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Mendeley readers
Attention Score in Context
| Title |
Cardinality as a highly descriptive feature in myoelectric pattern recognition for decoding motor volition
|
|---|---|
| Published in |
Frontiers in Neuroscience, October 2015
|
| DOI | 10.3389/fnins.2015.00416 |
| Pubmed ID | |
| Authors |
Max Ortiz-Catalan |
| Abstract |
Accurate descriptors of muscular activity play an important role in clinical practice and rehabilitation research. Such descriptors are features of myoelectric signals extracted from sliding time windows. A wide variety of myoelectric features have been used as inputs to pattern recognition algorithms that aim to decode motor volition. The output of these algorithms can then be used to control limb prostheses, exoskeletons, and rehabilitation therapies. In the present study, cardinality is introduced and compared with traditional time-domain (Hudgins' set) and other recently proposed myoelectric features (for example, rough entropy). Cardinality was found to consistently outperform other features, including those that are more sophisticated and computationally expensive, despite variations in sampling frequency, time window length, contraction dynamics, type, and number of movements (single or simultaneous), and classification algorithms. Provided that the signal resolution is kept between 12 and 14 bits, cardinality improves myoelectric pattern recognition for the prediction of motion volition. This technology is instrumental for the rehabilitation of amputees and patients with motor impairments where myoelectric signals are viable. All code and data used in this work is available online within BioPatRec. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 55 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 12 | 22% |
| Student > Ph. D. Student | 9 | 16% |
| Student > Bachelor | 5 | 9% |
| Researcher | 5 | 9% |
| Student > Doctoral Student | 3 | 5% |
| Other | 7 | 13% |
| Unknown | 14 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 26 | 47% |
| Computer Science | 4 | 7% |
| Neuroscience | 2 | 4% |
| Chemistry | 2 | 4% |
| Nursing and Health Professions | 1 | 2% |
| Other | 5 | 9% |
| Unknown | 15 | 27% |
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 24 November 2015.
All research outputs
#20,656,161
of 25,373,627 outputs
Outputs from Frontiers in Neuroscience
#9,456
of 11,538 outputs
Outputs of similar age
#216,512
of 295,443 outputs
Outputs of similar age from Frontiers in Neuroscience
#116
of 142 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,538 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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We're also able to compare this research output to 142 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.