Purpose： This study aimed to investigate the construct of external visual imagery （EVI） vs. internal visual imagery （IV/） by comparing the athletes＇ imagery ability with their levels of skill and types of sports...Purpose： This study aimed to investigate the construct of external visual imagery （EVI） vs. internal visual imagery （IV/） by comparing the athletes＇ imagery ability with their levels of skill and types of sports. Methods： Seventy-two young athletes in open （n = 45） or closed （n = 27） sports and with different skill levels completed 2 custom-designed tasks. The EVI task involved the subject generating and visualizing the rotated images of different body parts, whereas the IVI task involved the subject visualizing himself or herself performing specific movements. Results： The significant Skill-Level x Sport Type interactions for the EVI task revealed that participants who specialized in open sports and had higher skill-levels had a higher accuracy rate as compared to the other subgroups. For the IVI task, the differences between the groups were less clear： those with higher skill-levels or open sports had a higher accuracy rate than those with lower skill-levels or closed sports. Conclusion： EVI involves the visualization of others and the environment, and would be relevant to higher skill-level athletes who engage in open sports. IVI, in contrast, tends to be more self-oriented and would be relevant for utilization by higher skill-level athletes regardless of sport type.展开更多
The human brain is built to process complex visual impressions within milliseconds. In comparison with sequentially coded spoken language and written texts, we are capable of consuming graphical information at a high ...The human brain is built to process complex visual impressions within milliseconds. In comparison with sequentially coded spoken language and written texts, we are capable of consuming graphical information at a high bandwidth in a parallel fashion, producing a picture worth more than a thousand words. Effective information visualization can be a powerful tool to capture people's attention and quickly communicate large amounts of data and complex information. This is particularly important in the context of communication data, which often describes entities (people, organizations) and their connections through communication. Visual analytics approaches can optimize the user-computer interaction to gain insights into communication networks and learn about their structures. Network visualization is a perfect instrument to better communicate the results of analysis. The precondition for effective information visualization and successful visual reasoning is the capability to draw "good" pictures. Even though communication networks are often large, including thousands or even millions of people, underlying visualization principles are identical to those used for visualizing smaller networks. In this article, you will learn about these principles, giving you the ability to assess the quality of network visualizations and to draw better network pictures by yourself.展开更多
基金supported by the Dr.and Mrs.Sui Kau Chan donation grant for sports training and rehabilitation held by Chetwyn C.H.Chan and Amy S.N.Fuand by an internal grant awarded to Chetwyn C.H.Chan by The Hong Kong Polytechnic University
文摘Purpose： This study aimed to investigate the construct of external visual imagery （EVI） vs. internal visual imagery （IV/） by comparing the athletes＇ imagery ability with their levels of skill and types of sports. Methods： Seventy-two young athletes in open （n = 45） or closed （n = 27） sports and with different skill levels completed 2 custom-designed tasks. The EVI task involved the subject generating and visualizing the rotated images of different body parts, whereas the IVI task involved the subject visualizing himself or herself performing specific movements. Results： The significant Skill-Level x Sport Type interactions for the EVI task revealed that participants who specialized in open sports and had higher skill-levels had a higher accuracy rate as compared to the other subgroups. For the IVI task, the differences between the groups were less clear： those with higher skill-levels or open sports had a higher accuracy rate than those with lower skill-levels or closed sports. Conclusion： EVI involves the visualization of others and the environment, and would be relevant to higher skill-level athletes who engage in open sports. IVI, in contrast, tends to be more self-oriented and would be relevant for utilization by higher skill-level athletes regardless of sport type.
文摘The human brain is built to process complex visual impressions within milliseconds. In comparison with sequentially coded spoken language and written texts, we are capable of consuming graphical information at a high bandwidth in a parallel fashion, producing a picture worth more than a thousand words. Effective information visualization can be a powerful tool to capture people's attention and quickly communicate large amounts of data and complex information. This is particularly important in the context of communication data, which often describes entities (people, organizations) and their connections through communication. Visual analytics approaches can optimize the user-computer interaction to gain insights into communication networks and learn about their structures. Network visualization is a perfect instrument to better communicate the results of analysis. The precondition for effective information visualization and successful visual reasoning is the capability to draw "good" pictures. Even though communication networks are often large, including thousands or even millions of people, underlying visualization principles are identical to those used for visualizing smaller networks. In this article, you will learn about these principles, giving you the ability to assess the quality of network visualizations and to draw better network pictures by yourself.
