Abdel-Rahman Akl

Bio: Abdel-Rahman Akl is an academic researcher from Alexandria University. The author has contributed to research in topics: Preferred walking speed & Throwing. The author has an hindex of 3, co-authored 13 publications receiving 38 citations. Previous affiliations of Abdel-Rahman Akl include University of Vienna.

Relationship between reaction time and deception type during smash in badminton

Abstract: The purpose of the present study was to determine the relationship between reaction time and deception type and investigate the effect of deception type on reaction time during smash in Badminton. Six Badminton players are high level athletes in the world participated in the last Olympic championship "London 2012", (mass 69.17±6.31 kg, length 178.00±0.06 cm. Reaction time is defined as the period of time that elapses between offensive player stroke the shuttle and opponent player move to shuttle direction. Smashes were analyzed of the last six matches in Olympic championship London 2012, two matches in Quarter-finals, two matches of Semi-finals, Bronze Medal Match and Gold Medal Match. Dartfish v.7 software motion analysis used to analysis 230 smashes and for the statistical analysis of the data the IBM SPSS Statistics 21 was used. The complex deception is more difficult types of deception for the opponents as the player use more than a tool during the striking and then the degree of difficulty followed by arm deception, while the performance of the smashes without deception gives a greater opportunity for an opponent to anticipate the strike and then stopped, and this means that the increase the degree of difficulty of deception increased the time of reaction necessary to repel the strike, thereby increasing the opportunity to make the point, therefore must specify a part in the content of the training programs for the smashes combined with different types of deception.

Predicting Wins, Losses and Attributes' Sensitivities in the Soccer World Cup 2018 Using Neural Network Analysis.

Abstract: Predicting the results of soccer competitions and the contributions of match attributes, in particular, has gained popularity in recent years. Big data processing obtained from different sensors, cameras and analysis systems needs modern tools that can provide a deep understanding of the relationship between this huge amount of data produced by sensors and cameras, both linear and non-linear data. Using data mining tools does not appear sufficient to provide a deep understanding of the relationship between the match attributes and results and how to predict or optimize the results based upon performance variables. This study aimed to suggest a different approach to predict wins, losses and attributes' sensitivities which enables the prediction of match results based on the most sensitive attributes that affect it as a second step. A radial basis function neural network model has successfully weighted the effectiveness of all match attributes and classified the team results into the target groups as a win or loss. The neural network model's output demonstrated a correct percentage of win and loss of 83.3% and 72.7% respectively, with a low Root Mean Square training error of 2.9% and testing error of 0.37%. Out of 75 match attributes, 19 were identified as powerful predictors of success. The most powerful respectively were: the Total Team Medium Pass Attempted (MBA) 100%; the Distance Covered Team Average in zone 3 (15-20 km/h; Zone3_TA) 99%; the Team Average ball delivery into the attacking third of the field (TA_DAT) 80.9%; the Total Team Covered Distance without Ball Possession (Not in_Poss_TT) 76.8%; and the Average Distance Covered by Team (Game TA) 75.1%. Therefore, the novel radial based function neural network model can be employed by sports scientists to adapt training, tactics and opposition analysis to improve performance.

The Role of Biomechanical Parameters and Muscle Activity during Eccentric and Concentric Contractions in Vertical Jump Performance

Abstract: (ProQuest: ... denotes formula omitted.)IntroductionMany studies investigated the performance of vertical jump in its different types, especially from the biomechanical performance considering that the performance of the vertical jump is subject to the laws of projectiles because the body loses contact with the ground and moves to the upward of reverse gravity, and based on the force gained by the result of the ground reaction force and how to take advantage of all the natural factors (physical laws) and physical abilities and skills to be determined vertical jump height and which reflects a player's ability to perform the highest high and then achieve many of the objectives and results in skills and various sports activities.The vertical jump is very important in sports. A high vertical jump contributes to successful athletic performance, particularly in sports such as basketball, volleyball, and football (Bobbert and van Ingen Schenau, 1988; Pandy and Zajac, 1991; Van Soest et al., 1993). And hopping, jumping, and running are considered as most typical forms of SSC (Komi and Nicol, 2011). In many sporting movements, the muscles contract in a stretch-shortening cycle (SSC) sequence, whereby the concentric contraction phase is immediately preceded by an eccentric contraction phase (active pre-stretch) (Ettema et al., 1990). Countermovement jumps (CMJ) are also SSC actions, because they include the sequence of stretch and shortening (Komi and Nicol, 2011). The combination of eccentric and concentric actions forms a natural type of muscle function called the stretchshortening cycle or SSC (Norman and Komi, 1979; Komi, 1984; Komi and Nicol, 2000; Komi, 2000).Studies of the neuromuscular system often employ recordings of the electrical activity of skeletal muscle. These electromyographic recordings may be of electrical signals detected within a muscle via needle or wire electrodes or from the surface of the skin via surface electrodes. Surface electromyography (EMG) is frequently used to estimate the amount of muscle activation required for specific tasks (Soderberg and Cook, 1983; Veiersted et al., 1990), and to examine changes in muscle activation as a result of training (Narici et al., 1989). Despite the fact that performance improvement is attributed mainly to neural factors, few researchers evaluated simultaneously the changes in performance with the changes in muscle activation using surface electromyography (EMG) (Jones and Lees, 2003). Generally the EMG signal variables related to the amplitude of the electrical activity (root mean square, i.e. RMS or integrated EMG, i.e. IEMG) is quantified as activity level (Ozgunen et al., 2010).In a vertical jump, there are two ways to propel the body's center of mass (CM) upward: a countermovement jump (CMJ) and a so-called squat jump (SJ). In a CMJ, people start from an upright position and initiate downward movement before starting to move upward, while in a SJ they start from a squatted (or semi squatted) position without a preparatory countermovement. It is well known that CMJ are generally 2-4 cm higher than SJs as a result of the stored elastic energy (Komi and Bosco, 1978), stretch reflexes (Viitasalo and Bosco, 1982), and the active states of the muscles (Bobbert and Casius, 2005).The time history of the vertical ground reaction force (GRF) of a CMJ decreases below body weight during eccentric contraction phase in the counter movement and rises to a few times body weight in the concentric contraction phase (Fukashiro and Komi, 1987; Hubley and Wells, 1983; Vanezis and Lees, 2005).And some views indicate that it may be beneficial to increase the range of motion of the stretching phase and decrease the range of motion of the shortening phase, in many complex movements this is not possible as an increase in the joint range of stretching tends to result in an increase in the range of shortening (Moran and Wallace, 2007), they depend to the previous studies results, (1) the magnitude of enhancement in mechanical output of the concentric contraction phase is greater with an increase in eccentric loading (Bober et al. …

Muscle Co-Activation around the Knee during Different Walking Speeds in Healthy Females.

Abstract: The purpose of this study was to examine the changes in co-activation around the knee joint during different walking speeds in healthy females using the co-activation index. Ten healthy females (age: 21.20 ± 7.21 years, height: 164.00 ± 4.00 cm, mass: 60.60 ± 4.99 kg) participated in this study and performed three walking speeds (slow, normal, and fast). A Qualisys 11-camera motion analysis system sampling at a frequency of 200 Hz was synchronized with a Trigno EMG Wireless system operating at a 2000 Hz sampling frequency. A significant decrease in the co-activation index of thigh muscles was observed between the slow and fast, and between the normal and fast, walking speeds during all walking phases. A non-significant difference was observed between the slow and normal walking speeds during most walking phases, except the second double support phase, during which the difference was significant. A negative relationship was found between walking speed and the co-activation index of thigh muscles in all speeds during walking phases: first double support (r = -0.3386, p < 0.001), single support (r = -0.2144, p < 0.01), second double support (r = -0.4949, p < 0.001), and Swing (r = -0.1639, p < 0.05). In conclusion, the results indicated high variability of thigh muscle co-activation in healthy females during the different walking speeds, and a decrease in the co-activation of the thigh muscles with the increase of speed.

The Influence of X-Factor (Trunk Rotation) and Experience on the Quality of the Badminton Forehand Smash

Abstract: No existing studies of badminton technique have used full-body biomechanical modeling based on three-dimensional (3D) motion capture to quantify the kinematics of the sport. The purposes of the current study were to: 1) quantitatively describe kinematic characteristics of the forehand smash using a 15-segment, full-body biomechanical model, 2) examine and compare kinematic differences between novice and skilled players with a focus on trunk rotation (the X-factor), and 3) through this comparison, identify principal parameters that contributed to the quality of the skill. Together, these findings have the potential to assist coaches and players in the teaching and learning of the forehand smash. Twenty-four participants were divided into two groups (novice, n = 10 and skilled, n = 14). A 10-camera VICON MX40 motion capture system (200 frames/s) was used to quantify full-body kinematics, racket movement and the flight of the shuttlecock. Results confirmed that skilled players utilized more trunk rotation than novices. In two ways, trunk rotation (the X-factor) was shown to be vital for maximizing the release speed of the shuttlecock - an important measure of the quality of the forehand smash. First, more trunk rotation invoked greater lengthening in the pectoralis major (PM) during the preparation phase of the stroke which helped generate an explosive muscle contraction. Second, larger range of motion (ROM) induced by trunk rotation facilitated a whip-like (proximal to distal) control sequence among the body segments responsible for increasing racket speed. These results suggest that training intended to increase the efficacy of this skill needs to focus on how the X-factor is incorporated into the kinematic chain of the arm and the racket.

Unsupervised Pattern Recognition of Physical Fitness Related Performance Parameters among Terengganu Youth Female Field Hockey Players

Abstract: This study aims to identify the most significant physical fitness parameters among youth female Terengganu field hockey players. Multivariate methods of unsupervised pattern recognition of principal component analysis (PCA) and descriptive statistic were used to determine the most significant physical fitness related performance parameters on 42 Terengganu youth female field hockey players. The first PC’s projected high factor loading in BMI (0.86) and predicted VO2max (-0.82) as the most significant parameters indicating the requirements of body composition in this sport. The second PC’s displayed high factor loading in 1-minute sit up (0.89) and 20-meter speed (-0.84) highlighting the need for core muscle strength. The third PC’s demonstrated high factor loading in V-sit and reach (0.71) and maximum push up (0.82) recognising the importance of upper muscle strength in the sport. The results from the current study revealed that certain physical fitness components are seemed to be more pronounced in the performance of the game by the Terengganu female youth hockey players. The study has indicated that body composition, core muscle strength and upper muscle strength are the most outstanding physical fitness variables possess by the players for the enactment of the game compared to other fitness parameters. Highlighting the physical fitness performance related parameters might help to evaluate the strength and weakness of the players on the relevant parameters which could prompt to the adjustment of the training programme for the inclusive improvement of the players.

Machine learning-based identification of the strongest predictive variables of winning and losing in Belgian professional soccer

Abstract: This study aimed to identify the strongest predictive variables of winning and losing in the highest Belgian soccer division. A predictive machine learning model based on a broad range of variables (n = 100) was constructed, using a dataset consisting of 576 games. To avoid multicollinearity and reduce dimensionality, Variance Inflation Factor (threshold of 5) and BorutaShap were respectively applied. A total of 13 variables remained and were used to predict winning or losing using Extreme Gradient Boosting. TreeExplainer was applied to determine feature importance on a global and local level. The model showed an accuracy of 89.6% ± 3.1% (precision: 88.9%; recall: 90.1%, f1-score: 89.5%), correctly classifying 516 out of 576 games. Shots on target from the attacking penalty box showed to be the best predictor. Several physical indicators are amongst the best predictors, as well as contextual variables such as ELO -ratings, added transfers value of the benched players and match location. The results show the added value of the inclusion of a broad spectrum of variables when predicting and evaluating game outcomes. Similar modelling approaches can be used by clubs to identify the strongest predictive variables for their leagues, and evaluate and improve their current quantitative analyses.

Relationship between reaction time and deception type during smash in badminton

Abstract: The purpose of the present study was to determine the relationship between reaction time and deception type and investigate the effect of deception type on reaction time during smash in Badminton. Six Badminton players are high level athletes in the world participated in the last Olympic championship "London 2012", (mass 69.17±6.31 kg, length 178.00±0.06 cm. Reaction time is defined as the period of time that elapses between offensive player stroke the shuttle and opponent player move to shuttle direction. Smashes were analyzed of the last six matches in Olympic championship London 2012, two matches in Quarter-finals, two matches of Semi-finals, Bronze Medal Match and Gold Medal Match. Dartfish v.7 software motion analysis used to analysis 230 smashes and for the statistical analysis of the data the IBM SPSS Statistics 21 was used. The complex deception is more difficult types of deception for the opponents as the player use more than a tool during the striking and then the degree of difficulty followed by arm deception, while the performance of the smashes without deception gives a greater opportunity for an opponent to anticipate the strike and then stopped, and this means that the increase the degree of difficulty of deception increased the time of reaction necessary to repel the strike, thereby increasing the opportunity to make the point, therefore must specify a part in the content of the training programs for the smashes combined with different types of deception.

A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions

Abstract: Recent developments in video analysis of sports and computer vision techniques have achieved significant improvements to enable a variety of critical operations. To provide enhanced information, such as detailed complex analysis in sports like soccer, basketball, cricket, badminton, etc., studies have focused mainly on computer vision techniques employed to carry out different tasks. This paper presents a comprehensive review of sports video analysis for various applications: high-level analysis such as detection and classification of players, tracking player or ball in sports and predicting the trajectories of player or ball, recognizing the team‟s strategies, classifying various events in sports. The paper further discusses published works in a variety of application-specific tasks related to sports and the present researcher‟s views regarding them. Since there is a wide research scope in sports for deploying computer vision techniques in various sports, some of the publicly available datasets related to a particular sport have been provided. This work reviews a detailed discussion on some of the artificial intelligence (AI) applications in sports vision, GPU-based work stations, and embedded platforms. Finally, this review identifies the research directions, probable challenges, and future trends in the area of visual recognition in sports.