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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using “Smart Stimulators” to Treat Parkinson’s Disease: Re-Engineering Neurostimulation Devices
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, January 2012
|
| DOI | 10.3389/fncom.2012.00069 |
| Pubmed ID | |
| Authors |
Julien Modolo, Anne Beuter, Alex W. Thomas, Alexandre Legros |
| Abstract |
Let's imagine the cruise control of your car locked at 120 km/h on any road in any condition (city, country, highway, sunny or rainy weather), or your car air conditioner set on maximum cold in any temperature condition (even during a snowy winter): would you find it efficient? That would probably not be the most optimal strategy for a proper and comfortable driving experience. As surprising as this may seem, this is a pretty accurate illustration of how deep brain stimulation is used today to treat Parkinson's disease motor symptoms and other neurological disorders such as essential tremor, obsessive-compulsive disorder, or epilepsy. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 3% |
| Italy | 1 | 2% |
| Cuba | 1 | 2% |
| United Kingdom | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 56 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 26% |
| Student > Ph. D. Student | 11 | 18% |
| Student > Master | 10 | 16% |
| Student > Doctoral Student | 4 | 6% |
| Professor | 4 | 6% |
| Other | 11 | 18% |
| Unknown | 6 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 12 | 19% |
| Engineering | 11 | 18% |
| Agricultural and Biological Sciences | 8 | 13% |
| Neuroscience | 8 | 13% |
| Computer Science | 4 | 6% |
| Other | 11 | 18% |
| Unknown | 8 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 21 September 2012.
All research outputs
#13,870,800
of 22,675,759 outputs
Outputs from Frontiers in Computational Neuroscience
#626
of 1,336 outputs
Outputs of similar age
#151,722
of 244,088 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#31
of 69 outputs
Altmetric has tracked 22,675,759 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,336 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 49th percentile – i.e., 49% 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 244,088 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 69 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 52% of its contemporaries.