Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/35842
Title: Assessment and classification of lower back pain
Authors: ZHANG XIN YUE
Keywords: SEMG, 3-axis accelerometers, LBP, ValedoTM motion system, objective classification of lower back pain, Gaussian mixture model
Issue Date: 22-Aug-2012
Source: ZHANG XIN YUE (2012-08-22). Assessment and classification of lower back pain. ScholarBank@NUS Repository.
Abstract: This thesis presents work done towards developing a reliable determining system to assess and classify the lower back pain. In the initial stage, we seek to explore the possibilities of coming up an effective and user-friendly way to assess patients with non-specific lower back pain thereby ValedoTM motion system. However, the data collected by ValedoTM motion sensors cannot be directly exported for in-depth analysis due to the commercial confidentiality. Therefore, another novel determining system has proposed to assess the lower back pain patients based on Maximum-Likelihood Estimation of Gaussian Mixture Model algorithm. To validate the proposed classification algorithm, a motion testing experiment is conducted to analyze the motion data from healthy participants and LBP patients by collecting the data from DelsysTM TrignoTM EMG system.
URI: http://scholarbank.nus.edu.sg/handle/10635/35842
Appears in Collections:Master's Theses (Open)

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