Control of static posture is constrained by multiple sensory inputs, motor ability, and task constraints. Development of static postural control across the lifespan can be analyzed effectively using nonlinear analyses of center of pressure (CoP) time series, including approximate and sample entropy. In this paper, the key findings from studies using nonlinear analysis tools are reviewed to describe the development of postural control. Preschool children learn to adopt relatively unstable postures (e.g., standing) in which the regularity of CoP initially increases as a consequence of restricting mechanical degrees of freedom. As children age, CoP regularity decreases as degrees of freedom are released, thus enabling a more functional, adaptable type of postural control. Changes to sensory inputs or task constraints also affect the regularity of CoP sway. For example, removing vision, adding vibration, or imposing dual-task conditions affect performer’s CoP regularity differently. One limitation of approximate and sample entropy analysis is the influence of different input parameters on the output and subsequent interpretation. Ongoing refinement to entropy analysis tools concern determining appropriate values for the length of sequence to be matched and the tolerance level used with CoP data.
Neil Anderson and Chris Button
Yumeng Li, Melissa A. Mache, and Teri A. Todd
physiological complexity. 18 Multiscale entropy is a nonlinear analysis tool to quantify complexity or irregularity of a time-series signal over multiple time scales. Compared with approximate entropy and sample entropy, multiscale entropy quantifies the overall complexity of a system and allows researchers to
Beth A. Smith, Nick Stergiou, and Beverly D. Ulrich
In previous studies we found that preadolescents with Down syndrome (DS) produce higher amounts of variability (Smith et al., 2007) and larger Lyapunov exponent (LyE) values (indicating more instability) during walking than their peers with typical development (TD) (Buzzi & Ulrich, 2004). Here we use nonlinear methods to examine the patterns that characterize gait variability as it emerges, in toddlers with TD and with DS, rather than after years of practice. We calculated Lyapunov exponent (LyE) values to assess stability of leg trajectories. We also tested the use of 3 algorithms for surrogation analysis to investigate mathematical periodicity of toddlers’ strides. Results show that toddlers’ LyE values were not different between groups or with practice and strides of both groups become more periodic with practice. The underlying control strategies are not different between groups at this point in developmental time, although control strategies do diverge between the groups by preadolescence.
Yumeng Li, Jupil Ko, Marika A. Walker, Cathleen N. Brown, and Kathy J. Simpson
The purpose of the present study was to examine the effect of chronic ankle instability (CAI) on lower-extremity joint coordination and stiffness during landing. A total of 21 female participants with CAI and 21 pair-matched healthy controls participated in the study. Lower-extremity joint kinematics were collected using a 7-camera motion capture system, and ground reaction forces were collected using 2 force plates during drop landings. Coupling angles were computed based on the vector coding method to assess joint coordination. Coupling angles were compared between the CAI and control groups using circular Watson–Williams tests. Joint stiffness was compared between the groups using independent t tests. Participants with CAI exhibited strategies involving altered joint coordination including a knee flexion dominant pattern during 30% and 70% of their landing phase and a more in-phase motion pattern between the knee and hip joints during 30% and 40% and 90% and 100% of the landing phase. In addition, increased ankle inversion and knee flexion stiffness were observed in the CAI group. These altered joint coordination and stiffness could be considered as a protective strategy utilized to effectively absorb energy, stabilize the body and ankle, and prevent excessive ankle inversion. However, this strategy could result in greater mechanical demands on the knee joint.
Philip W. Fink, Sarah P. Shultz, Eva D’Hondt, Matthieu Lenoir, and Andrew P. Hills
Multifractal analyses have been used in recent years as a way of studying balance, with the goal of understanding the patterns of movement of the center of pressure at different spatial scales. A multifractal detrended fluctuation analysis was used to compare obese and nonobese children to investigate the cause of previously demonstrated deficiencies in balance for obese children. Twenty-two children (11 obese and 11 nonobese), aged 8–15 years, performed 30-s trials of bilateral static balance on a plantar pressure distribution measuring device. Both the obese and nonobese groups demonstrated greater persistence for small fluctuations, but the effect was greater in the obese group. This was particularly evident with the eyes closed, where significant differences between the obese and nonobese were observed for small fluctuations. These results demonstrate that balance deficiencies in obese children may be the result of decreased proprioceptive abilities in obese children.
Yumeng Li, Rumit S. Kakar, Marika A. Walker, Li Guan, and Kathy J. Simpson
The upper trunk–pelvic coordination patterns used in running are not well understood. The purposes of this study are to (1) test the running speed effect on the upper trunk–pelvis axial rotation coordination and (2) present a step-by-step guide of the relative Fourier phase algorithm, as well as some further issues to consider. A total of 20 healthy young adults were tested under 3 treadmill running speeds using a 3-dimensional motion capture system. The upper trunk and pelvic segmental angles in axial rotation were calculated, and the coordination was quantified using the relative Fourier phase method. Results of multilevel modeling indicated that running speed did not significantly contribute to the changes in coordination in a linear pattern. A qualitative template analysis suggested that participants displayed different change patterns of coordination as running speed increased. Participants did not significantly change the upper trunk and pelvis coordination mode in a linear pattern at higher running speeds, possibly because they employed different motion strategies to achieve higher running speeds and thus displayed large interparticipant variations. For most of our runners, running at a speed deviated from the preferred speed could alter the upper trunk–pelvis coordination. Future studies are still needed to better understand the influence of altered coordination on running performance and injuries.
This laboratory study investigated seated computer work before and after prolonged constrained sitting. Discomfort ratings and kinetic and kinematics data were recorded in nine healthy males performing computer work for 5 min before and after 96 min of sitting. The displacement of the center of pressure (CoP) in anterior-posterior and medial-lateral directions and lumbar curvature (LC) were calculated. The root mean square, standard deviation, and sample entropy values were computed from the CoPs and LC signals to assess the magnitude, amount of variability, and regularity of sitting dynamics, respectively. The discomfort increased for the buttocks (p = .02).The standard deviation and sample entropy values of the CoPs and LC signals, respectively, increased (p < .04) and decreased (p < .004) whereas the root mean square remained unchanged (p > .15) after prolonged constrained sitting compared with before. This present study showed that during seated computer work, prolonged constrained sitting affected the amount of variability and the regularity of sitting postural control, whereas the magnitude was not affected. The importance of the dynamics of sitting control may challenge the idea of a static and ideal seated posture at work.
Senia Smoot Reinert, Allison L. Kinney, Kurt Jackson, Wiebke Diestelkamp, and Kimberly Bigelow
movement quality because they only give the maximum displacement of COP. However, newer nonlinear analysis methods, such as sample entropy, allow us to describe movement quality. Sample entropy quantifies the underlying regularity of human movements and has been used to study phenomena such as the effect
Renee Beach Sample, Kurt Jackson, Allison L. Kinney, Wiebke S. Diestelkamp, Senia Smoot Reinert, and Kimberly Edginton Bigelow
Falls occur in 33% of older adults each year, some leading to moderate to severe injuries. To reduce falls and fall-related injuries, it is important to identify individuals with subtle risk factors elevating their likelihood of falling. The objective of this study was to determine how postural sway measures differed between fallers and nonfallers under standard and dual-task conditions. Quietstanding posturography measures were collected from 150 older adults during standard, cognitive, manual, and cognitive+manual tasks, and analyzed through traditional and nonlinear analyses. Of the traditional measures, M/L sway range and 95% confidence ellipse sway area showed statistically significant differences in all 4 test conditions between fallers and nonfallers. Although the manual dual task showed the most stable balance, effect sizes demonstrated larger differences between fallers and nonfallers. Nonlinear analysis revealed M/L sample entropy and M/L α-scaling exponent differentiating between fallers and nonfallers, with the cognitive task demonstrating larger differences. Based on the results, it is recommended to: (1) apply M/L sway range and 95% confidence ellipse area, (2) use the manual task to differentiate between fallers and nonfallers when using traditional analyses, and (3) use the cognitive task and M/L alpha and M/L sample entropy when using nonlinear analyses.
Adam C. King
Context: Altered postural control represents one of the most common motor consequences following a concussion and there is a paucity of data monitoring the recovery trajectory that identifies the persistent changes of postural control. Objective: To determine whether the recovery trajectory of postural control was consistent across different measures of postural stability and whether increased postural challenge (ie, sloped surface) revealed subtle postural impairments. Design: A single-subject case study. Setting: Research laboratory. Patients or Other Participants: One concussed individual with a cohort of healthy controls (n = 10) used for comparison. Main Outcome Measures: Center of pressure variability (linear—SD and nonlinear—multiscale entropy) was used to index postural sway preinjury and at periodic intervals following the concussion. Results: The concussed individuals displayed reduced amounts of sway during the initial recovery phase that failed to returned to preinjury levels but reached the level of healthy controls at 1-month postinjury. The multiscale entropy analysis revealed increased center of pressure irregularity throughout recovery that persisted up to 1-month post injury. Conclusions: The findings identified subtle, persistent postural control impairments revealed through the nonlinear analysis of center of pressure and supports the notion that the consequences of a concussion (ie, impaired postural control) need to be considered beyond the resolution of behavioral symptoms.