Results 81 to 90 of about 294 (105)

Properties of Gaze Strategies Based on Eye-Head Coordination in a Ball-Catching Task. [PDF]

Vision (Basel)
Ono S, Yoshimura Y, Shinkai R, Kizuka T.
europepmc   +1 more source

The Contact Conundrum: Are We Introducing Contact at the Correct Time in Youth Sports? [PDF]

Sports Med
West SW, Hendricks S, Cumming SP, Dane K, O'Connor S, Jones B, Patterson B, Kolstad AT, Broglio S, Emery CA, McKay CD.   +10 more
europepmc   +1 more source

Quantitative analysis and evaluation of research on the application of computer vision in sports since the 21st century. [PDF]

Front Sports Act Living
Chen C, Xue J, Gou W, Xie M, Yao X.
europepmc   +1 more source

E-Textiles for Sports and Fitness Sensing: Current State, Challenges, and Future Opportunities. [PDF]

Sensors (Basel)
Yang K, McErlain-Naylor SA, Isaia B, Callaway A, Beeby S.   +4 more
europepmc   +1 more source

Physical and Psychosocial Benefits of Sports Participation Among Children and Adolescents with Chronic Diseases: A Systematic Review. [PDF]

Sports Med Open
Sañudo B, Sánchez-Oliver AJ, Fernández-Gavira J, Gaser D, Stöcker N, Peralta M, Marques A, Papakonstantinou S, Nicolini C, Sitzberger C.   +9 more
europepmc   +1 more source

Analysis of Machine Learning-Based Investigation Into Multivariate Factors of Team Performance in Serious Games: Cross-Sectional Retrospective Study. [PDF]

JMIR Serious Games
Abdul-Rahman GG, de Lange F, Zwitter A, Haleem N.   +3 more
europepmc   +1 more source

Predicting sport event outcomes using deep learning. [PDF]

PeerJ Comput Sci
Gao J, Cheng Y, Gao J.
europepmc   +1 more source

Cloud-to-Thing continuum-based sports monitoring system using machine learning and deep learning model. [PDF]

PeerJ Comput Sci
Alshardan A, Mahgoub H, Alahmari S, Alonazi M, Marzouk R, Mohamed A.   +5 more
europepmc   +1 more source

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Identification of key performance parameters during off-spin bowling with a smart cricket ball

Sports Technology, 2011
A smart cricket ball, instrumented with three high-speed MEMS gyroscopes, was used to measure performance parameters during off-spin bowling. The average spin rate and finger torque generated by the bowler were 22.7 rps and 0.28 N·m, respectively. The arm motion could be clearly identified on the spin-axis vector diagram. The spin-axis vector described
Franz Konstantin Fuss, Noel Lythgo, Amanda C Benson   +2 more
exaly   +3 more sources