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The influence of speed, grade and mass during simulated off road bicycling
Applied Ergonomics 31 (2000) 531}536
The in#uence of speed, grade and mass during simulated o! road bicycling Michael J. Berry*, Timothy R. Koves, John J. Benedetto Department of Health and Exercise Science, Wake Forest University, Winston-Salem, NC 27109-7868, USA Received 3 September 1999; accepted 14 January 2000
Abstract The purpose of this investigation was to examine the e!ects of bicycle mass, speed, and grade on oxygen consumption (V O ), heart rate (HR), and ratings of perceived exertion (RPE) during a simulated o!-road riding paradigm. Nine adult subjects with mean $ SD age, mass, and V O max of 26.1$5.6 years, 71.7$7.5 kg, 56.6$5.2 ml ) kg\ ) min\, respectively, were trained to ride a fully suspended Trek Y-22 mountain bike on a treadmill with a 3.8 cm bump a$xed to the belt. Riders completed a maximum of nine separate trials encompassing three di!erent bike masses (11.6, 12.6 and 13.6 kg), 3 speeds (2.7, 3.6 and 4.5 m ) s\), and 3 grades (0, 2.5, and 5%). Throughout a trial, bike mass and speed remained constant while riding grade was increased every 5 min. During simulated o!-road riding on a fully suspended mountain bike, increases in speed and grade signi"cantly increased V O , heart rate, and RPE. Increases in bike mass had no signi"cant e!ects on V O , heart rate or RPE. In addition, speed and grade changes interacted to di!erentially a!ect V O , heart rate, and RPE at all speeds and grades. 2000 Elsevier Science Ltd. All rights reserved. Keywords: Oxygen consumption; Bicycle mass; Energy expenditure; Mountain bike; Cycling
1. Introduction The factors that a!ect energy expenditure during road cycling have been well characterized. They include: (1) rolling resistance, or the resistance due to deformation of the tire, wheel and road; and bearing and chain drag, (2) air resistance, which is the drag caused by the bike}rider system moving through the air and (3) gravitational e!ects of ascents or descents on the bike}rider system. The e!ect of these factors on energy expenditure was originally expressed mathematically by di Prampero et al. (1979), and more recently by Swain (1994) as factor 1 factor 2 factor 3 Energy cost"(k Ps)#(k Avs)#(gPIs) where k is the rolling resistance coe$cient, P the com bined mass of cyclist and bicycle, s the bicycle road speed, k the air resistance coe$cient, A the cyclist's surface area, v the bicycle speed in air, g the acceleration of gravity and I the road incline.
* Corresponding author. Tel.: #336-758-5847; fax: 336-758-4680. E-mail address: [email protected] (M.J. Berry).
The force required to overcome rolling resistance is in#uenced by the mass of the bike}rider system such that as mass increases so does the force required to overcome this resistance. Kyle suggested that at a given force output the addition of as little as 1 kg of mass to a road bicycle could decrease speed as a result of an increase in rolling resistance (1991). The force required to overcome air resistance is the greatest contributor to the energy cost of level road cycling and increases rapidly with speed. Hagberg and McCole (1996) reported that air resistance accounts for less than 20% of the total resistance to movement at speeds less than 10 km/h. However, at speeds of 20 and 40 km/h, air resistance accounts for 54 and 82% of the total resistance, respectively. The force required to overcome gravity is the third factor and is also in#uenced by the mass of the bike}rider system such that as mass increases so does the force required to overcome this resistance. Howe (1995) estimated that during uphill road cycling gravity may account for more than 90% of the resistance to motion. Additionally, he estimated that reducing the weight of the bicycle by using lightweight parts could signi"cantly improve performance during uphill road cycling.
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M.J. Berry et al. / Applied Ergonomics 31 (2000) 531}536
From the above discussion, it is clear that air resistance and mass are determinants of the energy cost of road cycling. How these factors a!ect o! road cycling performance has not been well documented. Typically, the speeds reached during o! road cycling are much less than those achieved on the road, and, as such, the e!ects of air resistance do not add signi"cantly to the energy cost. Furthermore, strategies used by road cyclists to obviate the e!ects of speed (i.e. drafting) are not applicable during o! road cycling. Therefore, one of the strategies adopted by o! road cyclists to improve performance is to decrease the mass of the bike as much as possible. Previously, it was demonstrated that the use of a welldesigned suspension system would decrease the energy cost during simulated o! road cycling (Berry et al., 1993). However, a potential problem with the use of such systems is that they usually add additional mass to the bike potentially increasing the force required to overcome the increased rolling resistance and the increased resistance due to gravity. Thus, it appears that the two strategies used by o! road cyclists to decrease energy expenditure, use of a suspension system and the decrease in bike mass, are diametrical. Therefore, the purpose of this investigation was to determine the e!ects of bike mass on the energy cost of simulated o! road cycling at di!erent speeds and grades.
2. Methods 2.1. Subjects Subjects for this study consisted of 8 males and 1 female. All were avid o! road cyclists, were informed of their rights as subjects, and signed an informed consent form approved by Wake Forest University's Institutional Review Board. The mean ($SD) age, mass, height and maximal oxygen consumption of the subjects was 26.1$5.6 years, 177.5$6.6 cm, 71.7$7.5 kg and 56.6$5.2 ml ) kg\ ) min\, respectively. 2.2. Procedures The test bike was an 18 in, fully suspended, stock equipped Trek Y-22 (Trek USA) mountain bike having a mass of 11.6 kg. Prior to experimental testing, all subjects were taught to ride the test bike on a 3 hp Quinton 18}60 treadmill capable of speeds up to 7.1 m ) s\ (15 miles ) h\). The belt area available for riding was 188 cm long by 44.5 cm wide. As a safety precaution, the front rail of the treadmill was out"tted with a tether that was attached to the handlebar stem of the bike. The tether restricted the rearward travel of the bicycle on the treadmill belt so riders would not fall o! the back. Riders were instructed to maintain slack in the tether during all
rides. As a further precaution, two spotters were positioned on either side of the treadmill to aid in controlling unwanted lateral movements of the bike and rider during practice and testing sessions. All subjects were allowed to practice riding the testing bike on the treadmill until they felt comfortable. Once riders felt comfortable riding on the treadmill, a 44.5 cm long by 3.8 cm by 8.9 cm wooden board was taped to the belt of the treadmill. This yielded a 3.8 cm high obstacle that the riders traversed with every full revolution of the treadmill belt. Again, subjects were allowed to practice until they felt comfortable riding under this condition. These practice sessions were necessary to ease subject apprehensions and to allow baseline measures in the study to minimally re#ect anxiety about the novel testing mode. For the experimental testing, each subject visited the laboratory on a maximum of ten occasions. All subjects were asked to refrain from exercising for 24 h prior to testing and not to eat 3 h prior to testing. During the "rst visit to the laboratory, height and mass determinations were made on all subjects. Additionally, each subject adjusted the seat height of the test bicycle such that it approximated that of his or her personal bicycle. Once this height had been determined, all subsequent trials were performed at that seat height. Handlebar position for each rider remained constant. Subjects then completed a maximal oxygen consumption test on the bike and treadmill without the bump attached. Subjects started riding at 3.1 m ) s\ (7 miles ) h\) and 0% grade with speed increased by 1 mile/h each minute thereafter until the subjects reached a speed of 5.8 m ) s\ (13 miles ) h\). Grade was then increased by 1% each minute thereafter until volitional fatigue. Oxygen consumption was monitored continuously throughout this test. On subsequent visits, subjects completed a maximum of nine experimental trials encompassing three bike masses (11.6, 12.6, 13.6 kg), three speeds (2.7, 3.6 and 4.5 m ) s\ (6, 8, 10 miles ) h\)), and three grades (0, 2.5, 5%) presented in a randomized fashion for mass and speed. Within a given trial, riders pedaled the bike at a set mass and speed for 5 min at 0% grade after which time the grade was increased by 2.5% each 5 min thereafter. The three grades investigated were presented in ascending order so that the increased e!ort that would be required at the higher grades would not mask e!ects at lower workloads. At the three speeds of 2.7, 3.6 and 4.5 m ) s\, the frequency of bump impacts was 39, 52 and 65/min, respectively. Subjects were asked to select their choice of gear and preferred cadence during the initial minute of each stage and to maintain that selected gear and cadence for the duration of the stage. As the speed of the treadmill was maintained throughout each stage and subjects were not allowed to change gears during each stage, this insured that cadence was maintained during each stage. Oxygen consumption values, heart rates, and
M.J. Berry et al. / Applied Ergonomics 31 (2000) 531}536
ratings of perceived exertion were recorded during the last two minutes of each stage. Values for minutes 4 and 5 for all three dependent variables were averaged to obtain a single value representative for the particular stage. During all trials, heart rates were monitored using a Physio-Control Lifepak 5 heart rate monitor. Ratings of perceived exertion were taken during minutes 4 and 5 of each 5 min stage according to the methods of Borg (1973). In some instances, multiple trials were performed within the same visit. If this occurred, subjects were given at least 20 min between trials to allow recovery of oxygen consumption values, heart rates, and perceived exertion to baseline values. Mass was added to the bike by attaching a water bottle "lled with either 1 or 2 kg of lead shot. The water bottle was a$xed to the bike along the center tube secured by a standard water bottle cage. The 26 in wheels and tires that came standard with the bike were used during all trials. Tire pressures were maintained at 45 lb/in throughout the course of the study to minimize di!erences in e!ects due to rolling resistance. The subjects mass was maintained constant throughout the study via addition/subtraction of water mass from a 2 l Camelbak water carrier that the subjects wore. The subjects wore the Camelbak containing 1 l of water during the initial maximal oxygen consumption test. This mass was then used as the reference mass for all subsequent testing. The treadmill was calibrated according to the manufacturer's recommendations periodically throughout the study period. Three of the riders completed all their rides with oxygen consumption being measured using a Medical Graphics CPX automated gas analysis system. The remaining six riders in the study completed all their rides with oxygen consumption being measured using a Medical Graphics CardiO automated gas analysis system. Calibrations of the pneumotachograph and analyzers for the CPX and CardiO systems were performed according to the manufacturer's speci"cations. On-line computer analysis for the determination of oxygen consumption was performed by the host computer system and displayed breath-by-breath during all tests. 2.3. Statistical analyses A three way analysis of variance (ANOVA), with mass, grade, and speed as the independent variables, was used to test for signi"cant di!erences in the following dependent variables: oxygen consumption, heart rate, and ratings of perceived exertion. If the omnibus test was found signi"cant, simple main e!ects and Newman-Keuls post hoc procedures were used to determine the exact nature of the di!erences among experimental means. The experiment-wise alpha level was set at the 0.05 signi"cance level.
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3. Results 3.1. Oxygen consumption The results of the three way ANOVA showed no signi"cant interaction among bike mass, speed or grade. There was, however a signi"cant interaction between speed and grade (see Fig. 1). When examining the e!ect of bike mass on oxygen consumption, no signi"cant di!erences were found among the three di!erent bike masses (see Table 1). To examine the interaction between speed and grade, mass was collapsed across both factors since it had no e!ect on oxygen consumption and was not found to
Fig. 1. The e!ects of speed and grade, when collapsed across bike mass, on oxygen consumption.
Table 1 Values for oxygen consumption (V O ), heart rate and rating of per ceived exertion (RPE) when riding the bikes of di!erent masses Bike Mass
V O , ml ) kg\ ) min\ Heart rate, beats min\ RPE
11.6 kg
12.6 kg
13.6 kg
30.3$0.7 135.6$1.7 10.0$0.2
29.8$0.7 132.6$1.9 10.0$0.2
30.6$0.7 136.5$1.8 10.1$0.2
All values are mean$SEM and are collapsed across the three speeds (2.7, 3.6 and 4.5 m ) s\) and three grades (0, 2.5 and 5.0%). No signi"cant di!erences were found among the di!erent bike masses for any of the variables.
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interact with speed, grade or speed and grade. When examining the interaction between speed and grade (see Fig. 1), oxygen consumption was found to increase significantly at each speed with increases in grade (i.e., at 2.7, 3.6 and 4.5 m ) s\, oxygen consumption increased significantly with each increase in grade). Oxygen consumption was also found to be signi"cantly di!erent among the three di!erent speeds at each grade (i.e., at 0, 2.5 and 5% grade, oxygen consumption was signi"cantly greater at each speed). As can be seen in Fig. 1, the changes in oxygen consumption among the di!erent speeds become progressively larger as the grade increases. 3.2. Heart rate The results of the three way ANOVA showed no signi"cant interaction among bike mass, speed or grade. There was, however a signi"cant interaction between speed and grade (see Fig. 2). When examining the e!ect of bike mass on heart rate, no signi"cant di!erences were found among the three di!erent bike masses (see Table 1). To examine the interaction between speed and grade, mass was collapsed across both factors since it had no e!ect on heart rate and was not found to interact with speed, grade or speed and grade. When examining the interaction between speed and grade (see Fig. 2), heart rate was found to increase signi"cantly at each speed with increases in grade (i.e., at 2.7, 3.6 and 4.5 m ) s\, heart rate increased signi"cantly with each increase in grade). Heart rate was also found to be signi"cantly di!erent among the three di!erent speeds at each grade (i.e., at 0, 2.5 and 5% grade, heart rate was signi"cantly
Fig. 2. The e!ects of speed and grade, when collapsed across bike mass, on heart rate.
greater at each speed). As can be seen in Fig. 2, the changes in heart rate among the di!erent speeds became progressively larger as the grade increased.
3.3. Rating of perceived exertion The results of the three-way ANOVA showed no signi"cant interaction among bike mass, speed or grade. There was, however a signi"cant interaction between speed and grade (see Fig. 3). When examining the e!ect of bike mass on rating of perceived exertion, no signi"cant di!erences were found among the three di!erent bike masses (see Table 1). To examine the interaction between speed and grade, mass was collapsed across both factors since it had no e!ect on rating of perceived exertion and was not found to interact with speed, grade or speed and grade. When examining the interaction between speed and grade (see Fig. 3), rating of perceived exertion was found to increase signi"cantly at each speed with increases in grade (i.e., at 2.7, 3.6 and 4.5 m ) s\, rating of perceived exertion increased signi"cantly with each increase in grade). Rating of perceived exertion was also found to be signi"cantly di!erent among the three di!erent speeds at each grade (i.e., at 0, 2.5 and 5% grade, rating of perceived exertion was signi"cantly greater at each speed). As can be seen in Fig. 3, the changes in rating of perceived exertion among the di!erent speeds become progressively larger as the grade increases.
Fig. 3. The e!ects of speed and grade, when collapsed across bike mass, on rating of perceived exertion.
M.J. Berry et al. / Applied Ergonomics 31 (2000) 531}536
4. Discussion The purpose of this experiment was to systematically examine the e!ects of changes in mountain bike mass on oxygen consumption, heart rate, and ratings of perceived exertion at di!erent speeds and grades during a simulated o!-road riding paradigm. Three di!erent bicycle masses were tested at three di!erent speeds and three di!erent grades. Increasing the mass of a fully suspended mountain bike from a stock mass of 11.6}12.6 and "nally 13.6 km had no signi"cant e!ect on oxygen consumption when examined across speeds of 2.7, 3.6, and 4.5 m ) s\ and across grades of 0, 2.5 or 5%. Furthermore, neither heart rate responses nor reported rates of perceived exertion were signi"cantly a!ected as a result of increasing the mass of the bicycle. In addition, no interaction was found between bike mass and grade or bike mass and speed for any of the dependent variables. When the bicycle mass was collapsed across the three di!erent speeds and grades tested, speed and grade were found to interact to a!ect oxygen consumption, heart rate and ratings of perceived exertion di!erentially. This study was a limited laboratory simulation such that a small bump was added to the treadmill and ridden over repeatedly at regular intervals. While this design o!ered a number of advantages, such as ease of data collection and greater control over the speed at which the riders rode, there were several disadvantages. A primary limitation is that the simulation did not truly represent o! road riding. While bumps are frequently encountered during o! road riding, the frequency with which they are encountered and the size of the bumps will vary. Our constant frequency and size could have resulted in compensation in pedal rate and/or the riding style of the rider. While this may have occurred, we feel that these results still provide important information regarding o! road bicycling. However, the results should be interpreted in light of this limitation. Because this was a laboratory simulation and the experiments were carried out on the treadmill, the second term of the equation of motion (di Prampero et al., 1979) is forced to zero. The equation then reduces to: Energy cost"(Ps)(k #gI), where k is the rolling resistance coe$cient, P the com bined mass of cyclist and bicycles, s the bicycle road speed, g the acceleration of gravity and I the road incline. It was hypothesized that the bike mass would have signi"cantly a!ected the physiological variables of oxygen consumption and heart rate. According to the above equation, bicycle mass comprises a part of the bike}rider system mass, and it, along with speed will a!ect both the rolling resistance and gravitational components of total energy cost. Kyle (1991) noted that during competitive road cycling the addition of as little as 1 kg to the mass of a bicycle on #at terrain could decrease bicycle speed due
535
to increases in rolling resistance. Also supporting this hypothesis, Howe (1995) estimated that the reduction in mass could signi"cantly improve uphill cycling performance. A closer examination of the above equation reveals that mass changes of 1}2 kg will have minimal e!ects on the oxygen consumption of a cyclist riding on a relatively smooth surface. While the original equation of di Prampero et al. (1979) was developed based on riding a road racing bike on a relatively smooth surface outdoors, the reduced above equation was used to estimate oxygen consumption at the di!erent speeds, grades and masses used in this investigation. This was done by taking the average mass of the cyclists in this investigation and adding it to the bike masses of 11.6, 12.6 and 13.6 kg to obtain bike and rider masses. A coe$cient of rolling resistance equal to 0.013 instead of the coe$cient of rolling resistance of 0.0086 as suggested by di Prampero et al. (1979) was also used. This was due to the fact that Kyle (1986) calculated the coe$cient of rolling resistance for a 26 in knobby tire, similar to that found on the Trek Y22, to be 0.013. Applying these factors and the speeds and grades used in this investigation, the expected oxygen consumption for each speed, grade and mass was calculated. Using this approach, it was found that any speed or grade di!erences in oxygen consumption between the di!erent bike masses were less than 1 ml ) kg\ ) min\. That is to say, increases in bike mass had a negligible e!ect on oxygen consumption irrespective of speed and grade. Howe (1995) estimated that over the course of a 1 h ride up a 12.1% grade a cyclist could save 42.7 s with a 1 kg reduction in bicycle weight. Based on Howe's data and methods (1995), this 1 kg reduction in bicycle weight would result in an approximately four watt power reduction if the cyclist were to complete the course in the same amount of time while riding the lighter bike. This 4 W power reduction equates to a less than 1 ml ) kg\ ) min\ oxygen consumption saving, similar to that we estimated. This expected di!erence of less than 1 ml ) kg\ ) min\ is smaller than the average measurement error expected when measuring oxygen consumption (Howley et al., 1995). The interaction between speed and grade found in this study is described in the equation of motion of a cyclist by di Prampero et al. (1979) and in an equation developed by Hagberg et al. (1978) to predict oxygen consumption when riding a bicycle on a motor driven treadmill. Additionally, the equation by di Prampero et al. (1979) shows that the energy cost of cycling should be directly proportional to the mass of the cyclist and bicycle and that mass, bike speed and grade should all interact. The fact that mass did not interact is most likely due to the fact that the variations in mass were so small. Based on the equations, larger changes in mass would have most likely resulted in an interaction among mass, bike speed and grade. However, larger changes in mass
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would have hurt the validity of the study in the bicycling community since the range of masses used in this investigation are representative of the masses of bikes being sold today. If the speeds, grades and masses of the bike and riders used in this investigation are used to calculate the expected oxygen consumption from the equations by di Prampero et al. (1979) and Hagberg et al. (1978), when graphed they demonstrate the same pattern as the data in Fig. 1. Examination of Fig. 1 shows that as the grade increases the di!erence in oxygen consumption at di!ering speeds becomes greater. The oxygen consumption values obtained in this investigation are 7 to 20 ml ) kg\ ) min\ higher than those calculated from the equation of motion of a cyclist by di Prampero et al. (1979) and in an equation developed by Hagberg et al. (1978). The higher oxygen consumption values measured at each of the speeds and grades in this investigation compared to those calculated from the equations of di Prampero et al. (1979) and Hagberg et al. (1978) are probably due to an increase in rolling resistance. The coe$cient of rolling resistance for knobby tires suggested by Kyle (1986) would only increase oxygen consumption by 1 to 2 ml ) kg\ ) min\ compared to the coe$cient of rolling resistance suggested by di Prampero et al. (1979). Therefore, it appears that the greatest contributor to this 7}20 ml ) kg\ ) min\ increase in oxygen consumption is the energy required to traverse the bump. Deformation of the wheel, tire and road at the point of contact is the cause of rolling resistance. Energy is lost when the wheel, tire and surface do not spring back elastically and fail to return all the lost energy to the bicycle (Kyle, 1986). Contact with the 3.8 cm bump on the treadmill would obviously cause a greater deformation compared to rolling on a smooth surface. In a previous investigation examining the use of a suspension system and oxygen consumption, a 10.9 ml ) kg\ ) min\ (41%) increase in oxygen consumption was found when comparing riding an o! road bicycle with knobby tires on a treadmill with a 3.8 cm bump at 2.9 m ) s\ and 4% grade to riding a bicycle with knobby tires on a treadmill with no bump at 2.9 m ) s\ and 4% grade (Berry et al., 1993). Based on this previous "nding it appears as if the di!erences between the measured oxygen consumption values and those estimated from the equation of motion of di Prampero et al. (1979) are due to the increased rolling resistance of the bump. A problem with this investigation was the fact that the expected di!erences in oxygen consumption were smaller than the error found in measuring oxygen consumption. Subsequently, the study runs into a signal to noise problem. Unfortunately, techniques for determining such small di!erences in oxygen consumption, if they do in-
deed exist, are not available. Even if the technology were available to measure these hypothesized di!erences, there is a question of whether these proposed di!erences would be of practical signi"cance. Given the fact that oxygen consumption is but one factor that in#uences cycling performance, additional studies should evaluate whether changes in bicycle mass have e!ects that may be of more practical signi"cance to riders, such as place of "nish. Future studies should also be directed toward determining what e!ects, if any, are due to increases in mountain bike mass using fully suspended bicycles lighter than 11.6 kg. It would also be of interest to have riders bike at grades greater than 5% to determine if additional mass has a greater or di!erential e!ects as gravitational forces are increased. In addition, with the advent of portable metabolic measuring devices, future experiments should be conducted in the "eld over a variety of terrains to assess which factors are most related to increases in energy expenditure.
Acknowledgements This work has been supported in part by a grant from Trek USA.
References Berry, M.J., Woodard, C.M., Dunn, C.J., Edwards, D.G., Pittman, C.L., 1993. The e!ects of a mountain bike suspension system on metabolic energy expenditure. Cycling Sci. 5, 8}14. Borg, G.A., 1973. Perceived exertion: a note on `historya and methods. Med. Sci. Sports 5, 90}93. di Prampero, P.E., Cortili, G., Mognoni, P., Saibene, F., 1979. Equation of motion of a cyclist. J. Appl. Physiol. 47, 201}206. Hagberg, J.M., Giese, M.D., Schneider, R.B., 1978. Comparison of the three procedures for measuring VO2 max in competitive cyclists. Eur. J. Appl. Physiol. 39, 47}52. Hagberg, J.M., McCole, S., 1996. Energy expenditure during cycling. In: Burke, E.R. (Ed.), High-Tech Cycling. Human Kinetics, Champaign, IL, pp. 167}184. Howe, C.R., 1995. Course terrain and bicycle set-up. Cycling Sci. 6, 14}26. Howley, E.T., Bassett, D.R.J., Welch, H.G., 1995. Criteria for maximal oxygen uptake: review and commentary. Med. Sci. Sports Exercise 27, 1292}1301. Kyle, C., 1986. Mechanical factors a!ecting the speed of a cycle. In: Burke, E.R. (Ed.), Science of Cycling. Human Kinetics, Champaign, IL, pp. 123}136. Kyle, C.R., 1991. Ergogenics for bicycling. In: Lamb, D.R., Williams, M.H. (Eds.), Perspectives in Exercise Science and Sports Medicine Vol. 4: Ergonomics-Enhancement of Performance in Exercise and Sport. Wm. C. Brown, Indianapolis, IN; pp. 373}419. Swain, D.P., 1994. The in#uence of body mass in endurance bicycling. Med. Sci. Sports Exercise 26, 58}63.
The in#uence of speed, grade and mass during simulated o! road bicycling Michael J. Berry*, Timothy R. Koves, John J. Benedetto Department of Health and Exercise Science, Wake Forest University, Winston-Salem, NC 27109-7868, USA Received 3 September 1999; accepted 14 January 2000
Abstract The purpose of this investigation was to examine the e!ects of bicycle mass, speed, and grade on oxygen consumption (V O ), heart rate (HR), and ratings of perceived exertion (RPE) during a simulated o!-road riding paradigm. Nine adult subjects with mean $ SD age, mass, and V O max of 26.1$5.6 years, 71.7$7.5 kg, 56.6$5.2 ml ) kg\ ) min\, respectively, were trained to ride a fully suspended Trek Y-22 mountain bike on a treadmill with a 3.8 cm bump a$xed to the belt. Riders completed a maximum of nine separate trials encompassing three di!erent bike masses (11.6, 12.6 and 13.6 kg), 3 speeds (2.7, 3.6 and 4.5 m ) s\), and 3 grades (0, 2.5, and 5%). Throughout a trial, bike mass and speed remained constant while riding grade was increased every 5 min. During simulated o!-road riding on a fully suspended mountain bike, increases in speed and grade signi"cantly increased V O , heart rate, and RPE. Increases in bike mass had no signi"cant e!ects on V O , heart rate or RPE. In addition, speed and grade changes interacted to di!erentially a!ect V O , heart rate, and RPE at all speeds and grades. 2000 Elsevier Science Ltd. All rights reserved. Keywords: Oxygen consumption; Bicycle mass; Energy expenditure; Mountain bike; Cycling
1. Introduction The factors that a!ect energy expenditure during road cycling have been well characterized. They include: (1) rolling resistance, or the resistance due to deformation of the tire, wheel and road; and bearing and chain drag, (2) air resistance, which is the drag caused by the bike}rider system moving through the air and (3) gravitational e!ects of ascents or descents on the bike}rider system. The e!ect of these factors on energy expenditure was originally expressed mathematically by di Prampero et al. (1979), and more recently by Swain (1994) as factor 1 factor 2 factor 3 Energy cost"(k Ps)#(k Avs)#(gPIs) where k is the rolling resistance coe$cient, P the com bined mass of cyclist and bicycle, s the bicycle road speed, k the air resistance coe$cient, A the cyclist's surface area, v the bicycle speed in air, g the acceleration of gravity and I the road incline.
* Corresponding author. Tel.: #336-758-5847; fax: 336-758-4680. E-mail address: [email protected] (M.J. Berry).
The force required to overcome rolling resistance is in#uenced by the mass of the bike}rider system such that as mass increases so does the force required to overcome this resistance. Kyle suggested that at a given force output the addition of as little as 1 kg of mass to a road bicycle could decrease speed as a result of an increase in rolling resistance (1991). The force required to overcome air resistance is the greatest contributor to the energy cost of level road cycling and increases rapidly with speed. Hagberg and McCole (1996) reported that air resistance accounts for less than 20% of the total resistance to movement at speeds less than 10 km/h. However, at speeds of 20 and 40 km/h, air resistance accounts for 54 and 82% of the total resistance, respectively. The force required to overcome gravity is the third factor and is also in#uenced by the mass of the bike}rider system such that as mass increases so does the force required to overcome this resistance. Howe (1995) estimated that during uphill road cycling gravity may account for more than 90% of the resistance to motion. Additionally, he estimated that reducing the weight of the bicycle by using lightweight parts could signi"cantly improve performance during uphill road cycling.
0003-6870/00/$ - see front matter 2000 Elsevier Science Ltd. All rights reserved. PII: S 0 0 0 3 - 6 8 7 0 ( 0 0 ) 0 0 0 2 2 - 3
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From the above discussion, it is clear that air resistance and mass are determinants of the energy cost of road cycling. How these factors a!ect o! road cycling performance has not been well documented. Typically, the speeds reached during o! road cycling are much less than those achieved on the road, and, as such, the e!ects of air resistance do not add signi"cantly to the energy cost. Furthermore, strategies used by road cyclists to obviate the e!ects of speed (i.e. drafting) are not applicable during o! road cycling. Therefore, one of the strategies adopted by o! road cyclists to improve performance is to decrease the mass of the bike as much as possible. Previously, it was demonstrated that the use of a welldesigned suspension system would decrease the energy cost during simulated o! road cycling (Berry et al., 1993). However, a potential problem with the use of such systems is that they usually add additional mass to the bike potentially increasing the force required to overcome the increased rolling resistance and the increased resistance due to gravity. Thus, it appears that the two strategies used by o! road cyclists to decrease energy expenditure, use of a suspension system and the decrease in bike mass, are diametrical. Therefore, the purpose of this investigation was to determine the e!ects of bike mass on the energy cost of simulated o! road cycling at di!erent speeds and grades.
2. Methods 2.1. Subjects Subjects for this study consisted of 8 males and 1 female. All were avid o! road cyclists, were informed of their rights as subjects, and signed an informed consent form approved by Wake Forest University's Institutional Review Board. The mean ($SD) age, mass, height and maximal oxygen consumption of the subjects was 26.1$5.6 years, 177.5$6.6 cm, 71.7$7.5 kg and 56.6$5.2 ml ) kg\ ) min\, respectively. 2.2. Procedures The test bike was an 18 in, fully suspended, stock equipped Trek Y-22 (Trek USA) mountain bike having a mass of 11.6 kg. Prior to experimental testing, all subjects were taught to ride the test bike on a 3 hp Quinton 18}60 treadmill capable of speeds up to 7.1 m ) s\ (15 miles ) h\). The belt area available for riding was 188 cm long by 44.5 cm wide. As a safety precaution, the front rail of the treadmill was out"tted with a tether that was attached to the handlebar stem of the bike. The tether restricted the rearward travel of the bicycle on the treadmill belt so riders would not fall o! the back. Riders were instructed to maintain slack in the tether during all
rides. As a further precaution, two spotters were positioned on either side of the treadmill to aid in controlling unwanted lateral movements of the bike and rider during practice and testing sessions. All subjects were allowed to practice riding the testing bike on the treadmill until they felt comfortable. Once riders felt comfortable riding on the treadmill, a 44.5 cm long by 3.8 cm by 8.9 cm wooden board was taped to the belt of the treadmill. This yielded a 3.8 cm high obstacle that the riders traversed with every full revolution of the treadmill belt. Again, subjects were allowed to practice until they felt comfortable riding under this condition. These practice sessions were necessary to ease subject apprehensions and to allow baseline measures in the study to minimally re#ect anxiety about the novel testing mode. For the experimental testing, each subject visited the laboratory on a maximum of ten occasions. All subjects were asked to refrain from exercising for 24 h prior to testing and not to eat 3 h prior to testing. During the "rst visit to the laboratory, height and mass determinations were made on all subjects. Additionally, each subject adjusted the seat height of the test bicycle such that it approximated that of his or her personal bicycle. Once this height had been determined, all subsequent trials were performed at that seat height. Handlebar position for each rider remained constant. Subjects then completed a maximal oxygen consumption test on the bike and treadmill without the bump attached. Subjects started riding at 3.1 m ) s\ (7 miles ) h\) and 0% grade with speed increased by 1 mile/h each minute thereafter until the subjects reached a speed of 5.8 m ) s\ (13 miles ) h\). Grade was then increased by 1% each minute thereafter until volitional fatigue. Oxygen consumption was monitored continuously throughout this test. On subsequent visits, subjects completed a maximum of nine experimental trials encompassing three bike masses (11.6, 12.6, 13.6 kg), three speeds (2.7, 3.6 and 4.5 m ) s\ (6, 8, 10 miles ) h\)), and three grades (0, 2.5, 5%) presented in a randomized fashion for mass and speed. Within a given trial, riders pedaled the bike at a set mass and speed for 5 min at 0% grade after which time the grade was increased by 2.5% each 5 min thereafter. The three grades investigated were presented in ascending order so that the increased e!ort that would be required at the higher grades would not mask e!ects at lower workloads. At the three speeds of 2.7, 3.6 and 4.5 m ) s\, the frequency of bump impacts was 39, 52 and 65/min, respectively. Subjects were asked to select their choice of gear and preferred cadence during the initial minute of each stage and to maintain that selected gear and cadence for the duration of the stage. As the speed of the treadmill was maintained throughout each stage and subjects were not allowed to change gears during each stage, this insured that cadence was maintained during each stage. Oxygen consumption values, heart rates, and
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ratings of perceived exertion were recorded during the last two minutes of each stage. Values for minutes 4 and 5 for all three dependent variables were averaged to obtain a single value representative for the particular stage. During all trials, heart rates were monitored using a Physio-Control Lifepak 5 heart rate monitor. Ratings of perceived exertion were taken during minutes 4 and 5 of each 5 min stage according to the methods of Borg (1973). In some instances, multiple trials were performed within the same visit. If this occurred, subjects were given at least 20 min between trials to allow recovery of oxygen consumption values, heart rates, and perceived exertion to baseline values. Mass was added to the bike by attaching a water bottle "lled with either 1 or 2 kg of lead shot. The water bottle was a$xed to the bike along the center tube secured by a standard water bottle cage. The 26 in wheels and tires that came standard with the bike were used during all trials. Tire pressures were maintained at 45 lb/in throughout the course of the study to minimize di!erences in e!ects due to rolling resistance. The subjects mass was maintained constant throughout the study via addition/subtraction of water mass from a 2 l Camelbak water carrier that the subjects wore. The subjects wore the Camelbak containing 1 l of water during the initial maximal oxygen consumption test. This mass was then used as the reference mass for all subsequent testing. The treadmill was calibrated according to the manufacturer's recommendations periodically throughout the study period. Three of the riders completed all their rides with oxygen consumption being measured using a Medical Graphics CPX automated gas analysis system. The remaining six riders in the study completed all their rides with oxygen consumption being measured using a Medical Graphics CardiO automated gas analysis system. Calibrations of the pneumotachograph and analyzers for the CPX and CardiO systems were performed according to the manufacturer's speci"cations. On-line computer analysis for the determination of oxygen consumption was performed by the host computer system and displayed breath-by-breath during all tests. 2.3. Statistical analyses A three way analysis of variance (ANOVA), with mass, grade, and speed as the independent variables, was used to test for signi"cant di!erences in the following dependent variables: oxygen consumption, heart rate, and ratings of perceived exertion. If the omnibus test was found signi"cant, simple main e!ects and Newman-Keuls post hoc procedures were used to determine the exact nature of the di!erences among experimental means. The experiment-wise alpha level was set at the 0.05 signi"cance level.
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3. Results 3.1. Oxygen consumption The results of the three way ANOVA showed no signi"cant interaction among bike mass, speed or grade. There was, however a signi"cant interaction between speed and grade (see Fig. 1). When examining the e!ect of bike mass on oxygen consumption, no signi"cant di!erences were found among the three di!erent bike masses (see Table 1). To examine the interaction between speed and grade, mass was collapsed across both factors since it had no e!ect on oxygen consumption and was not found to
Fig. 1. The e!ects of speed and grade, when collapsed across bike mass, on oxygen consumption.
Table 1 Values for oxygen consumption (V O ), heart rate and rating of per ceived exertion (RPE) when riding the bikes of di!erent masses Bike Mass
V O , ml ) kg\ ) min\ Heart rate, beats min\ RPE
11.6 kg
12.6 kg
13.6 kg
30.3$0.7 135.6$1.7 10.0$0.2
29.8$0.7 132.6$1.9 10.0$0.2
30.6$0.7 136.5$1.8 10.1$0.2
All values are mean$SEM and are collapsed across the three speeds (2.7, 3.6 and 4.5 m ) s\) and three grades (0, 2.5 and 5.0%). No signi"cant di!erences were found among the di!erent bike masses for any of the variables.
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interact with speed, grade or speed and grade. When examining the interaction between speed and grade (see Fig. 1), oxygen consumption was found to increase significantly at each speed with increases in grade (i.e., at 2.7, 3.6 and 4.5 m ) s\, oxygen consumption increased significantly with each increase in grade). Oxygen consumption was also found to be signi"cantly di!erent among the three di!erent speeds at each grade (i.e., at 0, 2.5 and 5% grade, oxygen consumption was signi"cantly greater at each speed). As can be seen in Fig. 1, the changes in oxygen consumption among the di!erent speeds become progressively larger as the grade increases. 3.2. Heart rate The results of the three way ANOVA showed no signi"cant interaction among bike mass, speed or grade. There was, however a signi"cant interaction between speed and grade (see Fig. 2). When examining the e!ect of bike mass on heart rate, no signi"cant di!erences were found among the three di!erent bike masses (see Table 1). To examine the interaction between speed and grade, mass was collapsed across both factors since it had no e!ect on heart rate and was not found to interact with speed, grade or speed and grade. When examining the interaction between speed and grade (see Fig. 2), heart rate was found to increase signi"cantly at each speed with increases in grade (i.e., at 2.7, 3.6 and 4.5 m ) s\, heart rate increased signi"cantly with each increase in grade). Heart rate was also found to be signi"cantly di!erent among the three di!erent speeds at each grade (i.e., at 0, 2.5 and 5% grade, heart rate was signi"cantly
Fig. 2. The e!ects of speed and grade, when collapsed across bike mass, on heart rate.
greater at each speed). As can be seen in Fig. 2, the changes in heart rate among the di!erent speeds became progressively larger as the grade increased.
3.3. Rating of perceived exertion The results of the three-way ANOVA showed no signi"cant interaction among bike mass, speed or grade. There was, however a signi"cant interaction between speed and grade (see Fig. 3). When examining the e!ect of bike mass on rating of perceived exertion, no signi"cant di!erences were found among the three di!erent bike masses (see Table 1). To examine the interaction between speed and grade, mass was collapsed across both factors since it had no e!ect on rating of perceived exertion and was not found to interact with speed, grade or speed and grade. When examining the interaction between speed and grade (see Fig. 3), rating of perceived exertion was found to increase signi"cantly at each speed with increases in grade (i.e., at 2.7, 3.6 and 4.5 m ) s\, rating of perceived exertion increased signi"cantly with each increase in grade). Rating of perceived exertion was also found to be signi"cantly di!erent among the three di!erent speeds at each grade (i.e., at 0, 2.5 and 5% grade, rating of perceived exertion was signi"cantly greater at each speed). As can be seen in Fig. 3, the changes in rating of perceived exertion among the di!erent speeds become progressively larger as the grade increases.
Fig. 3. The e!ects of speed and grade, when collapsed across bike mass, on rating of perceived exertion.
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4. Discussion The purpose of this experiment was to systematically examine the e!ects of changes in mountain bike mass on oxygen consumption, heart rate, and ratings of perceived exertion at di!erent speeds and grades during a simulated o!-road riding paradigm. Three di!erent bicycle masses were tested at three di!erent speeds and three di!erent grades. Increasing the mass of a fully suspended mountain bike from a stock mass of 11.6}12.6 and "nally 13.6 km had no signi"cant e!ect on oxygen consumption when examined across speeds of 2.7, 3.6, and 4.5 m ) s\ and across grades of 0, 2.5 or 5%. Furthermore, neither heart rate responses nor reported rates of perceived exertion were signi"cantly a!ected as a result of increasing the mass of the bicycle. In addition, no interaction was found between bike mass and grade or bike mass and speed for any of the dependent variables. When the bicycle mass was collapsed across the three di!erent speeds and grades tested, speed and grade were found to interact to a!ect oxygen consumption, heart rate and ratings of perceived exertion di!erentially. This study was a limited laboratory simulation such that a small bump was added to the treadmill and ridden over repeatedly at regular intervals. While this design o!ered a number of advantages, such as ease of data collection and greater control over the speed at which the riders rode, there were several disadvantages. A primary limitation is that the simulation did not truly represent o! road riding. While bumps are frequently encountered during o! road riding, the frequency with which they are encountered and the size of the bumps will vary. Our constant frequency and size could have resulted in compensation in pedal rate and/or the riding style of the rider. While this may have occurred, we feel that these results still provide important information regarding o! road bicycling. However, the results should be interpreted in light of this limitation. Because this was a laboratory simulation and the experiments were carried out on the treadmill, the second term of the equation of motion (di Prampero et al., 1979) is forced to zero. The equation then reduces to: Energy cost"(Ps)(k #gI), where k is the rolling resistance coe$cient, P the com bined mass of cyclist and bicycles, s the bicycle road speed, g the acceleration of gravity and I the road incline. It was hypothesized that the bike mass would have signi"cantly a!ected the physiological variables of oxygen consumption and heart rate. According to the above equation, bicycle mass comprises a part of the bike}rider system mass, and it, along with speed will a!ect both the rolling resistance and gravitational components of total energy cost. Kyle (1991) noted that during competitive road cycling the addition of as little as 1 kg to the mass of a bicycle on #at terrain could decrease bicycle speed due
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to increases in rolling resistance. Also supporting this hypothesis, Howe (1995) estimated that the reduction in mass could signi"cantly improve uphill cycling performance. A closer examination of the above equation reveals that mass changes of 1}2 kg will have minimal e!ects on the oxygen consumption of a cyclist riding on a relatively smooth surface. While the original equation of di Prampero et al. (1979) was developed based on riding a road racing bike on a relatively smooth surface outdoors, the reduced above equation was used to estimate oxygen consumption at the di!erent speeds, grades and masses used in this investigation. This was done by taking the average mass of the cyclists in this investigation and adding it to the bike masses of 11.6, 12.6 and 13.6 kg to obtain bike and rider masses. A coe$cient of rolling resistance equal to 0.013 instead of the coe$cient of rolling resistance of 0.0086 as suggested by di Prampero et al. (1979) was also used. This was due to the fact that Kyle (1986) calculated the coe$cient of rolling resistance for a 26 in knobby tire, similar to that found on the Trek Y22, to be 0.013. Applying these factors and the speeds and grades used in this investigation, the expected oxygen consumption for each speed, grade and mass was calculated. Using this approach, it was found that any speed or grade di!erences in oxygen consumption between the di!erent bike masses were less than 1 ml ) kg\ ) min\. That is to say, increases in bike mass had a negligible e!ect on oxygen consumption irrespective of speed and grade. Howe (1995) estimated that over the course of a 1 h ride up a 12.1% grade a cyclist could save 42.7 s with a 1 kg reduction in bicycle weight. Based on Howe's data and methods (1995), this 1 kg reduction in bicycle weight would result in an approximately four watt power reduction if the cyclist were to complete the course in the same amount of time while riding the lighter bike. This 4 W power reduction equates to a less than 1 ml ) kg\ ) min\ oxygen consumption saving, similar to that we estimated. This expected di!erence of less than 1 ml ) kg\ ) min\ is smaller than the average measurement error expected when measuring oxygen consumption (Howley et al., 1995). The interaction between speed and grade found in this study is described in the equation of motion of a cyclist by di Prampero et al. (1979) and in an equation developed by Hagberg et al. (1978) to predict oxygen consumption when riding a bicycle on a motor driven treadmill. Additionally, the equation by di Prampero et al. (1979) shows that the energy cost of cycling should be directly proportional to the mass of the cyclist and bicycle and that mass, bike speed and grade should all interact. The fact that mass did not interact is most likely due to the fact that the variations in mass were so small. Based on the equations, larger changes in mass would have most likely resulted in an interaction among mass, bike speed and grade. However, larger changes in mass
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would have hurt the validity of the study in the bicycling community since the range of masses used in this investigation are representative of the masses of bikes being sold today. If the speeds, grades and masses of the bike and riders used in this investigation are used to calculate the expected oxygen consumption from the equations by di Prampero et al. (1979) and Hagberg et al. (1978), when graphed they demonstrate the same pattern as the data in Fig. 1. Examination of Fig. 1 shows that as the grade increases the di!erence in oxygen consumption at di!ering speeds becomes greater. The oxygen consumption values obtained in this investigation are 7 to 20 ml ) kg\ ) min\ higher than those calculated from the equation of motion of a cyclist by di Prampero et al. (1979) and in an equation developed by Hagberg et al. (1978). The higher oxygen consumption values measured at each of the speeds and grades in this investigation compared to those calculated from the equations of di Prampero et al. (1979) and Hagberg et al. (1978) are probably due to an increase in rolling resistance. The coe$cient of rolling resistance for knobby tires suggested by Kyle (1986) would only increase oxygen consumption by 1 to 2 ml ) kg\ ) min\ compared to the coe$cient of rolling resistance suggested by di Prampero et al. (1979). Therefore, it appears that the greatest contributor to this 7}20 ml ) kg\ ) min\ increase in oxygen consumption is the energy required to traverse the bump. Deformation of the wheel, tire and road at the point of contact is the cause of rolling resistance. Energy is lost when the wheel, tire and surface do not spring back elastically and fail to return all the lost energy to the bicycle (Kyle, 1986). Contact with the 3.8 cm bump on the treadmill would obviously cause a greater deformation compared to rolling on a smooth surface. In a previous investigation examining the use of a suspension system and oxygen consumption, a 10.9 ml ) kg\ ) min\ (41%) increase in oxygen consumption was found when comparing riding an o! road bicycle with knobby tires on a treadmill with a 3.8 cm bump at 2.9 m ) s\ and 4% grade to riding a bicycle with knobby tires on a treadmill with no bump at 2.9 m ) s\ and 4% grade (Berry et al., 1993). Based on this previous "nding it appears as if the di!erences between the measured oxygen consumption values and those estimated from the equation of motion of di Prampero et al. (1979) are due to the increased rolling resistance of the bump. A problem with this investigation was the fact that the expected di!erences in oxygen consumption were smaller than the error found in measuring oxygen consumption. Subsequently, the study runs into a signal to noise problem. Unfortunately, techniques for determining such small di!erences in oxygen consumption, if they do in-
deed exist, are not available. Even if the technology were available to measure these hypothesized di!erences, there is a question of whether these proposed di!erences would be of practical signi"cance. Given the fact that oxygen consumption is but one factor that in#uences cycling performance, additional studies should evaluate whether changes in bicycle mass have e!ects that may be of more practical signi"cance to riders, such as place of "nish. Future studies should also be directed toward determining what e!ects, if any, are due to increases in mountain bike mass using fully suspended bicycles lighter than 11.6 kg. It would also be of interest to have riders bike at grades greater than 5% to determine if additional mass has a greater or di!erential e!ects as gravitational forces are increased. In addition, with the advent of portable metabolic measuring devices, future experiments should be conducted in the "eld over a variety of terrains to assess which factors are most related to increases in energy expenditure.
Acknowledgements This work has been supported in part by a grant from Trek USA.
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