dc.contributor.department | Brain Research Center | en_US |
dc.contributor.department | Department of Industrial Engineering and Management | en_US |
dc.identifier.wosnumber | WOS:000255148600013 | - |
dc.citation.woscount | 35 | - |
Appears in Collections: | Articles |
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