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«BOOK OF ABSTRACTS Edited by: Loland, S., Bø, K., Fasting, K., Hallén, J., Ommundsen, Y., Roberts, G., Tsolakidis, E. Hosted by: The Norwegian ...»

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ACE ID and ACTN3 RX polymorphisms did not influence muscle function phenotypes in this cohort. Serum ACE activity appeared to have a small effect on muscle function. The association of ACTN3 genotype with fat mass suggests that this polymorphism affects the accumulation of body fat over the life span of Caucasian men.

1. Skelton, D. et al (1994). Age and Ageing, 23 (5),371-377

2.Williams, A. et al (2005). MSSE, 37 (6),944-948

3. Clarkson et al (2007). Journal of App Physiol, 99,154-163.

4. Charbonneau et al (2008). MSSE,40 (4),677-683.

5. McArthur et al (2004). BioEssays, 26,786-795.

08:30 - 10:00 Oral presentations OP-CS01 Computer Sciences and Statistics





Introduction: There are few studies concerning the relationship between vestibular load and oculomotor and spinalmotor activation during complex sport specific movements. Up to now no commercial software tool has been able to fulfil the combined exposure of kinematic, electromyographic and oculomotor signals in the field of sports. The development of the multimodal prototype software tool “VISMO” tries to close this gap to enable a better understanding of oculomotor, neuromuscular and kinematic interaction and their consequences for motor learning and technomotor modelling in sports. The aim of this publication is to present the functions of this tool.

Methods and Results: The measurement components consist of 3D-Video-kinemetry or a Vicon system, telemetric electromyography (Noraxon) and a videonystagmography system (Interacoustics) combined with a prototype of a sport specific videonystagmography goggle. The software is able to integrate these components, to calibrate and synchronize the data and to calculate a frame based 6-field view of various multifunction graphic tools and data plots. The software itself (developed by von Laßberg, C. & Reimann, M., 2008) presents 6 onscreen windows for simultaneous view or for presentation in various combinations of the windows.

–  –  –

The windows show a virtual athlete based on a 15 segment lattice model in virtual space. The virtual room can be exactly adapted to the real dimensions of the athlete’s environment. Gaze lines and gaze spots are integrated into the virtual space. The spots represent the resulting coordinates, calculated by the head related eye data and the heads position in space. The diameter of the spots correlates with the visual fixation time on theese gaze spots. Occulomotor gain of nystagmus can also be calculated. In the model, all muscles being registered by the EMG are depicted using coloured matrices. The higher the activation level, the darker the colour with which they are visualized. Onset threshold can be defined for all muscles separately. The virtual model and room can be zoomed or moved along and around all axes. Vectors of vestibular load can be visualized within the head-model, separately. Optionally the subjective visual view of the athlete in the virtual room can be visualised and screened in helmet mounted displays for the use in further research concerning visuo-mental training methods. All data plots calculated by the software are visualized synchroneously in a separate window: The plots can be selected as required and be exported to other programs (e.g. for further statistical analysis).

Conclusion To better understand the complexity of human movement, it is necessary to have a deeper insight into human control processes. The benefit of this software is the ability to combine the extrinsic view with intrinsic data of movement control to better understand their relationships in sports and daily life.




We develop methods for data acquisition, analysis, modeling and visualization of performance parameters in endurance sports with emphasis on competitive cycling. For this purpose, we designed a simulator to facilitate the measurement of training parameters in a laboratory environment, to familiarize cyclists with unknown tracks, and to develop models for training control and performance prediction.

The simulator is based on a Cyclus2 ergometer (RBM Elektronik-Automation GmbH, Leipzig, Germany), which provides a realistic cycling experience since one can mount arbitrary bikes and its elastic suspension even allows for a sway pedal stroke. The eddy current brake guarantees non-slipping transmission of a braking resistance up to 3000 W.

Operating the Cyclus2 in the gradient mode, we impose arbitrary slopes by our own platform independent PC-based control software at a sampling rate of 2 Hz. The height profiles for various tracks were recorded using a commercial GPS device.

The Cyclus2 has two major constraints with respect to simulating real tracks: We must focus on tracks without downhill accelerations since it has no engine and the eddy current brake requires a minimum rotation velocity of the flywheel to accurately generate the brake force. Therefore, we fixed the derailleurs to a heavy gear and mounted four electronic buttons to the handlebar which act like shift levers of virtual gears. Our software incorporates the virtual gear into the gradient so that the cyclist feels a correct resistance while the flywheel exceeds the minimum rotation velocity in all realistic uphill scenarios. Moreover, we can simulate arbitrary gears easily and record them over time. As the physical flywheel rotation is faster than in the simulation, our software must correct the related performance data.

The simulation includes a video playback that is synchronized with the cyclist’s current position on the track. In addition, time, distance, speed, cadence, heart rate, power and gears are monitored, a 2D-projection of the course gives feedback on the progress and a gradient profile indicates the slope in the surrounding of the current position.

Comparative outdoor tests with an SRM power meter (Schoberer Rad Messtechnik, Welldorf, Germany) show that the simulator gives reasonable estimates for different pacing strategies (constant power/speed/heart rate).

In future, we strive to integrate a more precise mechanical model (Martin et al., 1998), extend the palette of physiological measurements (oxygen consumption, ECG, lactate etc) and implement models for these parameters. The whole system shall indicate the optimum pacing strategy as Gordon derived in 2005 for simple models and synthetic data. Using sophisticated biofeedback visualization, cyclists shall be able to optimally prepare themselves even for unfamiliar tracks on our simulator.

Martin JC, Milliken DL, Cobb JE, McFadden KL, Coggan AR. (1998). J Appl Biomech, 14, 276-291.

Gordon S. (2005). J Sport Sci, 8, 81-90.




Introduction: The aiming strategy in biathlon shooting is a crucial factor for success. Because of the preceding high exertions of the athletes a well controlled motion of the barrel just before shooting is essential (Zatsiorsky and Aktov, 1990). Methods are required for analyzing the stability of the aiming process with a special focus on exertion. The aim of this study was to investigate the applicability of special self-organizing maps to identify and compare patterns in the aiming motion in standing shooting.

Methods: A video based system (Baca and Kornfeind, 2006) was used to track the motion of the muzzle of the barrel in two dimensions (left-right, up-down) automatically. Six parameters were calculated describing the motion in ten time intervals of 0.2 s length before the shot. Four athletes (I, II, III, IV) (I, III, IV: Austrian national “B” team, II: “C” team) participated in the study. Each athlete performed four series of five shots before and after exertion making 160 shots altogether.

Based on these data a special self organizing map (Perl et al., 2006) consisting of 400 neurons was trained and data sets were generated on the neurons. The attribute values of those data sets represent the six components describing a motion of a muzzle in a 0.2 s time interval. Similar neurons were combined to clusters.

The ten successive data-sets describing each shot were then mapped to the corresponding neurons of the net. The sequence of the related clusters in the respective succession was then used as 1-dimensional representation (a pattern) of the complex aiming motion.

Results: Regarding intra-individual stability, some peculiarities were found. The number of a shot within a series of five shots clearly influenced the pattern observed. This was particularly the case after exertion. Moreover, in this condition less stable shot types were found. Subjects were able to maintain their pattern before the exertion to a different degree. Subject II, who showed the largest deviations, scored worst.

Although inter-individual variability was difficult to assess, some similarities (e.g. in timing) could be identified.

Discussion: The method is promising to analyze inter- and inter-individual similarities and differences. One shortfall might be that only a restricted set of parameter values originating from a 2-dimensional recording of the muzzle has been considered. Time series data


TH Thursday, June 25th, 2009 describing the 3-dimensional motion of the barrel would probably increase the explanatory power. In addition, alternatives not based of a fixed time interval for analysis (2 seconds before the shot) are conceivable.

References Baca A, Kornfeind P (2007). IEEE Perv. Comp., 5, 70-76.

Perl J, Memmert D, Bischof J, Gerharz C. (2006). Int J Comp Sci Sport, 5, 33–37.

Zatsiorsky VM, Aktov AV (1990). J Biomech., 23 (Suppl. 1), 35-41.




Introduction: In recent years experts have criticized the analysis of single actions in sports games (Carling et al., 2005). Simple tally counts of observed single actions do not represent the process of sport games sufficiently. The missing consideration of game interactions leads to information out of context which limits useful conclusions for practitioners. Therefore, the aim of this study was to analyse the action sequences in beach volleyball by using a database with single action descriptions and subsequent specific database queries. Deduced from sports practice the following questions were of interest: How does the service technique affect the reception performance? How does the setting quality affect the attack performance? Do men and women perform similar?

Methods: The basis of action sequence analysis is a systematic notational analysis of single actions out of video recordings. The behaviour of male and female world league players (29 matches during a world tour tournament) was described and registered with the game analysis software “Statshot” concerning technique, quality, location of action, direction and type of movement (Tilp et al., 2006). During the analysis the collected actions (approx. 16000) were classified regarding their affiliation to rallies and their temporal position during the rallies. Subsequently, database queries allowed the analysis of actions sequences. Chi-square tests were used to test statistical significance (p0.05).

Results: The relationship between service technique and reception performance was observed to be gender specific. Female athletes received 44% of all float serves without a jump in poor (low ball trajectory or imprecise) or bad (mistake) quality (men: 30%). In contrast, 39% of all jump serves received by male athletes were of weak quality (women: 37%). Gender differences could also be detected in the relationship between setting quality and attacking technique. While men and women used the same distribution of the two attacking techniques (smash and shot) following excellent and poor setting actions, a different behaviour could be observed following setting actions of medium quality. While women played much more shots (72%) than smashes (28%), men used both techniques equally. All mentioned differences were statistically significant.

Discussion: The presented and additional results indicate that the analysis of sequential beach volleyball actions allows more specific conclusions in the game context than the analysis of single actions. It is possible to gain new and useful results for structure- and team analysis. Further research should reveal if stereotypic behaviour of teams can be identified with this method.

References Carling C, Williams M, Reilly T, (2005). Handbook of soccer match analysis. Routledge, Oxon.

Tilp M, Koch C, Stifter S, Ruppert G, (2006). Int J Perform Analysis, 6(1), 140-148.




The 2008 Beijing Olympic competition is into historical perspective. China’s 100 medals represent an increase by the host nation of 59% over the 63 medals won four years earlier. This is superior to the 44% average home-nation advantage for the 11 most recent fullyattended Games.

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