ArticleScientific reports2022
Decoding the cognitive states of attention and distraction in a real-life setting using EEG.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Impact of sky view factor on multimodal physiological responses: integrating EEG, heart rate, and thermal sensation in urban landscapes.Scientific reports · 2026Article
- Cortical alpha changes during visuospatial attention: a deep learning-enriched EEG analysis.Cerebral cortex (New York, N.Y. : 1991) · 2026Article
- Decoding the Self: Single-Trial Prediction of Self-Boundary Meditation States From Magnetoencephalography Recordings.Human brain mapping · 2026Article
- A novel approach for the EEG-driven assessment of divided attention through mutual information theory: A case study at the wheel.PloS one · 2026Article
- Neural dynamics of mindfulness training: A longitudinal EEG network analysis of focused attention and open monitoring meditation.Network neuroscience (Cambridge, Mass.) · 2026Article
- From finger to whole-body movements: How movement type affects our sense of time.Psychological research · 2025Article
- Cognitive efficiency in VR simulated natural indoor environments examined through EEG and affective responses.Scientific reports · 2025Article
- Design and Demonstration of a Hybrid FES-BCI-Based Robotic Neurorehabilitation System for Lower Limbs.Sensors (Basel, Switzerland) · 2025Article
- Evidence of physiological changes associated with single-session pre-frontal tDCS: a pilot study.Frontiers in human neuroscience · 2025Article
- Neurotechnology for enhancing human operation of robotic and semi-autonomous systems.Frontiers in robotics and AI · 2025Review
- Article
- The impact of virtual reality and distractors on attentional processes: insights from EEG.Pflugers Archiv : European journal of physiology · 2024Article
- Article
- Transcranial focused ultrasound to V5 enhances human visual motion brain-computer interface by modulating feature-based attention.Nature communications · 2024Article
- Closed-Loop Transcranial Electrical Neurostimulation for Sustained Attention Enhancement: A Pilot Study towards Personalized Intervention Strategies.Bioengineering (Basel, Switzerland) · 2024Article
- EEG complexity measures for detecting mind wandering during video-based learning.Scientific reports · 2024Article
- Mind wandering state detection during video-based learning via EEG.Frontiers in human neuroscience · 2023Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Lapses in attention can have serious consequences in situations such as driving a car, hence there is considerable interest in tracking it using neural measures. However, as most of these studies have been done in highly controlled and artificial laboratory settings, we want to explore whether it is also possible to determine attention and distraction using electroencephalogram (EEG) data collected in a natural setting using machine/deep learning. 24 participants volunteered for the study. Data were collected from pairs of participants simultaneously while they engaged in Tibetan Monastic debate, a practice that is interesting because it is a real-life situation that generates substantial variability in attention states. We found that attention was on average associated with increased left frontal alpha, increased left parietal theta, and decreased central delta compared to distraction. In an attempt to predict attention and distraction, we found that a Long Short Term Memory model classified attention and distraction with maximum accuracy of 95.86% and 95.4% corresponding to delta and theta waves respectively. This study demonstrates that EEG data collected in a real-life setting can be used to predict attention states in participants with good accuracy, opening doors for developing Brain-Computer Interfaces that track attention in real-time using data extracted in daily life settings, rendering them much more usable.
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