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Attention Score in Context
| Title |
Decoding the ERD/ERS: influence of afferent input induced by a leg assistive robot
|
|---|---|
| Published in |
Frontiers in Systems Neuroscience, May 2014
|
| DOI | 10.3389/fnsys.2014.00085 |
| Pubmed ID | |
| Authors |
Giuseppe Lisi, Tomoyuki Noda, Jun Morimoto |
| Abstract |
This paper investigates the influence of the leg afferent input, induced by a leg assistive robot, on the decoding performance of a BMI system. Specifically, it focuses on a decoder based on the event-related (de)synchronization (ERD/ERS) of the sensorimotor area. The EEG experiment, performed with healthy subjects, is structured as a 3 × 2 factorial design, consisting of two factors: "finger tapping task" and "leg condition." The former is divided into three levels (BMI classes), being left hand finger tapping, right hand finger tapping and no movement (Idle); while the latter is composed by two levels: leg perturbed (Pert) and leg not perturbed (NoPert). Specifically, the subjects' leg was periodically perturbed by an assistive robot in 5 out of 10 sessions of the experiment and not moved in the remaining sessions. The aim of this study is to verify that the decoding performance of the finger tapping task is comparable between the two conditions NoPert and Pert. Accordingly, a classifier is trained to output the class of the finger tapping, given as input the features associated with the ERD/ERS. Individually for each subject, the decoding performance is statistically compared between the NoPert and Pert conditions. Results show that the decoding performance is notably above chance, for all the subjects, under both conditions. Moreover, the statistical comparison do not highlight a significant difference between NoPert and Pert in any subject, which is confirmed by feature visualization. |
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 % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Taiwan | 1 | 2% |
| Unknown | 52 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 24% |
| Researcher | 8 | 15% |
| Student > Bachelor | 7 | 13% |
| Student > Master | 5 | 9% |
| Professor > Associate Professor | 4 | 7% |
| Other | 8 | 15% |
| Unknown | 9 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 15 | 28% |
| Neuroscience | 10 | 19% |
| Psychology | 4 | 7% |
| Computer Science | 3 | 6% |
| Agricultural and Biological Sciences | 3 | 6% |
| Other | 8 | 15% |
| Unknown | 11 | 20% |
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 01 May 2014.
All research outputs
#18,371,293
of 22,754,104 outputs
Outputs from Frontiers in Systems Neuroscience
#1,127
of 1,340 outputs
Outputs of similar age
#164,019
of 227,199 outputs
Outputs of similar age from Frontiers in Systems Neuroscience
#52
of 62 outputs
Altmetric has tracked 22,754,104 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,340 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 8th percentile – i.e., 8% 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 227,199 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.