Recent research suggests that meditation affects the structure and function of the brain. Cognitive load can be handled in effective way by the meditators. EEG signals are used to quantify cognitive load. The research of investigating effect of meditation on cognitive workload using EEG signals in pre and post-meditation is an open problem. The subjects for this study are young healthy 11 engineering students from our institute. The focused attention meditation practice is used for this study. EEG signals are recorded at the beginning of meditation and after four weeks of regular meditation using EMOTIV device. The subjects practiced meditation daily 20 minutes for 4 weeks. The 7 level arithmetic additions of single digit (low level) to three digits with carry (high level) are presented as cognitive load. The cognitive load indices such as arousal index, performance enhancement, neural activity, load index, engagement, and alertness are evaluated in pre and post meditation. The cognitive indices are improved in post meditation data. Power Spectral Density (PSD) feature is compared between pre and post-meditation across all subjects. The result hints that the subjects were handling cognitive load without stress (ease of cognitive functioning increased for the same load) after 4 weeks of meditation.
Rotational invariant texture classification is required for many real world applications. Rotation invariant texture features are derived from the even symmetric Gabor filtered images of texture. The feature used is ADD from mean. It can be shown that rotation of input image is equivalent to a translation of the channel output along the orientation axis. This property is exploited to convert rational variant features to rotational invariant features. Discrete Fourier Transform of the feature is taken in rogation dimension to make the feature ration invariant. The classification of 45 Brodatz textures rotated in 12 different directions is done using these features. The number of samples used for training and testing phase are 4320. The percentage correct classification is 85.25.
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