Neural Network Based Analysis of Electro Photonic Data for Disease Diagnosis and Intervention Recognition

Abstract

This work has two components, analysis of Electro Photonic Imaging (EPI) newlinedata for anapansati meditation and mudra data with an intent to identify statistically significant newlinechanges and detecting a pattern for training a neural network for intervention recognition. The newlineother parts involve collecting of EPI data from diabetic and non-diabetic subjects and explore the newlinepossibility of classifying the two samples.To study the effect of the pattern of variation of EPI parameters using neural networks for newlinediseased condition specifically diabetes, variation of EPI parameters with mudra and meditation newlineas interventions.Electro Photonic Imaging (EPI) data was collected from 200 subjects including male newlineand female in the age group of 20 to 60 years from a diabetic center in Bangalore, India. The EPI newlinedata was captured from all the ten fingers from the subjects who came for regular blood test. The newlineEPI data corresponding to the meridians of the ring finger, chakras, organs and organ systems newlinerelated to diabetes were analyzed using general linear model in IBM SPSS. A built-in neural newlinenetwork classifier from IBM SPSS was used to classify diabetic subjects from non-diabetic newlinesubjects.The mean and standard deviation values for pancreas were 5.024 and 1.027 (Energy newlineunits) for the diabetic subjects and 4.73 and 0.87 for non-diabetic subjects. Similarly, for newlinehypothalamus the mean and standard deviation values were 4.97 and 0.759 for diabetes and 4.61 newlineand 0.861for non-diabetic subjects. The classification accuracy of the neural network classifier newlinewas in the range of 80% to 100% for classifying diabetic and non-diabetic subjects. Meditation newlinewas found to have a significant impact on EPI parameters. Further, neural network was able to newline8 newlineclassify pre and post meditative population using EPI data with an accuracy ranging from 84% to newline100%. The EPI data for prana mudra has statistically significant changes in the meridians newlinecorresponding to thumb, little and ring fingers.