Dataset Information

Full course macro-kinematic analysis of a 10 km classical cross-country skiing competition.

ABSTRACT: In this study micro-sensors were employed to analyse macro-kinematic parameters during a classical cross-country skiing competition (10 km, 2-lap). Data were collected from eight male participants during the Australian championship competition wearing a single micro-sensor unit (MinimaxX™, S4) positioned on their upper back. Algorithms and visual classification were used to identify skiing sub-techniques and calculate velocities, cycle lengths (CL) and cycle rates (CR) over the entire course. Double poling (DP) was the predominant cyclical sub-technique utilised (43 ± 5% of total distance), followed by diagonal stride (DS, 16 ± 4%) and kick double poling (KDP, 5 ± 4%), with the non-propulsive Tuck technique accounting for 24 ± 4% of the course. Large within-athlete variances in CL and CR occurred, particularly for DS (CV% = 25 ± 2% and CV% = 15 ± 2%, respectively). For all sub-techniques the mean CR on both laps and for the slower and faster skiers were similar, while there was a trend for the mean velocities in all sub-techniques by the faster athletes to be higher. Overall velocity and mean DP-CL were significantly higher on Lap 1, with no significant change in KDP-CL or DS-CL between laps. Distinct individual velocity thresholds for transitions between sub-techniques were observed. Clearly, valuable insights into cross-country skiing performance can be gained through continuous macro-kinematic monitoring during competition.

SUBMITTER: Marsland F

PROVIDER: S-EPMC5538647 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Full course macro-kinematic analysis of a 10 km classical cross-country skiing competition.

Marsland Finn F Mackintosh Colin C Holmberg Hans-Christer HC Anson Judith J Waddington Gordon G Lyons Keith K Chapman Dale D

PloS one 20170801 8

In this study micro-sensors were employed to analyse macro-kinematic parameters during a classical cross-country skiing competition (10 km, 2-lap). Data were collected from eight male participants during the Australian championship competition wearing a single micro-sensor unit (MinimaxX™, S4) positioned on their upper back. Algorithms and visual classification were used to identify skiing sub-techniques and calculate velocities, cycle lengths (CL) and cycle rates (CR) over the entire course. Do ...[more]

PMID: 28763504

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Project description:Cross-country skiing is a popular Olympic winter sport, which is also used extensively as a recreational activity. While cross-country skiing primarily is regarded as a demanding endurance activity it is also technically challenging, as it contains two main styles (classical and skating) and many sub-techniques within these styles. To further understand the physiological demands and technical challenges of cross-country skiing it is imperative to identify sub-techniques and basic motion features during training and competitions. Therefore, this paper presents features for identification and assessment of the basic motion patterns used during classical-style cross-country skiing. The main motivation for this work is to contribute to the development of a more detailed platform for comparing and communicating results from technique analysis methods, to prevent unambiguous definitions and to allow more precise discussions and quality assessments of an athlete's technical ability. To achieve this, our paper proposes formal motion components and classical style technique definitions as well as sub-technique classifiers. This structure is general and can be used directly for other cyclic activities with clearly defined and distinguishable sub-techniques, such as the skating style in cross country skiing. The motion component features suggested in our approach are arm synchronization, leg kick, leg kick direction, leg kick rotation, foot/ski orientation and energy like measures of the arm, and leg motion. By direct measurement, estimation, and the combination of these components, the traditional sub-techniques of diagonal stride, double poling, double poling kick, herringbone, as well as turning techniques can be identified. By assuming that the proposed definitions of the classical XC skiing sub-techniques are accepted, the presented classifier is proven to map measures from the motion component definitions to a unique representation of the sub-techniques. This formalization and structure may be used on new motion components, measurement principles, and classifiers, and therefore provides a framework for comparing different methodologies. Pilot data from a group of high-level cross-country skiers employing inertial measurement sensors placed on the athlete's arms and skis are used to demonstrate the approach. The results show how detailed sub-technique information can be coupled with physical, track, and environmental data to analyze the effects of specific motion patterns, to develop useful debriefing tools for coaches and athletes in training and competition settings, and to explore new research hypotheses.

Project description:Since physical inactivity especially prevails during winter months, we set out to identify outdoor alternatives to indoor cycling (IC) by comparing the metabolic and cardiorespiratory responses during alpine skiing (AS), cross-country skiing (XCS) and IC and analyse the effects of sex, age and fitness level in this comparison. Twenty one healthy subjects performed alpine skiing (AS), cross-country skiing (XCS), and IC. Oxygen uptake (VO2), total energy expenditure (EE), heart rate (HR), lactate, blood glucose and rate of perceived exertion (RPE) were determined during three 4-min stages of low, moderate and high intensity. During XCS and IC VO2max and EE were higher than during AS. At least 2½ hours of AS are necessary to reach the same EE as during one hour of XCS or IC. HR, VO2, lactate, and RPEarms were highest during XCS, whereas RPEwhole-body was similar and RPElegs lower than during AS and IC, respectively. Weight adjusted VO2 and EE were higher in men than in women while fitness level had no effect. Male, fit and young participants were able to increase their EE and VO2 values more pronounced. Both AS and XCS can be individually tailored to serve as alternatives to IC and may thus help to overcome the winter activity deficit. XCS was found to be the most effective activity for generating a high EE and VO2 while AS was the most demanding activity for the legs. Key pointsDuring cross-country skiing and indoor cycling VO2max and energy expenditure were higher than during alpine skiingApproximately 2½ hours of alpine skiing are necessary to reach the same energy expenditure of one hour of cross-country skiing or indoor cycling.Alpine skiing and cross-country skiing can be individually tailored to serve as sports alternatives in winter to activity deficit.By applying different skiing modes as parallel ski steering, carving long radii and short turn skiing, metabolic and cardiorespiratory response can be increased during alpine skiing.Male, fit and young participants were able to increase their energy expenditure and VO2 more pronounced with an increase in intensity compared with their counterparts.

Project description:Objective: To develop a framework for the investigation of speed, power, and kinematic patterns across varying terrain in cross-country (XC) sit-skiing, and to test this framework in a XC sit-skier of the LW12 class during high- (HIT) and low-intensity (LIT) endurance training. Methods: One XC sit-skiing athlete of the LW12 class with a single above-the-knee amputation was equipped with a GNSS enabled sports watch with integrated barometry and heart rate monitoring (peak heart rate: 195 beats·min-1), and an inertial measurement unit. After a warm-up, he performed two 20-m maximal speed tests on a flat and an uphill section to determine maximal speed and power, followed by skiing 5.75 km at both LIT and HIT in varying terrain. Results: 51, 28, and 21% of the time during HIT and 53, 28, and 19% of the time during LIT were spent in uphill, flat and downhill terrain, respectively. Maximal speed in the uphill and flat section was 4.0 and 6.2 m·s-1, respectively, and the corresponding maximal power output 342 and 252 W. The % of maximal speed did not differ between the uphill and the flat section (HIT: 66 vs. 67%, LIT: 47 vs. 50%), whereas the % of maximal power output was lower in the uphill than flat section (HIT: 65 and 80%, LIT: 46 and 58%). Still, the absolute power output was slightly higher in the uphill than the flat section (HIT: 222 vs. 201 W, LIT: 156 vs. 145 W). Furthermore, cycle rate was significantly higher during HIT than LIT (60-61 vs. 45-55 cycles·min-1, across all terrains, all p < 0.03), while cycle length was longer in the uphill terrain (3.0 vs. 2.6 m, p < 0.001). Furthermore, the % of peak heart rate was significantly higher in HIT than LIT (90 vs. 78, 85 vs. 67, and 88 vs. 66%, respectively, in the uphill, flat and downhill terrain, all p < 0.001). Conclusions: Here, we present a new integrative framework for future investigations of performance, technical and physical demands in XC sit-skiing. In this case study, the increase in speed from LIT to HIT was due to increases in cycle rate in all terrains, while cycle length was less affected. Although the absolute power output was slightly higher in the uphill compared to the flat section both for HIT and LIT, the athlete worked closer to his maximum power output in the flat section.

Dataset Information

Full course macro-kinematic analysis of a 10 km classical cross-country skiing competition.

Publications

Full course macro-kinematic analysis of a 10 km classical cross-country skiing competition.

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