Mindfulness intervention for improving cognitive abilities using EEG signal

•Investigation for effect of mindfulness on visual cognitive load.•CAMI, Fractal dimension, and state transition in HMM quantifies cognitive load.•Effective handling of cognitive load is seen after mindfulness intervention. Mindfulness is a flexible state of mind noticing actively things in the pres...

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Bibliographic Details
Published in:Biomedical signal processing and control Vol. 70; p. 103072
Main Authors: Gupta, Shankar S., Manthalkar, Ramchandra R., Gajre, Suhas S.
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.09.2021
Subjects:
Electroencephalogram
Hidden Markov model
Mindfulness
Visual cognitive workload
Hidden Markov model
Electroencephalogram
Mindfulness
Visual cognitive workload
ISSN:1746-8094, 1746-8108
Online Access:Get full text
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Summary:•Investigation for effect of mindfulness on visual cognitive load.•CAMI, Fractal dimension, and state transition in HMM quantifies cognitive load.•Effective handling of cognitive load is seen after mindfulness intervention. Mindfulness is a flexible state of mind noticing actively things in the present context, strengthening an individual’s attention. Mindfulness practices are vigorously pursued in the present-day world to improve well-being, resilience, and leading healthful lives. The cognitive load encountered in daily life can be effectively handled by strengthening the attention muscle of the mind. This work investigates the effect of mindfulness training by using the acquired electroencephalogram (EEG) signal of 40 subjects. Total subjects are equally divided into two groups. Twenty in a group have undergone mindfulness training, and the other twenty formed the control group. Each subject in the mindfulness training group practiced focused attention meditation 20 min daily for eight weeks by concentrating on in-breath and out-breath in a comfortable sitting posture. The visual cognitive protocol used for this work acquires data for four cognitive levels of increasing complexity. This research work is conducted by using a three-pronged approach, namely cognitive ability modulation index (CAMI), fractal dimension and state transition. CAMI and fractal dimension are used as criteria for choosing the subjects to examine state transitions using the Hidden Markov model (HMM). Emission states are identified by using the autoregressive model coefficients. The fuzzy c-means clustering algorithm is used to label emission states. Arousal, observation, and relaxation functional states are analysed using HMM. The percentage of subjects showing significant cognitive improvement across four levels after mindfulness intervention are 22.22(17.64), 55.55(23.52), 61.11(17.64) and 77.77(23.52), respectively, where the figure in parenthesis is of the control group.
ISSN:1746-8094
1746-8108
DOI:10.1016/j.bspc.2021.103072