Search Results (66)

This study aimed to examine how physiological determinants are associated with skiing technique and race performance in cross-country roller skiing by integrating motion data obtained via a Global Navigation Satellite System (GNSS) with laboratory-based physiological assessments. Nineteen well-trained male skiers completed a 10 km roller ski race, during which skiing velocity, cycle length, cycle time, and sub-technique usage were measured using GNSS. Whole-body and upper-body endurance and power were evaluated on the treadmill and ski ergometer. Time to exhaustion during the double poling test (r = −0.84, p < 0.01) and VO_2max from the pole walk and run test (r = −0.72, p < 0.01) were the strongest predictors of race performance, and both were significantly associated with skiing velocity (VO_2max: r = 0.79, p < 0.01; TTE-DPT: r = 0.81, p < 0.01) and cycle length (VO_2max: r = 0.58, p < 0.01; TTE-DPT: r = 0.47, p < 0.05) in the most frequently used technique. These findings suggest that the development of both whole-body and upper-body endurance plays a crucial role in improving technical efficiency and race performances. Full article

This study explores the predictive factors influencing sport coaches’ perceived performance levels following an 18-month mentor-based education program. The study employed a quasi-experimental, pre-test/post-test control group design to assess changes in perceived coach performance over time. The experimental group participated in six group gatherings and at least 15 individual mentoring sessions over 18 months, while the control group received no intervention. Participants were recruited from a non-formal coach education program run by the Norwegian Olympic Sports Center (NOSC), requiring recommendations from their respective sport federations. Of the 159 coaches who applied, 73 were selected for the program and invited to participate, along with 29 additional coaches from specialized high schools for elite sports, forming a total sample of 98 coaches (69 in the experimental group, 29 in the control group) at pre-test. The sample consisted of 61 males (62%) and 37 females (38%), aged 26 to 71 years (M = 38.3, SD = 8.3), representing over 20 sports, with handball (15.3%), cross-country skiing (10.2%), soccer (7.1%), and track and field (7.1%) being the most common. Data collection included an online questionnaire measuring perceived coach performance, coaching hours, age, and dimensions of the coach–athlete working alliance (task, bond, and goal development). After 18 months, 75 coaches completed the study, yielding a response rate of 73.5%. Hierarchical regression analyses revealed that coaches’ ages, weekly coaching hours, baseline perceived performance, and task development within the coach–athlete working alliance positively predicted their performance perception post-test. Participation in the mentor-based program also had a significant positive effect. However, neither bond nor goal development in the working alliance predicted performance perception. These findings underscore the importance of mentoring, structured self-reflection, and task-focused coaching strategies in enhancing coaching effectiveness. The results have implications for coach education programs seeking to foster professional growth and performance development. Full article

This work presents a comparative study of low cost and low invasiveness sensors (plantar pressure and inertial measurement units) for classifying cross-country skiing techniques. A dataset was created for symmetrical comparative analysis, with data collected from skiers using instrumented insoles that measured plantar pressure, foot angles, and acceleration. A deep learning model based on CNN and LSTM was trained on various sensor combinations, ranging from two specific pressure sensors to a full multisensory array per foot incorporating 4 pressure sensors and an inertial measurement unit with accelerometer, magnetometer, and gyroscope. Results demonstrate an encouraging performance with plantar pressure sensors and classification accuracy closer to inertial sensing. The proposed approach achieves a global average accuracy of 94% to 99% with a minimal sensor setup, highlighting its potential for low-cost and precise technique classification in cross-country skiing and future applications in sports performance analysis. Full article

Forest areas have recently become increasingly popular for physical activity in society, especially among niche sports enthusiasts. We analysed the attitude of the specific social group of cross-country skiers in Poland to pay for recreation in forest areas using their Willingness-To-Pay (WTP) and Willingness-To-Accept (WTA) declarations, which was endorsed by classification and regression tree (CART) analysis. In January–March 2023, we surveyed 50 (in a pilot study) and 255 (in the main survey) cross-country skiers, of whom 117 declared both their WTP and WTA amounts. The investigated explanatory variables included gender, age, education, residency, employment in the forestry sector, and respondents’ income or engagement in skiing. The average WTP and WTA values equalled PLN 68.6 ± 46.4 and PLN 81.3 ± 59.0/person, respectively. Despite apparent differences in the distribution of the declared WTP and WTA amounts, their medians differed only insignificantly. We found a significant correlation only between the WTP value and respondents’ income per capita, and between WTP and WTA. The CART models showed that WTP and WTA levels depended primarily on the frequency of skiing, with higher values declared by less frequent visitors. At the current respondent income level, the expenses for skiing were related the most to the respondents’ age and the frequency of skiing. In the case of increased income, they were related mostly to the respondents’ age and place of residence. The research provides practical information for forest managers in the field of recreational access to forests for people who spend their time actively in forests. Full article

This study aimed to identify key biomechanical and physiological parameters affecting cross-country skiing performance and develop a neural network model for predicting skiing speed. Biomechanical attributes (cycle length and rate, vertical displacement of the center of mass, and angular kinematics) and physiological factors (maximal oxygen uptake, 30 s anaerobic power), along with physical fitness (standing long jump, pull-ups) were assessed for 82 cross-country skiers (52 men and 30 women). Random forest analysis was utilized to identify the most influential parameters on skiing speed, which were subsequently used as input parameters to develop a neural network aimed at predicting this speed. The findings identified the primary predictors of skiing speed as the cycle length on both flat and uphill terrains, vertical displacement of the center of mass during the poling phase on uphill terrain, maximal oxygen uptake, and 30 s anaerobic power. The developed neural network model demonstrated high precision in predicting skiing speeds, evidenced by a strong correlation with actual speeds (correlation coefficient of 0.953) and 97.1% of predictions falling within the 95% Bland–Altman agreement limits, affirming the model’s reliability and effectiveness in forecasting skiing performance. Full article

Background: Identifying factors affecting heart health in amateur athletes can significantly impact their health and help them achieve high performance. The current knowledge of these predictors is insufficient. The purpose of this study was to identify the biochemical determinants of maximal oxygen uptake (VO2 max) in male amateur long-distance cross-country skiers (37.9 ± 6.58 years, 51.08 ± 4.61 VO2 max ml/kg/min) in the preparation period. Methods: In this cross-sectional study, a time trial test was used to determine VO2 max and venous blood via biochemical markers. Descriptive statistics and Pearson correlation were used to analyze the data. The regression model determined the predictors. Results: VO2 max was significantly correlated with nine moderate or weak variables. Two regression models (R² = 0.94 and R² = 0.9) each identified two determinants of VO2 max, hemoglobin (p < 0.001) and C-reactive protein (p < 0.001), as well as erythrocyte sedimentation (p < 0.001) and platelets (p = 0.03). Only hemoglobin positive affected VO2 max. Conclusions: The results may indicate, in addition to results regarding hemoglobin concentration and its changes, the necessity to monitor the immune system, which may affect the capacity for amateur exercise. Biochemical monitoring is an essential tool for evaluating the individual adaptation to exercise and developing an effective training plan. The application of this knowledge can facilitate the achievement of optimal individual performance capabilities among cross-country skiing amateurs. Full article

Background/Objectives: Research on the effects of training on the health of amateur cross-country skiers remains limited, particularly on biochemical parameters. Therefore, this study aimed to assess such changes in response to four months of training for amateur cross-country skiers. Methods: Blood samples were collected after spring training in May (active rest) and in September at the end of the preparatory period. The Wilcoxon signed-rank test was used for comparison of both measurements (initial and final). Results: Training in a group of amateur cross-country skiers exerts a statistically significant influence on the decrease in leukocyte count (thousand/µL) (p = 0.045) and the decrease in mean corpuscular hemoglobin concentration (MCHC) (g/dL) (p = 0.021). The other parameters did not show statistically significant changes. Conclusions: The change in MCHC and WBC can be attributed to adaptation to prolonged exercise, with a simultaneous increase in VO₂ max. It should not be identified with pathology. The decrease in MCHC was likely attributable to changes in hydration status and a slight reduction in hemoglobin concentration. Similarly, it is recommended that other biochemical parameters be within the reference ranges. Full article

The aim of this current work is to identify three different gears of cross-country skiing utilizing embedded inertial measurement units and a suitable deep learning model. The cross-country style studied was the skating style during the uphill, which involved three different gears: symmetric gear pushing with poles on both sides (G3) and two asymmetric gears pushing with poles on the right side (G2R) or to the left side (G2L). To monitor the technique, inertial measurement units (IMUs) were affixed to the skis, recording acceleration and Euler angle data during the uphill tests performed by two experienced skiers using the gears under study. The initiation and termination points of the tests were controlled via Bluetooth by a smartphone using a custom application developed with Android Studio. Data were collected on the smartphone and stored on the SD memory cards included in each IMU. Convolutional neural networks combined with long short-term memory were utilized to classify and extract spatio-temporal features. The performance of the model in cross-user evaluations demonstrated an overall accuracy of 90%, and it achieved an accuracy of 98% in the cross-scene evaluations for individual users. These results indicate a promising performance of the developed system in distinguishing between different ski gears within skating styles, providing a valuable tool to enhance ski training and analysis. Full article

A comprehensive analysis of cross-country skiing races is a pivotal step in establishing effective training objectives and tactical strategies. This study aimed to develop a method of classifying sub-techniques and analyzing skiing characteristics during cross-country skiing skating style timed races on snow using high-precision kinematic GNSS devices. The study involved attaching GNSS devices to the heads of two athletes during skating style timed races on cross-country ski courses. These devices provided precise positional data and recorded vertical and horizontal head movements and velocity over ground (VOG). Based on these data, sub-techniques were classified by defining waveform patterns for G2, G3, G4, and G6P (G6 with poling action). The validity of the classification was verified by comparing the GNSS data with video analysis, a process that yielded classification accuracies ranging from 95.0% to 98.8% for G2, G3, G4, and G6P. Notably, G4 emerged as the fastest technique, with sub-technique selection varying among skiers and being influenced by skiing velocity and course inclination. The study’s findings have practical implications for athletes and coaches as they demonstrate that high-precision kinematic GNSS devices can accurately classify sub-techniques and detect skiing characteristics during skating style cross-country skiing races, thereby providing valuable insights for training and strategy development. Full article

In cross-country skiing, ski poles play a crucial role in technique, propulsion, and overall performance. The kinematic parameters of ski poles can provide valuable information about the skier’s technique, which is of great significance for coaches and athletes seeking to improve their skiing performance. In this work, a new smart ski pole is proposed, which combines the uniaxial load cell and the inertial measurement unit (IMU), aiming to provide comprehensive data measurement functions more easily and to play an auxiliary role in training. The ski pole can collect data directly related to skiing technical actions, such as the skier’s pole force, pole angle, inertia data, etc., and the system’s design, based on wireless transmission, makes the system more convenient to provide comprehensive data acquisition functions, in order to achieve a more simple and efficient use experience. In this experiment, the characteristic data obtained from the ski poles during the Double Poling of three skiers were extracted and the sample t-test was conducted. The results showed that the three skiers had significant differences in pole force, pole angle, and pole time. Spearman correlation analysis was used to analyze the sports data of the people with good performance, and the results showed that the pole force and speed (r = 0.71) and pole support angle (r = 0.76) were significantly correlated. In addition, this study adopted the commonly used inertial sensor data for action recognition, combined with the load cell data as the input of the ski technical action recognition algorithm, and the recognition accuracy of five kinds of cross-country skiing technical actions (Diagonal Stride (DS), Double Poling (DP), Kick Double Poling (KDP), Two-stroke Glide (G2) and Five-stroke Glide (G5)) reached 99.5%, and the accuracy was significantly improved compared with similar recognition systems. Therefore, the equipment is expected to be a valuable training tool for coaches and athletes, helping them to better understand and improve their ski maneuver technique. Full article

A variable pacing profile is common in different endurance events. In these races, several factors, such as changes in elevation or race dynamics, lead participants to perform numerous surges in intensity. These surges are so frequent that certain events, such as cross-country (XC) skiing, mountain biking (MTB), triathlon, and road cycling, have been termed “intermittent endurance events”. The characteristics of these surges vary depending on the sport: MTB and triathlon require athletes to perform numerous short (<10 s) bouts; XC skiing require periods of short- and moderate-(30 s to 2 min) duration efforts, while road cycling is comprised of a mix of short-, moderate-, and long-duration (>2 min) bouts. These bouts occur at intensities above the maximal metabolic steady state (MMSS), with many efforts performed at intensities above the athletes’ maximal aerobic power or speed (MAP/MAS) (i.e., supramaximal intensities). Given the factors that influence the requirement to perform surges in these events, athletes must be prepared to always engage in a race with a highly stochastic pace. The aim of this review is to characterize the variable pacing profile seen in endurance events and to discuss how the performance of multiple maximal and supramaximal surges in intensity can affect how athletes fatigue during a race and influence training strategies that can lead to success in these races. Full article

Background: Troponin I and T are biomarkers to diagnose myocardial infarction and damage. Studies indicate that strenuous physical activity can cause transient increases in these troponin levels, typically considered physiological. However, current data show differences in the exercise-induced increase in troponin I and T in elite athletes. Method: This prospective clinical study aimed to determine troponin I and T levels in 36 top cross-country skiers of the German national team (18 male, 18 female) after a standardized competition load over two days. All study participants underwent a comprehensive sports medical and cardiological evaluation, including ECG and echocardiography. A multivariable regression analysis was utilized to identify possible predictors of increased troponin I levels. Results: Only three male athletes (8.1%) showed an isolated increase in Troponin I (Ø 112.49 ng/L, cut off < 45.2 ng/L), while no increase in troponin T in the study population was detected. Conclusions: The analysis suggested several potential predictors for increased troponin I levels, such as height, weight, weekly training hours, and indications of an enlarged sports heart, though none achieved statistical significance. Knowing the different exercise-induced detectability of the various troponins in the clinical setting is essential. Full article

A total of nineteen elite youth cross-country skiers (16 ± 2 years) were divided into three groups: a low-load group (LL, n = 6) performing 15–20 repetitions per exercise, a high-load group (HL, n = 9) executing 6–12 repetitions, and a control group (CON, n = 4) exclusively engaging in endurance training. Testing included 1RM in upper-body exercises, VO_2max running tests, and double-poling (DP) ergometer exhaustion and sprint tests to determine peak oxygen uptake (VO_2peak-DP) and peak power (PP). The results indicated that HL and LL showed significant increases in VO_2peak-DP, both in absolute values (d = −1.2 and −1.2, p < 0.05) and when normalized to body mass (d = 0.93 and 1.3, p < 0.05). Although there were no group*time effects for VO_2peak-DP, PP during DP tests to exhaustion increased in both HL (d = −1.6, p < 0.05) and LL (d = 1.4, p < 0.05) compared to CON. Standardized to body mass, only HL showed significant improvements in PP during the sprint test (d = 1.7, p < 0.05). During the sprint test, both absolute and body-mass-normalized peak power increased only in the high-load group (d = −1.0 and 0.93, p < 0.05). In conclusion, high-load resistance training resulted in the greatest improvements in strength, DP performance, and VO_2peak-DP, indicating a dose–response relationship to the load magnitude of resistance training. Full article

Roller skiing is one primary form of training method as it is an off-snow equivalent to cross-country (XC) skiing during the dry land preseason training, but the results could only be applied to on-snow skiing with appropriate caution. The aim of this present study was to investigate the similarities and differences in roller skiing and on-snow skiing with the diagonal stride (DS) technique. Six youth (age: 14.3 ± 2.9 years) skiers participated in this study. Two high-definition video camcorders and FastMove 3D Motion 2.23.3.3101 were used to obtain the three-dimensional kinematic data. The cycle characteristics and joint angle ROM of the DS technique while skiing on different surfaces were similar. Almost all joint angle–time curves that were obtained from roller skiing showed a moderate-to-high degree of similarity to the angle–time curves obtained from on-snow skiing, except the hip adduction–abduction angle. The differences between roller skiing and on-snow skiing were mainly found in the body and calf anteversion angles, and the joint angles at critical instants. DS roller skiing can simulate DS on-snow skiing to a large extent in youth athletes. The hip movement, knee flexion, and calf anteversion at ski/roller ski touchdown and take-off, pole inclination at pole touchdown, body anteversion angle, and trunk anteversion angle at pole touchdown were the points that required caution when transferring preseason practice roller skiing to on-snow skiing. Full article

Sports participation and the risk of osteoarthritis (OA) have been a concern for decades. Few research efforts have been dedicated to clarify this issue for females, although they are considered at greater risk of developing OA than males. In contrast, several reviews have established an association between sports participation and OA for males. The aim of the systematic review was to assess the association between OA and participation in popular sports for females. PubMed, Embase, and Google Scholar were searched and yielded 578 articles. Nine eligible studies were included and covered ballet (age range: 19–54 years), running or tennis (age range: 40–65 years), Olympic sports (age range: not specified), volleyball (age range: 16.0 ± 0.8 to 46.8 ± 5.1 years), and cross-country skiing (age range: 15 to ≥60 years). For females, participating in sports at an elite level was associated with a higher risk of OA and an increased need for surgical treatment. At non-elite level, it was associated with a higher risk of OA, but it did not materialize to an increased risk for surgical treatment. Few studies compared females and males, and these studies suggested that sex did not affect the risk of developing OA from participating in sports. Nevertheless, to isolate the precise effect of sports participation on the development of OA remains difficult as injuries are common among athletes and are independently associated with an increased risk of OA. Full article