Objective and parametric methods used in functional classification disabled swimmers

Physiotherapy ◽  
2013 ◽  
Vol 21 (3) ◽  
Author(s):  
Natalia Uścinowicz ◽  
Wojciech Seidel ◽  
Paweł Zostawa ◽  
Sebastian Klich

AbstractThe recent Olympic Games in London incited much interest in the competition of disabled athletes. Various people connected with swimming, including coaches and athletes, have speculated about the fairness of competitions of disabled athletes. A constant problem are the subjective methods of classification in disabled sport. Originally, athletes with disabilities were classified according to medical diagnosis. Due to the injustice which still affects the competitors, functional classification was created shortly after. In the present review, the authors show the anomalies in the structure of the classification. The presented discovery led to the suggestion to introduce objective methods, thanks to which it would be no longer necessary to rely on the subjective assessment of the classifier. According to the authors, while using objective methods does not completely rule out the possibility of fraud by disabled athletes in the classification process, it would certainly reduce their incidence. Some of the objective methods useful for the classification of disabled athletes are: posturography, evaluation of the muscle parameters, electrogoniometric assessment, surface electromyography, and analysis of kinematic parameters. These methods have provide objective evaluation in the diagnostic sense but only if they are used in tandem. The authors demonstrate the undeniable benefits of using objective methods. Unfortunately, there are not only advantages of such solution, there also several drawbacks to be found. The conclusion of the article is the statement by the authors that it is right to use objective methods which allow to further the most important rule in sport: fair-play.

2020 ◽  
Vol 73 (3) ◽  
pp. 358-367
Author(s):  
Júlio Cezar Rebés Azambuja Filho ◽  
Paulo Cesar de Faccio Carvalho ◽  
Olivier Jean François Bonnet ◽  
Denis Bastianelli ◽  
Magali Jouven

2000 ◽  
Vol 302 (1) ◽  
pp. 189-203 ◽  
Author(s):  
John R Cort ◽  
Adelinda Yee ◽  
Aled M Edwards ◽  
Cheryl H Arrowsmith ◽  
Michael A Kennedy

Author(s):  
Jan Willem Gorter ◽  
Peter L Rosenbaum ◽  
Steven E Hanna ◽  
Robert J Palisano ◽  
Doreen J Bartlett ◽  
...  

2013 ◽  
Vol 411-414 ◽  
pp. 1362-1367 ◽  
Author(s):  
Qing Lan Wei ◽  
Yuan Zhang

This paper presents the thoughts about application of saliency map to the video objective quality evaluation system. It computes the SMSE and SPSNR values as the objective assessment scores according to the saliency map, and compares with conditional objective evaluation methods as PSNR and MSE. Experimental results demonstrate that this method can well fit the subjective assessment results.


Mekatronika ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. 1-12
Author(s):  
Muhammad Nur Aiman Shapiee ◽  
Muhammad Ar Rahim Ibrahim ◽  
Muhammad Amirul Abdullah ◽  
Rabiu Muazu Musa ◽  
Noor Azuan Abu Osman ◽  
...  

The skateboarding scene has arrived at new statures, particularly with its first appearance at the now delayed Tokyo Summer Olympic Games. Hence, attributable to the size of the game in such competitive games, progressed creative appraisal approaches have progressively increased due consideration by pertinent partners, particularly with the enthusiasm of a more goal-based assessment. This study purposes for classifying skateboarding tricks, specifically Frontside 180, Kickflip, Ollie, Nollie Front Shove-it, and Pop Shove-it over the integration of image processing, Trasnfer Learning (TL) to feature extraction enhanced with tradisional Machine Learning (ML) classifier. A male skateboarder performed five tricks every sort of trick consistently and the YI Action camera captured the movement by a range of 1.26 m. Then, the image dataset were features built and extricated by means of  three TL models, and afterward in this manner arranged to utilize by k-Nearest Neighbor (k-NN) classifier. The perception via the initial experiments showed, the MobileNet, NASNetMobile, and NASNetLarge coupled with optimized k-NN classifiers attain a classification accuracy (CA) of 95%, 92% and 90%, respectively on the test dataset. Besides, the result evident from the robustness evaluation showed the MobileNet+k-NN pipeline is more robust as it could provide a decent average CA than other pipelines. It would be demonstrated that the suggested study could characterize the skateboard tricks sufficiently and could, over the long haul, uphold judges decided for giving progressively objective-based decision.


2018 ◽  
Vol 33 (3) ◽  
pp. 3784-3794 ◽  
Author(s):  
Qian Shi ◽  
Fei Zhuang ◽  
Ji-Ting Liu ◽  
Na Li ◽  
Yuan-Xiu Chen ◽  
...  

1997 ◽  
Vol 8 (S3) ◽  
pp. 273-279 ◽  
Author(s):  
Eric D. Caine

Establishing a medical diagnosis serves two utilitarian purposes: providing information necessary to initiate treatment and communicating information regarding prognosis. A nosology or diagnostic nomenclature (i.e., a classification of diagnoses) provides further utility by establishing a foundation for clinical research. In his book, Wulff outlined four types of diagnoses: (1) symptomatic or pseudoanatomic diagnoses (e.g., chronic headache, persistent diarrhea, or irritable bowel); (2) syndromes; (3) anatomic diagnoses; and (4) causal diagnoses. By definition, syndromes have no means of being validated by measures external to the constructs themselves. Often, specific syndromes reflect diverse origins, and conversely, specific etiologies may cause multiple syndromes (e.g., syphilis, human immunodeficiency virus, and diabetes).


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