%0 Journal Article
%T Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors
%A Lun-De Liao
%A Chi-Yu Chen
%A I-Jan Wang
%A Sheng-Fu Chen
%A Shih-Yu Li
%A Bo-Wei Chen
%A Jyh-Yeong Chang
%A Chin-Teng Lin
%J Journal of NeuroEngineering and Rehabilitation
%D 2012
%I BioMed Central
%R 10.1186/1743-0003-9-5
%X The monitoring of brain activity is widely used for investigative neuroscience and rehabilitation engineering [1]. The brain-computer interface (BCI) technique has become a major tool that provides a direct communication pathway between the brain and the external world by translating signals from brain activities into machine codes or commands [2-5]. The acquisition of brain activities by BCIs can be divided into two different categories [4]: invasive BCIs [6,7] and noninvasive BCIs [8,9]. An invasive BCI is implanted directly into the grey matter of the brain to obtain the highest quality of brain activity signals or to send external signals into the brain [7]. However, invasive BCIs depend on surgical techniques and are potentially risky because of the interaction between the device and brain tissues when used in the long term. Therefore, noninvasive BCIs have become another major BCI research direction. These noninvasive devices are worn on the outside of the head and are removable. Recently, electroencephalogram (EEG)-based BCIs have been shown to provide a feasible and noninvasive method to communicate between the human brain and external devices [10,11]. The use of EEG signals has become the most common approach for BCIs because of their usability and strong reliability [12,13]. In recent years, the advanced designs of the sensors and system techniques have made it possible to integrate the sensors into portable acquisition devices to measure a wide variety of physiological signals. The development of EEG-based BCIs and their corresponding applications have also been reported [14-16]. A BCI system that is based on steady-state visual-evoked potentials (SSVEPs) has been commonly used for controlling functional neuroprostheses [8,17-19]. Gollee et al. used a BCI system that was based on SSVEPs combined with a functional electrical stimulation (FES) system to allow the user to control stimulation settings and parameters [17]. In addition, a P300-based BCI has als
%K Electroencephalography (EEG)
%K Brain-computer interface
%K Dry EEG sensor
%K Cognitive applications
%U http://www.jneuroengrehab.com/content/9/1/5