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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A free geometry model-independent neural eye-gaze tracking system
|
|---|---|
| Published in |
Journal of NeuroEngineering and Rehabilitation, November 2012
|
| DOI | 10.1186/1743-0003-9-82 |
| Pubmed ID | |
| Authors |
Massimo Gneo, Maurizio Schmid, Silvia Conforto, Tommaso D’Alessio |
| Abstract |
Eye Gaze Tracking Systems (EGTSs) estimate the Point Of Gaze (POG) of a user. In diagnostic applications EGTSs are used to study oculomotor characteristics and abnormalities, whereas in interactive applications EGTSs are proposed as input devices for human computer interfaces (HCI), e.g. to move a cursor on the screen when mouse control is not possible, such as in the case of assistive devices for people suffering from locked-in syndrome. If the user's head remains still and the cornea rotates around its fixed centre, the pupil follows the eye in the images captured from one or more cameras, whereas the outer corneal reflection generated by an IR light source, i.e. glint, can be assumed as a fixed reference point. According to the so-called pupil centre corneal reflection method (PCCR), the POG can be thus estimated from the pupil-glint vector. |
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 % |
|---|---|---|
| Brazil | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 59 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 19 | 32% |
| Student > Bachelor | 11 | 19% |
| Researcher | 8 | 14% |
| Student > Doctoral Student | 4 | 7% |
| Student > Ph. D. Student | 3 | 5% |
| Other | 5 | 8% |
| Unknown | 9 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 13 | 22% |
| Computer Science | 11 | 19% |
| Medicine and Dentistry | 6 | 10% |
| Neuroscience | 6 | 10% |
| Nursing and Health Professions | 4 | 7% |
| Other | 8 | 14% |
| Unknown | 11 | 19% |
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 03 March 2023.
All research outputs
#5,240,151
of 25,373,627 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#304
of 1,413 outputs
Outputs of similar age
#34,972
of 179,074 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#2
of 11 outputs
Altmetric has tracked 25,373,627 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 1,413 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has done well, scoring higher than 78% 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 179,074 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 80% of its contemporaries.
We're also able to compare this research output to 11 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.