| Title |
The relationship between action anticipation and emotion recognition in athletes of open skill sports
|
|---|---|
| Published in |
Cognitive Processing, May 2016
|
| DOI | 10.1007/s10339-016-0764-7 |
| Pubmed ID | |
| Authors |
Yu-Ling Shih, Chia-Yen Lin |
| Abstract |
Action anticipation plays an important role in the successful performance of open skill sports, such as ball and combat sports. Evidence has shown that elite athletes of open sports excel in action anticipation. Most studies have targeted ball sports and agreed that information on body mechanics is one of the key determinants for successful action anticipation in open sports. However, less is known about combat sports, and whether facial emotions have an influence on athletes' action anticipation skill. It has been suggested that the understanding of intention in combat sports relies heavily on emotional context. Based on this suggestion, the present study compared the action anticipation performances of taekwondo athletes, weightlifting athletes, and non-athletes and then correlated these with their performances of emotion recognition. This study primarily found that accurate action anticipation does not necessarily rely on the dynamic information of movement, and that action anticipation performance is correlated with that of emotion recognition in taekwondo athletes, but not in weightlifting athletes. Our results suggest that the recognition of facial emotions plays a role in the action prediction in such combat sports as taekwondo. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| Unknown | 90 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 17 | 19% |
| Researcher | 9 | 10% |
| Student > Ph. D. Student | 8 | 9% |
| Student > Postgraduate | 7 | 8% |
| Student > Bachelor | 7 | 8% |
| Other | 18 | 20% |
| Unknown | 25 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Sports and Recreations | 23 | 25% |
| Psychology | 8 | 9% |
| Medicine and Dentistry | 7 | 8% |
| Neuroscience | 7 | 8% |
| Social Sciences | 4 | 4% |
| Other | 14 | 15% |
| Unknown | 28 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 61. 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 18 May 2016.
All research outputs
#593,730
of 22,869,263 outputs
Outputs from Cognitive Processing
#4
of 337 outputs
Outputs of similar age
#12,014
of 301,827 outputs
Outputs of similar age from Cognitive Processing
#1
of 9 outputs
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So far Altmetric has tracked 337 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.3. This one has done particularly well, scoring higher than 98% of its peers.
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