Determining bioenergy field of autistic and normal healthy children: an electrophotonic imaging study

Surendra Singh Sankhala, Singh Deeepeshwar, Shivakumar Kotikalapudi, Srideep Chaterjee


Background: Currently assessment of autistic behavior is done based on learning disabilities, personal observation of behavioral patterns and standard autistic scales. Electrophotonic imaging (EPI) instrument is used to assess health status based on bio-energy field of various organ and organ system of human body. And can be useful to determine the early diagnosis of autistic symptoms and degree of improvement for any therapeutic intervention given to these autistic children on a regular basis. This study aimed to investigate the differences of EPI parameters of autistic children and healthy children of the same age group.

Methods: This study was carried out by taking the EPI images of 33 autistic and 36 healthy children of age group 4 to 14 years from an autistic center and nearby school in Bangalore. The statistical analysis on acquired data were done using IBM SPSS Version 20.0.

Results: The variables activation coefficient, integral area, sacrum, hypothalamus, thyroid gland, pancreas and coronary vessels showed a significant statistical difference in their mean value for autistic and healthy children (p<0.05).

Conclusions: The EPI parameters for autistic and healthy children open up the possibility of using EPI based instrument for early diagnosis. Deeper analysis of the differing parameters gave us more insight into the type of intervention to be selected for improving the health of autistic children.


Electrophotonic imaging, Autism spectrum disorder, Gas discharge visualization, Autistic children

Full Text:



Barthelemy C, Brilhault BF. Autism, In: Neuroscience in the 21st Century. New York, NY: Springer New York; 2016: 3233-3246.

Arora NK, Nair MKC, Gulati S. Neurodevelopmental disorders in children aged 2-9 years: Population-based burden estimates across five regions in India. Persson LA, ed. PLoS Med. 2018;15(7):1002615.

Srikantha P, Mohajeri HM. The possible role of the microbiota-gut-brain-axis in autism spectrum disorder. Int J Mol Sci. 2019;20(9):2115.

Modabbernia A, Velthorst E, Reichenberg A. Environmental risk factors for autism: an evidence-based review of systematic reviews and meta-analyses. Mol Autism. 2017;8(1):13.

Czeizel AE, Puho EH, Langmar Z, Acs N, Banhidy F. Possible association of folic acid supplementation during pregnancy with reduction of preterm birth: a population-based study. Eur J Obstet Gynecol Reprod Biol. 2010;10:16.

Zwaigenbaum L, Bauman ML, Choueiri R. Early identification and interventions for autism spectrum disorder: Executive summary. In: Pediatrics; 2015.

Schopler E, Reichler RJ, Vellis RF, Daly K. Toward objective classification of childhood autism: Childhood Autism Rating Scale (CARS). J Autism Dev Disord. 1980;10:1007.

Eyberg SM, Ross AW. Assessment of child behavior problems: The validation of a new inventory. J Clin Child Psychol. 1978;10:1080.

Volkmar FR, Cicchetti DV, Dykens E, Sparrow SS, Leckman JF, Cohen DJ. An evaluation of the autism behavior checklist. J Autism Dev Disord. 1988;18(1):81-97.

Lord C, Rutter M, Couteur LA. Autism Diagnostic Interview-Revised: A revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Dev Disord. 1994;24(5):659-85.

Lord C, Risi S, Lambrecht L. The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. J Autism Dev Disord. 2000;30(3):205-23.

Bundzen P, Korotkov KG. Health quality evaluation on the basis of GDV parameters. In: Human Energy Field: Study with bioelectrography. In: Bio-Well.Com. Health quality evaluation on the basis of GDV parameters. Human energy field: study with bioelectrography. Fair Lawn, NJ: Backbone Publishing Co. 2002:103-7.

Korotkov KG, Matravers P, Orlov DV, Williams BO. Application of Electrophoton Capture (EPC) Analysis Based on Gas Discharge Visualization (GDV) Technique in Medicine: A Systematic Review. J Altern Complement Med. 2010;16(1):13-25.

Wijk VR, Wijk EPA. An introduction to human biophoton emission. Forschende Komplementarmedizin und Klass Naturheilkd; 2005.

Kataoka Y, Cui Y, Yamagata A. Activity-Dependent Neural Tissue Oxidation Emits Intrinsic Ultraweak Photons. Biochem Biophys Res Commun. 2001;285(4):1007-11.

Devaraj B, Usa M, Inaba H. Biophotons: Ultraweak light emission from living systems. Curr Opin Solid State Mater Sci; 1997.

Hossu M, Rupert R. Quantum Events of Biophoton Emission Associated with Complementary and Alternative Medicine Therapies: A Descriptive Pilot Study. J Altern Complement Med. 2006;12(2):119-124.

Hacker GW, Pawlak E, Pauser G. Biomedical Evidence of Influence of Geopathic Zones on the Human Body: Scientifically Traceable Effects and Ways of Harmonization. Complement Med Res. 2005;12(6):315-27.

Korotkov K. The Principles of GDV Analysis. (Piet. M, ed.). Embourg, Belgium: Publishing; 2009.

Anufrieva E, Anufriev V, Starchenko M, Timofeev N. Thought’s Registration by means of Gas-Discharge Visualization. 2014:1-5.

Cohly H, Kostyuk N, Isokpehi R, Rajnarayanan R. Bio-electrographic method for preventive health care. In: First Annual ORNL Biomedical Science and Engineering Conference. IEEE; 2009:1-4.

Kostyuk N, Cole P, Meghanathan N, Isokpehi RD, Cohly HHP. Gas Discharge Visualization: An Imaging and Modeling Tool for Medical Biometrics. Int J Biomed Imaging. 2011;2011:1-7.

Bhat R, Mavathur R, Srinivasan T. Diabetes mellitus type 2 and yoga: Electro photonic imaging perspective. Int J Yoga. 2017;10(3):152.

Bhargav H, Srinivasan TM, Varambally S, Gangadhar BN, Koka P. Effect of Mobile Phone-Induced Electromagnetic Field on Brain Hemodynamics and Human Stem Cell Functioning: Possible Mechanistic Link to Cancer Risk and Early Diagnostic Value of Electronphotonic Imaging. J Stem Cells. 2015;10(4):287-94.

Yakovleva EG, Korotkov KG, Fedorov ED, Ivanova EV, Plahov RV, Belonosov SS. Engineering Approach to Identifying Patients with Colon Tumors on the Basis of Electrophotonic Imaging Technique Data. Open Biomed Eng J. 2016;10(1):72-80.

Aleksandrova E. GDV Analysis of Arterial Hypertension. Bio-WellEu. 2009:1-9.

Deo G, Kumar IR, Srinivasan TM, Kushwah KK. Cumulative effect of short-term and long-term meditation practice in men and women on psychophysiological parameters of electrophotonic imaging: A cross-sectional study. J Complement Integr Med. 2016;13(1):73-82.

Ming X, Julu POO, Brimacombe M, Connor S, Daniels ML. Reduced cardiac parasympathetic activity in children with autism. Brain Dev. 2005;27(7):509-16.

Kostyuk N, Rajnarayanan RV, Isokpehi RD, Cohly HH. Autism from a biometric perspective. Int J Environ Res Public Health. 2010;7(5):1984-95.

Kamal A. Assessment of Autonomic Function in Children with Autism and Normal Children Using Spectral Analysis and Posture Entrainment: A Pilot Study. J Neurol Neurosci. 2015;6(3):2171-6625.

Ewen BS. The neurobiology of stress: From serendipity to clinical relevance. Brain Res; 2000.

Bharath R, Moodithaya SS, Bhat SU, Mirajkar AM, Shetty SB. Comparison of physiological and biochemical autonomic indices in children with and without autism spectrum disorders. Med; 2019.

Kushki A, Brian J, Dupuis A, Anagnostou E. Functional autonomic nervous system profile in children with autism spectrum disorder. Mol Autism; 2014.

Kurth F, Narr KL, Woods RP. Diminished gray matter within the hypothalamus in autism disorder: A potential link to hormonal effects. Biol Psychiatry. 2011;70(3):278-82.

Uys JDK, Marais L, Faure J. Developmental trauma is associated with behavioral hyperarousal, altered HPA axis activity, and decreased hippocampal neurotrophin expression in the adult rat. In: Annals of the New York Academy of Sciences; 2006.

Frye RE, Wynne R, Rose S. Thyroid dysfunction in children with autism spectrum disorder is associated with folate receptor α autoimmune disorder. J Neuroendocrinol; 2017.

Ishiyama A, Komaki H, Saito T. Unusual exocrine complication of pancreatitis in mitochondrial disease. Brain Dev. 2013;35(7):654-9.

Borre YE, Keeffe GW, Clarke G, Stanton C, Dinan TG, Cryan JF. Microbiota and neurodevelopmental windows: implications for brain disorders. Trends Mol Med. 2014;20(9):509-18.

Rudie JD, Brown JA, Pancer BD. Altered functional and structural brain network organization in autism. NeuroImage Clin. 2013;2(1):79-94.

Levy SE, Mandell DS, Schultz RT. Autism. Lancet. 2009;374(9701):1627-38.

Oyarzabal A, Valencia MI. Synaptic energy metabolism and neuronal excitability, in sickness and health. J Inherit Metab Dis. 2019;42(2):220-36.