R Tucker1, A Bester, E V Lambert, T D Noakes, C L Vaughan, A St Clair Gibson. 1. Brain Sciences Research Group, MRC/UCT Research Unit of Exercise Science and Sports Medicine, Department of Human Biology, University of Cape Town and Sport Science Institute of South Africa, Newlands, South Africa.
Abstract
OBJECTIVES: To analyse the power output measured during a self-paced 20-km cycling time trial, during which power output was free to vary, in order to assess the level and characteristics of the variability in power output that occurred during the exercise bout. METHODS: Eleven well-trained cyclists performed a 20-km cycling time trial, during which power output was sampled every 200 m. Power spectrum analysis was performed on the power output data, and a fractal dimension was calculated for each trial using the Higuchi method. RESULTS: In all subjects, power output was maintained throughout the trial until the final kilometre, when it increased significantly, indicating the presence of a global pacing strategy. The power spectrum revealed the presence of 1/f-like scaling of power output and multiple frequency peaks during each trial, with the values of the frequency peaks changing over the course of the trial. The fractal dimension (D-score) was similar for all subjects over the 20-km trial and ranged between 1.5 and 1.9. CONCLUSIONS: The presence of an end spurt in all subjects, 1/f-like scaling and multiple frequency peaks in the power output data indicate that the measured oscillations in power output during cycling exercise activity may not be system noise, but may rather be associated with system control mechanisms that are similar in different individuals.
OBJECTIVES: To analyse the power output measured during a self-paced 20-km cycling time trial, during which power output was free to vary, in order to assess the level and characteristics of the variability in power output that occurred during the exercise bout. METHODS: Eleven well-trained cyclists performed a 20-km cycling time trial, during which power output was sampled every 200 m. Power spectrum analysis was performed on the power output data, and a fractal dimension was calculated for each trial using the Higuchi method. RESULTS: In all subjects, power output was maintained throughout the trial until the final kilometre, when it increased significantly, indicating the presence of a global pacing strategy. The power spectrum revealed the presence of 1/f-like scaling of power output and multiple frequency peaks during each trial, with the values of the frequency peaks changing over the course of the trial. The fractal dimension (D-score) was similar for all subjects over the 20-km trial and ranged between 1.5 and 1.9. CONCLUSIONS: The presence of an end spurt in all subjects, 1/f-like scaling and multiple frequency peaks in the power output data indicate that the measured oscillations in power output during cycling exercise activity may not be system noise, but may rather be associated with system control mechanisms that are similar in different individuals.
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