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Steven J. Elmer and James C. Martin

Eccentric cycling serves a useful exercise modality in clinical, research, and sport training settings. However, several constraints can make it difficult to use commercially available eccentric cycle ergometers. In this technical note, we describe the process by which we built an isokinetic eccentric cycle ergometer using exercise equipment modified with commonly available industrial parts. Specifically, we started with a used recumbent cycle ergometer and removed all the original parts leaving only the frame and seat. A 2.2 kW electric motor was attached to a transmission system that was then joined with the ergometer. The motor was controlled using a variable frequency drive, which allowed for control of a wide range of pedaling rates. The ergometer was also equipped with a power measurement device that quantified work, power, and pedaling rate and provided feedback to the individual performing the exercise. With these parts along with some custom fabrication, we were able to construct an isokinetic eccentric cycle ergometer suitable for research and training. This paper offers a guide for those individuals who plan to use eccentric cycle ergometry as an exercise modality and wish to construct their own ergometer.

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Chee-Hoi Leong, Steven J. Elmer, and James C. Martin

Noncircular chainrings could increase cycling power by prolonging the powerful leg extension/flexion phases, and curtailing the low-power transition phases. We compared maximal cycling power-pedaling rate relationships, and joint-specific kinematics and powers across 3 chainring eccentricities (CON = 1.0; LOWecc = 1.13; HIGHecc = 1.24). Part I: Thirteen cyclists performed maximal inertial-load cycling under 3 chainring conditions. Maximum cycling power and optimal pedaling rate were determined. Part II: Ten cyclists performed maximal isokinetic cycling (120 rpm) under the same 3 chainring conditions. Pedal and joint-specific powers were determined using pedal forces and limb kinematics. Neither maximal cycling power nor optimal pedaling rate differed across chainring conditions (all p > .05). Peak ankle angular velocity for HIGHecc was less than CON (p < .05), while knee and hip angular velocities were unaffected. Self-selected ankle joint-center trajectory was more eccentric than HIGHecc with an opposite orientation that increased velocity during extension/flexion and reduced velocity during transitions. Joint-specific powers did not differ across chainring conditions, with a small increase in power absorbed during ankle dorsiflexion with HIGHecc. Multiple degrees of freedom in the leg, crank, and pedal system allowed cyclists to manipulate ankle angular velocity to maintain their preferred knee and hip actions, suggesting maximizing extension/flexion and minimizing transition phases may be counterproductive for maximal power.

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Steven J. Elmer, John McDaniel, and James C. Martin

One-legged cycling has served as a valuable research tool and as a training and rehabilitation modality. Biomechanics of onelegged cycling are unnatural because the individual must actively lift the leg during flexion, which can be difficult to coordinate and cause premature fatigue. We compared ankle, knee, and hip biomechanics between two-legged, one-legged, and counterweighted (11.64 kg) one-legged cycling. Ten cyclists performed two-legged (240 W), one-legged (120 W), and counterweighted one-legged (120 W) cycling (80 rpm). Pedal forces and limb kinematics were recorded to determine work during extension and flexion. During counterweighted one-legged cycling relative ankle dorsiflexion, knee flexion, and hip flexion work were less than one-legged but greater than two-legged cycling (all P < .05). Relative ankle plantar flexion and hip extension work for counterweighted one-legged cycling were greater than one-legged but less than two-legged cycling (all P < .05). Relative knee extension work did not differ across conditions. Counterweighted one-legged cycling reduced but did not eliminate differences in joint flexion and extension actions between one- and two-legged cycling. Even with these differences, counterweighted one-legged cycling seemed to have advantages over one-legged cycling. These results, along with previous work highlighting physiological characteristics and training adaptations to counterweighted one-legged cycling, demonstrate that this exercise is a viable alternative to one-legged cycling.

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Jeffrey J. Martin, Laurie A. Malone, and James C. Hilyer

Research on elite female athletes with disabilities is extremely rare. Therefore, using the Sixteen Personality Factor Questionnaire (Cattell, Cattell, & Cattell, 1993) and Profile of Mood States (Droppleman, Lorr, & McNair, 1992), we examined differences between the top 12 athletes comprising the gold medal winning 2004 USA women’s Paralympic basketball team and 13 athletes attending the selection camp who did not make the team. Multivariate analysis of variance with follow-up tests revealed that athletes who made the Paralympic team scored higher on tough-mindedness (M = 5.7 vs. 4.3) and lower in anxiety (M = 5.6 vs. 7.8). For mood state, the Paralympians scored higher in vigor (M = 19.5 vs. 14.8) and lower in depressed mood (M = 3.9 vs. 6.7) and confusion (M = 5.5 vs. 7.5). The effect sizes were large (e.g., Cohen’s d = 0.91 - 1.69) for all five results.

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James C. Martin, Steven J. Elmer, Robert D. Horscroft, Nicholas A.T. Brown, and Barry B. Shultz

The purpose of this study was to develop and evaluate an alternative method for determining the position of the anterior superior iliac spine (ASIS) during cycling. The approach used in this study employed an instrumented spatial linkage (ISL) system to determine the position of the ASIS in the parasagittal plane. A two-segment ISL constructed using aluminum segments, bearings, and digital encoders was tested statically against a calibration plate and dynamically against a video-based motion capture system. Four well-trained cyclists provided data at three pedaling rates. Statically, the ISL had a mean horizontal error of 0.03 ± 0.21 mm and a mean vertical error of −0.13 ± 0.59 mm. Compared with the video-based motion capture system, the agreement of the location of the ASIS had a mean error of 0.30 ± 0.55 mm for the horizontal dimension and −0.27 ± 0.60 mm for the vertical dimension. The ISL system is a cost-effective, accurate, and valid measure for two-dimensional kinematic data within a range of motion typical for cycling.

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John McDaniel, N. Scott Behjani, Steven J. Elmer, Nicholas A.T. Brown, and James C. Martin

Previous authors have reported power-pedaling rate relationships for maximal cycling. However, the joint-specific power-pedaling rate relationships that contribute to pedal power have not been reported. We determined absolute and relative contributions of joint-specific powers to pedal power across a range of pedaling rates during maximal cycling. Ten cyclists performed maximal 3 s cycling trials at 60, 90, 120, 150, and 180 rpm. Joint-specific powers were averaged over complete pedal cycles, and extension and flexion actions. Effects of pedaling rate on relative joint-specific power, velocity, and excursion were assessed with regression analyses and repeated-measures ANOVA. Relative ankle plantar flexion power (25 to 8%; P = .01; R 2 = .90) decreased with increasing pedaling rate, whereas relative hip extension power (41 to 59%; P < .01; R 2 = .92) and knee flexion power (34 to 49%; P < .01; R 2 = .94) increased with increasing pedaling rate. Knee extension powers did not differ across pedaling rates. Ankle joint angular excursion decreased with increasing pedaling rate (48 to 20 deg) whereas hip joint excursion increased (42 to 48 deg). These results demonstrate that the often-reported quadratic power-pedaling rate relationship arises from combined effects of dissimilar joint-specific power-pedaling rate relationships. These dissimilar relationships are likely influenced by musculoskeletal constraints (ie, muscle architecture, morphology) and/or motor control strategies.

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James C. Martin, Douglas L. Milliken, John E. Cobb, Kevin L. McFadden, and Andrew R. Coggan

This investigation sought to determine if cycling power could be accurately modeled. A mathematical model of cycling power was derived, and values for each model parameter were determined. A bicycle-mounted power measurement system was validated by comparison with a laboratory ergometer. Power was measured during road cycling, and the measured values were compared with the values predicted by the model. The measured values for power were highly correlated (R 2 = .97) with, and were not different than, the modeled values. The standard error between the modeled and measured power (2.7 W) was very small. The model was also used to estimate the effects of changes in several model parameters on cycling velocity. Over the range of parameter values evaluated, velocity varied linearly (R 2 > .99). The results demonstrated that cycling power can be accurately predicted by a mathematical model.