A Novel Algorithm to Diagnose Individuals with Low Back Pain and Cluster Analysis of Lumbar Movement Using Inertial Sensors

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Ashouri, Sajad | 2015

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 47860 (08)
University: Sharif University of Technology
Department: Mechanical Engineering
Advisor(s):
Abstract:
Low back pain is the most prevalence musculoskeletal pain that people experience in their life. Some cases of low back pain are called non-specific. These are cases for which the reason of pain is not well defined. The aim of this study is to propose a simple approach to diagnose and cluster low back pain patients which helps clinicians to evaluate patients by an affordable and simple tool. In this study, data are collected in two steps using Inertial Sensors. Inertial Sensors consist of a 3-axis gyroscope and a 3-axis accelerometer which represent the kinematic parameters of lumbar movement. In the first step, we examine 24 healthy and 28 patients with low back pain and in the second, 84 patients with low back pain are classified in 3 subgroup by START questionnaire. The results in the first steps indicate that the kinematic parameters are good factors to differentiate between healthy and patient subjects. Although, in the second one, we concluded that kinematic parameters are not appropriate to cluster patient based on the START questionnaire
Keywords:
Clustering ; Classification ; Low Back Pain ; Inertial Sensor ; Tree Dimentional Kinematics

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