Mid Sweden University

Purpose: This study aimed to investigate how rifle carriage and skiing speed during biathlon roller skiing affect range of motion (ROM) in joint angles and equipment (skis and poles), the vertical distance between shoulders and treadmill (vertdist), as well as possible sex differences associated with rifle carriage. Methods: Fourteen biathletes (6 women, 8 men) roller-skied on a treadmill at submaximal and simulated race speeds, with (WR) and without (NR) a rifle, using gears 3 and 2. Kinematical data for the whole body, poles, roller-skis, rifle, and treadmill were monitored using a 3D motion capture system. Movements determined as flexion/extension (x), abduction/adduction (y), and/or internal/external rotation (z) were analyzed for the hip, shoulder, thorax, knee, ankle, elbow, poles, and roller skis. ROM (the difference between maximal and minimal angles) in joints and equipment, and vertdist were analyzed over six skiing cycles during each condition (WR and NR) and speed. Results: The maximal vertdist was lower for WR compared with NR (gear 3: 1.53 ± 0.06 vs 1.54 ± 0.06 m; gear 2: 1.49 ± 0.06 vs 1.51 ± 0.06 m; both p < 0.001). ROM in the upper body was altered when roller skiing WR (movements decreased in thorax and shoulder (x) and increased in elbow (only gear 3) (x), thorax (only gear 2), and shoulder (y) and (z); all p < 0.05) and increased with speed, without differences between sexes (p > 0.05). Conclusion: Since rifle carriage and speed appear to affect the kinematics of roller skiing, coaches, and biathletes are advised to perform skiing technique training under competition-like conditions (i.e., at race speeds while carrying the rifle). 

Our aims were to measure anthropometric and oxygen uptake (V&#x2D9;" role="presentation" style="box-sizing: border-box; display: inline; line-height: normal; font-size: 20px; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; color: rgb(62, 61, 64); font-family: Georgia, "Times New Roman", Times, serif; position: relative; outline: 0px !important;">V˙V˙O2) variables in the laboratory, to measure kinetic and stride characteristics during a trail running time trial, and then analyse the data for correlations with trail running performance. Runners (13 men, 4 women: mean age: 29 ± 5 years; stature: 179.5 ± 0.8 cm; body mass: 69.1 ± 7.4 kg) performed laboratory tests to determine V&#x2D9;" role="presentation" style="box-sizing: border-box; display: inline; line-height: normal; font-size: 20px; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; color: rgb(62, 61, 64); font-family: Georgia, "Times New Roman", Times, serif; position: relative; outline: 0px !important;">V˙V˙O2 max, running economy (RE), and anthropometric characteristics. On a separate day they performed an outdoor trail running time trial (two 3.5 km laps, total climb: 486 m) while we collected kinetic and time data. Comparing lap 2 with lap 1 (19:40 ± 1:57 min vs. 21:08 ± 2:09 min, P < 0.001), runners lost most time on the uphill sections and least on technical downhills (-2.5 ± 9.1 s). Inter-individual performance varied most for the downhills (CV > 25%) and least on flat terrain (CV < 10%). Overall stride cycle and ground contact time (GCT) were shorter in downhill than uphill sections (0.64 ± 0.03 vs. 0.84 ± 0.09 s; 0.26 ± 0.03 vs. 0.46 ± 0.90 s, both P < 0.001). Force impulse was greatest on uphill (248 ± 46 vs. 175 ± 24 Ns, P < 0.001) and related to GCT (r = 0.904, P< 0.001). Peak force was greater during downhill than during uphill running (1106 ± 135 vs. 959 ± 104 N, P< 0.01). Performance was related to absolute and relative V&#x2D9;" role="presentation" style="box-sizing: border-box; display: inline; line-height: normal; font-size: 20px; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; color: rgb(62, 61, 64); font-family: Georgia, "Times New Roman", Times, serif; position: relative; outline: 0px !important;">V˙V˙O2 max (P < 0.01), vertical uphill treadmill speed (P < 0.001) and fat percent (P < 0.01). Running uphill involved the greatest impulse per step due to longer GCT while downhill running generated the highest peak forces. V&#x2D9;" role="presentation" style="box-sizing: border-box; display: inline; line-height: normal; font-size: 20px; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; color: rgb(62, 61, 64); font-family: Georgia, "Times New Roman", Times, serif; position: relative; outline: 0px !important;">V˙V˙O2 max, vertical running speed and fat percent are important predictors for trail running performance. Performance between runners varied the most on downhills throughout the course, while pacing resembled a reversed J pattern. Future studies should focus on longer competition distances to verify these findings and with application of measures of 3D kinematics.

Biomechanical differences in double poling (DP) between sex and performance level were investigated in female and male cross-country skiers during a classical race (10/15 km). Skiers were divided into faster and slower on basis of race performance: females faster (n=20), females slower (n=20), males faster (n=20), and males slower (n=20). Based on video analysis while DP in a flat section of the track, joint and pole angles at pole plant (PP) and pole-off, cycle characteristics and the use and coordination pattern of heel-raise (raise of heels from the ground to have a higher body position at PP) were analysed. Faster females and males had 4.3% and 7.8% higher DP velocity than their slower counterparts (both P<0.001). Faster males had 6.5% longer cycles than slower males (P<0.001). Faster skiers stopped heel-raise later than slower skiers (females: 2.0±3.4% vs. −1.0±3.5%, P<0.05; males: 3.9±2.4% vs. 0.8±3.2% of cycle time in relation to PP, P<0.001). At PP, faster skiers and male skiers had a smaller pole angle and greater ankle to hip and ankle to shoulder angle with respect to vertical, resulting in a more distinct forward body lean. However, the majority of the differences are likely due to higher DP velocity.

This study investigates the feasibility to use a passive marker motion capture system on ice to collect 3D kinematics of slap shots and one timers. Kinematic data were collected within a volume of 40x15x2 m by 20 motion capture cameras at 300 Hz, a resolution of 12 megapixels and a mean residual for all cameras of 3.4±2.5 mm, at a distance of 11.6 m. Puck velocity, blade velocity, ice contact time and distance to the puck were analysed for ten consecutive shots for each technique, for two professional ice hockey players. The total mean puck velocity was 38.0 ± 2.7 m/s vs. 36.4 ± 1.0 m/s. (p=0.053), for one timers and slap shots respectively. One player had higher puck velocity with one timers compared to slap shots 40.5 ± 1.0 m/s vs. 36.9 ± 1.0 m/s (p=0.001). Puck contact time was longer for slap shots than for one timers, 0.020 ± 0.002 s vs. 0.015 ± 0.002 s, (p<0.001). The motion capture system allowed continuous kinematic analyses of the puck and blade velocities, ice contact times and detailed stance information. The results demonstrate the possibilities to use motion capture systems to collect and analyse shooting kinematics on ice, in detail.

Background: Sprint events in cross-country skiing are unique not only with respect to their length (0.8–1.8 km), but also in involving four high-intensity heats of ~3 min in duration, separated by a relatively short recovery period (15–60 min). Objective: Our aim was to systematically review the scientific literature to identify factors related to the performance of elite sprint cross-country skiers. Methods: Four electronic databases were searched using relevant medical subject headings and keywords, as were reference lists, relevant journals, and key authors in the field. Only original research articles addressing physiology, biomechanics, anthropometry, or neuromuscular characteristics and elite sprint cross-country skiers and performance outcomes were included. All articles meeting inclusion criteria were quality assessed. Data were extracted from each article using a standardized form and subsequently summarized. Results: Thirty-one articles met the criteria for inclusion, were reviewed, and scored an average of 66 ± 7 % (range 56–78 %) upon quality assessment. All articles except for two were quasi-experimental, and only one had a fully-experimental research design. In total, articles comprised 567 subjects (74 % male), with only nine articles explicitly reporting their skiers’ sprint International Skiing Federation points (weighted mean 116 ± 78). A similar number of articles addressed skating and classical techniques, with more than half of the investigations involving roller-skiing assessments under laboratory conditions. A range of physiological, biomechanical, anthropometric, and neuromuscular characteristics was reported to relate to sprint skiing performance. Both aerobic and anaerobic capacities are important qualities, with the anaerobic system suggested to contribute more to the performance during the first of repeated heats; and the aerobic system during subsequent heats. A capacity for high speed in all the following instances is important for the performance of sprint cross-country skiers: at the start of the race, at any given point when required (e.g., when being challenged by a competitor), and in the final section of each heat. Although high skiing speed is suggested to rely primarily on high cycle rates, longer cycle lengths are commonly observed in faster skiers. In addition, faster skiers rely on different technical strategies when approaching peak speeds, employ more effective techniques, and use better coordinated movements to optimize generation of propulsive force from the resultant ski and pole forces. Strong uphill technique is critical to race performance since uphill segments are the most influential on race outcomes. A certain strength level is required, although more does not necessarily translate to superior sprint skiing performance, and sufficient strength-endurance capacities are also of importance to minimize the impact and accumulation of fatigue during repeated heats. Lastly, higher lean mass does appear to benefit sprint skiers’ performance, with no clear advantage conferred via body height and mass. Limitations: Generalization of findings from one study to the next is challenging considering the array of experimental tasks, variables defining performance, fundamental differences between skiing techniques, and evolution of sprint skiing competitions. Although laboratory-based measures can effectively assess on-snow skiing performance, conclusions drawn from roller-skiing investigations might not fully apply to on-snow skiing performance. A low number of subjects were females (only 17 %), warranting further studies to better understand this population. Lastly, more training studies involving high-level elite sprint skiers and investigations pertaining to the ability of skiers to maintain high-sprint speeds at the end of races are recommended to assist in understanding and improving high-level sprint skiing performance, and resilience to fatigue. Conclusions: Successful sprint cross-country skiing involves well-developed aerobic and anaerobic capacities, high speed abilities, effective biomechanical techniques, and the ability to develop high forces rapidly. A certain level of strength is required, particularly ski-specific strength, as well as the ability to withstand fatigue across the repeated heats of sprint races. Cross-country sprint skiing is demonstrably a demanding and complex sport, where high-performance skiers need to simultaneously address physiological, biomechanical, anthropometric, and neuromuscular aspects to ensure success.

The purpose of the current study was to explore if training regimes utilizing diverse training intensity distributions result in different responses on neuromuscular status, anaerobic capacity/power and acute heart rate recovery (HRR) in well-trained endurance athletes.

Methods: Thirty-six male (n = 33) and female (n = 3) runners, cyclists, triathletes and cross-country skiers [peak oxygen uptake: (VO_2peak): 61.9 ± 8.0 mL·kg⁻¹·min⁻¹] were randomly assigned to one of three groups (blocked high intensity interval training HIIT; polarized training POL; high volume low intensity oriented control group CG/HVLIT applying no HIIT). A maximal anaerobic running/cycling test (MART/MACT) was performed prior to and following a 9-week training period.

Results: Only the HIIT group achieved improvements in peak power/velocity (+6.4%, P < 0.001) and peak lactate (P = 0.001) during the MART/MACT, while, unexpectedly, in none of the groups the performance at the established lactate concentrations (4, 6, 10 mmol·L⁻¹) was changed (P > 0.05). Acute HRR was improved in HIIT (11.2%, P = 0.002) and POL (7.9%, P = 0.023) with no change in the HVLIT oriented control group.

Conclusion: Only a training regime that includes a significant amount of HIIT improves the neuromuscular status, anaerobic power and the acute HRR in well-trained endurance athletes. A training regime that followed more a low and moderate intensity oriented model (CG/HVLIT) had no effect on any performance or HRR outcomes.

Purpose:

To 1) investigate the cardiorespiratory and metabolic response of trail running and 2) evaluate whether heart rate (HR) adequately reflects the exercise intensity or whether the tissue saturation index (TSI) could provide a more accurate measure when running in hilly terrain.

Methods:

Seventeen competitive runners (female: n=4, V’O_2max: 55±6 mL·kg⁻¹·min⁻¹; male: n=13, V’O_2max: 68±6 mL·kg⁻¹·min⁻¹) performed a time trial on an off-road trail course. The course was made up of two laps covering a total distance of 7 km and included six steep up- and downhill sections with an elevation gain of 486 m. All runners were equipped with a portable breath-by-breath gas analyzer, HR belt, global positioning system receiver and near-infrared spectroscopy (NIRS) device to measure the TSI.

Results:

During the trail run, the exercise intensity within the uphill and downhill sections was 94±2% and 91±3% of HR_max, 84±8% and 68±7% of V’O_2max, respectively. The oxygen uptake (V’O₂) increased within the uphill and decreased within the downhill sections (P< .01). While HR was unaffected by the altering slope conditions, the TSI was inversely correlated to the changes in V’O₂ (r = - .70, P< .05).

Conclusions:

The HR was unaffected by the continuously changing exercise intensity, however, the TSI reflected the alternations in V’O₂. Recently used exclusively for scientific purpose, this NIRS based variable may offer a more accurate alternative to HR to monitor running intensity in the future, especially for training and competition in hilly terrain.

In this study the pacing strategy, cycle characteristics and choice of technique of elite male cross-country (XC) skiers during a three-lap, 15-km classical race with interval start were measured. During the Norwegian Championships in 2016, fast (n = 18, age: 26±4 yr; height: 182±4 cm; body mass: 78±3 kg (means±SD)) and slow skiers (n = 18, age: 22±2 yr; height: 183±5 cm; body mass: 78±6 kg) were video recorded on flat (0), intermediate (3.5) and uphill sections (7.1) of the first and final laps. All skiers adopted a positive pacing strategy, skiing more slowly (11.8%) with shorter cycles (11.7%) on the final than first lap (both p&lt;0.001; pη2 = 0.93 and 0.87, respectively). The fast skiers were 7.0% faster overall (p&lt;0.001, d = 4.20), and 6.1% (p&lt;0.001, d = 3.32) and 7.0% (p&lt;0.001, d = 3.68) faster on the first and final laps, respectively, compared to slower skiers. On all sections of both laps, the fast skiers exhibited 9.5% more rapid (pη2 = 0.74) and 8.9% (pη2 = 0.48) longer cycles (both p&lt;0.001). On intermediate terrain, the fast skiers employed primarily double poling (DP, 38.9% on the first lap) and double poling with a kick (DPKICK, 50% on the final lap). In contrast, the slow skiers utilized for the most part DP alone (lap 1: 33.3%, lap 3: 38.9%) or in combination with other techniques (lap 1: 33.3%, lap 3: 38.9%) and decreased their usage of DPKICK from 27.8% on the first to 16.7% on the final lap. Skiing velocity on flat and intermediate terrain proved to be the best predictor of race performance (p&lt;0.001). In conclusion, during a 15-km classical XC skiing race, velocity and cycle length decreased from the first to the final lap, most extensively on flat terrain and least uphill. Moreover, on the intermediate sections the fast and slow skiers chose to use different techniques.

Introduction Elite alpine skiers frequently adjust insoles, boots and skis to optimize skiing performance. There are numerous different constructions of custom made insoles. However, nobody has, to the authors’ knowledge, investigated the mechanisms behind a plausible performance increase. The purpose of the study was therefore to investigate the potential difference in pressure distribution under the feet when skiing with regular insoles compared to custom made insoles. Method A pre-study investigated differently constructed insoles and their possible effects on the pressure distribution under the feet. One test subject performed different squat and fly-wheel exercises with six differently constructed insoles. Kinetics and 3D-kinematics were collected to identify possible differences. One insole construction, with a flat bottom and a semi-soft upper layer, was thereafter chosen to be used for field tests. Nine professional skiers, including both race skiers and full time ski instructors, were recruited for the field tests. Each skier performed in a randomized order, three runs with a standard insole and three runs with a custom made insole. Plantar pressure under the feet was measured with the Pedar Mobile System at 100 Hz, for eight consecutive carving turns. The skiers were instructed to have the smallest possible time difference between all runs. The three runs for each situation were synchronized and the mean total, forefoot and midfoot pressure distributions were calculated. Results The pre-study results show that the pressure distribution between foot and insole and between insole and ski-boot depends on the insole construction. The mean time for all 54 runs was 26.62 ± 2.41 s and the mean individual time difference between the fastest and the slowest runs was 0.62 ± 0.33 s. All skiers showed large individual differences in percentage of “used” area under the feet, between the two types of insoles (5-80%). When skiing with the custom made insole, the total mean difference in percentage usage of the forefoot was -17 ± 19% and 8 ± 12% for the midfoot. Discussion The results show that the pressure distribution under the feet depends on the type of insole. However, the effect of a custom made insole is very individual. Hence, when performing studies of skiing kinetics and/or equipment, it is of vast importance that all subjects use similarly constructed custom made insoles. It can also be hypothesized that e.g., different canting angles of the ski-boot, affect the skier differently depending on the type of insole. Our suggestion is therefore to perform measurements to optimize the insoles before investigating and optimizing canting angles. The results also show that custom made insoles can assist the skier to utilize different areas of the foot. However, future studies are needed to investigate whether the decreased usage of the forefoot affects the overall aggressiveness of the setup and whether custom made insoles have a positive effect on skiing performance.