ARUP; ISBN: 978-0-9562121-5-3 - CMBBE 2012 - Cardiff University

PREDICTION OF INTERNAL SPINE CURVATURE USING BACK
SURFACE INFORMATION
1. ABSTRACT
K. Ben Mansour 1 , T. T. Dao 2 , M. C. Ho Ba Tho 3 and F. Marin 4
The estimation of lumbar spine curvature during rehabilitation and daily life activities
require knowledge of the shape of internal lumbar spine. Several techniques exist for
quantifying spinal internal curvature [1], however these methods are designed to be
used in a clinical environment for a limited range of postures and are not adequate for
the study of motion. The aim of this study is to propose a model for predicting the
internal lumbar curvature using external back surface information. Five asymptomatic
male subjects with an age ranging from 28 to 55 years participated in this study on a
voluntary basis. The 3D reconstructions of the lumbar spine were realized using a
supine MRI (Sagittal T2 FRESE sequence). Each subject performs three postures in the
supine position: standard supine, hyper-lordosis and hypo-lordosis. Using MRI data, the
study of the correspondence between internal and external lumbar curvature support the
possibility to predict one using the other (R=0.88). This funding was implemented in
real time allowing the estimation of internal curvature during rehabilitation exercises
using a motion capture technique.
2. INTRODUCTION
The human spine can exhibit three types of spinal deformity or curvature, namely:
scoliosis, kyphosis and lordosis. These curvatures can lead to pain and discomfort of the
individual involved, disturbing productivity; and require expansive and prolonged
treatment. The low back pain is one of the most common and costly problem in
industrialized countries. Nearly 80% of people over the age of 30 will experience low
back pain problems during some periods of their life [2].
Thus, the need for frequent follow-up evaluations during therapy and the necessity to
greatly reduce the overall radiation load during the duration of the treatment motivate
the development of accurate, reliable and low cost methods. Various techniques such as
Moiré topography [3], structured light [4] and laser scanners [5] are currently proposed
to estimate the spinal curvature. However, these techniques are limited to the analysis of
static standing positions. The purpose of this study was to propose a model for
predicting the internal lumbar curvature using external back surface information to
estimate lumbar curvature during clinical functional evaluation and rehabilitation.
3. METHODS
3.1 Subject identification and data acquisition
1,2 Research engineer, 3,4 Professor : Université de Technologie de Compiègne, CNRS UMR 6600,
Biomécanique et Bioingénierie, France