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AI Meditation App: Enhancing Mindfulness Through AI and EEG Integration
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence
Abstract
The increasing demand for mental health and well-being solutions has led to advancements in meditation technology. Traditional applications focus primarily on guided sessions without offering real-time performance monitoring or actionable insights. The proposed AI Meditation App combines Artificial Intelligence (AI) and Electroencephalogram (EEG) technologies to address these gaps. Key features include Computer Vision for monitoring attentiveness, Natural Language Processing (NLP) for assessing emotional health, and EEG for tracking mindfulness and restfulness levels. This paper provides a comprehensive overview of the app?s architecture, implementation, and performance evaluation. Results demonstrate high accuracy in eye-tracking (98%), emotional analysis (85%), and EEG-based mindfulness assessment. The AI Meditation App serves as a pioneering step towards creating proctored and insightful meditation tools for personal and corporate wellness.
Keywords
Electroencephalogram (EEG), Emotional Health Analysis, Mindfulness Tracking
How to cite this paper
@article{1706941,
author = {Utkarsh Singh, Anish Rao, Arti Khapard, Shray Gupta, Aanjney Gupta},
title = {AI Meditation App: Enhancing Mindfulness Through AI and EEG Integration},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {8},
number = {7},
pages = {376-381},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1706941.pdf},
abstract = {The increasing demand for mental health and well-being solutions has led to advancements in meditation technology. Traditional applications focus primarily on guided sessions without offering real-time performance monitoring or actionable insights. The proposed AI Meditation App combines Artificial Intelligence (AI) and Electroencephalogram (EEG) technologies to address these gaps. Key features include Computer Vision for monitoring attentiveness, Natural Language Processing (NLP) for assessing emotional health, and EEG for tracking mindfulness and restfulness levels. This paper provides a comprehensive overview of the app?s architecture, implementation, and performance evaluation. Results demonstrate high accuracy in eye-tracking (98%), emotional analysis (85%), and EEG-based mindfulness assessment. The AI Meditation App serves as a pioneering step towards creating proctored and insightful meditation tools for personal and corporate wellness.},
keywords = {Electroencephalogram (EEG), Emotional Health Analysis, Mindfulness Tracking},
month = {January},
}