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Application of advanced biomechanical methods in studying low back pain – recent development in estimation of lower back loads and large-array surface electromyography and findings

Overview of attention for article published in Journal of Pain Research, July 2017
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  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Average Attention Score compared to outputs of the same age and source

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Citations

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103 Mendeley
Title
Application of advanced biomechanical methods in studying low back pain – recent development in estimation of lower back loads and large-array surface electromyography and findings
Published in
Journal of Pain Research, July 2017
DOI 10.2147/jpr.s139185
Pubmed ID
Authors

Babak Bazrgari, Ting Xia

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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 103 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 14%
Researcher 11 11%
Student > Ph. D. Student 11 11%
Student > Bachelor 11 11%
Other 7 7%
Other 15 15%
Unknown 34 33%
Readers by discipline Count As %
Medicine and Dentistry 16 16%
Nursing and Health Professions 15 15%
Engineering 10 10%
Sports and Recreations 8 8%
Agricultural and Biological Sciences 3 3%
Other 9 9%
Unknown 42 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 August 2017.
All research outputs
#12,987,550
of 22,990,068 outputs
Outputs from Journal of Pain Research
#843
of 1,757 outputs
Outputs of similar age
#148,550
of 314,061 outputs
Outputs of similar age from Journal of Pain Research
#36
of 59 outputs
Altmetric has tracked 22,990,068 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,757 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one has gotten more attention than average, scoring higher than 51% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 314,061 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.