CNN sensor based motion capture system application in basketball training and injury prevention.

Basketball is a high-intensity sport, and sports injuries often occur. Therefore, how to monitor the sports status of basketball players in real time, discover and prevent the occurrence of sports injuries in time, has become an urgent problem for athletes and coaches. In this paper, a motion capture system based on CNN sensor is proposed. Through the application of sensor, real-time monitoring of athletes' motion state, the system can collect athletes' movement track, speed, acceleration, stride frequency, heart rate, energy consumption and other parameters in real time. By analyzing the movement data, it can timely warn and deal with the occurrence of sports injuries. In this paper, convolutional neural network (CNN) is used to process and analyze motion data, so that the motion capture system has higher precision and accuracy. Through the training and optimization of CNN, the system can identify and analyze motion data more accurately, and improve the performance and effect of the motion capture system. The motion capture system based on CNN sensor can realize real-time monitoring and prevention of sports injuries for basketball players, provide more comprehensive, scientific and real-time sports data for athletes and coaches, help them better conduct training and adjust tactics, and improve the competitive level and safety of basketball games.

Sense of self-efficacy and the content of energy and nutrients in the diet of elite Polish basketball players.

Background: In research on the subject, the predictive importance of personal resources is indicated for diet quality. Objective: The aim of the study was quantitative assessment of diet depending on the level of generalised self- efficacy among elite Polish basketball players. Material and Methods: Food diaries (2 training days and 1 no training day) of 48 basketball players were analysed. Further assessed were 144 food rations based on the Diet 6.0 program, and the results were compared to the current Polish nutritional standards. The Generalised Self-Efficacy Scale (GSES) was also used. Statistical analyses were performed by estimating Spearman's rank correlation coefficients (p<0.05). Results: The share of energy from proteins, fats and carbohydrates was 18.2%, 29.4% and 52.4%, respectively. Of the mineral salts, the average diet contained: 2,107.6 mg sodium, 2,918.3 mg potassium, 736.3 mg calcium, 1,372.2 mg phosphorus, 380.1 mg magnesium, and 11.6 mg iron. Of the vitamins, the average diet contained: 1,100.3 µg of vitamin A, 5.3 µg of vitamin D, vitamin E in the amount of 8.2 mg, 78.1 mg of vitamin C, 1.1 mg vitamin B1, 1.3 mg vitamin B2, 1.9 mg of vitamin B6, 271.7 µg of vitamin B9 and 4.7 µg of vitamin B12. It was also shown that as the sense of self-efficacy developed, the supply of energy, water, protein, digestible carbohydrates, energy from carbohydrates, sucrose and PUFAs also increased in the players' diets. At the same time, along with the increase in self-efficacy, the supply of: Na, K, Ca, Mg, P, Fe, Cu and iodine as well as vitamins: A, E, B1, B3, B6 and C, also increased in the players' diets. Conclusions: Incomplete diet balance has been demonstrated, as well as significant relationships between the level of self-efficacy and the supply of certain nutrients in the diet of elite Polish basketball players. The obtained results indicate the legitimacy of diet monitoring and nutritional education as well as considering personality traits in activities promoting maintaining a proper diet among athletes.

Technical-tactical profile, perceived exertion, mental demands and enjoyment of different tactical tasks and training regimes in basketball small-sided games.

This study aimed to evaluate the technical-tactical, perceptual and mental demands of basketball small-sided games (SSGs). Twelve male semi-professional players participated in four half-court 3vs3 SSGs characterized by different tactical tasks (offensive; defensive) and training regimes (long-intermittent; short-intermittent). The SSGs were video-recorded to perform notational analysis of technical-tactical parameters. Ratings of perceived exertion (RPE, CR-100 scale), mental effort (ME) and e njoyment were collected after completion of each SSG. Before and after the SSGs, players reported their perceived mental fatigue (MF); for this indicator, the difference between post- and pre-SSG values was calculated (ΔMF). Notational analysis evidenced a higher volume of play (ball possessions, ball possessions per minute) [large effect size (ES)], dribbles and shot attempts (moderate ES) in short-intermittent regimes compared to long-intermittent. Two-way (tactical task; training regime) repeated-measures ANOVA showed an interaction effect for RPE (moderate ES). Players reported that playing the offensive task required higher mental effort compared to playing defence (moderate ES), while no differences for mental effort were found between regimes. Enjoyment did not differ between tasks or regimes. No effects were found for ΔMF, while this indicator was significantly correlated with RPE scores (r= 0.50, large). This study suggests that, in basketball SSGs, shorter regimes induce higher technical demands, while tactical tasks influence perceived exertion responses and mental effort. Furthermore, perceived exertion appears significantly associated with variations of mental fatigue induced by training drills.

Effect of different number of players and training regimes on physiological and technical demands of ball-drills in basketball.

This study aimed to analyse the effects of two factors (number of players and training regimes) on players' physiological and technical demands in basketball ball-drills. Twenty-one young basketball players performed four different ball-drills (two levels for each factor). The number of players involved was 2vs2 and 4vs4, while ball-drill regimes were continuous and intermittent. Physiological demand was assessed using the percentage of maximal heart rate (%HRmax), Edwards' training load and rating of perceived exertion (RPE). Furthermore, the following technical actions were collected: dribbles, steals, rebounds, turnovers, passes (total, correct, wrong and % of correct pass) and shots (total, scored, missed and % of made shot). A 2 × 2 (number of players × regime) two-way ANOVA with repeated measures was applied for physiological parameters and technical actions. The 2vs2 condition showed higher %HRmax (P < 0.001), Edwards' training load (P < 0.001), RPE (P < 0.001), number of dribbles (P < 0.001), rebounds (P < 0.001), passes [total (P = 0.005) and correct (P = 0.005)] and shots [total (P < 0.001) scored (P < 0.001) and missed (P < 0.001)] than 4vs4. Moreover, the continuous regime revealed higher %HRmax (P < 0.001), Edwards' training load (P < 0.001), RPE (P = 0.006) and dribbles (P < 0.001) than the intermittent regime. This study showed that both number of players and regime are useful variables able to modify basketball ball-drills workload.

Artificial Intelligence Technology in Basketball Training Action Recognition.

The primary research purpose lies in studying the intelligent detection of movements in basketball training through artificial intelligence (AI) technology. Primarily, the theory of somatosensory gesture recognition is analyzed, which lays a theoretical foundation for research. Then, the collected signal is denoised and normalized to ensure that the obtained signal data will not be distorted. Finally, the four algorithms, decision tree (DT), naive Bayes (NB), support vector machine (SVM), and artificial neural network (ANN), are used to detect the data of athletes' different limb movements and recall. The accuracy of the data is compared and analyzed. Experiments show that the back propagation (BP) ANN algorithm has the best action recognition effect among the four algorithms. In basketball training athletes' upper limb movement detection, the average accuracy rate is close to 93.3%, and the average recall is also immediate to 93.3%. In basketball training athletes' lower limb movement detection, the average accuracy rate is close to 99.4%, and the average recall is immediate to 99.4%. In the detection of movements of upper and lower limbs: the recognition method can efficiently recognize the basketball actions of catching, passing, dribbling, and shooting, the recognition rate is over 95%, and the average accuracy of the four training actions of catching, passing, dribbling, and shooting is close to 98.95%. The intelligent basketball training system studied will help basketball coaches grasp the skilled movements of athletes better to make more efficient training programs and help athletes improve their skill level.

Defensive Strategy and Player Sex Impact Heart-Rate Responses During Games-Based Drills in Professional Basketball.

PURPOSE: Games-based drills (GBD) are the predominant form of training stimulus prescribed to male and female basketball players. Despite being readily manipulated during GBD, the impact of defensive strategy on the sex-specific demands of GBD remains unknown. Therefore, the aim of this study was to quantify and compare the heart-rate (HR) responses experienced during 5v5 GBD using different defensive strategies (man-to-man defense vs zone defense [ZD] formations) according to player sex. METHOD: HR was recorded in 11 professional male and 10 professional female basketball players while performing 5v5 GBD with different defensive strategies (man-to-man defense or ZD). HR-based training load was also calculated using the summated heart-rate zones model. RESULTS: During man-to-man defense, mean HR (ηp2=.02), relative time (in percentage) spent working at 90% to 100% maximal HR (ηp2=.03), and summated heart-rate zones (ηp2=.02) were greater (P < .05) in female players compared with males. During ZD, higher (P < .01) peak HR (ηp2=.07), mean HR (ηp2=.11), relative and absolute (in minutes) time spent working at 80% to 89% maximal HR (ηp2=.03 and .03, respectively) and 90% to 100% maximal HR (ηp2=.12 and .09, respectively), and summated heart-rate zones (ηp2=.19) were observed in female players compared with males. CONCLUSIONS: The defensive strategy employed during 5v5 full-court GBD influences HR responses and training load differently according to sex, where female players experience higher HR responses than males, especially when ZD are adopted. Basketball coaching staff can use these findings for the precise manipulation of team defenses during GBD to elicit desired cardiovascular stress on players.

Adoption of Machine Learning Algorithm-Based Intelligent Basketball Training Robot in Athlete Injury Prevention.

In order to effectively prevent sports injuries caused by collisions in basketball training, realize efficient shooting, and reduce collisions, the machine learning algorithm was applied to intelligent robot for path planning in this study. First of all, combined with the basketball motion trajectory model, the sport recognition in basketball training was analyzed. Second, the mathematical model of the basketball motion trajectory of the shooting motion was established, and the factors affecting the shooting were analyzed. Thirdly, on this basis, the machine learning-based improved Q-Learning algorithm was proposed, the path planning of the moving robot was realized, and the obstacle avoidance behavior was accomplished effectively. In the path planning, the principle of fuzzy controller was applied, and the obstacle ultrasonic signals acquired around the robot were taken as input to effectively avoid obstacles. Finally, the robot was able to approach the target point while avoiding obstacles. The results of simulation experiment show that the obstacle avoidance path obtained by the improved Q-Learning algorithm is flatter, indicating that the algorithm is more suitable for the obstacle avoidance of the robot. Besides, it only takes about 250 s for the robot to find the obstacle avoidance path to the target state for the first time, which is far lower than the 700 s of the previous original algorithm. As a result, the fuzzy controller applied to the basketball robot can effectively avoid the obstacles in the robot movement process, and the motion trajectory curve obtained is relatively smooth. Therefore, the proposed machine learning algorithm has favorable obstacle avoidance effect when it is applied to path planning in basketball training, and can effectively prevent sports injuries in basketball activities.

Physical and physiological demands and hormonal responses in basketball small-sided games with different tactical tasks and training regimes.

OBJECTIVES: To evaluate external and internal training load (TL) and hormonal responses in basketball 3-versus-3 small-sided games (SSGs). DESIGN: Randomized repeated-measures study. METHODS: Twelve male basketball players participated to four 3-versus-3 SSGs characterized by different tactical tasks (offensive; defensive) and training regimes (long-intermittent: three 4-min bouts with 2' rest in between; short-intermittent: six 2-min bouts with 1' rest in between). Variables measured were: PlayerLoad (PL); percentage of maximal heart rate (%HRmax); Edwards' TL. Before and after the SSGs, saliva samples were collected to measure cortisol (C) and testosterone (T). Two-way (task; regime) repeated-measures ANOVA was performed for PL and %HRmax; C concentrations were analysed with a three-way (task; regime; time: pre/post) repeated-measures ANOVA; non-parametric analyses were performed for Edwards' TL and T. RESULTS: PL was moderately higher in offensive task (148.0±16.8 AU) compared to defensive (137.1±15.5 AU), and short regime (147.0±18.2 AU) compared to long (137.9±14.6 AU). %HRmax was moderately higher in offensive task (91.1±4.1%) compared to defensive: (88.7±5.4%), while it did not differ between regimes (long: 90.0±5.6%) (short: 89.8±4.2%); additionally, an interaction (task*regime) effect was found (ES: strong). Edwards' TL was moderately higher in offense-long SSG (56.6+2.4 AU) compared to defense-short (52.4+4.4 AU). C increased after the SSGs (ES: strong). T decreased after offense-short (ES: moderate) and increased after defense-long (ES: moderate) SSGs. CONCLUSIONS: Tactical tasks and training regimes influence external and internal demands of basketball SSGs. Steroid hormones respond in SSGs.

Effect of Number of Players and Maturity on Ball-Drills Training Load in Youth Basketball.

This study aimed to assess the basketball ball-drills workload analyzing: (1) the effect of varying the number of players involved on physiological and technical demands; (2) the temporal changes in players' responses across bouts; and (3) the relationship of players' workload with their maturation status and training age. Twelve young male basketball players (mean ± SD; age 13.9 ± 0.7 years; height 1.76 ± 0.06 m; body mass 65.7 ± 12.5 kg; HRmax 202 ± 8 beat·min-1) completed three bouts of 4 min interspersed by 2 min of passive recovery of two vs. two and four vs. four ball-drills. The mean percentage of HRmax (%HRmax) and ratings of perceived exertion (RPE) were collected. Technical actions (TAs) (dribbles, passes, shots, interceptions, steals, rebounds, and turnovers) were calculated through notational analysis. Players' genitalia development (GD) and pubic hair (PH) growth were assessed using Tanner scale. Results showed a higher %HRmax (p = 0.018), RPE (p = 0.042), dribbles (p = 0.007), shots (p = 0.003), and rebounds (p = 0.006) in two vs. two compared to four vs. four condition. Furthermore, a statistical difference was found for %HRmax (p = 0.005) and number of passes (p = 0.020) between bouts. In addition, no correlation between GD, PH, and training age with %HRmax, RPE, and TAs was found. These findings suggest that variations of the number of players involved affect ball-drills workload and that ball-drills training intensity varies across bouts. Finally, ball-drills elicit an adequate training stimulus, regardless of players' maturation status and training age.

The Reasearch on the Anti-Fatigue Effect of Whey Protein Powder in Basketball Training.

In order to observe the effects of whey protein powder on hematological indexes of players majoring in physical education in the basketball training, the authors divided the players randomly into a control group and a nutrition group. Athletes complete the 30 minutes quantitative exercise using cycle ergometer respectively before the trial and after one month trial. Then we exsanguinated immediately after exercise, extracted heparin and measured hemoglobin, red blood cell count, hematocrit and mean corpuscular volume and other hematological indices. The results showed that after taking whey protein powder, the HB, RBC, HCT of nutrition group was significantly higher that the control group. This suggests that in high-intensity training, taking whey protein powder can cause changes of HB, RBC and HCT in human body, meanwhile MCV essentially the same. So whey protein powder can improve exercise capacity, and has anti-fatigue effect.