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Assessing Brain–Muscle Connectivity in Human Locomotion through Mobile Brain/Body Imaging: Opportunities, Pitfalls, and Future Directions

Overview of attention for article published in Frontiers in Public Health, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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Title
Assessing Brain–Muscle Connectivity in Human Locomotion through Mobile Brain/Body Imaging: Opportunities, Pitfalls, and Future Directions
Published in
Frontiers in Public Health, February 2018
DOI 10.3389/fpubh.2018.00039
Pubmed ID
Authors

Federico Gennaro, Eling D. de Bruin

Abstract

Assessment of the cortical role during bipedalism has been a methodological challenge. While surface electroencephalography (EEG) is capable of non-invasively measuring cortical activity during human locomotion, it is associated with movement artifacts obscuring cerebral sources of activity. Recently, statistical methods based on blind source separation revealed potential for resolving this issue, by segregating non-cerebral/artifactual from cerebral sources of activity. This step marked a new opportunity for the investigation of the brains' role while moving and was tagged mobile brain/body imaging (MoBI). This methodology involves simultaneous mobile recording of brain activity with several other body behavioral variables (e.g., muscle activity and kinematics), through wireless recording wearable devices/sensors. Notably, several MoBI studies using EEG-EMG approaches recently showed that the brain is functionally connected to the muscles and active throughout the whole gait cycle and, thus, rejecting the long-lasting idea of a solely spinal-driven bipedalism. However, MoBI and brain/muscle connectivity assessments during human locomotion are still in their fledgling state of investigation. Mobile brain/body imaging approaches hint toward promising opportunities; however, there are some remaining pitfalls that need to be resolved before considering their routine clinical use. This article discusses several of these pitfalls and proposes research to address them. Examples relate to the validity, reliability, and reproducibility of this method in ecologically valid scenarios and in different populations. Furthermore, whether brain/muscle connectivity within the MoBI framework represents a potential biomarker in neuromuscular syndromes where gait disturbances are evident (e.g., age-related sarcopenia) remains to be determined.

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X Demographics

The data shown below were collected from the profiles of 37 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 83 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 18%
Student > Master 12 14%
Researcher 8 10%
Student > Doctoral Student 5 6%
Professor 4 5%
Other 11 13%
Unknown 28 34%
Readers by discipline Count As %
Neuroscience 12 14%
Sports and Recreations 8 10%
Engineering 8 10%
Nursing and Health Professions 6 7%
Agricultural and Biological Sciences 5 6%
Other 14 17%
Unknown 30 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 24 April 2023.
All research outputs
#1,729,511
of 25,807,758 outputs
Outputs from Frontiers in Public Health
#853
of 14,424 outputs
Outputs of similar age
#36,500
of 345,106 outputs
Outputs of similar age from Frontiers in Public Health
#22
of 112 outputs
Altmetric has tracked 25,807,758 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,424 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done particularly well, scoring higher than 94% 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 345,106 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 112 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.