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Trunk control during standing reach: A dynamical system analysis of movement strategies in patients with mechanical low back pain
Journal article   Open access   Peer reviewed

Trunk control during standing reach: A dynamical system analysis of movement strategies in patients with mechanical low back pain

Sheri P Silfies, Anand Bhattacharya, Scott Biely, Sue S Smith and Simon Giszter
Gait & posture, v 29(3), pp 370-376
Apr 2009
PMID: 19046882
url
https://doi.org/10.1016/j.gaitpost.2008.10.053View
Published, Version of Record (VoR) Open

Abstract

Lumbosacral Region - physiology Low Back Pain - physiopathology Movement - physiology Humans Adult Biomechanical Phenomena - physiology Female Male Pelvis - physiology
The purpose of this study was to quantify lumbo-pelvic control differences between patients with mechanical low back pain (MLBP) and asymptomatic controls using a dynamical systems approach to data reduction and interpretation. Subjects were 30 patients with chronic MLBP (age: 41.1+/-8.9 years, body mass index: 26.2+/-5.2 kg/m(2)) and 35 asymptomatic controls (age: 38.8+/-9.2 years, body mass index: 25.3+/-4.8 kg/m(2)). Kinematic data were collected from the femur, pelvis and lumbar spine during repeated trials of bilateral forward reaching under two loading conditions. Sagittal plane angular motion was filtered and time normalized. Continuous relative phases were then calculated for each data point. Mean absolute relative phase (MARP) and deviation phase (DP) parameters were derived to quantify intersegmental coordination and pattern variability. Mixed-model ANOVAs revealed that lumbo-pelvic coordination was more separated in time and more variable in the chronic MLBP group during this task. Trunk neuromuscular control was thus altered in our MLBP group. Unresolved extensor muscle dysfunction is suggested by (a) preliminary analysis of phase plane trajectories, (b) subjects' greater difficulty controlling aspects of the task that required the extensors to contribute to trunk stability and primary movement control.

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90 citations in Scopus

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Web of Science research areas
Neurosciences
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