Analysis of effect of Meditation on Cognitive Load using Higher Order Crossing Features

DOI

10.2991/iccasp-16.2017.65How to use a DOI?

Keywords

EEG, EMOTIV, Cognitive Load, Meditation, K-NN

Abstract

In this paper, the effect of meditation on the seven load arithmetic tasks using Electroencephalogram (EEG) is investigated. The focused attention on breathing is taught to 11 healthy subjects as a simple meditation tech-nique. EEG signals have been recorded at the beginning of meditation and after four weeks of regular medita-tion (daily 20 minutes) using EMOTIV device. The higher order crossings (HOC) features are derived from EEG signals for analysis of seven cognitive loads. The pre and post-experiment results are compared based on reac-tion time and effect on brain lobe. The K-Nearest Neighbors (K-NN) classifier is used for classification of seven loads and achieved 83.57% accuracy in the post and 89.61 % accuracy in pre-experiment. The EEG-based cognitive load analysis is an important tool for continuous memory load measurement application.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - N. Jadhav
AU  - R. Manthalkar
AU  - Y. Joshi
PY  - 2016/12
DA  - 2016/12
TI  - Analysis of effect of Meditation on Cognitive Load using Higher Order Crossing Features
BT  - Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
PB  - Atlantis Press
SP  - 431
EP  - 437
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasp-16.2017.65
DO  - 10.2991/iccasp-16.2017.65
ID  - Jadhav2016/12
ER  -