Search Results - Sensors
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Agility in handball: Position- and age-specific insights in performance and kinematics using proximity and wearable inertial sensors
Heuvelmans, P., Gokeler, A., Benjaminse, A., Baumeister, J., Büchel, D.Published in Sensors (2025)Subjects: “…Sensor…”
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Understanding acceleration-based load metrics: from concepts to implementation
Freitas, J., Moreira, A., Carvalho, J., Conceição, F., Estriga, L.Published in Sensors (2025)Subjects: “…Sensor…”
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Evaluating external load responses to cumulative playing time and position in the European Handball Federation Women`s Euro 2022 through an IoT and Big Data architecture approach
Karcher, C., Font, R., Marcos-Jorquera, D., Gilart-Iglesias, V., Manchado, C.Published in Biology of Sport (2025)“…The study employed a cutting-edge computational framework integrating sensor network technologies, Local Positioning Systems (LPS), and Big Data Analytics within a descriptive analytics methodology. …”
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The burdens of sitting on the bench - comparison of absolute and relative match physical load between handball players with high and low court time and implications for compensator...
Büchel, D., Döring, M., Baumeister, J.Published in Journal of Sports Sciences (2024)“…Activity of all players competing in the 2021/2022 Bundesliga (Germany) was tracked using Kinexon LPS sensors. Gaps in physical load were quantified comparing the 25% of appearances with the highest (HIGH; 51.8 ± 5.2 mins) and lowest court times (LOW; 10.1 ± 4.3 mins). …”
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Monitoring external load during real competition in male handball players through big data analytics: Differences by playing positions
Manchado, C., Tortosa-Martinez, J., Marcos-Jorquera, D., Gilart-Iglesias, V., Pueo, B., Chirosa-Rios, L. J.Published in Kinesiology (2024)“…A system based on three phases was designed: 1) information capture of game events through sensor networks, LPS system and WebScraping techniques; 2) information processing based on Big Data Analytics; 3) extraction of results based on a descriptive analytics approach. …”
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Worst-case scenario analysis of physical demands in elite men handball players by playing position through big data analytics
Cartón-Llorente, A., Lozano, D., Iglisias, V. G., Jorquera, D. M., Manchado, C.Published in Biology of Sport (2023)“…A systematic three-phase analysis process was designed: 1) information capture of match activities and context through sensor networks, the LPS system, and WebScraping techniques; 2) information processing based on big data analytics; 3) extraction of results based on a descriptive analytics approach. …”
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Physical match demands of four LIQUI-MOLY Handball-Bundesliga teams from 2019-2022: effects of season, team, match outcome, playing position, and halftime
Saal, C., Baumgart, C., Wegener, F., Ackermann, N., Sölter, F., Hoppe, M. W.Published in Frontiers in Sports and Active Living (2023)Subjects: “…Sensor…”
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Analysis of movement and activities of handball players using deep neural networks
Host, K., Pobar, M., Ivasic-Kos, M.Published in Journal of Imaging (2023)“…The aim of the paper is to explore the computer vision-based solutions for recognizing player actions that can be applied in unconstrained handball scenes with no additional sensors and with modest requirements, allowing a broader adoption of computer vision applications in both professional and amateur settings. …”
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Chronic and acute effects on skin temperature from a sport consisting of repetitive impacts from hitting a ball with the hands
Sánchez-Jiménez, J. L., Tejero-Pastor, R., Calzadillas-Valles, M. d. C., Jimenez-Perez, I., Cibrián Ortiz de Anda, R. M., Salvador-Palmer, R., Priego-Quesada, J. I.Published in Sensors (2022)“…Sensors…”
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External load analysis in beach handball using a local positioning system and inertial measurement units
Müller, C., Willberg, C., Reichert, L., Zentgraf, K.Published in Sensors (2022)Subjects: “…Sensor…”
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