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Effective Synchronization of EEG and EMG for Mobile Brain/Body Imaging in Clinical Settings

Overview of attention for article published in Frontiers in Human Neuroscience, January 2018
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Title
Effective Synchronization of EEG and EMG for Mobile Brain/Body Imaging in Clinical Settings
Published in
Frontiers in Human Neuroscience, January 2018
DOI 10.3389/fnhum.2017.00652
Pubmed ID
Authors

Fiorenzo Artoni, Annalisa Barsotti, Eleonora Guanziroli, Silvestro Micera, Alberto Landi, Franco Molteni

Abstract

Mobile Brain/Body Imaging (MoBI) is rapidly gaining traction as a new imaging modality to study how cognitive processes support locomotion. Electroencephalogram (EEG) and electromyogram (EMG), due to their time resolution, non-invasiveness and portability are the techniques of choice for MoBI, but synchronization requirements among others restrict its use to high-end research facilities. Here we test the effectiveness of a technique that enables us to achieve MoBI-grade synchronization of EEG and EMG, even when other strategies (such as Lab Streaming Layer (LSL)) cannot be used e.g., due to the unavailability of proprietary Application Programming Interfaces (APIs), which is often the case in clinical settings. The proposed strategy is that of aligning several spikes at the beginning and end of the session. We delivered a train of spikes to the EEG amplifier and EMG electrodes every 2 s over a 10-min time period. We selected a variable number of spikes (from 1 to 10) both at the beginning and end of the time series and linearly resampled the data so as to align them. We then compared the misalignment of the "middle" spikes over the whole recording to test for jitter and synchronization drifts, highlighting possible nonlinearities (due to hardware filters) and estimated the maximum length of the recording to achieve a [-5 to 5] ms misalignment range. We demonstrate that MoBI-grade synchronization can be achieved within 10-min recordings with a 1.7 ms jitter and [-5 5] ms misalignment range. We show that repeated spike delivery can be used to test online synchronization options and to troubleshoot synchronization issues over EEG and EMG. We also show that synchronization cannot rely only on the equipment sampling rate advertised by manufacturers. The synchronization strategy described can be used virtually in every clinical environment, and may increase the interest among a broader spectrum of clinicians and researchers in the MoBI framework, ultimately leading to a better understanding of the brain processes underlying locomotion control and the development of more effective rehabilitation approaches.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 88 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 18 20%
Student > Ph. D. Student 14 16%
Researcher 12 14%
Student > Bachelor 10 11%
Student > Doctoral Student 5 6%
Other 16 18%
Unknown 13 15%
Readers by discipline Count As %
Engineering 21 24%
Neuroscience 14 16%
Computer Science 9 10%
Medicine and Dentistry 7 8%
Psychology 6 7%
Other 11 13%
Unknown 20 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 18 January 2018.
All research outputs
#15,486,175
of 23,012,811 outputs
Outputs from Frontiers in Human Neuroscience
#5,289
of 7,191 outputs
Outputs of similar age
#270,801
of 443,293 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#132
of 160 outputs
Altmetric has tracked 23,012,811 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,191 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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 443,293 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 160 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.