Multiple timescales in postural dynamics associated with vision and a secondary task are revealed by wavelet analysis

Abstract

Discrete wavelet analysis is used to resolve the center of pressure time series data into several timescale components, providing new insights into postural control. Healthy young and elderly participants stood quietly with their eyes open or closed and either performed a secondary task or stood quietly. Without vision, both younger and older participants had reduced energy in the long timescales, supporting the concept that vision is used to control low frequency postural sway. Furthermore, energy was increased at timescales corresponding to closed-loop (somatosensory and vestibular) and open-loop mechanisms, consistent with the idea of a shift from visual control to other control mechanisms. However, a relatively greater increase was observed for older adults. With a secondary task a similar pattern was observed-increased energy at the short and moderate timescales, decreased energy at long timescales. The possibility of a common strategy-at the timescale level-in response to postural perturbations is considered.

A Non Linear Scoring Approach for Evaluating Balance: Classification of Elderly as Fallers and Non-Fallers

“…It has been mentioned that in individual’s real life, falls often occurs when multiple tasks or external stimulations exists simultaneously and fragile individuals cannot process them accurately [12]. Therefore, they proposed richer and more dynamic protocols involving multiple tasks [19, 33]. Increase of exercises’ difficulty such as stance in foam surface were also proposed [3].…”

“…Previous works have proposed a variety of empirical indices (or features) derived by the actual CoP displacements (such as the area covered by the CoP’s trajectory or sway area, mean distance of points from centre of CoP trajectory, velocity and acceleration of trajectory), showing that in some cases sway area, mean velocity or mean acceleration are affected by instability [3, 16]. Other approaches used indices derived from CoP-trajectory transformations such as Fourier [17, 18], Wavelet [19] or Sway density [17, 20]. However, as it has been reported in healthy and non healthy populations [21, 22], no agreement has been reached whether these approaches alone can provide enough information to characterize the complex synergies of postural control.…”

Gait Detection in Children with and without Hemiplegia Using Single-Axis Wearable Gyroscopes

“…We expect that this mismatch can be remedied in future incarnations of this work, which will use a variety of training datasets to build a set of models covering everyday tasks. Moreover, the use of FSR data for partitioning gait cycles may be unnecessary for training in later models, as numerical algorithms, such as wavelet analysis, have proven capable of interpreting sensor data measuring posture and gait [20], [34].…”

Noise and Complexity in Human Postural Control: Interpreting the Different Estimations of Entropy

“…Based on the Nyquist theorem, a sampling frequency greater than 20 Hz would be sufficient to provide an alias-free signal of postural sway and there would be no further advantage of increasing the sampling frequency when examining the dynamics of the behavior. However, postural control occurs at a variety of time scales [15], so lower sampling frequencies may not provide an accurate record of the system's dynamics. Conversely, oversampling could lead to co-linearities in the signal [16], thus artificially affecting the dynamics.…”