Electrophotonic Imaging Based Analysis of Diabetes
All metabolic processes involve electron transfer mechanisms. Eletrophotonic Imaging (EPI) captures the coronal discharge around the finger as a result of electron capture from the ten fingers. The coronal discharge around each fingertip supposedly represents the energy state of the corresponding organs and organ systems. The Periodic assessment of blood sugar is essential for the management of diabetes. An EPI based measurement process could be an alternative.
Research Article
Abstract
Volume 4 Issue 5 – 2016
Electrophotonic Imaging (EPI) data is collected from 200 subjects including males and females in the age group of 40 to 60 years from a diabetic center in Bangalore. The EPI data was captured from all the ten fingers from the subjects who came for the regular blood test. The EPI data corresponding to the meridians of the ring finger, chakras, organs and organ systems related to diabetes were analyzed using general linear model in IBM SPSS version 20.0. A built in neural network classifier from IBM SPSS was used to classify diabetic subjects from non-diabetic subjects.
The mean and standard deviation values for pancreas were 5.0240 and 1.02754 for the diabetic subjects and 4.7383 and 0.87618 for the non-diabetic subjects. Similarly for the hypothalamus the mean and standard deviation values were 4.9760 and 0.75926 for diabetes and 4.6150 and 0.86120 for non-diabetic subjects. The units for all the measurements are pixel units and represent empirical value for photonic energy. The classification accuracy of the neural network classifier was in the range of 80% to 100%.
*Corresponding author: Shiva Kumar Kotikalapudi, SVYASA Yoga University Bangalore, India. #19, ‘Eknath Bhavan’, Circle, Kempe Gowda Bengaluru,, Gavipura, Kempegowda Nagar, Bengaluru, Karnataka 560019, Tel: +91-9945578216;Email:
EPI parameters had a statistically significant difference from the non-diabetic subjects. EPI data could be refined more to make use of it as a bio-metric fordiabetes.