Research in Sport Medicine and Technology

Using appropriate devices and scientific methods can accelerate the process of sport talent identification and development to achieve championship level, and could also provide condition in which capable and talented athletes obtain highest level performance rapidly, so they will have long life championship. Former researches in scope of sport talent identification usually have been done in order to determine or normalize effective parameters. The purpose of this study was to design football talent identification algorithm based on fuzzy logic which classifies the football athletes. Due to expert opinion, essential parameters of football talent identification which also used in this software are; Cardio respiratory capacity (Physiology), Agility (Ability of motion), Dribble (technical skill) and Motivation (psychology). Norms of elite football player teenagers (14-16 yrs) are also used as index. Then with considering parameters and index, a fuzzy algorithm is designed which classifies football players in Unmatched, Semi-matched, Matched, Brilliant and Rare class. These results can help trainers and coaches in order to select talented and capable football players. In validation and reliability, records of elite junior Brazilian and Portuguese soccer have compared with norms of Iranian elite soccer.

The most commonly used empirical approach to address issues of attention constraint is evaluate the degree of interference in dual or multiple tasks. The purpose of this study was designing software to estimate the relative interference between multiple tasks and determine its validity in performance prediction of simultaneous multiple tasks. in order to assess the validity of software, 46 students with a driving certificate from East Tehran branch of Islamic Azad University were selected by available sampling method, the response time to the visual and auditory stimulus of participants during driving in different conditions was measured by using software and hardware installed on their cars, and then relative interference in the above mentioned conditions was estimated by using relative interference software. The result of pearson correlation analysis showed that there is a high, meaningful and direct correlation between the amount of estimated relative interference with the software and measured participants' response time in different driving conditions (r=0.95, p≤0.01). Therefore, the designed software can be used to predict the amount of interference between two or more simultaneous tasks.

Using appropriate devices and scientific methods by coaches and trainers can accelerate the process of sport talent identification and development, and could also provide condition in which capable athletes to be directed in to suitable sport according to their abilities and skills. Former researches in scope of sport talent identification usually have been done in order to determine or normalize effective parameters. The purpose of this study was to design volleyball talent identification algorithm based on fuzzy logic which ranks the volleyball athletes. Due to expert opinion, essential parameters of volleyball talent identification which also used in this software are; Height (Anthropometry), Velocity (Ability of motion), Vertical jump with run-up (technical skill) and Pair jump (functional skill). Norms of young elite volleyball players are also used as index. Then with considering parameters and index, a fuzzy algorithm is designed which classifies volleyball players in Unmatched, Semi-matched, Matched, Brilliant and Rare class. These results can help trainers and coaches in order to select talented and capable volleyball players.