Understanding meditation through neural computing approach

Meditation is considered to be an altered state of consciousness associated with heightened cognitive functions and transcendental experiences [1]. The neural dynamics in meditative states needs to be explored and an objective analysis of such states is required in order to achieve best result in this study. In this paper we do brain signal detection by using Bimec EEG to 20 subjects. EEG is the recording of electrical activity in the brain. The activity is recorded by placing electrodes on the skull over electrically active tissue and measuring the voltage across these electrodes. The area of interest will be the wave signals of the neurons. We use the kernel density estimation (KDE) as tools to extract features. Then, we use these features to recognize the emotion of the driver by using multi layer perceptron (MLP) as classifier. This research and investigation will eventually detect whether each subject reach the level of expected emotions which is calmness during meditation (Zikrullah