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Simulator for guiding towards most appropriate mindfulness meditation approach

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dc.contributor.author Rajapaksha, M.
dc.contributor.author Karunananda, A.
dc.date.accessioned 2017-01-06T04:59:48Z
dc.date.available 2017-01-06T04:59:48Z
dc.date.issued 2016
dc.identifier.citation Rajapaksha, M. and Karunananda, A. 2016. Simulator for guiding towards most appropriate mindfulness meditation approach. In Proceedings of the International Research Symposium on Pure and Applied Sciences (IRSPAS 2016), Faculty of Science, University of Kelaniya, Sri Lanka. p 110. en_US
dc.identifier.isbn 978-955-704-008-0
dc.identifier.uri http://repository.kln.ac.lk/handle/123456789/15765
dc.description.abstract Mindfulness is one of the best cognitive skills which helps to save the energy of a particular person. Mindfulness can be considered as a part of Vipassana meditation which was found by Lord Buddha before centuries ago. Guiding towards meditation is not an easy task since it is quite hard to understand the current status of the meditator’s mind. Because even for the meditator it is hard to explain the guider, what’s going on his mind due to rapid changes of his thoughts. Proper identification of five hindrances (pancha neewarna): sensory desire (kamachchanda), ill-will (byapada), sloth and torpor (thina-middha), restlessness (uddhacca-kukkucca) and skeptical doubt (vichikitchca) offers nice way to detect when mindfulness goes wrong. Brain computer interfacing which is the emerging technology used here, directs communication pathway between an enhanced or wired brain and an external device. Mind waves of the meditator is captured using NeuroSky Mindwave Mobile headset and then find the relationship between them and library of meditation expertise’s mind waves. Mind wave patterns of meditation expertise library is created capturing EEG (Electroencephalography) waves of expertise which is captured through non-invasive interface to brain, then using Fast Fourier Transformation (FFT) produce an optimized conversion of EEG with output values of alpha, beta, gamma, theta and delta. The gathered data is passed to an ANN to identify the significant patterns of expertise. Capturing EEG signals method has used due to its fine temporal resolution, ease of use, portability and low set-up cost. Simulating engine developed is going to be tested with people who are following different meditation approaches(karmasthana). The system identifies the relationship between distracting factors and expertise mind waves provide the meditator guiding towards most appropriate way of meditation pattern. en_US
dc.language.iso en en_US
dc.publisher Faculty of Science, University of Kelaniya, Sri Lanka en_US
dc.subject Mindfulness en_US
dc.subject EEG signals en_US
dc.subject Brain-computer interfacing en_US
dc.subject Meditation en_US
dc.subject Vipassana meditation en_US
dc.title Simulator for guiding towards most appropriate mindfulness meditation approach en_US
dc.type Article en_US


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