, , ,
Volume 10, Issue 4 (10-2012)
Abstract
Abstract
Identification of one karateka pave the way to reach the top honor. One of the
parameters affecting at success of kumite players is The performance velocity
of techniques. The purpose of this study was to investigate the relationship
between anthropometric characteristics with the performance velocity of Gyakuzuki
technique in Elite female Karatekas. Thirty-one senior female kumite
competitors of the Sepahan Mobarakeh Foolad karate team participated in this
study. Somatotype and The anthropometric profile were measured. Also, The
performance velocity of techniques was evaluated using quintic software. The
findings showed that The mean somatotype of Karatekas was 3.9 - 4.8 – 3.1
(values for endomorph, mesomorph and ectomorph, respectively). The
Mesomorphic component strongly correlated with velocity of techniques Gyakuzuki.
While, The values height, sitting height and humorous bone length
negative correlated with velocity of technique Gyaku-zuki. The results indicated
that the somatotype and anthropometric characteristics influence on the
performance velocity of Gyaku-zuki technique
, , ,
Volume 12, Issue 8 (10-2014)
Abstract
As one of the most famous martial arts karate kata and kumite are two main ]1[. Different techniques when doing sports, including quadriceps muscles and joints (knee extensor muscles) and joint use. In this study, called the internal and external obliques broad kata and kumite athletes dominant leg when the two techniques were compared Znkutsudachi and Movashi Gray. Therefore, local and wide flat external obliques muscle activity during the two techniques in the dominant leg Karate Twenty healthy female elite athletes, (mean age 21/8) were recorded. After the onset of muscle activity was determined and the results of data processing using statistical techniques to design a mixed ANOVA between groups and within groups were examined. The results showed that flattened the internal oblique muscle Znkutsudachi techniques in kumite athletes Katakaran to be done first.
, , Elham Shirzad,
Volume 19, Issue 21 (9-2021)
Abstract
Despite the importance of talent for sports, but it has yet received little attention. The purpose of this study was to present a pattern design for talent identification in karate based on artificial intelligence algorithms. Subjects divided to adolescent elite karate athletes (n = 19) and non-karate athletes adolescent (n=20) by convenience sampling. Besed on previous literature, we selected and measured biomechanical and anthropometric variables. The normal distribution of all data was analyzed using Shapiro-Wilk test. Principal component Analysis (PCA) was performed to reduce the number of variables and identify the most important anthropometric and biomechanical variables. Then, for modeling, the neural network algorithm was used with three input layer (10 neurons), middle (7 neurons) and output (2 neurons). The results showed the most important anthropometric variables of adolescent elite karate athletes were thoracic subcutaneous fat, height, jump, static balance, grip strength, chest circumference, ankle circumference, abdominal subcutaneous fat and apparent length leg respectively. Also, percentage of correct classification and sensitive of data was high and 87% and 85% respectively. According to the results of this study, this method can be used for talent karate athletes along with other methods.