Recording and Characterization of EEGs by Using Wearable EEG Device

Electroencephalographic (EEG) record provides the state of the brain activations and is useful for the clinical diagnosis of the brain dysfunction. However, the preparation of EEG recording such as attachment of electrodes, measurement device setting, etc., is time-consuming and complex. In addition, interpretation of recorded EEG requires particular knowledge and experiences. Therefore, the use of EEG recording is limited. Recent years, simple and easy wearable EEG devices have been developed and are considered to be the practical level. Those devices are easy to attach the measurement electrodes to the scalp without special skills and do not constrain the subjects' movement. In contrast to conventional EEG recordings, the number of electrodes is limited, so the accurate interpretation and/or analysis of EEG characteristics would rather be difficult. Especially, discrimination of actual EEG activities from various contaminated artifacts are crucial for clinical application. In this study, the characteristics of the recorded EEG by using a wearable EEG device was analyzed. Automatic detection method for contaminated artifacts such eye blinking, lateral eye movement (LEM) and electromyographic (EMG) activity were developed. Results were compared with the visual inspection for the recorded data.