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Mendeley readers
Attention Score in Context
| Title |
Surface EMG pattern recognition for real-time control of a wrist exoskeleton
|
|---|---|
| Published in |
BioMedical Engineering OnLine, August 2010
|
| DOI | 10.1186/1475-925x-9-41 |
| Pubmed ID | |
| Authors |
Zeeshan O Khokhar, Zhen G Xiao, Carlo Menon |
| Abstract |
Surface electromyography (sEMG) signals have been used in numerous studies for the classification of hand gestures and movements and successfully implemented in the position control of different prosthetic hands for amputees. sEMG could also potentially be used for controlling wearable devices which could assist persons with reduced muscle mass, such as those suffering from sarcopenia. While using sEMG for position control, estimation of the intended torque of the user could also provide sufficient information for an effective force control of the hand prosthesis or assistive device. This paper presents the use of pattern recognition to estimate the torque applied by a human wrist and its real-time implementation to control a novel two degree of freedom wrist exoskeleton prototype (WEP), which was specifically developed for this work. |
Mendeley readers
The data shown below were compiled from readership statistics for 430 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 3 | <1% |
| Portugal | 2 | <1% |
| Brazil | 2 | <1% |
| United States | 2 | <1% |
| France | 1 | <1% |
| Austria | 1 | <1% |
| Malaysia | 1 | <1% |
| India | 1 | <1% |
| United Kingdom | 1 | <1% |
| Other | 6 | 1% |
| Unknown | 410 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 90 | 21% |
| Student > Master | 88 | 20% |
| Researcher | 41 | 10% |
| Student > Bachelor | 38 | 9% |
| Student > Doctoral Student | 21 | 5% |
| Other | 81 | 19% |
| Unknown | 71 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 227 | 53% |
| Computer Science | 28 | 7% |
| Medicine and Dentistry | 17 | 4% |
| Unspecified | 16 | 4% |
| Agricultural and Biological Sciences | 9 | 2% |
| Other | 44 | 10% |
| Unknown | 89 | 21% |
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 11 April 2011.
All research outputs
#4,655,198
of 22,705,019 outputs
Outputs from BioMedical Engineering OnLine
#120
of 821 outputs
Outputs of similar age
#19,639
of 93,748 outputs
Outputs of similar age from BioMedical Engineering OnLine
#2
of 6 outputs
Altmetric has tracked 22,705,019 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 821 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 85% 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 93,748 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 79% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.