Feasibility Study of Human Lumbar Motion using Variability Techniques

Abstract

More than 80 percent of people suffer from low back pain at some point in their lifetime. It is one of the most prevalent musculoskeletal disorders in the United States. The pain can be short-lived or long-lasting. In either case, low back pain can make many daily activities difficult to perform. Even though it is one of the most studied disorders, the etiology of low back pain is still unknown. Kinematics and kinetics of body movements can be affected by low back pain and may result in spinal instability. Previous studies have quantified this spinal stability using linear and nonlinear motion analysis techniques. The purpose of this study was to obtain the variation in kinematics of healthy volunteer subjects using these two techniques while the volunteer subjects are performing the lumbar movement during flexion-extension while sitting on an unstable surface. In addition, a second objective was to study the variation on a cadaveric specimen during flexion and extension motions. Five healthy volunteers performed repetitive trunk flexion and extension movements while sitting on an unstable surface with different starting positions (forward, neutral, and backward) and two different movement initiation (forward and backward) directions. The cadaveric specimen was subjected to flexion-extension movements at different speeds. Traditional linear techniques such as mean, standard deviation, and coefficient of variation, along with nonlinear technique such as approximate entropy, were calculated from measured trunk kinematics to estimate the variability of the human motions. The average values for the motions had a range from 10.556 degrees to 26.101 degrees. The standard deviation values had a range from 1.941 to 3.278. The coefficients of variation had a range from 7.258 to 26.597. The Approximate Entropy values had a range from 0.209 to 0.274. To the best of the authors’ knowledge this is the first study to determine the variability of sitting motions on an unstable surface using approximate entropy. Linear and nonlinear dynamic systems analyses were successfully applied to trunk flexion-extension data, which can serve as control data for further studies and understanding kinematics and kinetics of low back pain patients.