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Mendeley readers
Attention Score in Context
| Title |
On the Kinematic Motion Primitives (kMPs) – Theory and Application
|
|---|---|
| Published in |
Frontiers in Neurorobotics, January 2012
|
| DOI | 10.3389/fnbot.2012.00010 |
| Pubmed ID | |
| Authors |
Federico L. Moro, Nikos G. Tsagarakis, Darwin G. Caldwell |
| Abstract |
Human neuromotor capabilities guarantee a wide variety of motions. A full understanding of human motion can be beneficial for rehabilitation or performance enhancement purposes, or for its reproduction on artificial systems like robots. This work aims at describing the complexity of human motion in a reduced dimensionality, by means of kinematic Motion Primitives (kMPs). A set of five invariant kMPs are identified for periodic motions, and a set of two kMPs for discrete motions. It is shown how these two sets of kMPs can be combined to synthesize more complex motion as the simultaneous execution of the periodic and the discrete motions. The results reported are an evidence of the theory of Central Pattern Generators (CPG), showing its effects on the kinematics, and are related to what presented in the literature on the Motor Primitives extracted from EMG signals. Experimental tests with the COmpliant huMANoid (COMAN) were performed to show that the kMPs extracted from human subjects can be used to transfer the features of human locomotion to the gait of a robot. |
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 % |
|---|---|---|
| Switzerland | 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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Iran, Islamic Republic of | 1 | 2% |
| Japan | 1 | 2% |
| Germany | 1 | 2% |
| Italy | 1 | 2% |
| Unknown | 49 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 21% |
| Researcher | 10 | 19% |
| Professor | 7 | 13% |
| Student > Ph. D. Student | 7 | 13% |
| Student > Doctoral Student | 5 | 9% |
| Other | 9 | 17% |
| Unknown | 4 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 26 | 49% |
| Computer Science | 11 | 21% |
| Neuroscience | 3 | 6% |
| Medicine and Dentistry | 2 | 4% |
| Agricultural and Biological Sciences | 1 | 2% |
| Other | 5 | 9% |
| Unknown | 5 | 9% |
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 12 October 2012.
All research outputs
#22,759,802
of 25,374,917 outputs
Outputs from Frontiers in Neurorobotics
#777
of 1,039 outputs
Outputs of similar age
#228,486
of 250,100 outputs
Outputs of similar age from Frontiers in Neurorobotics
#8
of 10 outputs
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So far Altmetric has tracked 1,039 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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