Grid is a project by University of Houston-Downtown's CSET Department.

Words from the Principle Investigator

We plan to use electroencephalography (EEG) data to build a brain waves model that can identify characteristics of meditation states. The practical significance of finding a meditation model is two fold. Firstly, it can be used to guide and regulate meditation practices. Secondly, it can be used to assist meditation teachers to verify the effectiveness of the meditation methodologies. The proposed project is an extension to a collaborative study with the University of Canberra, and the Royal North Shore Hospital, the University of Sydney. Existing work that has been done in this collaborative project includes collecting EEG data from medical Qigong classes at the Royal North Shore Hospital, the University of Sydney, and investigating brain state modeling using EEG data. At the University of Houston-Downtown, we designed a program for EEG data visualization and analysis and an iPad application for real-time EEG data monitoring. The proposed project will focus on meditation brain states using test subjects with cascaded meditation mastery levels, viz., subjects with no or little experience or in a poor health condition, meditation trainees with entry level experience, and experienced meditation masters. With over 20 years experience in meditation and the knowledge in the philosophy of meditation, I am suitable to be the PI for the proposed project. I will use my knowledge to gear the data collection and analysis towards supposed behaviors of brain states in a successful meditation process. My knowledge about sectors of meditation practitioners and social liaison will help me identify meditation masters. My high performance computing background will contribute to the establishment of necessary algorithma and a proper computing platform for efficient processing of large EEG data volumes. The orchestrated project that involves participating researchers who have demonstrated strong expertise in meditation training and EEG data analysis will contribute significantly to scientific studies of meditation.

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