Citation: Chhabra, G.; Onyema, E.M.; Kumar, S.; Goutham, M.; Mandapati, S.; Iwendi, C. Human Emotions Recognition, Analysis and Transformation by the Bioenergy Field in Smart Grid Using Image Processing. Electronics 2022, 11, 4059. https://doi.org/10.3390/electronics 11234059 Academic Editor: Chiman Kwan Received: 29 October 2022 Accepted: 5 December 2022 Published: 6 December 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). electronics Article Human Emotions Recognition, Analysis and Transformation by the Bioenergy Field in Smart Grid Using Image Processing Gunjan Chhabra 1 , Edeh Michael Onyema 2,3, *, Sunil Kumar 4 , Maganti Goutham 5 , Sridhar Mandapati 6 and Celestine Iwendi 7, * 1 Department of Computer Science and Engineering, Graphic Era Hill University, Dehradun 248002, India 2 Department of Vocational and Technical Education, Faculty of Education, Alex Ekwueme Federal University (Ndufu-Alike), Abakaliki 482131, Nigeria 3 Department of Mathematics and Computer Science, Coal City University, Enugu 400104, Nigeria 4 School of Computer Science, University of Petroleum and Energy Studies, Dehradun 248007, India 5 CSE Department, Malla Reddy University, Hyderabad 500043, India 6 Department of Computer Applications, R.V.R. & J.C. College of Engineering, Chowdavaram, Guntur 522019, India 7 School of Creative Technologies, University of Bolton, Bolton BL3 5AB, UK * Correspondence: mikedreamcometrue@gmail.com (E.M.O.); celestine.iwendi@ieee.org (C.I.) Abstract: The passage of electric signals throughout the human body produces an electromagnetic field, known as the human biofield, which carries information about a person’s psychological health. The human biofield can be rehabilitated by using healing techniques such as sound therapy and many others in a smart grid. However, psychiatrists and psychologists often face difficulties in clarifying the mental state of a patient in a quantifiable form. Therefore, the objective of this research work was to transform human emotions using sound healing therapy and produce visible results, confirming the transformation. The present research was based on the amalgamation of image processing and machine learning techniques, including a real-time aura-visualization interpretation and an emotion- detection classifier. The experimental results highlight the effectiveness of healing emotions through the aforementioned techniques. The accuracy of the proposed method, specifically, the module combining both emotion and aura, was determined to be ~88%. Additionally, the participants’ feedbacks were recorded and analyzed based on the prediction capability of the proposed module and their overall satisfaction. The participants were strongly satisfied with the prediction capability (~81%) of the proposed module and future recommendations (~84%). The results indicate the positive impact of sound therapy on emotions and the biofield. In the future, experimentation using different therapies and integrating more advanced techniques are anticipated to open new gateways in healthcare. Keywords: human biofield; emotion detection; sound therapy; biofield healing; convolution neural networks; bioinformatics; smart grid 1. Introduction The human body functions based on the transmission of various signals both inside and outside the body. Electrical signals such as those recorded in Electroencephalogram (EEG), Electrocardiogram (ECG), and others that are easy to measure indicate the health condition of a human [1–3]. The human biofield is an electromagnetic energy field produced by these signals inside the human body, which is highly complex in nature and, thus, difficult to decode. Numerous studies have reported that interpreting the information carried by this biofield could bring a remarkable revolution in the field of healthcare. The biofield contains significant information related to both the physical health and the mental condition of an individual. Previous works have shown that by analyzing the human Electronics 2022, 11, 4059. https://doi.org/10.3390/electronics11234059 https://www.mdpi.com/journal/electronics