Skinner et al. (2019) Int J Res Ex Phys. 15(1):73-86. Sponsored by: Exercise and Sport Science Program Western Colorado University

Effect of Equipment Weight on Energy Cost and Efficiency during Simulated Uphill Touring

Adam D.C. Skinner1, Duncan Koehn1, Christina A. Buchanan1, Lance C. Dalleck1 1High Altitude Exercise Physiology Program, Western Colorado University, Gunnison, CO, USA

ABSTRACT

Purpose The purpose of this study was to quantify changes in energy cost (EC) associated with increased equipment weight during simulated uphill ski touring at a constant speed and grade and to identify potential factors affecting energy cost other than equipment weight. Methods 8 subjects skinned on a treadmill at a constant speed and grade using three different ski touring setups (6.1, 7.9 and 10.4kg in total mass) in a randomized order. Heart rate, respiratory exchange ratio, blood lactate concentration and energy expenditure were measured while subjects maintained a steady state workload. Results A statistically significant positive correlation was found between total weight (setup mass + participant mass) and energy cost (r = 0.501, n = 24, p < 0.05). Non-linear increases were found in EC (13.8, 14.7, 16.3 J kg-1m-1), heart rate (164, 167, 177 bpm) and oxygen consumption (41.8, 44.3, 49.1 mL kg-1min-1) with 6.1, 7.9 and 10.4kg setups respectively. Conclusions A significant relationship exists between equipment weight and measured energy cost of uphill skinning, but a greater increase in workload was observed between the 7.9kg and 10.4kg setups compared to the changes found between the 6.1kg and 7.9kg setups. This may be due to the binding design on the heaviest setup, which was different from the bindings on the two lighter setups. When choosing an equipment setup, recreational ski mountaineers should consider the type of binding used and its potentially greater effect on energy cost compared to equipment weight alone.

KEY WORDS: Exercise Physiology, Ski Touring.

Introduction applied to the bottom of to ascend and Ski touring has become a popular winter ski down terrain not accessible by . leisure activity in mountainous regions all Equipment for ski touring has evolved over the world. Ski touring requires the use substantially in recent years to be lighter and of boots with ankle rotation capabilities, increase locomotion efficiency for the user1. heel-release bindings and adhesive skins Advances in boot and binding design as well

73 Skinner et al. (2019) Int J Res Ex Phys. 15(1):73-86. Sponsored by: Exercise and Sport Science Program Western Colorado University as climbing techniques in uphill have understand exactly how the weight of a led to increases in energy efficiency and skier’s equipment affects energy cost and performance2-4. While saving weight may locomotion efficiency. seem like an effective way to abate energy cost, skiers and manufacturers claim that The aim of the current study was first to add heavier equipment (skis, boots, bindings) to the relatively sparse literature relating to may actually be preferable during the the energy kinematics on ski demanding descents of backcountry ski touring/. Researchers also touring due to their associated performance aimed to determine whether or not characteristics4. equipment weight alone affects energy cost of ski touring and therefore has an impact on Though these studies illustrate there are locomotion efficiency. Additionally, it many factors that affect locomotion addressed whether or not heavier efficiency, only one examined the potential equipment, that may be ideal for effects of equipment weight on energy cost descending, would significantly increase and efficiency during ski touring1. During this energy cost during uphill locomotion. Finally, study weights ranging from 0.5kg to 2 kg researchers aimed to quantify the changes in were attached to participants’ ankles during energy cost and efficiency while climbing repeated uphill bouts on with ski touring setups of different weights. snow at a self-selected pace. Researchers The purpose of this study was to quantify the found that locomotion efficiency in ski effect of ski touring equipment weight on mountaineering changed only slightly with the energy cost of simulated uphill skiing on ankle loading; a 1kg weight added to the a treadmill in male recreational backcountry ankles of an 80kg skier (including gear) skiers. We hypothesized that energy cost of yielded an energy cost increase of 3 percent. uphill locomotion would increase They determined that these changes with proportionately with the added weight of ankle loading appear to be slight in the ski equipment used; that is, utilizing one recreational skiers, but that this energy cost touring setup that weighs more than increase would be accentuated in elite another would yield a proportionately athletes due to their level of energy higher energy cost and therefore decrease expenditure and time spent at high exercise locomotion efficiency. intensities during competition5-7. While the study by Tosi et al.1 was the first and only to Methods examine the effects of loaded weight on Subjects efficiency of ski touring, some aspects of Eight healthy males, skilled and experienced their study could be refined to control for in ski touring and acclimatized to moderate factors that play a role in energy cost elevation (2250m-2750m) took part in this providing the opportunity to better study. All procedures were completed in the

74 Skinner et al. (2019) Int J Res Ex Phys. 15(1):73-86. Sponsored by: Exercise and Sport Science Program Western Colorado University High Altitude Performance Laboratory the study. Researchers gained approval to (HAPLab) on the Western State Colorado conduct this study through the Western University campus (2250m elevation). All State Colorado University Human Research participants took part voluntarily, giving Committee. Mean baseline measurements informed consent prior to participating in of participants appear in Table 1.

Table 1. Descriptive characteristics of the eight participants (mean ± SD).

Maximal Heart VO2max Age (years) Height (cm) Body mass (kg) Rate (beats min-1) (mL∙kg-1∙min-1) 24.0 ± 3.7 181.5 ± 6.2 75.7 ± 6.7 190.0 ± 9.2 62.3 ± 11.1

Experimental Design familiarization session and performed a Participants made two visits to the HAPLab baseline test measuring maximal oxygen

during this repeated measures study. During consumption (VO2max). The familiarization the first session participants completed an session acted as a warm up for the informed consent as well as a physical subsequent graded exercise test. During the activity readiness questionnaire and a health second session participants performed three history questionnaire. Participants were submaximal bouts using three different then familiarized with uphill skiing on the skiing setups in a randomized fashion. Figure treadmill during a low-intensity 5-minute 1 illustrates the design of this study.

− Figure 1. Experimental flow chart of the present study; VO2 - oxygen consumption, [La ]b – blood lactate concentration; RPE – rating of perceived exertion; HR – heart rate.

75 Skinner et al. (2019) Int J Res Ex Phys. 15(1):73-86. Sponsored by: Exercise and Sport Science Program Western Colorado University Procedures USA). Setup 3 (HBC) was a heavy Equipment Setups backcountry setup with a heavy alpine ski

Three different ski setups were utilized (106 175cm, ROMP Skis, CO, USA) a frame during this study. Setup 1 (SKIMO) alpine touring binding (Tracker MNC 16 L, represented a ski mountaineering setup and Atomic, AT), and the same mid-weight alpine consisted of a lightweight ski (Tour Rando touring boot from the LBC setup (Mercury, 178cm, SKI TRAB, Bormio, IT), tech bindings DYNAFIT, CO, USA). Figure 2 illustrates the (TLT ST Demo, DYNAFIT, CO, USA) and differences in design between the two lightweight boots (Alien, SCARPA, CO, USA). binding types used in this study. All setups Setup 2 (LBC) represented a lightweight included a pair of climbing skins (Ascension setup and consisted of a STS, Black Diamond, UT, USA) cut specifically lightweight alpine ski (106 carbon 175cm, for that ski to control for friction between ROMP Skis, CO, USA), tech bindings (TLT ST the ski and treadmill. Measured mass of the Demo, DYNAFIT, CO, USA), and a mid-weight three setups, including skins, is displayed in alpine touring boots (Mercury, DYNAFIT, CO, Table 2.

Table 2. Inter-setup mass comparisons (kg, equipment reported as a pair). % Total Skis, mass bindings, % change Total mass change Setup skins Boots Total from SKIMO (mean ± SD) from SKIMO SKIMO 4.4 1.7 6.1 -- 81.5 ± 6.1 -- LBC 4.8 3.1 7.9 + 29.5% 83.3 ± 6.1 + 2.2% ± 0.1 HBC 7.3 3.1 10.4 + 70.5% 85.8 ± 6.1 + 5.3% ± 0.4

Boots were provided in sizes 27 and 29 Boot and binding adjustments were made (mondopoint). Participants were fit with by a certified ski repair technician. Setup boots prior to the familiarization session. mass was measured using a digital scale.

76 Skinner et al. (2019) Int J Res Ex Phys. 15(1):73-86. Sponsored by: Exercise and Sport Science Program Western Colorado University

Figure 2. Frame bindings (A) vs. tech bindings (B). Note that the frame binding remains attached to the boot during a stride while the tech binding remains attached to the ski and the boot is able to rotate independently.

Participants then underwent a if a subject could not demonstrate familiarization session on the motorized proficiency skiing on the treadmill they treadmill (Fitnex Fitness Equipment, Inc., TX, would be removed from the study as a safety USA). The familiarization session consisted precaution. No participants were removed of three portions: (1) researchers explaining from the study. Participants took part in the equipment fit, use, and treadmill procedures familiarization session while wearing the -1 to participants, (2) slow (less than 1m ∙ s ), SKIMO setup prior to their VO2max test. low grade (less than 10%) uphill locomotion on treadmill using skis while being spotted at Maximal Graded Exercise Test the lower back by researchers, and (3) a self- Following the familiarization session, selected pace locomotion at a steeper grade participants participated in a maximal (15%) on the treadmill for two minutes. graded exercise test using ski touring Participants were instructed by researchers equipment on a treadmill to measure

to select a speed that was comfortable and VO2max. During maximal test boots and that they could sustain for the duration of a bindings were in walk mode to allow for full typical (non-competitive) ski tour. range of uphill striding motion and Participants participated in each portion of participants used the 7-degree heel risers on the familiarization until they demonstrated the provided bindings. The test began at 15% proficiency and gave verbal affirmation that grade with the self- selected speed they felt comfortable with uphill skiing on determined during the familiarization the treadmill. Researchers determined that session. Treadmill grade was increased 3%

77 Skinner et al. (2019) Int J Res Ex Phys. 15(1):73-86. Sponsored by: Exercise and Sport Science Program Western Colorado University per minute until volitional fatigue. Average to allow for full range of uphill striding total test time was 10.1 ± 1.3 minutes (mean motion and participants used the 7- degree

± SD). Oxygen consumption (VO2), carbon heel risers on the provided bindings.

dioxide production (VCO2) and respiratory Researchers calculated participants’ second exchange ratio (RER) were measured using a ventilatory thresholds (VT2) using VE and gas analyzer (True One 2400, Parvomedics, VCO2 measurements obtained during their Sandy, UT, USA). Heart rate and rating of maximal exercise test. Based upon these perceived exertion (RPE) measurements calculations, the submaximal exercise test were taken at the end of every one-minute protocol was developed to keep participants stage during the test. Each subject was given below VT2 while achieving a steady state of verbal encouragement to provide a maximal exercise long enough to collect data effort during this test. Researchers measurements. During this test the treadmill determined that VO2max was attained by was set to the speed and grade verifying that each subject attained an RER corresponding to the 90% of the participants of at least 1.0 and a change in VO2 less than HR at VT2 as determined from their maximal 350 mL∙min-1 between 15-second sampling exercise test. This intensity was reported to periods was observed. Following the be less than that of a competitive ski conclusion of the test, participants mountaineer6 during a race, and was performed a 5-minute cool-down session at intended to simulate a bout of recreational low intensity. Researchers monitored ski touring5,7. Speed and grade means for participants’ heart rate during this cool- submaximal tests were 1.05±0.07 m/s and down period to ensure proper recovery. 25.12±5.1% grade respectively (mean ± SD). Each submaximal bout lasted ten minutes, Submaximal Exercise Protocol which pilot trials and previous studies

Participants returned to the HAPLab for their demonstrated was long enough to reach a second and final visit between 1 day and 1 steady state of exercise2,4. Gas exchange was week after their initial visit. Resting collected on a breath-by-breath basis and measurements (height, body mass, resting averaged in 15-s intervals for analysis. HR, blood lactate) were taken before the Expired gasses were collected and measured submaximal tests. To determine differences during all ten minutes of each submaximal in EC of using ski touring setups of differing bout. HR and RPE were measured once weight all participants performed three during each minute of the test. To ensure separate submaximal treadmill bouts—one data reflected workload parameters at a while using each ski setup (SKIMO, LBC, steady state of exercise, only HR, VO2, and HBC). The order in which participants used RER measurements taken from the final five the three setups was randomized by a minutes of each test were considered. These computer program. During the sub-maximal measurements were subsequently averaged test, boots and bindings were in walk mode and reported as mean measurements for the

78 Skinner et al. (2019) Int J Res Ex Phys. 15(1):73-86. Sponsored by: Exercise and Sport Science Program Western Colorado University corresponding touring setup. Three blood checked for normal distribution using the lactate measurements were taken via finger Kolmogorov-Smirnov test for normality. A prick during the eight, ninth, and tenth Pearson’s r correlation was conducted to minutes of each test (Lactate PLUS, NOVA measure the relationship between total Biomedical, MA, USA). Each submaximal weight and energy cost. A one-way analysis bout was separated by a 15-minute rest of variance (ANOVA) was employed to period during which participants rested determine the effects of the independent passively and researchers were able to variable (ski setup weight) on multiple – change equipment in preparation for the dependent variables (EC, % VO2, [La ]b, HR). subsequent test. Alpha level was set at p<0.05 to determine statistical significance and all confidence Calculating Energy Cost intervals (CI) were set to 95%. After main

EC (J ∙ kg-1∙ m-1) was calculated by the value effect significance was found, a Bonferroni

of oxygen consumption (VO2) (assuming an test was used for post hoc comparisons. IBM

energy equivalent of 20.9 kJ per liter O2) per SPSS 24 statistical software (Armonk, NY) mass unit (body mass plus equipment) was utilized for all data analysis. divided by the speed1-3. This calculation allowed for comparison of energy Results expenditure relative to the body mass, One participant did not complete the study loaded weight and speed during individual due to scheduling conflicts. Data for eight bouts. Two previous studies examining participants who completed the study are optimal slopes and speeds in uphill ski presented. Submaximal tests were ten mountaineering calculated EC in terms of minutes in length. Three [La–]b 2-3 relative vertical displacement . However, measurements were taken during minutes 8, recent studies in which researchers 9, and 10 of each test and were averaged for

quantified EC of ski mountaineering have data analysis. HR, RER, and VO2 values were reported EC in terms of meters traveled, not averaged for the final five minutes of each 1-3 including vertical displacement . test and these average values were used to Therefore, EC in this study was calculated identify changes between the three setups. and reported for linear meters traveled Figure 3 illustrates the steady state VO2 and -1 -1 using the following equation: EC (J∙kg ∙ m ) HR achieved during a typical submaximal -1 -1 -1 = 20.9*VO2 (J∙kg ∙min )/V(m*min ) session on the treadmill. Though researchers had no defined criteria for determining Statistical Analysis whether participants reached a steady state Descriptive statistics were used to of exercise, previous studies have determine the mean, SD, and mean percent demonstrated that 10 minutes is sufficient in change for each of the baseline tests and bringing athletes to a steady state at an 2-4 anthropometric measurements. Data was intensity below VT2 .

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Figure 3. VO2 and HR data for a typical submaximal test. Data for EC calculations and analysis were obtained and averaged in steady state conditions from 5 to 10 min.

Physiological responses as well as energy rate (% HRmax) were calculated by dividing

cost of simulated uphill ski touring using the average VO2 and HR values during their

three provided setups are displayed in Table respective submaximal test by VO2max and 3. Percent of maximal oxygen consumption HRmax attained during the maximal graded (% VO2max) and percent of maximal heart exercise test.

Table 3. Average results for submaximal trials using the three different equipment setups (mean ± SD). EC VO [La–] HR 2 b -1 -1 -1 -1 (J∙kg ∙min ) (mL∙kg ∙min ) % VO2max (mmol) RER (bpm) % HRmax SKIMO 13.8±1.8 41.8±8.2 67.0±4.1 2.1±0.6 0.83±0.02 164 ± 5.9 86.4 ± 3.3 LBC 14.7±2.3 44.3±9.5 70.9±5.5 2.8±1.0 0.85±0.02 167 ± 7.2 87.9 ± 5.2 HBC 16.3±2.4 49.1±9.8 78.9±5.5 3.3±1.0 0.88±0.02 177 ± 7.4 93.3 ± 3.7 #+& #+& #+& & & +& +& − EC - energy cost; VO2 - oxygen consumption; % VO2 MAX – percent maximum oxygen consumption; [La ]b – blood lactate concentration; RER – respiratory exchange ratio; HR – heart rate; %HRMAX – percent maximal heart rate. Statistically significant (p < 0.05) differences in measurements between setups are signified by the following: SKIMO-LBC (#), LBC-HBC (+), SKIMO-HBC (&)

Pearson correlation coefficient was 24, p < 0.05]. The coefficient of calculated for the relationship between total determination (r2 = 0.251) indicated a small weight (body mass + setup weight) and relationship between the two variables, i.e. energy cost. A statistically significant greater total weights were associated with positive correlation was found [r = 0.501, n = greater energy costs of locomotion.

80 Skinner et al. (2019) Int J Res Ex Phys. 15(1):73-86. Sponsored by: Exercise and Sport Science Program Western Colorado University

– Energy cost and % VO2max [La ]b between the SKIMO and HBC setups Energy cost and % VO2max both increased [1.19, CI (0.262, 2.125)] but no significant with each incremental increase in difference between the SKIMO and LBC or equipment setup weight. There was a between the LBC and HBC setups (p>0.05). significant effect of ski setup on EC [F = Similar findings existed for RER, with 30.97, p = 0.001]. Post hoc testing revealed significant differences (p<0.05) between the significant differences (p<0.05) in EC SKIMO and HBC setups [0.04, CI (0.009, between the SKIMO setup and both the LBC 0.08)] and no significant difference between [0.82, CI (0.51, 1.58)] and HBC setups [2.43, the SKIMO/LBC or LBC/HBC setups (p>0.05). CI (1.38, 3.47)], as well as a significant

difference between the LBC and HBC setups Heart rate and % HRmax [1.61, CI (1.00, 2.23)]. Figure 4a illustrates There was a significant effect of setup on HR differences in mean EC between the three and % HRmax [F = 23.31, p = 0.001; F = 23.65, equipment setups. There was a significant p = 0.001, respectively]. For changes in HR, effect of setup on % VO2max [F = 28.23, p = post hoc tests revealed statistically 0.001] and post hoc tests showed similar significant (p<0.05) differences between the significant differences (p<0.05) between the SKIMO and HBC [13.1, CI (7.40, 18.86)] and three setups [SKIMO vs LBC: 3.9, CI (0.50, the LBC and HBC [10.6, CI (2.73, 18.41)] 7.20); SKIMO vs HBC: 11.9, CI (7.00, 16.80); setups, suggesting that the HBC setup LBC vs HBC: 8.0, CI (4.70, 11.30)]. These data elicited moderate to large increases in HR suggest that there are greater increases in compared to the SKIMO and LBC setups. both EC and % VO2max between the LBC and However, no significant difference was HBC setups than between the SKIMO and found in HR between the SKIMO and LBC LBC setups. Figure 4b shows the increase in setups (p>0.05). Post hoc tests showed

% VO2max between the SKIMO, LBC, and similar results for % HRmax, with statistically HBC setups. significant (p<0.05) changes between the SKIMO and HBC [6.9, CI (3.9, 9.8)] as well as Blood lactate and RER LBC and HBC [5.4, CI (1.4, 9.4)] setups, and There was a significant effect of setup on no significant differences between the both [La–]b and RER [F = 7.20, p = 0.025; F = SKIMO and LBC setups (p>0.05). Figure 4c 6.74, p = 0.029, respectively]. Post hoc tests shows mean changes in % HRmax between revealed a significant difference (p<0.05) in the three equipment setups.

81 Skinner et al. (2019) Int J Res Ex Phys. 15(1):73-86. Sponsored by: Exercise and Sport Science Program Western Colorado University

Figure 4. Mean differences in energy cost (4a), percent maximal oxygen uptake (4b), and percent maximal heart rate (4c) between the SKIMO, LBC, and HBC equipment setups. * indicates significant (p<0.05) differences between the two designated setups only. ** indicates significant (p<0.05) differences between all equipment setups.

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Discussion touring and determined how changes in Our findings support the hypothesis that those components affect energy cost and energy cost increases with equipment efficiency of uphill skinning. The findings of weight, i.e. using heavier ski touring Schwameder et al.4 show effects of touring equipment setups elicits significant equipment on energy cost similar to those in increases in oxygen consumption, heart rate the current study. They found that and therefore energy cost. However, these mechanical energy required to lift the ski observed increases in energy cost were not boot was significantly higher when using a proportional to the increase in total frame touring binding similar to those in the equipment weight. While the greatest HBC setup (3.51 J) compared to a tech changes were observed between the SKIMO binding similar to SKIMO and LBC setups and HBC setups, the most noteworthy (1.96 J). Their data on locomotion using the differences were found between LBC and three different bindings with identical skis HBC setups with averages of 1.6 J∙kg-1∙m-1 support these findings with significantly

higher energy cost, 9% greater relative VO2, higher metabolic cost of using the frame and 5.4% greater relative HR when using the binding compared to the tech bindings. HBC setup compared to the LBC setup. A These findings are analogous with results significant difference in EC was found from the current study; though we expected between the SKIMO and LBC setups, but to a to see an increase in energy cost with setup lesser degree (p = 0.038) than between the weight, this increase was greater between LBC and HBC setups (p = 0.001). the LBC and HBC setups compared to the SKIMO and LBC setups, perhaps due to These findings show that while there are presence of the frame binding, not just a substantial increases in physiological heavier setup. workload when climbing with heavier ski touring setups, the most profound increases Another study using ankle loading to elicit were found between the LBC and HBC changes in energy cost during uphill skiing setups. With incremental increases in overall showed that with loads of 0.5, 1, and 2 kg setup weight, researchers expected to see added to each ankle, energy cost increased proportional increases in EC and other in a linear manner1. These researchers found workload markers. However, this a significant linear relationship (n = 21, r = significantly larger increase from LBC to HBC 0.58, p < 0.05) between ankle loading and EC setup suggests that setup weight alone is not and expressed their relationship with the the only factor influencing EC and efficiency following equation: %EC=1.71%weight. In of locomotion during uphill ski touring. the current study, the LBC and HBC setups increased subject’s total weight an average In recent studies, researchers have observed of 2.2% and 5.3% from the SKIMO setups, different locomotion components of ski respectively. Based upon the

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aforementioned study, EC increases from 5% of their HRmax. Previous studies the SKIMO setup should have been around examining workload during ski 4% for the LBC setups and 9% for the HBC mountaineering races show that well trained setup. Data shows actual mean energy cost and national level competitive ski

increases from SKIMO to be 6.5% for LBC and mountaineers have VO2max values near 68 18% for HBC setups. This non-linear increase mL∙kg-1∙min-1 (compare to 63 ± 11.1 mL∙kg- in EC, with respect to equipment weight, 1∙min-1) for participants in the current study) supports the previous statement about the and high ventilatory thresholds (VT2 @ 90% possibility of a factor other than total VO2max compared to VT2 @ 82 ± 7% VO2max equipment weight affecting EC. for participants in the current study) which allow them to perform at high intensities6-8. One substantial difference that should be A study examining race time spent between noted is the method of increasing weight in ventilatory thresholds showed that 7% of a the study by Tosi et al.1 compared to the ski mountaineering race was spent below current study, in which weight was added to VT1, 51% was spent between VT1 and VT2, 5 each setup by changing the actual and 42% was spent above VT2 . These equipment used. The researchers believe measurements indicate that researchers in that using heavier equipment more the current study were able to keep accurately represents changes that would participants at a workload less than that take place with recreational skiers. Tosi et exhibited during competitive ski al.1 also state that effects on energy cost mountaineering. This, in conjunction with from ankle loading appear negligible for the results of the current study, further recreational skiers. Based upon the findings verifies that changes in equipment during of the current study, energy cost during recreational ski touring can elicit significant submaximal uphill climbing does, in fact, changes in energy cost. change with 1.8 and 4.3 kg increases in setup weight. Researchers do agree with the To the researcher’s knowledge, this is the statement by Tosi et al.1, however, that second study of its kind to use a treadmill changes in energy cost in response to with real skis/skins to examine energy cost increases in equipment weight would be and other workload indicators. This exacerbated in elite-level athletes and methodology was advantageous in providing during competition when athletes are researchers the ability to conduct maximal performing at a significantly higher tests in a laboratory setting as well as workload. controlling speed, grade, and friction between the skins and the ground—three During the submaximal bouts in the current factors that Tosi et al.1 suggest could be study, participants were working at an controlled for in future research. Previous

average of 72 ± 7% of their VO2max and 89 ± studies have used roller skis modified with

84 Skinner et al. (2019) Int J Res Ex Phys. 15(1):73-86. Sponsored by: Exercise and Sport Science Program Western Colorado University ski touring bindings on treadmills1-2 or real between the skin and treadmill. The shape skis on snow3,5,8. The study by Schwameder and surface area of the skis and skins used et al.4 is the only other study to use touring during the current study were not skis on a treadmill, though it is unclear controlled. The SKIMO setup used skis with a whether or not skins were used in addition width of 68mm underfoot that had a to the skis. Changes in energy cost and other cambered profile, while the LBC and HBC markers of workload observed in the current setups used a ski with a width of 106mm study demonstrate that increases in ski underfoot and a rockered profile. This touring equipment weight of 1.8 kg and 4.3 difference in shape and construction could kg are associated with increases in workload have affected the surface area of the skin and energy cost. The use of a different boot contacting the treadmill, the associated and binding system for one of the three friction, and potentially the energy cost of setups appeared to increase energy cost and locomotion. heart rate disproportionately compared to the increase in setup weight, suggesting that The findings of this study add to the binding design and distribution of added relatively sparse literature on the energy equipment weight may significantly impact cost of ski touring and ski mountaineering; uphill efficiency when ski touring. and demonstrate the importance of further research in this field. Future research on ski While the design of this study gave touring should examine how binding design researchers the ability to control for speed alone (frame vs. tech) impacts economy in and grade, and to measure relative touring setups of identical total weight. workloads for each subject, it was not Additionally, field tests measuring total without its limitations. Due to equipment energy expenditure during a complete tour availability, distribution of setup mass and would be beneficial to researchers and incremental mass differences between recreational athletes as a means of touring setups could not be controlled. It determining how these demonstrated should also be noted that, while changes in changes in energy cost affect performance energy cost between setups are valid, over the course of a long, real-world ski tour. skinning on a treadmill compared to snow Finally, quantifying downhill skiing might elicit greater energy requirements due performance of different touring setups to the amount of friction during the forward would help identify how individual pieces of glide phase of the stride. Participants equipment might be detrimental to uphill informally reported that the skis did not efficiency, but beneficial for downhill glide as easily on the treadmill as they were performance and reliability thereby accustomed to on snow. However, identical rationalizing the increased cost of the uphill skins were used in all three setups, thus portion. controlling for any changes in the friction

85 Skinner et al. (2019) Int J Res Ex Phys. 15(1):73-86. Sponsored by: Exercise and Sport Science Program Western Colorado University Conclusion appears to play a substantial role in It can be concluded that increases in determining economy and efficiency during equipment weight are associated with uphill ski touring. Further research is needed significantly greater energy cost, heart rate, to verify these claims and to determine the and oxygen consumption during uphill ski effect of binding design on energy cost of touring. Tosi et al.1 demonstrated that uphill ski touring. added ankle weight increases energy cost of Address for Correspondence uphill skiing. However, disproportional Lance Dalleck, Ph.D., High Altitude Exercise increases in workload as well as the findings Physiology Program, 600 N. Adams St., Western 4 of Schwameder et al. demonstrate that Colorado University, Gunnison, CO, United States, weight may not be the only factor impacting 81231. Phone: 970-943-3095; energy cost of locomotion. Binding design Email: [email protected].

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