We fabricated a carbon nanotube (CNT)/adhesive polydimethylsiloxane (aPDMS) composite-based dry electroencephalograph (EEG) electrode for capacitive measuring of EEG signals. As research related to brain–computer interface applications has advanced, the presence of hairs on a patient's scalp has continued to present an obstacle to recorder EEG signals using dry electrodes. The CNT/aPDMS electrode developed here is elastic, highly conductive, self-adhesive, and capable of making conformal contact with and attaching to a hairy scalp. Onto the conductive disk, hundreds of conductive pillars coated with Parylene C insulation layer were fabricated. A CNT/aPDMS layer was attached on the disk to transmit biosignals to the pillar. The top of disk was designed to be solderable, which enables the electrode to connect with a variety of commercial EEG acquisition systems. The mechanical and electrical characteristics of the electrode were tested, and the performances of the electrodes were evaluated by recording EEGs, including alpha rhythms, auditory-evoked potentials, and steady-state visually-evoked potentials. The results revealed that the electrode provided a high signal-to-noise ratio with good tolerance for motion. Almost no leakage current was observed. Although preamplifiers with ultrahigh input impedance have been essential for previous capacitive electrodes, the EEGs were recorded here by directly connecting a commercially available EEG acquisition system to the electrode to yield high-quality signals comparable to those obtained using conventional wet electrodes.

Usefulness of an EEG-based brain-computer interface to establish communication in ALS

Self-Adhesive and Capacitive Carbon Nanotube-Based Electrode to Record Electroencephalograph Signals From the Hairy Scalp

BioSig is an open-source software library for biomedical signal processing. Besides several other application areas, BioSig also has been developed for BCI research. It provides a common interface to many different dataformats, it supports artifact processing and quality control, it provides adaptive signal processing and feature extraction methods that are very suitable for online and real-time processing, it supports handling of missing values, and it includes several classification methods for single-trial classification of EEG. This chapter provides an overview of the current status and an outline of future possibilities. BioSig is licensed with the GNU General Public License; it provides an open development platform unencumbered from legal restrictions. Therefore, it is also an ideal tool for research and development.

Usefulness of an EEG-based brain-computer interface to establish communication in ALS

Citations

Self-Adhesive and Capacitive Carbon Nanotube-Based Electrode to Record Electroencephalograph Signals From the Hairy Scalp

BioSig - an open source software library for BCI research

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