Document Type
Thesis
Date of Award
5-31-1986
Degree Name
Master of Science in Electrical Engineering - (M.S.)
Department
Electrical Engineering
First Advisor
Stanley S. Reisman
Second Advisor
W. H. Warren Ball
Abstract
Occurance of highly coherent brain activity (EEG) specific to the meditation has been reported in the literature. The present thesis is an effort to look into the mechanics of meditation using the recent technique of analysis of high coherence in the EEG. Based on previous work, reporting increased EEG coherence during practice of Transcendental Meditation, a closed loop model and hypothesis is proposed using biofeedback to close the loop. The hypothesis proposes that very high coherence in the EEG is a very significant neurophysiological parameter, reflecting instantaneous quality of meditation in the form of an average high coherence above threshold.
A system is developed having required hardware and software capabilites, to test the hypothesis. The system is able to process two channel EEG data on-line for coherence analysis and plot the result :an overall running summation indicative of average coherence during the past one minute, on the monitor, as well as mirror this value to the meditator by adjusting the volume level of biofeedback. The data is also stored on a cassette for further off-line processing at a later time. The algorithm used for coherence calculations uses an ensemble averaging technique, by defining several overlapping subsets from original data of 256 samples/chan./epoch at 60 Hz sampling rate.
Experiments have been performed to test the system and the results accumulated so far seem very promising. It is found difficult to prove the hypothesis in the general form because of the subjective nature of quality of meditation. However, until now, the data does not disprove the hypothesis, so it still remains an open question for further research.
Recommended Citation
Rawal, Deepak Dinkerrai, "On-line analysis of highly coherent brain activity during transcendental meditation and automated biofeedback" (1986). Theses. 3372.
https://digitalcommons.njit.edu/theses/3372
