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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Integrating Brain Implants With Local and Distributed Computing Devices: A Next Generation Epilepsy Management System
|
|---|---|
| Published in |
IEEE Journal of Translational Engineering in Health and Medicine, September 2018
|
| DOI | 10.1109/jtehm.2018.2869398 |
| Pubmed ID | |
| Authors |
Vaclav Kremen, Benjamin H. Brinkmann, Inyong Kim, Hari Guragain, Mona Nasseri, Abigail L. Magee, Tal Pal Attia, Petr Nejedly, Vladimir Sladky, Nathanial Nelson, Su-Youne Chang, Jeffrey A. Herron, Tom Adamski, Steven Baldassano, Jan Cimbalnik, Vince Vasoli, Elizabeth Fehrmann, Tom Chouinard, Edward E. Patterson, Brian Litt, Matt Stead, Jamie Van Gompel, Beverly K. Sturges, Hang Joon Jo, Chelsea M. Crowe, Timothy Denison, Gregory A. Worrell |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 160 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 160 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 25 | 16% |
| Researcher | 23 | 14% |
| Student > Bachelor | 15 | 9% |
| Student > Master | 14 | 9% |
| Student > Doctoral Student | 7 | 4% |
| Other | 26 | 16% |
| Unknown | 50 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 26 | 16% |
| Neuroscience | 26 | 16% |
| Medicine and Dentistry | 18 | 11% |
| Computer Science | 11 | 7% |
| Agricultural and Biological Sciences | 5 | 3% |
| Other | 22 | 14% |
| Unknown | 52 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 02 November 2022.
All research outputs
#4,838,109
of 25,385,509 outputs
Outputs from IEEE Journal of Translational Engineering in Health and Medicine
#31
of 228 outputs
Outputs of similar age
#89,125
of 351,260 outputs
Outputs of similar age from IEEE Journal of Translational Engineering in Health and Medicine
#2
of 16 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 228 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done well, scoring higher than 83% 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 351,260 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 73% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.