Detecting meditation using a dry mono-electrode EEG sensor

A vast researches are concentrated towards the development of EEG based human computer interface to enhance the quality of life for medical applications. There is a recent attraction to wireless EEG devices as they are cheaper and easily available in the market. The devices use dry electrodes and send signals via wireless, thus are easier to use and more comfortable to wear. Such technology can be used in psychology, neuro therapy, and for real-time patients monitoring. One such off-the-shelf device is Neurosky MindWave headset. In this paper, it is utilized to measure electrical activity of user's forehead. The collected data in voltage is wirelessly transmitted to a computer for further processing. After processing the EEG data, signals were categorized to requisite frequency bands of brain waves for feature extraction. The collected signal can be used to differentiate between meditation and attention activities. Examples of attention activities are reading, problem solving, etc. Meditation level obtained directly from MindWave was not observed to be a good feature for classification of different brain activities. The two psycho-physiological states, attention and meditation are of interest to psychological therapies. This paper shows that meditation and other activities related to attention can be detected and differentiated better with frequency and frequency-time analysis of the EEG signal. The EEG signal recorded from MindWave can be effectively used to plot visual feedback of brain activity.