An Intelligent System to Improve Athlete Depression and Eating Disorder using Artificial Intelligence and Big Data Analysis

The inspiration for the creation of this app stemmed from the deeply rooted history of eating disorders in sports, particularly in sports that emphasize appearance and muscularity which often includes gymnastics, figure skating, dance, and diving [1]. All three sports require rapid rotation in the air which automatically results in the necessity of a more stringent weight requirement. Eating disorders can also be aggravated by sports who focus on individual performances rather than team-oriented like basketball or soccer [5]. According to research, up to thirteen percent of all athletes have, or are currently suffering from a form of eating disorder such as anorexia [2] and bulimia [3]. In the National Collegiate Athletic Association, it is estimated that up to sixteen percent of male athletes and forty-five percent of female athletes have been diagnosed with an eating disorder.

Shared Representations in Athletes: Segmenting Action Sequences From Taekwondo Reveals Implicit Agreement

How do athletes represent actions from their sport? How are these representations structured and which knowledge is shared among experts in the same discipline? To address these questions, the event segmentation task was used. Experts in Taekwondo and novices indicated how they would subjectively split videos of Taekwondo form sequences into meaningful units. In previous research, this procedure was shown to unveil the structure of internal action representations and to be affected by sensorimotor knowledge. Without specific instructions on the grain size of segmentation, experts tended to integrate over longer episodes which resulted in a lower number of single units. Moreover, in accordance with studies in figure-skating and basketball, we expected higher agreement among experts on where to place segmentation marks, i.e., boundaries. In line with this hypothesis, significantly more overlap of boundaries was found within the expert group as compared to the control group. This was observed even though the interindividual differences in the selected grain size were huge and expertise had no systematic influence here. The absence of obvious goals or objects to structure Taekwondo forms underlines the importance of shared expert knowledge. Further, experts might have benefited from sensorimotor skills which allowed to simulate the observed actions more precisely. Both aspects may explain stronger agreement among experts even in unfamiliar Taekwondo forms. These interpretations are descriptively supported by the participants’ statements about features which guided segmentation and by an overlap of the group’s agreed boundaries with those of an experienced referee. The study shows that action segmentation can be used to provide insights into structure and content of action representations specific to experts. The mechanisms underlying shared knowledge among Taekwondoists and among experts in general are discussed on the background of current theoretic frameworks.

American Poverty and Social Rejection in Craig Gillespie’s I, Tonya

This paper examines the image of American poverty, rejection and social engagement in a recent sports biopic inspired by the story of American skater Tonya Harding, Craig Gillespie’s I, Tonya (2017). It draws on data presented in recent poverty studies to determine the extent of deprivation and attend to its representation in American cinema. In the light of the above, I closely analyze the biopic, focusing on its depiction of professional figure skating, expectations of female athletes, and most importantly, the figure of Tonya Harding. I argue that the protagonist’s social background dominates her portrayal, which also challenges the common conception of a sports biopic; Harding’s narrative is defined by her mismatch with ice skating’s normative expectations and, most importantly, by her social standing.

Biomechanics of Rotational Movement in Off-Ice Figure Skating Jumps: Applications to Training

Introduction The aim of this study was to characterize kinematic parameters of the rotational body movement during the office figure skating multi-revolution jumping exercise and to propose applications to training. Material and Methods Six elite Polish female junior singles figure skaters were examined performing single and their respective maximum total rotation vertical jumps in off-ice conditions. Measurements of the ground reaction force were performed with a KISTLER (500 Hz) piezoelectric sensor platform with BioWare Software, synchronized with the cinematographic analysis using the Vicon T-Series motion capture system. Results The analysis revealed positive linear relations between selected jump parameters of the pre-take-off phase and after the landing. Two moments of countering torque were also noticed: the first in the landing phase, and the second before reaching the stabilized position. Conclusions Applications of the findings for off-ice training were discussed.