Abstract

Low back pain (LBP) is a major public health problem and the leading disabling musculoskeletal disorder globally. A number of biomechanical methods using kinematic, kinetic and/or neuromuscular approaches have been used to study LBP. In this narrative review, we report recent developments in two biomechanical methods: estimation of lower back loads and large-array surface electromyography (LA-SEMG) and the findings associated with LBP. The ability to estimate lower back loads is very important for the prevention and the management of work-related low back injuries based on the mechanical loading model as one category of LBP classification. The methods used for estimation of lower back loads vary from simple rigid link-segment models to sophisticated, optimization-based finite element models. In general, reviewed reports of differences in mechanical loads experienced in lower back tissues between patients with LBP and asymptomatic individuals are not consistent. Such lack of consistency is primarily due to differences in activities under which lower back mechanical loads were investigated as well as heterogeneity of patient populations. The ability to examine trunk neuromuscular behavior is particularly relevant to the motor control model, another category of LBP classification. LA-SEMG not only is noninvasive but also provides spatial resolution within and across muscle groups. Studies using LA-SEMG showed that healthy individuals exhibit highly organized, symmetric back muscle activity patterns, suggesting an orderly recruitment of muscle fibers. In contrast, back muscle activity patterns in LBP patients are asymmetric or multifocal, suggesting lack of orderly muscle recruitment. LA-SEMG was also shown capable of capturing unique back muscle response to manual therapy. In conclusion, estimation of low back load and LA-SEMG techniques demonstrated promising potentials for understanding LBP and treatment effects. Future studies are warranted to fully establish clinical validity of these two biomechanical methods.

Document Type

Article

Publication Date

7-17-2017

Notes/Citation Information

Published in Journal of Pain Research, v. 10, p. 1677-1685.

© 2017 Bazrgari and Xia.

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Digital Object Identifier (DOI)

https://doi.org/10.2147/JPR.S139185

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