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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MoBILAB: an open source toolbox for analysis and visualization of mobile brain/body imaging data
|
|---|---|
| Published in |
Frontiers in Human Neuroscience, March 2014
|
| DOI | 10.3389/fnhum.2014.00121 |
| Pubmed ID | |
| Authors |
Alejandro Ojeda, Nima Bigdely-Shamlo, Scott Makeig |
| Abstract |
A new paradigm for human brain imaging, mobile brain/body imaging (MoBI), involves synchronous collection of human brain activity (via electroencephalography, EEG) and behavior (via body motion capture, eye tracking, etc.), plus environmental events (scene and event recording) to study joint brain/body dynamics supporting natural human cognition supporting performance of naturally motivated human actions and interactions in 3-D environments (Makeig et al., 2009). Processing complex, concurrent, multi-modal, multi-rate data streams requires a signal-processing environment quite different from one designed to process single-modality time series data. Here we describe MoBILAB (more details available at sccn.ucsd.edu/wiki/MoBILAB), an open source, cross platform toolbox running on MATLAB (The Mathworks, Inc.) that supports analysis and visualization of any mixture of synchronously recorded brain, behavioral, and environmental time series plus time-marked event stream data. MoBILAB can serve as a pre-processing environment for adding behavioral and other event markers to EEG data for further processing, and/or as a development platform for expanded analysis of simultaneously recorded data streams. |
X Demographics
The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 14% |
| Netherlands | 2 | 14% |
| India | 1 | 7% |
| Canada | 1 | 7% |
| United States | 1 | 7% |
| Unknown | 7 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 43% |
| Scientists | 4 | 29% |
| Practitioners (doctors, other healthcare professionals) | 3 | 21% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 1% |
| Germany | 1 | <1% |
| Austria | 1 | <1% |
| Cuba | 1 | <1% |
| Brazil | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 169 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 44 | 25% |
| Researcher | 30 | 17% |
| Student > Master | 27 | 15% |
| Student > Doctoral Student | 13 | 7% |
| Student > Bachelor | 13 | 7% |
| Other | 31 | 18% |
| Unknown | 18 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 34 | 19% |
| Psychology | 28 | 16% |
| Engineering | 25 | 14% |
| Computer Science | 17 | 10% |
| Medicine and Dentistry | 8 | 5% |
| Other | 29 | 16% |
| Unknown | 35 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 22 May 2017.
All research outputs
#3,558,812
of 22,745,803 outputs
Outputs from Frontiers in Human Neuroscience
#1,681
of 7,136 outputs
Outputs of similar age
#35,925
of 221,292 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#38
of 93 outputs
Altmetric has tracked 22,745,803 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,136 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one has done well, scoring higher than 76% 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 221,292 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 83% of its contemporaries.
We're also able to compare this research output to 93 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.