A recent fMRI study directly assessed motor-cognitive dual- tasking in young and old adults using a simulated balance task concurrently with a calculation task ( Papegaaij et al., 2017 ). Age-related differences in the up-regulation of activity from single to dual tasks were shown in the right insular cortex. However, no dual-task-specific activity was present for the applied dual task in that study. This suggests that task performance might not have involved higher working memory load or additional coordination processes, which in turn might be subject to inter-individual variability to a higher degree and thus might underly brain-behavior correlations. The cognitive dual task applied in our study revealed such dual- task-specific activity. Still, the association with posturalsway remains an indirect one, as brain and behavioral measures were obtained in different sessions. This reflects the trade- off between using a naturalistic whole body balance task and obtaining anatomically precise online imaging data, which currently has to be resolved depending on the specific research question.
Attention can be defined as the information processing capacity of an individual, which is presumably limited (see e.g., Kahneman, 1973; Wickens, 1980, 1989). Usually, studies in the context of postural control used so called cognitive-motor dual-tasks (e.g., Dault et al., 2003) to determine the attentional demand. In these cognitive-motor dual-tasks a postural task (e.g., balancing on a balance board, standing, or walking) and a secondary cognitive task (e.g., counting backward; see Yardley et al., 1999) are performed at the same time and performance is compared to performing only one task separately. According to the notion of limited attentional resources, a more demanding postural task should induce more interference with a cognitive tasks and vice versa (Woollacott and Shumway- Cook, 2002; Fraizer and Mitra, 2008; Boisgontier et al., 2013). However, empirical evidence is ambiguous, as some studies report interference between a motor task and a cognitive task (e.g., Andersson et al., 1998), whereas others did not report an effect of postural control demands (whether participants were sitting or standing) on the performance in the cognitive tasks in general (Dault et al., 2001; see also Huxhold et al., 2006). Other studies tackled this issue but the majority focused on the question whether postural control suffers in terms of for example posturalsway and sway velocity increases in cognitive-motor dual tasks compared to single tasks (in this case if a cognitive task is added vs. only a postural task is given; see e.g., Beurskens et al., 2016).
maintenance of postural equilibrium in ACLR patients. The first experimental study in healthy individuals demonstrated that functional brain connectivity allowed to reasonably describe the allocation of cortical activation appearing with postural instability and changed sensory information induced by a narrowed base of support. Compared to bipedal standing, the single leg stance was characterized by increased inhibition of transcortical connections in conjunction with a global increase in cortical excitability. These findings indicated an enhanced task-specific cortical processing as a consequence of incremental posturalsway. Thus, a critical finding of studies I & II was that postural control assessment based on single leg standing may allow to identify postural deficiencies, as this simple balance task already requires increased cortical alertness and selective inhibition of sensorimotor pathways within the cortex to properly control postural stability. While PSD in study II solely allowed to draw broad conclusions regarding cortical excitability, functional connectivity provided a more differentiated and revelatory view into cortical contributions to postural control.
associated PM k to the overall variance. The EV k were therefore not subject specific in the current study. It has been proposed to calculate relative variances rVAR k of the scores as subject- specific variables that directly correspond to the EV k and quantify how much each PM k contributed to this subject’s overall postural variance ( Federolf et al., 2013 ). However, as both rVARs and EVs quantify the variance in the data, they are proportional to the square of the postural movement amplitude. Therefore, in the current study the square roots of the subject specific variances were calculated to compute relative standard deviations rSTD k , to obtain variables that scale directly to postural movement amplitudes. For each subject, the rSTD k quantify the percentage of the subject-specific overall postural motion that is explained by each PM k . If systematic differences exist in the rSTDs between groups, then this indicates a difference in the coordinative structure of the postural movements in the sense that specific PMs are more or less important for the subjects’ overall posturalsway.
meaning that the headshake direction had an effect on the entire trial. The results and associated graphs from the MPF of the PV were unexpected, which adds weight to the assumption that the variable is, in this context, unreliable. In addition many statistical and interactional effects were analysed which can lead to random errors, and it is important to note the variables and PMs that did not confirm this hypothesis. Consequently, no conclusion can be drawn from the results of the different headshaking directions and their influence on directional sensitivity and corpus callosum. No other studies in this field have been able to conclusively determine whether any specific head movement would have a greater effect on posturalsway. Some studies suggest that an upward head position (neck extension) increases posturalsway more than other positions due to the utricular otoliths being placed in an unfavourable position (Jackson & Epstein, 1991; Barin et al., 1992, Kogler et al., 2000), however the study from Lamontagne et al., (2003) showed no difference between frontal and sagittal head movements. The different populations sampled and the diverse test settings may explain these discrepancies in results.
Regarding CoP in standing, in the reviewed studies we also found no difference between groups in CoP sway in standing on a stable surface with eyes open. However, we found an indication for differences between groups in situations with higher postural demands. In terms of standing on a stable surface with eyes open, the majority of the studies included in our review could not find any difference between groups. In the condition where visual information is excluded, a slight majority of studies included in our review showed a higher CoP sway for the LBP group. For that reason and owing to the higher quality of studies reporting a difference, we conclude that there is a tendency for a higher CoP sway in LBP group during standing conditions with higher demands. These results are somewhat different from the results of Mazaheri et al. (2013) and Ruhe et al. (2011a) . Regarding standing on a stable surface our results are in line with those of Mazaheri et al. (2013) , who did not find any differences, but not with Ruhe et al. (2011a) , who reported differences in posturalsway. In their review Ruhe et al. (2011a) only referred to studies confirming differences in parameters, while the ratio to studies with non-significant differences in single parameters is not mentioned. In contrast, when evaluating a parameter, we also considered non-significant results, since it is also necessary to see how consistent the results were. In terms of standing on a stable surface with vision occluded our results are in line with
When the vision sense is suppressed, greater participation from other sensory and processing systems is required. This factor may explain the need for greater adjustments to maintain balance. Scholz et al. (2012) predicted an increase body sway due the increased task difficulty in estimating the dynamics of the body. In the study of Alonso et al. (2012), the mediolateral displacement of COP decreased during the EC trial in both height groups; the smaller group (women) had a greater ML - displacement (-0.629 (0.17)) than men group (-0.594 (0.15)). Similar results were found in the current study, although no statistical significant height group effect in bipedal stance was detected. The COP_EA (normalized and not-normalized) results reflected Alonso et al.,(2012) results; COP dispersion for both height groups increased in >1,90 group (EC) and decreased in <1,80 group (EC), shown in figures (7) and (8). In tandem stance both height groups, comparing EO vs EC, showed an increment in all not-normalised variables considered. Especially the taller group had an evident increase in the sway ellipse area, EC (>1,90, 120.5 ± 111.7) (<1,80 23.6 ± 11.4), shown in figure (13). The increased posturalsway under eyes-closed condition compared to eyes-open condition, is in agreement with many studies on healthy subjects (Remaud, 2012; Remaud, 2013;) In absence of vision, Hsu et al., (2007) and Krishanmoorthy (2005), reported that overall joint configuration variance increased in the eyes-closed condition compared to the eyes-open condition. According to Murillo et al., (2012), changes in control complexity are an indicator of how the system components’ relationship modifies to adapt to the difficulty of the task.
In our present study we found results indicative of an adaptive process in terms of lower leg muscle activity and steady state sway, with a general decrease over time, independently whether Light Touch was used or not. This supports the idea that exposing people repetitively to a perturbation leads to an optimization of the postural response. Interestingly, this adaptive process was present although participants were perturbed to a randomized sequence of three different force pushes within one block. Given the range of the perturbations with a small, medium and strong force push, one possibility is that instead of finding three strategies against the perturbation force, the postural control systems settled for a compromise across the three forces and prepared for a medium configuration. If this were the case we would expect to see greater improvement, respectively greater decrease of muscle activity and posturalsway in the medium force push condition. Looking at the decrease in percentages, this was the case. While in the small and strong force push condition we see a reduction in the EMG integral of the Tibialis of 13% and 11% respectively, the medium force push condition shows the highest decrease with 16%. Similar results can be found for the asymptote, with a decrease of 15% in both the small and strong force push condition and 20% decrease in the medium force push. Unexpectedly, cTBS stimulation resulted in more decreased levels of activity of the Tibialis anterior and peak activity of the Gastrocnemius compared to sham stimulation. This observa- tion contrasts with tonic activity of the Gastrocnemius, where activity stayed relatively the same over time, independently of the type of stimulation. Sozzi and colleagues [ 40 ] investi- gated the individual role of the lower leg muscles during standing in tandem Romberg stance and reported roles of the muscles specific to individual balancing functions. They concluded that while the soleus supports the body against gravity, the Tibialis Anterior and the peroneus stabilize the body in the medio-lateral direction. This supports our conclusion that the greater reduction in Tibialis anterior activity is tied to an improved postural adaptation following cTBS of the rPPC.
in the signal. So, multivariate alternatives have been considered more frequently. Linear approaches assume that movement (COP sway) is not random but structured and therefore higher sway values would lead to poorer performance. However, these methods do not take any temporal structure of the signal or dynamical postural fluctuations into account. Non-linear dynamic approaches on the other hand address that chaotically driven processes of posturalsway across timescales. In these, higher levels of posturalsway do not necessarily lead to decreased postural control. By referring to the terminology of complexity, a high amount of random fluctuations within the signal display healthy behavior. Moreover, with respect to attentional processes, it is stated that the more regular the signal becomes the more attentional control is invested ( Donker et al., 2007 ). Busa and van Emmerik (2016) supported this notion by proposing that higher numbers of complexity indicate more autonomous movement control. When referring to common attentional focus theories such as the CAH, a constrained multiscale entropy signal which indicates “worse” balance performance would be associated with a lower CI. Henceforth, lower regularity of the signal as found for the wall 5 m distance can be linked to more functional performance.
No significant decrements in performance on a standard bat- tery of sensory organization tests, i.e. with the head erect, was observed after 42-63 days of bed rest 38 , suggesting that either no functionally significant change occurred or that the standard battery was insensitive to the changes that did occur. Ocular counter-rolling and subjective visual vertical assessed during 90º whole body roll tilt to the left and right were also unaf- fected by 21 days of bed rest 18,39 . Our result that postural in- stability increases during dynamic head tilts after bed rest of only 5 days indicates that there are some measurable decre- ments in balance control performance associated with bed rest.
The harmonic sway tests executed with the appended hull are presented in Figure 13. The differences at zero propeller rate are again minor compared to the bare hull results in Figure 9 but the mean sinkage at model speed 0.872 m/s shows more steep variations in the maximum sinkage range. The presence of the propeller and rudder influences the pattern of the time series. If the propeller is running at the model self-propulsion point, slightly -0.2
x Reporting about Postural Control strategies in patients with low back pain vary x We examine spinal kinematics and Centre of pressure in 3 standing tasks x Patients with low back pain differ in Postural Control strategies from controls x Frontal plane kinematics of the spine are best distinctive.
We believe that in order to study the effects of cognitive DT on postural control the following two aspects are important to be considered: First, the dual-task difficulty levels used in previous studies relied on several different forms of cognitive demands such as listening, memory, reaction time, spatial distinction or calculation [ 15 , 16 , 20 – 24 ]. Since previous results suggest that different forms of cognitive tasks display contrasting levels of interaction with postural control [ 10 ], this diversity in cognitive resource requirement makes comparisons among studies and even between trials in the same study difficult. Second, center of pressure COP-based variables are very common in postural control research. A great advantage of such analyses is that several interesting aspects of postural control can be quantified based on the COP time-series, since it contains the combined information about body positioning and acting forces [ 25 ]. Nevertheless, literature using COP variables is not consistent. For example, on the one hand COP-irregularity has been observed to increase with task difficulty, i.e., higher entropy was found when balancing with eyes closed, on foam, or when dual-tasking [ 26 – 28 ]. In addition, COP-entropy was also found to be linked to better health or training status, e.g., young vs. old, healthy vs. concussed or trained vs. non-trained subjects [ 20 – 22 , 29 , 30 ]. In these studies, higher COP-irregularity was associated with a more adaptable and alert system. On the other hand, however, higher COP-irregularity has also been associated with balancing in lower task difficulty (e.g., eyes open condition) or elderly fallers [ 20 , 21 , 24 , 31 , 32 ]. Here, higher entropy was linked to disordered and less effective postural control. Hence, although COP-variables have proven to be very effective distinguishing groups, their implications on the control of movements are not straight forward, explaining why the literature is not consistent.
Abbreviations: RPE: rating of perceived exertion; MSD: musculoskeletal disorder; OWAS: ovako working posture analysing system; RULA: rapid upper limb assessment; LUBA: postural loading on the upper body assessment; REBA: rapid entire body assessment; OCRA: occupational repeti- tive action;S D: standard deviation; EMG: surface electromyography; LUT: left upper trapezius pars descendens; RUT: right upper trapezius pars descendens; LLT: left trapezius pars ascendens; RLT: right trapezius pars ascendens; LAD: left anterior deltoideus; RAD: right anterior deltoideus; LES: left erector spinae longissimus; RES: right erector spinae longissimus; SENIAM: surface electroMyoGraphy for the non-invasive assessment of muscles; MVC: maximum voluntary con- traction; MANOVA: multivariate analysis of variance; ANOVA: analysis of variance; OLS: ordinary least squares; MANCOVA: multivariate analysis of covariance
Einfluss sportlicher Leistungsfähigkeit auf den Body Sway gezeigt haben. In einer Studie von Barnett und Kollegen konnte ein einjähriges Interventionsprogramm zu einer signifikanten Abnahme des Body Sways führen (Barnett et al. 2003). Brooke- Wavell und Kollegen verglichen eine Gruppe postmenopausaler Frauen, die täglich „Walken“ (von engl. walk = gehen) gingen, mit einer Gruppe, die keinen Sport trieb. Es zeigte sich, dass die sportlich aktiven Frauen signifikant niedrigere Ergebnisse in den Body Sway Messungen hatten (Brooke-Wavell et al 1998). Perrin und Kollegen wollten in ihrer Studie den Einfluss der „Lebenszeit-Sportlichkeit“ auf den Body Sway zeigen. Sie befragten die Patienten in welchem Abschnitt ihres Lebens eine regelmäßige sportliche Betätigung stattgefunden hatte. Es zeigte sich, dass die sportliche Betätigung zu jedem Zeitpunkt im Leben einen positiven Effekt auf die Body Sway Messung hatte. Zu betonen ist, dass jene Patienten, die immer Sport trieben (S/S), am besten abschnitten, gefolgt von jenen, die erst im höheren Alter sportlich aktiv wurden (-/S). Die Patienten, die nur in jüngerem Alter Sport getrieben hatten (S/-), zeigten einen niedrigeren Body Sway, als jene Patienten, die niemals einer körperlichen Betätigung nachgegangen waren (-/-) (Perrin et al. 1999). Anhand dieser Ergebnisse lässt sich ein Zusammenhang zwischen sportlicher Aktivität und Body Sway vermuten, der in der aktuellen Studie nicht bestätigt werden konnte. In der Untersuchung von Barnett und Mitarbeitern wurden im Gegensatz zur aktuellen Studie nur Patienten eingeschlossen, die ein deutlich erhöhtes Sturzrisiko aufwiesen. Diese Patientengruppe profitierte vermutlich am besten von einem sportlichen Interventionsprogramm. Hinzu kommt, dass das Trainingsprogramm der Interventionsgruppe von einem Physiotherapeuten explizit für Patienten mit erhöhtem Sturzrisiko und z.T. positiver Sturzanamnese entwickelt wurde. Es enthielt verschiedene Übungen, die gezielt Balance, Koordination, Beweglichkeit und Muskelkraft trainieren sollten. Übereinstimmung der aktuellen Ergebnisse findet man in einer Studie von Liu-Ambrose und Kollegen. In der Studie wurde vergleichbar mit der aktuellen Studie der mögliche Einfluss von Sport auf den Body Sway neben weiteren Einflussfaktoren untersucht. Die eigen gemachten Angaben der Patienten über ihre sportliche Aktivität zeigten ebenfalls keinen Zusammenhang mit dem Ausmaß des Body Sways.
In addition to the Rocabado cephalometry, postural assessment was based on measuring the distribution of weight on the foot. Under normal conditions, the physiological curves of the spine determine a percentage distribution of weight on the level of the feet which was quantified by Kapandji in the following way: 50% on the hindfoot and 50% on the fore- foot. The altered position of the cervical spine causes patients with second-class malocclu- sion to tend to carry most of their weight on the forefoot. For this reason we decided to use a stabilometric platform for postural evaluation. Each evaluation was performed using the Satbiloboard postural platform and each measurement was analyzed using the Global Pos- tural Analysis software (GPA).
al., 1973; Hepple, 2003; Papegaaij et al., 2014b) that may lead to increased body sway. However, sway variables are not always conclusive especially when testing healthy elderly subjects (Bernard-Demanze et al., 2009) and COP-variables are, once more, difficult to interpret. The results of the second study provided further evidence that the postural control of healthy golden agers is already affected, however not as a whole, since aging effects only emerged in the control of very specific movement strategies. In detail, the younger population’s control system intervened more often and with less variable timing than the older population’s, particularly, in the most critical movement that had the least base of support. In addition, this critical component also contributed less to the overall sway of the younger population, suggesting that the tight control constrained this movement strategy. Similar to the first study, these results also accentuate the importance of distinguishing movement strategies, since group differences that appear only in specific movement strategies could be overshadowed by other movement dynamics. Moreover, tight control combined with reduced relative sway in critical movement components might prove to be a meaningful criterion for good balance performance. However, follow-up research is needed to support this idea.
The purpose of the current study was to determine the origin of changes in COP regularity (quantified through SaEn of the COP time series) in response to moderate perturbations of the human postural control system. We hypothesized that changes in the regularity of movement components could produce changes in COP regularity (hypothesis 1), or that changes in coordinative complexity (i.e., changes in the structure and dimensionality of the whole-body movement) would produce changes in COP regularity (hypothesis 2). Our results supported the first, but not the second hypothesis: we did find decreased COP regularity immediately after head-shaking, particularly for tilting (ear-to-shoulder) head-shaking, and specifically in the anterior–posterior component of the COP time series. For these trials, we also found decreased regularity in the time series of the first five movement components, as predicted by hypothesis 1. However, we did not find significant changes in the structure or the dimensionality of the whole-body postural movements, contrary to the prediction of hypothesis 2. Figure 3 visualizes this finding: if changes in anterior–posterior COP entropy are observed (top graph), then hypothesis 1 predicts changes, particularly in the movement components with substantial anterior–posterior contributions (PM 1 , PM 3 , PM 5 ; middle three graphs), while hypothesis 2 predicts changes in the coordinative complexity (here represented through rCUM 5 ; bottom graph), which were not observed.
Foot arches in human feet absorb shock and are vital in maintaining balance. The contour of the foot widens with age, and inadequate exercise and increased body weight may cause foot muscle deterioration and increase flat footed structures [1-4]. Foot structure tends to worsen as the shock-absorbing effect deteriorates and as plantar pressure distribution abnormalities increase. An abnormal arch structure may cause plantar fasciitis, plantar pain, tendonitis, foot pain, muscle ache, knee pain, back pain, or other problems. Furthermore, the ability of people with flat feet to maintain postural stability deteriorates and leads to an increased risk of falling [5, 6]. Therefore, strategies such as corrective aids to control abnormal foot gait biomechanics are used to alleviate the discomfort experienced . However, appropriate assessment instruments that quantify changes in postural stability are still required [8, 9].
Impaired motor control of the lumbar spine has been proposed as one of the possible mechanisms underlying LBP (Panjabi, 1992; Cholewicki & McGill, 1996; Hodges et al., 2013b). Previous investigations detected alterations in motor control at the trunk particularly in situations of sudden load changes (Radebold et al., 2000; Cholewicki et al., 2005; Reeves et al., 2005). Thereby, LBP patients showed changes in muscle recruitment patterns in muscles of the trunk, with muscular responses being delayed or altered in activity levels and patterns of co-activations (Radebold et al., 2000; Cholewicki et al., 2005; Reeves et al., 2005; Stokes et al., 2006; Jacobs et al., 2011; Jones et al., 2012b). One limitation of previous studies is however that muscular responses were mostly tested under static and simplified conditions with external loads being applied directly at the trunk in (quasi) static standing or half seated positions (Radebold et al., 2000, 2001; Cholewicki et al., 2005; Reeves et al., 2005). While these specific testing situations enabled the study of isolated trunk responses to sudden external loading, they did not allow the investigation of reactive responses as they may occur under real life circumstances (Arendt-Nielsen et al., 1996). Outside laboratory conditions, external loadings are rarely applied directly at the trunk, but usually transferred indirectly to the trunk via upper or lower extremities (Marigold & Misiaszek, 2009). Thereby, trunk responses have to be realized in conjunction with responses of other contributors, such as the lower extremities in situations of perturbed postural control. Only a few studies investigated changes in motor control offsite the trunk in response to sudden perturbations (Jacobs et al., 2011; Jones et al., 2012b). Those investigations showed an altered response pattern at the trunk as well as at the lower extremities in response to sudden surface translations in free standing. Moreover, these first findings support the notion that motor adaptation in pain may not simply consist of changes in excitability at the painful area, but rather cause a comprehensive restructure of motor control, both at the region of pain and offsite (Hodges & Tucker, 2011).