Motor variability in sports: A non-linear analysis of race walking

Abstract

This aim of this study was to analyse the nature of movement variability and to assess whether entropy measures may represent a valuable synthetic index of neuromuscular organization. The regularity of kinematic/kinetic time series during race walking, the changes in the structure of intra-individual variability over the test session, and the influence of athletic skill in (inter)national rank athletes were investigated. Motion analysis techniques were used. Sample entropy (SampEn) was adopted to examine fluctuations in lower limb angles and ground reaction forces. The regularity of both original and surrogate time series was assessed and compared, by estimating SampEn, to verify the presence of non-linear features in movement variability. SampEn was statistically lower in the original data than in surrogates. In contrast, the regularity of time series did not change significantly throughout the subsequent intra-individual repetitions. Hip and ankle joint angles and vertical ground reaction force manifested increased entropy for skilled athletes. Results suggest that race walking variability was not only the product of random noise but also contained information about the inherent propriety of the neuro-musculo-skeletal system. Furthermore, they provide some indications about neuromuscular control of the lower limb joints during race walking gait, and about the differences between more and less skilled individuals.

ORIGINAL Lower Extremities' Joint Stability during the Elderly Woman's Walking

“…Whatever the case may be, the ApEn values from the original time series and surrogate data tests show differences in their rate of increase; however, the increased values are consistent with the results reported by precedent studies (Bartlett, Wheat, & Robins, 2007;Riley & Turvey, 2002). Based on these results, it is believed that in both young and elderly women groups, the periodicity of lower extremity joint flexion/extension motion possesses not only noise during walking but also a non-linear structure, indicating a functional information on the neuroskeletal system (Preatoni et al, 2010).…”

“…In the present study, both the young and elderly women groups showed a statistically significant increase in the ratios of surrogate ApEn values of the hip, knee, and ankle flexion/extension motion to those of the original data between the groups. Preatoni et al (2010) reported an increase of 59% in the SampEn value after a surrogate data test on hip flexion/extension angle data of race walking athletes, which was higher than the results in the present study. It is believed that such a difference may be attributed to movement speed and other factors.…”

“…Moreover, to test the assumption that the observed time series data represented the outcome of definitive dynamic types of the analyzed system (Theiler, Eubank, Longtin, Galdrikian, & Farmer, 1992), ApEn values were calculated after performing a surrogate data test (pseudo-periodic surrogate) on the time series data on 20 strides. The calculated values were averaged and compared with the ApEn values of the original time series data (Preatoni et al, 2010).…”

“…Even experienced race walking athletes are known not to show the same periodicity of steps or strides during walking (Preatoni, Ferrario, Dona, Hamill, & Rodano, 2010). Changes in gait periodicity represent outcomes from environmental changes, training, latent diseases, and unstable recovery impacting the neuromuscular tissues (Hausdorff et al, 1994;Nakamura, Meguro, & Sasaki, 1996;Papadakis et al, 2009;Preatoni et al, 2014).…”

The biomechanics of race walking: Literature overview and new insights

“…A further approach, based on sophisticated mathematical methods applied to race walking biomechanics, has been carried out in several investigations (Preatoni et al, 2010a;Preatoni, Ferrario, Donà, Hamill & Rodano, 2010b;Donà et al, 2009). Their outcomes may support researchers with functional guidelines and provide coaches with quantitative tools for skill prediction (Donà et al, 2009) and technique assessment (Preatoni et al, 2010b): i) a sequential estimation procedure defined that at least 15 trials are necessary for a reliable description of the kinematical parameters investigated, ii) a non-linear analysis based on entropy (measurement of the motor variability) may reflect the athletic condition and the performance enhancement due to a motor learning/adaptation, iii) a multivariate data analysis (functional Principal Component Analysis, fPCA) found differences in knee joint kinematics across athletes level.…”