Literature DB >> 23712680

Dynamics of revolution time variability in cycling pattern: voluntary intent can alter the long-range autocorrelations.

Thibault B Warlop1, Benjamin Bollens, Frédéric Crevecoeur, Christine Detrembleur, Thierry M Lejeune.   

Abstract

Long-range dependency has been found in most rhythmic motor signals. The origin of this property is unknown and largely debated. There is a controversy on the influence of voluntary control induced by requiring a pre-determined pace such as asking subjects to step to a metronome. We studied the cycle duration variability of 15 men pedaling on an ergometer at free pace and at an imposed pace (60 rpm). Revolution time was determined based on accelerometer signals (sample frequency 512 Hz). Revolution time variability was assessed by coefficient of variation (CV). The presence of long-range autocorrelations was based on scaling properties of the series variability (Hurst exponent) and the shape of the power spectral density (α exponent). Mean revolution time was significantly lower at freely chosen cadence, while values of CV were similar between both sessions. Long-range autocorrelations were highlighted in all series of cycling patterns. However, Hurst and α exponents were significantly lower at imposed cadence. This study demonstrates the presence of long-range autocorrelations during cycling and that voluntary intent can modulate the interdependency between consecutive cycles. Therefore, cycling may constitute a powerful paradigm to investigate the influence of central control mechanisms on the long-range interdependency characterizing rhythmic motor tasks.

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Year:  2013        PMID: 23712680     DOI: 10.1007/s10439-013-0834-2

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  4 in total

Review 1.  Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review.

Authors:  Valentina Camomilla; Elena Bergamini; Silvia Fantozzi; Giuseppe Vannozzi
Journal:  Sensors (Basel)       Date:  2018-03-15       Impact factor: 3.576

2.  Phase space methods for non-linear analysis of pedalling forces in cycling.

Authors:  Alexander Kunert; Marcel Ott; Thomas Reuter; Daniel Koska; Christian Maiwald
Journal:  PLoS One       Date:  2019-04-18       Impact factor: 3.240

3.  Multifractal Dynamics in Executive Control When Adapting to Concurrent Motor Tasks.

Authors:  Laurent M Arsac
Journal:  Front Physiol       Date:  2021-04-16       Impact factor: 4.566

4.  Concurrent Changes of Brain Functional Connectivity and Motor Variability When Adapting to Task Constraints.

Authors:  Grégoire Vergotte; Stéphane Perrey; Muthuraman Muthuraman; Stefan Janaqi; Kjerstin Torre
Journal:  Front Physiol       Date:  2018-07-10       Impact factor: 4.566

  4 in total

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