Dynamical analysis of balance in vestibular schwannoma patients.

The analysis of the complexity of postural fluctuations is a recent method for assessing postural control. Complexity relates to the irregularity of the center of pressure time series and characterizes the ability of postural control to meet a changing environment. In our study, we used the sample entropy (SampEn) parameter to evaluate the complexity of postural sway velocity time series in patients with vestibular schwannoma (n=19) compared to healthy controls (n=20), using the sensory organization test. Patients performed postural assessments three days before surgical ablation of the tumor, then three times after surgery, at eight, thirty, and ninety days. The control group underwent posturographic tests only once. Our results demonstrated that SampEn values distinguished both groups before surgery only in postural tasks where vestibular afferences significantly contribute to maintaining balance. We also found an immediate decrease of complexity after the surgical resection of the tumor. Our results are in line with the theory of complexity loss of physiological systems stating that reducing the number of their structural components or altering their coupling leads to a decrease in complexity. Finally, our findings showed that progressive restoration of complexity over time was such that no difference was found between the two groups ninety days after surgery, due to the implementation of central adaptive mechanisms and the substitution by other sensory afferences. Thus, the SampEn parameter can highlight the postural effects of vestibular pathology, and complexity analysis appears to be a valuable tool for investigating the temporal structure of CoP time series.

Dynamical and stabilometric measures are complementary for the characterization of postural fluctuations in older women.

We investigate the complementarities of several measures extracted from center of pressure (COP) recordings during quiet standing, in older women. The selected variables include classical stabilometric measures (SMs) and several dynamical measures (DMs). The computed DMs quantify various features of the temporal structure of COP signals, including predictability, regularity and smoothness of the trajectories. The postural fluctuations of a group of 101 healthy older women were recorded by means of a force platform. After estimating the SMs and DMs from the COP data, we used principal components analysis (PCA) to quantify the contribution of each measure. The results suggest that SMs and DMs are complementary. In addition, the different DMs are globally not redundant. This finding is a reinforcement argument in favor of the use of DMs as postural signatures.

Characterizing the dynamics of postural sway in humans using smoothness and regularity measures.

We investigate human postural sway velocity time series by computing two dynamical statistics quantifying the smoothness (the central tendency measure or CTM) and the regularity (the sample entropy or SampEn) of their underlying dynamics. The purpose of the study is to investigate the effect of aging and vision on the selected measures and to explore the nature of postural dynamics by performing surrogate data tests. A group of 14 young subjects was compared to a group of 11 older healthy subjects in two visual conditions: with eyes open (EO) and with eyes closed (EC). The results suggest that vision and age do not influence the two statistics of the velocity data in the same way. More specifically, the smoothness statistic is able to detect the aging effect. The regularity measure is sensitive to the visual feedback removal. In contrast with some findings in the literature, the results of the surrogate data tests indicate that the center of pressure velocity dynamics are stochastic and are not produced by a purely deterministic behavior. Finally, we discuss some potential implications of our results in terms of postural control mechanisms.

On the use of sample entropy to analyze human postural sway data.

We analyze the irregularity of human postural sway data during quiet standing using the sample entropy (SampEn) algorithm. By considering recent methodological developments, we show that the SampEn parameter is able to characterize the irregularity of the center of pressure fluctuations through the analysis of the velocity variable. We present a practical method to select the input parameters of the SampEn algorithm. We show that the computed SampEn successfully discriminates two sensory conditions (eyes-open and eyes-closed) in a group of healthy young adults. We also perform surrogate data tests to investigate the nature of the underlying dynamics of our experimental data. Finally, the results of the proposed approach are compared to those obtained with the multiscale entropy algorithm.

Dynamical structure of center of pressure fluctuations in elderly people.

This study investigates whether aging has an influence on the dynamics of the fluctuations of the displacement of the center of pressure (COP), during quiet standing. Two groups of healthy subjects were compared (11 young and 12 elderly) for two visual feedback conditions (eyes open and eyes closed). The data were analyzed using (i) classical stabilometric variables (length and surface) and (ii) recurrence quantification analysis (percentage of determinism and entropy), for the dynamical structure of COP signals. The length of the COP displacement was found to be the best discriminating stabilometric variable for both visual and aging effects. Visual feedback influenced recurrence quantification analysis (RQA) variables only for the elderly group. Both RQA outputs in the anterior posterior direction were sufficient to distinguish the young and elderly groups. The entropy estimation computed by RQA was significantly reduced for postural fluctuations in elderly people. We conclude that classical stabilometric variables and RQA outputs provide complementary information for the characterization of ageing effects on postural sway.