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Research Article Open Access
In this work, a non invasive technique is proposed to detect diabetes from tridosha analysis. This system uses ayurveda knowledge for diagnosis of diabetes based on human constitution (prakriti). This system uses three piezoelectric pressure sensors mounted on human wrist for capturing Vaat, Pitta and Kapha signals respectively. These three signals are then amplified and filtered using signal condition unit. By analyzing the variations in these signals, respective dosha is identified and prakriti of a person is determined. Along with tridosha analysis, artificial neural network (ANN) is used for pattern classification purpose. For training of ANN different features extracted from signals are applied as input. ANN is trained using back propagation algorithm to minimize the error and differentiate normal and diabetic person.
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Author(s): Rushikesh Pradip Kulkarni and Mahesh S Kumbhar
Artificial neural network, diabetes, piezoelectric pressure sensor, tridosha analysis, Nadi Pariksha.