Pain track analysis during gestation using machine learning techniques

Abstract

During the gestation period women experience Braxton Hicks which is called the false labor, contractions during the second trimester. These contractions are not in regular intervals and also they are often unnoticed. The real labour or the true labour contractions develop late in the third trimester of the gestation usually beyond 36th week (excluding pre-term birth). Some women often fail to identify these pains in the third trimester of the gestation where an efficient facial recognition algorithm along with the support vector machine (SVM) helps them to identify these pains and take optimum care of themselves. The authors in this paper convey a mechanism to identify the pains effectively by creating a database of images pertaining to the pregnant women, her emotional states through out the pregnancy. Using MATLAB the algorithm of decision tree is implemented and the values obtained from them help us analyze the pain type efficiently.