Literature DB >> 23366259

Design of the multi-channel electroencephalography-based brain-computer interface with novel dry sensors.

Shang-Lin Wu1, Lun-De Liao, Chang-Hong Liou, Shi-An Chen, Li-Wei Ko, Bo-Wei Chen, Po-Sheng Wang, Sheng-Fu Chen, Chin-Teng Lin.   

Abstract

The traditional brain-computer interface (BCI) system measures the electroencephalography (EEG) signals by the wet sensors with the conductive gel and skin preparation processes. To overcome the limitations of traditional BCI system with conventional wet sensors, a wireless and wearable multi-channel EEG-based BCI system is proposed in this study, including the wireless EEG data acquisition device, dry spring-loaded sensors, a size-adjustable soft cap. The dry spring-loaded sensors are made of metal conductors, which can measure the EEG signals without skin preparation and conductive gel. In addition, the proposed system provides a size-adjustable soft cap that can be used to fit user's head properly. Indeed, the results are shown that the proposed system can properly and effectively measure the EEG signals with the developed cap and sensors, even under movement. In words, the developed wireless and wearable BCI system is able to be used in cognitive neuroscience applications.

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Year:  2012        PMID: 23366259     DOI: 10.1109/EMBC.2012.6346298

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Design and Verification of a Dry Sensor-Based Multi-Channel Digital Active Circuit for Human Brain Electroencephalography Signal Acquisition Systems.

Authors:  Chin-Teng Lin; Chi-Hsien Liu; Po-Sheng Wang; Jung-Tai King; Lun-De Liao
Journal:  Micromachines (Basel)       Date:  2019-10-25       Impact factor: 2.891

2.  Novel wireless electroencephalography system with a minimal preparation time for use in emergencies and prehospital care.

Authors:  Andrei Jakab; Antti Kulkas; Timo Salpavaara; Pasi Kauppinen; Jarmo Verho; Hannu Heikkilä; Ville Jäntti
Journal:  Biomed Eng Online       Date:  2014-05-08       Impact factor: 2.819

  2 in total

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