Lower Back Pain Classification using Parameter Tuning

Abstract

Back pain is one of the most popular diseases which cause extreme discomfort for patients. More than 80% of the people’s day to day activities are affected due to lower back pain. The symptom sometimes gets neglected and worsens the situation, which can cause lifelong damage to vital organs. Lower back pain can be classified as normal and abnormal LBP based on the boundary values of various parameters. Extensive research has been carried out in this field and most of the classification techniques serve the purpose by classifying the data with already provided accuracy values. However, this paper provides a novel technique by adding feature parameter tuning which acts as a catalyst in increasing the accuracy and thereby identifying the effective parameters that help in the optimization.