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Experimental Study
| Published: October 31, 2025
Artificial Intelligence for Diagnosis and Balancing of Human Chakras and Aura: A Holistic Healing Approach
MMICT & BM, MM(DU), Mullana
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DIP: 18.01.042.20251304
DOI: 10.25215/1304.042
ABSTRACT
The combination of holistic health practices and artificial intelligence (AI) has created new opportunities for personal wellbeing in recent years. The use of artificial intelligence (AI) to diagnose and balance human chakras and the aura field—a crucial part of energy healing and spiritual healing traditions—is examined in this paper. This paper introduces a novel AI-based framework that detects energetic imbalances within the seven principal chakras and disturbances in the human biofield using computer vision, machine learning algorithms, and biosensory data. Using real-time biological inputs like heart rate variability, galvanic skin reaction, EEG patterns, and aura imaging techniques, the system evaluates emotional, mental, and energy states. The model recommends customized treatment plans, including guided meditations, breath work, sound therapy, and energy-focused therapies like pranic healing or Reiki, when imbalances are identified. Initial experimental results show promising accuracy in detecting subtle energy alterations, indicating that AI-assisted energy healing could be used as a non-invasive, scalable mental health support system. This paper lays the way for combining ancient healing expertise with modern AI techniques to provide a comprehensive, data-driven approach to emotional and energy well being.
Keywords
Artificial intelligence (AI), Chakra Checking, Aura Reading, Energy healing, Holistic Health Machine Learning, Personalized healing, Integrative, Medicine, Subtle energy systems
This is an Open Access Research distributed under the terms of the Creative Commons Attribution License (www.creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any Medium, provided the original work is properly cited.
© 2025, Grover, V.
Received: August 04, 2025; Revision Received: October 26, 2025; Accepted: October 31, 2025
Article Overview
ISSN 2348-5396
ISSN 2349-3429
18.01.042.20251304
10.25215/1304.042
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Published in Volume 13, Issue 4, October- December, 2025
