Estimation and validation of spatio-temporal parameters for sprint running using a radio-based tracking system

Seidl, Thomas; Linke, Daniel; Lames, Martin

doi:10.1016/j.jbiomech.2017.10.003

Cited by 8 publications

(8 citation statements)

References 17 publications

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“…Figure 1 shows the attachment of transmitters on the athletes' backs in a pocket of a compression shirt. For a more detailed description of the RedFIR system and the generated data streams see Grün et al ( 2011 ), Mutschler et al ( 2013 ), and Seidl et al ( 2017 ).…”

Section: Methodsmentioning

confidence: 99%

“…The RedFIR system as such has been validated before in a sprint-specific study (Seidl et al, 2017 ). To assess the validity of derived top speed parameters based on the proposed method we conducted additional validation experiments in the same location by simultaneously recording 100 m-sprints with RedFIR and criterion systems for horizontal speed (Laveg −13 runs) and step parameters (OptoGait −23 runs).…”

Section: Methodsmentioning

confidence: 99%

“…OptoGait is often used as criterion system for evaluation studies in sprinting (Gindre et al, 2016 ; Schmidt et al, 2016 ). For more details on the validation setting see Seidl et al ( 2017 ). Mean step length and step time estimates within the TSI based on RedFIR data were compared to criterion measurements captured by the OptoGait system.…”

Section: Methodsmentioning

confidence: 99%

“…However, due to the development of new tracking technologies with high spatial and temporal resolution (Sathyan et al, 2012 ; Seidl et al, 2016 , 2017 ), like the radio-based tracking system RedFIR, (Grün et al, 2011 ) the analysis of sprint parameters in field settings has come into reach. As tracking systems are designed for routine analyses on training and competition sites they represent an excellent prospect for innovative contributions to sprint analysis and training.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Assessment of Sprint Parameters in Top Speed Interval in 100 m Sprint—A Pilot Study Under Field Conditions

Seidl¹,

Russomanno²,

Stöckl³

et al. 2021

Front. Sports Act. Living

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Improving performances in sprinting requires feedback on sprint parameters such as step length and step time. However, these parameters from the top speed interval (TSI) are difficult to collect in a competition setting. Recent advances in tracking technology allows to provide positional data with high spatio-temporal resolution. This pilot study, therefore, aims to automatically obtain general sprint parameters, parameters characterizing, and derived from TSI from raw speed. In addition, we propose a method for obtaining the intra-cyclic speed amplitude in TSI. We analyzed 32 100 m-sprints of 7 male and 9 female athletes (18.9 ± 2.8 years; 100 m PB 10.55–12.41 s, respectively, 12.18–13.31 s). Spatio-temporal data was collected with a radio-based position detection system (RedFIR, Fraunhofer Institute, Germany). A general velocity curve was fitted to the overall speed curve (vbase), TSI (upper quintile of vbase values) was determined and a cosine term was added to vbase within TSI (vcycle) to capture the cyclic nature of speed. This allowed to derive TSI parameters including TSI amplitude from the fitted parameters of the cosine term. Results showed good approximation for vbase (error: 5.0 ± 1.0%) and for vcycle (2.0 ± 1.0%). For validation we compared spatio-temporal TSI parameters to criterion values from laser measurement (speed) and optoelectric systems (step time and step length) showing acceptable RMSEs for mean speed (0.08 m/s), for step time (0.004 s), and for step length (0.03 m). Top speed interval amplitude showed a significant difference between males (mean: 1.41 m/s) and females (mean: 0.71 m/s) and correlations showed its independence from other sprint parameters. Gender comparisons for validation revealed the expected differences. This pilot study investigated the feasibility of estimating sprint parameters from high-quality tracking data. The proposed method is independent of the data source and allows to automatically obtain general sprint parameters and TSI parameters, including TSI amplitude assessed here for the first time in a competition-like setting.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Assessment of Sprint Parameters in Top Speed Interval in 100 m Sprint—A Pilot Study Under Field Conditions

Seidl¹,

Russomanno²,

Stöckl³

et al. 2021

Front. Sports Act. Living

Self Cite

View full text Add to dashboard Cite

show abstract

“…Basically, an EPTS device can be attached to the body of football players during the match (or training) time, sensing a number of data related to the athletic and strategic performances. As exemplified in Figure 1 , the EPTS device may have a positioning system assisted by numerous calibration sensors [ 3 , 4 , 5 ], collecting quantitative data such as total distance covered, peak/average speed, or other physiological data. These on-site measurements can be used for analyzing the physical workloads of each player, providing valuable insights to optimize the performance [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Wearable EPTS Device Using On-Device DCNN Processing for Football Activity Classification

Kim

et al. 2020

Sensors

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This paper presents an energy-optimized electronic performance tracking system (EPTS) device for analyzing the athletic movements of football players. We first develop a tiny battery-operated wearable device that can be attached to the backside of field players. In order to analyze the strategic performance, the proposed wearable EPTS device utilizes the GNSS-based positioning solution, the IMU-based movement sensing system, and the real-time data acquisition protocol. As the life-time of the EPTS device is in general limited due to the energy-hungry GNSS sensing operations, for the energy-efficient solution extending the operating time, in this work, we newly develop the advanced optimization methods that can reduce the number of GNSS accesses without degrading the data quality. The proposed method basically identifies football activities during the match time, and the sampling rate of the GNSS module is dynamically relaxed when the player performs static movements. A novel deep convolution neural network (DCNN) is newly developed to provide the accurate classification of human activities, and various compression techniques are applied to reduce the model size of the DCNN algorithm, allowing the on-device DCNN processing even at the memory-limited EPTS device. Experimental results show that the proposed DCNN-assisted sensing control can reduce the active power by 28%, consequently extending the life-time of the EPTS device more than 1.3 times.

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Maximal Sprint Speed and the Anaerobic Speed Reserve Domain: The Untapped Tools that Differentiate the World’s Best Male 800 m Runners

et al. 2018

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Estimation and validation of spatio-temporal parameters for sprint running using a radio-based tracking system

Cited by 8 publications

References 17 publications

Assessment of Sprint Parameters in Top Speed Interval in 100 m Sprint—A Pilot Study Under Field Conditions

Assessment of Sprint Parameters in Top Speed Interval in 100 m Sprint—A Pilot Study Under Field Conditions

Energy-Efficient Wearable EPTS Device Using On-Device DCNN Processing for Football Activity Classification

Maximal Sprint Speed and the Anaerobic Speed Reserve Domain: The Untapped Tools that Differentiate the World’s Best Male 800 m Runners

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