Time-motion analysis in women’s team handball: importance of aerobic performance

Women’s handball is a sport, which has seen an accelerated development over the last decade. Data on movement patterns in combination with physiological demands are nearly nonexistent in the literature. The aim of this study was twofold: first, to analyze the horizontal movement pattern, including the sprint acceleration profiles, of individual female elite handball players and the corresponding heart rates (HRs) during a match and secondly to determine underlying correlations with individual aerobic performance. Players from one German First League team (n = 11) and the Norwegian National Team (n = 14) were studied during one match using the Sagit system for movement analysis and Polar HR monitoring for analysis of physiological demands. Mean HR during the match was 86 % of maximum HR (HRmax). With the exception of the goalkeepers (GKs, 78 % of HRmax), no position-specific differences could be detected. Total distance covered during the match was 4614 m (2066 m in GKs and 5251 m in field players (FPs)). Total distance consisted of 9.2 % sprinting, 26.7 % fast running, 28.8 % slow running, and 35.5 % walking. Mean velocity varied between 1.9 km/h (0.52 m/s) (GKs) and 4.2 km/h (1.17 m/s) (FPs, no position effect). Field players with a higher level of maximum oxygen uptake (V̇O2max) executed run activities with a higher velocity but comparable percentage of HRmax as compared to players with lower aerobic performance, independent of FP position. Acceleration profile depended on aerobic performance and the field player’s position. In conclusion, a high V̇O2max appears to be important in top-level international women’s handball. Sprint and endurance training should be conducted according to the specific demands of the player’s position.

Real time motion estimation using a neural architecture implemented on GPUs

This work describes a neural network based architecture that represents and estimates object motion in videos. This architecture addresses multiple computer vision tasks such as image segmentation, object representation or characterization, motion analysis and tracking. The use of a neural network architecture allows for the simultaneous estimation of global and local motion and the representation of deformable objects. This architecture also avoids the problem of finding corresponding features while tracking moving objects. Due to the parallel nature of neural networks, the architecture has been implemented on GPUs that allows the system to meet a set of requirements such as: time constraints management, robustness, high processing speed and re-configurability. Experiments are presented that demonstrate the validity of our architecture to solve problems of mobile agents tracking and motion analysis.

Performance Factors in Women's Team Handball: Physical and Physiological Aspects—A Review

Team handball is an Olympic sport played professionally in many European countries. Nevertheless, a scientific knowledge regarding women's elite team handball demands is limited. Thus, the purpose of this article was to review a series of studies (n = 33) on physical characteristics, physiological attributes, physical attributes, throwing velocity, and on-court performances of women's team handball players. Such empirical and practical information is essential to design and implement successful short-term and long-term training programs for women's team handball players. Our review revealed that (a) players that have a higher skill level are taller and have a higher fat-free mass; (b) players who are more aerobically resistant are at an advantage in international level women team handball; (c) strength and power exercises should be emphasized in conditioning programs, because they are associated with both sprint performance and throwing velocity; (d) speed drills should also be implemented in conditioning programs but after a decrease in physical training volume; (e) a time-motion analysis is an effective method of quantifying the demands of team handball and provides a conceptual framework for the specific physical preparation of players. According to our results, there are only few studies on on-court performance and time-motion analysis for women's team handball players, especially concerning acceleration profiles. More studies are needed to examine the effectiveness of different training programs of women's team handball players' physiological and physical attributes.

Active Visual Features Based on Events to Guide Robot Manipulators in Tracking Tasks

Traditional visual servoing systems do not deal with the topic of moving objects tracking. When these systems are employed to track a moving object, depending on the object velocity, visual features can go out of the image, causing the fail of the tracking task. This occurs specially when the object and the robot are both stopped and then the object starts the movement. In this work, we have employed a retina camera based on Address Event Representation (AER) in order to use events as input in the visual servoing system. The events launched by the camera indicate a pixel movement. Event visual information is processed only at the moment it occurs, reducing the response time of visual servoing systems when they are used to track moving objects.

Targetless image-based method for measuring displacements and strains on concrete surfaces with a consumer camera

Measurement of concrete strain through non-invasive methods is of great importance in civil engineering and structural analysis. Traditional methods use laser speckle and high quality cameras that may result too expensive for many applications. Here we present a method for measuring concrete deformations with a standard reflex camera and image processing for tracking objects in the concretes surface. Two different approaches are presented here. In the first one, on-purpose objects are drawn on the surface, while on the second one we track small defects on the surface due to air bubbles in the hardening process. The method has been tested on a concrete sample under several loading/unloading cycles. A stop-motion sequence of the process has been captured and analyzed. Results have been successfully compared with the values given by a strain gauge. Accuracy of our methods in tracking objects is below 8 μm, in the order of more expensive commercial devices.