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A Wearable Channel Selection-Based Brain-Computer Interface for Motor Imagery Detection.
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- Author(s): Lo CC;Lo CC;Lo CC; Chien TY; Chien TY; Chen YC; Chen YC; Tsai SH; Tsai SH; Fang WC; Fang WC; Lin BS; Lin BS; Lin BS
- Source:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2016 Feb 06; Vol. 16 (2), pp. 213. Date of Electronic Publication: 2016 Feb 06.- Publication Type:
Journal Article; Research Support, Non-U.S. Gov't- Language:
English - Source:
- Additional Information
- Source: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE
- Publication Information: Original Publication: Basel, Switzerland : MDPI, c2000-
- Subject Terms:
- Abstract: Motor imagery-based brain-computer interface (BCI) is a communication interface between an external machine and the brain. Many kinds of spatial filters are used in BCIs to enhance the electroencephalography (EEG) features related to motor imagery. The approach of channel selection, developed to reserve meaningful EEG channels, is also an important technique for the development of BCIs. However, current BCI systems require a conventional EEG machine and EEG electrodes with conductive gel to acquire multi-channel EEG signals and then transmit these EEG signals to the back-end computer to perform the approach of channel selection. This reduces the convenience of use in daily life and increases the limitations of BCI applications. In order to improve the above issues, a novel wearable channel selection-based brain-computer interface is proposed. Here, retractable comb-shaped active dry electrodes are designed to measure the EEG signals on a hairy site, without conductive gel. By the design of analog CAR spatial filters and the firmware of EEG acquisition module, the function of spatial filters could be performed without any calculation, and channel selection could be performed in the front-end device to improve the practicability of detecting motor imagery in the wearable EEG device directly or in commercial mobile phones or tablets, which may have relatively low system specifications. Finally, the performance of the proposed BCI is investigated, and the experimental results show that the proposed system is a good wearable BCI system prototype.
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- Publication Date: Date Created: 20160211 Date Completed: 20170104 Latest Revision: 20181113
- Publication Date: 20231215
- Accession Number: PMC4801589
- Accession Number: 10.3390/s16020213
- Accession Number: 26861347
- Source:
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