scholarly journals Postural control system influences intrinsic alerting state.

2015 ◽  
Vol 29 (2) ◽  
pp. 226-234 ◽  
Author(s):  
Julien Barra ◽  
Laurent Auclair ◽  
Agnès Charvillat ◽  
Manuel Vidal ◽  
Dominic Pérennou
2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Pilwon Hur ◽  
Yi-Tsen Pan ◽  
Christian DeBuys

AbstractHuman upright standing involves an integration of multiple sensory inputs such as vision, vestibular and somatosensory systems. It has been known that sensory deficits worsen the standing balance. However, how the modulation of sensory information contributes to postural stabilization still remains an open question for researchers. The purpose of this work was to formulate the human standing postural control system in the framework of the free-energy principle, and to investigate the efficacy of the skin stretch feedback in enhancing the human standing balance. Previously, we have shown that sensory augmentation by skin stretch feedback at the fingertip could modulate the standing balance of the people with simulated sensory deficits. In this study, subjects underwent ten 30-second trials of quiet standing balance with and without skin stretch feedback. Visual and vestibular sensory deficits were simulated by having each subject close their eyes and tilt their head back. We found that sensory augmentation by velocity-based skin stretch feedback at the fingertip reduced the entropy of the standing postural sway of the people with simulated sensory deficits. This result aligns with the framework of the free energy principle which states that a self-organizing biological system at its equilibrium state tries to minimize its free energy either by updating the internal state or by correcting body movement with appropriate actions. The velocity-based skin stretch feedback at the fingertip may increase the signal-to-noise ratio of the sensory signals, which in turn enhances the accuracy of the internal states in the central nervous system. With more accurate internal states, the human postural control system can further adjust the standing posture to minimize the entropy, and thus the free energy.


2020 ◽  
Vol 35 (1) ◽  
pp. 58-67
Author(s):  
Gabriel Felipe Moretto ◽  
Felipe Balistieri Santinelli ◽  
Tiago Penedo ◽  
Luis Mochizuki ◽  
Natalia Madalena Rinaldi ◽  
...  

Background Studies on short-term upright quiet standing tasks have presented contradictory findings about postural control in people with Parkinson’s disease (pwPD). Prolonged trial durations might better depict body sway and discriminate pwPD and controls. Objective The aim of this study was to investigate postural control in pwPD during a prolonged standing task. Methods A total of 26 pwPD and 25 neurologically healthy individuals performed 3 quiet standing trials (60 s) before completing a constrained prolonged standing task for 15 minutes. Motion capture was used to record body sway (Vicon, 100 Hz). To investigate the body sway behavior during the 15 minutes of standing, the analysis was divided into three 5-minute-long phases: early, middle, and late. The following body sway parameters were calculated for the anterior-posterior (AP) and medial-lateral (ML) directions: velocity, root-mean-square, and detrended fluctuations analysis (DFA). The body sway area was also calculated. Two-way ANOVAs (group and phases) and 1-way ANOVA (group) were used to compare these parameters for the prolonged standing and quiet standing, respectively. Results pwPD presented smaller sway area ( P < .001), less complexity (DFA; AP: P < .009; ML: P < .01), and faster velocity (AP: P < .002; ML: P < .001) of body sway compared with the control group during the prolonged standing task. Although the groups swayed similarly (no difference for sway area) during quiet standing, they presented differences in sway area during the prolonged standing task ( P < .001). Conclusions Prolonged standing task reduced adaptability of the postural control system in pwPD. In addition, the prolonged standing task may better analyze the adaptability of the postural control system in pwPD.


2005 ◽  
Vol 376 (3) ◽  
pp. 215-220 ◽  
Author(s):  
Maciej Bosek ◽  
Bronisław Grzegorzewski ◽  
Andrzej Kowalczyk ◽  
Ignacy Lubiński

2002 ◽  
Vol 11 (1) ◽  
pp. 51-66 ◽  
Author(s):  
Riann M. Palmieri ◽  
Christopher D. Ingersoll ◽  
Marcus B. Stone ◽  
B. Andrew Krause

Objective:To define the numerous center-of-pressure derivatives used in the assessment of postural control and discuss what value each might provide in the assessment of balance.Data Sources:MEDLINE and SPORTDiscus were searched with the termsbalance, postural control, postural sway,andcenter of pressure. The remaining citations were collected from references of similar papers. A total of 67 references were studied.Conclusions:Understanding what is represented by each parameter used to assess postural control is crucial. At the present time the literature has failed to demonstrate how the variables reflect changes made by the postural-control system. Until it can be shown that the center of pressure and its derivatives actually reveal changes in the postural-control system, the value of using these measures to assess deficits in postural control is minimized.


2019 ◽  
Vol 9 (11) ◽  
pp. 113 ◽  
Author(s):  
Harish Chander ◽  
Sachini N. K. Kodithuwakku Arachchige ◽  
Christopher M. Hill ◽  
Alana J. Turner ◽  
Shuchisnigdha Deb ◽  
...  

Background: Virtual reality (VR) is becoming a widespread tool in rehabilitation, especially for postural stability. However, the impact of using VR in a “moving wall paradigm” (visual perturbation), specifically without and with anticipation of the perturbation, is unknown. Methods: Nineteen healthy subjects performed three trials of static balance testing on a force plate under three different conditions: baseline (no perturbation), unexpected VR perturbation, and expected VR perturbation. The statistical analysis consisted of a 1 × 3 repeated-measures ANOVA to test for differences in the center of pressure (COP) displacement, 95% ellipsoid area, and COP sway velocity. Results: The expected perturbation rendered significantly lower (p < 0.05) COP displacements and 95% ellipsoid area compared to the unexpected condition. A significantly higher (p < 0.05) sway velocity was also observed in the expected condition compared to the unexpected condition. Conclusions: Postural stability was lowered during unexpected visual perturbations compared to both during baseline and during expected visual perturbations, suggesting that conflicting visual feedback induced postural instability due to compensatory postural responses. However, during expected visual perturbations, significantly lowered postural sway displacement and area were achieved by increasing the sway velocity, suggesting the occurrence of postural behavior due to anticipatory postural responses. Finally, the study also concluded that VR could be used to induce different postural responses by providing visual perturbations to the postural control system, which can subsequently be used as an effective and low-cost tool for postural stability training and rehabilitation.


Entropy ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 614 ◽  
Author(s):  
Felix Wachholz ◽  
Tove Kockum ◽  
Thomas Haid ◽  
Peter Federolf

Sample entropy (SaEn) applied on center-of-pressure (COP) data provides a measure for the regularity of human postural control. Two mechanisms could contribute to altered COP regularity: first, an altered temporal structure (temporal regularity) of postural movements (H1); or second, altered coordination between segment movements (coordinative complexity; H2). The current study used rapid, voluntary head-shaking to perturb the postural control system, thus producing changes in COP regularity, to then assess the two hypotheses. Sixteen healthy participants (age 26.5 ± 3.5; seven females), whose postural movements were tracked via 39 reflective markers, performed trials in which they first stood quietly on a force plate for 30 s, then shook their head for 10 s, finally stood quietly for another 90 s. A principal component analysis (PCA) performed on the kinematic data extracted the main postural movement components. Temporal regularity was determined by calculating SaEn on the time series of these movement components. Coordinative complexity was determined by assessing the relative explained variance of the first five components. H1 was supported, but H2 was not. These results suggest that moderate perturbations of the postural control system produce altered temporal structures of the main postural movement components, but do not necessarily change the coordinative structure of intersegment movements.


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