Background: Pain-related cognitions are associated with motor control changes in people with chronic low-back pain (CLBP). The mechanism underlying this association is unclear. We propose that perceived threat increases muscle-spindle-reflex-gains, which reduces the effect of mechanical perturbations, and simultaneously decreases movement precision. Aim: To evaluate effects of CLBP and pain-related cognitions on the impact of mechanical perturbations on trunk movement, and associations between these perturbation effects and movement precision. Methods: 30 participants with CLBP and 30 healthy controls, performed two consecutive trials of a seated repetitive reaching task. During both trials participants were warned for mechanical perturbations, which were only administered during the second trial. The perturbation effect was characterized by the deviation of the trajectory of the T8 vertebra relative to the sacrum. Trunk movement precision was expressed as tracking error during a trunk movement target tracking task. We assessed pain-related cognitions with the task-specific ‘Expected Back Strain’-scale (EBS). We used a two-way-Anova to assess the effect of Group (CLBP vs back-healthy) and dichotomized EBS (higher vs lower) on the perturbation effect, and a Pearson's correlation to assess associations between perturbation effects and movement precision. Findings: Higher EBS was associated with smaller perturbation effects (p ≤ 0.011). A negative correlation was found between the perturbation effect and the tracking error, in the higher EBS-group (r = −0.5, p = 0.013). Interpretation: These results demonstrate that pain-related cognitions influence trunk movement control and support the idea that more negative pain-related cognitions lead to an increased resistance against perturbations, at the expense of movement precision.
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Purpose: The purpose of this systematic review was to assess whether LBP patients demonstrate signs of splinting by evaluating the reactions to unexpected mechanical perturbations in terms of (1) trunk muscle activity, (2) kinetic and (3) kinematic trunk responses and (4) estimated mechanical properties of the trunk. Methods: The literature was systematically reviewed to identify studies that compared responses to mechanical trunk perturbations between LBP patients and healthy controls in terms of muscle activation, kinematics, kinetics, and/or mechanical properties. If more than four studies reported an outcome, the results of these studies were pooled. Results: Nineteen studies were included, of which sixteen reported muscle activation, five kinematic responses, two kinetic responses, and two estimated mechanical trunk properties. We found evidence of a longer response time of muscle activation, which would be in line with splinting behaviour in LBP. No signs of splinting behaviour were found in any of the other outcome measures. Conclusions: We conclude that there is currently no convincing evidence for the presence of splinting behaviour in LBP patients, because we found no indications for splinting in terms of kinetic and kinematic responses to perturbation and derived mechanical properties of the trunk. Consistent evidence on delayed onsets of muscle activation in response to perturbations was found, but this may have other causes than splinting behaviour.
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A commentary on: Older adults can improve compensatory stepping with repeated postural perturbations by Dijkstra,B.W., Horak,F.B., Kamsma,Y.P.T., and Peterson,D.S.(2015).Front.AgingNeurosci. 7:201. doi:10.3389/fnagi.2015.00201. In sum, the results of Dijkstra etal. (2015) are of importance and significance for the field of falls prevention and stability control in aging. In particular, the work highlights the importance of multidirectional step or perturbation training, due to a lack of transfer across tasks. Whether this would hold for multidirectional gait perturbations is unclear, due to the influence of forward velocity during walking. Future work should explore different types, intensities and frequencies of perturbations in order to determine the most effective strategy for improving dynamic stability control in healthy older adults and inpatients with declined locomotor performance and increased falls risk. Finally, as Dijkstra etal. (2015) and previous studies found floor effects in the adaptation of young participants, further attempts should be made to appropriately scale perturbations to participant or groupability, in order to reliably compare adaptation across different groups.
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PURPOSE: To compare the responses in knee joint muscle activation patterns to different perturbations during gait in healthy subjects.SCOPE: Nine healthy participants were subjected to perturbed walking on a split-belt treadmill. Four perturbation types were applied, each at five intensities. The activations of seven muscles surrounding the knee were measured using surface EMG. The responses in muscle activation were expressed by calculating mean, peak, co-contraction (CCI) and perturbation responses (PR) values. PR captures the responses relative to unperturbed gait. Statistical parametric mapping analysis was used to compare the muscle activation patterns between conditions.RESULTS: Perturbations evoked only small responses in muscle activation, though higher perturbation intensities yielded a higher mean activation in five muscles, as well as higher PR. Different types of perturbation led to different responses in the rectus femoris, medial gastrocnemius and lateral gastrocnemius. The participants had lower CCI just before perturbation compared to the same phase of unperturbed gait.CONCLUSIONS: Healthy participants respond to different perturbations during gait with small adaptations in their knee joint muscle activation patterns. This study provides insights in how the muscles are activated to stabilize the knee when challenged. Furthermore it could guide future studies in determining aberrant muscle activation in patients with knee disorders.
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Knee joint instability is frequently reported by patients with knee osteoarthritis (KOA). Objective metrics to assess knee joint instability are lacking, making it difficult to target therapies aiming to improve stability. Therefore, the aim of this study was to compare responses in neuromechanics to perturbations during gait in patients with self-reported knee joint instability (KOA-I) versus patients reporting stable knees (KOA-S) and healthy control subjects.Forty patients (20 KOA-I and 20 KOA-S) and 20 healthy controls were measured during perturbed treadmill walking. Knee joint angles and muscle activation patterns were compared using statistical parametric mapping and discrete gait parameters. Furthermore, subgroups (moderate versus severe KOA) based on Kellgren and Lawrence classification were evaluated.Patients with KOA-I generally had greater knee flexion angles compared to controls during terminal stance and during swing of perturbed gait. In response to deceleration perturbations the patients with moderate KOA-I increased their knee flexion angles during terminal stance and pre-swing. Knee muscle activation patterns were overall similar between the groups. In response to sway medial perturbations the patients with severe KOA-I increased the co-contraction of the quadriceps versus hamstrings muscles during terminal stance.Patients with KOA-I respond to different gait perturbations by increasing knee flexion angles, co-contraction of muscles or both during terminal stance. These alterations in neuromechanics could assist in the assessment of knee joint instability in patients, to provide treatment options accordingly. Furthermore, longitudinal studies are needed to investigate the consequences of altered neuromechanics due to knee joint instability on the development of KOA.
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Adverse Outcome Pathways (AOPs) are conceptual frameworks that tie an initial perturbation (molecular initiat- ing event) to a phenotypic toxicological manifestation (adverse outcome), through a series of steps (key events). They provide therefore a standardized way to map and organize toxicological mechanistic information. As such, AOPs inform on key events underlying toxicity, thus supporting the development of New Approach Methodologies (NAMs), which aim to reduce the use of animal testing for toxicology purposes. However, the establishment of a novel AOP relies on the gathering of multiple streams of evidence and infor- mation, from available literature to knowledge databases. Often, this information is in the form of free text, also called unstructured text, which is not immediately digestible by a computer. This information is thus both tedious and increasingly time-consuming to process manually with the growing volume of data available. The advance- ment of machine learning provides alternative solutions to this challenge. To extract and organize information from relevant sources, it seems valuable to employ deep learning Natural Language Processing techniques. We review here some of the recent progress in the NLP field, and show how these techniques have already demonstrated value in the biomedical and toxicology areas. We also propose an approach to efficiently and reliably extract and combine relevant toxicological information from text. This data can be used to map underlying mechanisms that lead to toxicological effects and start building quantitative models, in particular AOPs, ultimately allowing animal-free human-based hazard and risk assessment.
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Background: Steady-state gait characteristics appear promising as predictors of falls in stroke survivors. However, assessing how stroke survivors respond to actual gait perturbations may result in better fall predictions. We hypothesize that stroke survivors who fall have a diminished ability to adequately adjust gait characteristics after gait is perturbed. This study explored whether gait characteristics of perturbed gait differ between fallers and non fallers. Method: Chronic stroke survivors were recruited by clinical therapy practices. Prospective falls were monitored over a six months follow up period. We used the Gait Real-time Analysis Interactive Lab (GRAIL, Motekforce Link B.V., Amsterdam) to assess gait. First we assessed gait characteristics during steady-state gait and second we examined gait responses after six types of gait perturbations. We assessed base of support gait characteristics and margins of stability in the forward and medio-lateral direction. Findings: Thirty eight stroke survivors complete our gait protocol. Fifteen stroke survivors experienced falls. All six gait perturbations resulted in a significant gait deviation. Forward stability was reduced in the fall group during the second step after a ipsilateral perturbation. Interpretation: Although stability was different between groups during a ipsilateral perturbation, it was caused by a secondary strategy to keep up with the belt speed, therefore, contrary to our hypothesis fallers group of stroke survivors have a preserved ability to cope with external gait perturbations as compared to non fallers. Yet, our sample size was limited and thereby, perhaps minor group differences were not revealed in the present study.
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Older people today are more likely to age in their own private living environment. However, many face declining health and/or other issues that affect their ability to live independently and necessitate additional support. Such support can be provided by formal networks, but a considerable part can also be offered by informal networks of older people themselves. Going beyond these networks, older people can additionally and perhaps even more substantially benefit from vital communities. Nevertheless, even though this term is increasingly common in the literature, its meaning remains indistinct. A more thorough understanding of this concept might provide valuable knowledge that health care professionals, researchers and community workers can use to offer meaningful and effective support. The purpose of this paper is to draw on existing empirical research on vital communities to build knowledge of the different descriptions and dimensions of the concept. Arksey and O’Malley’s scoping review methodology was adopted. Our search, conducted on 23 March 2020 and updated on 06 January 2021, yielded 4433 articles, of which six articles were included in the scoping review. We deduced that the conceptualisation of a vital community is based on three dimensions: the aim of a vital community, the processes behind a vital community and the typical characteristics of a vital community. None of the selected studies have mapped all three dimensions. Nevertheless, we assume that understanding all three matters when vital communities aim to contribute to the quality of life of people ageing in place.
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Key to reinforcement learning in multi-agent systems is the ability to exploit the fact that agents only directly influence only a small subset of the other agents. Such loose couplings are often modelled using a graphical model: a coordination graph. Finding an (approximately) optimal joint action for a given coordination graph is therefore a central subroutine in cooperative multi-agent reinforcement learning (MARL). Much research in MARL focuses on how to gradually update the parameters of the coordination graph, whilst leaving the solving of the coordination graph up to a known typically exact and generic subroutine. However, exact methods { e.g., Variable Elimination { do not scale well, and generic methods do not exploit the MARL setting of gradually updating a coordination graph and recomputing the joint action to select. In this paper, we examine what happens if we use a heuristic method, i.e., local search, to select joint actions in MARL, and whether we can use outcome of this local search from a previous time-step to speed up and improve local search. We show empirically that by using local search, we can scale up to many agents and complex coordination graphs, and that by reusing joint actions from the previous time-step to initialise local search, we can both improve the quality of the joint actions found and the speed with which these joint actions are found.
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In order to achieve a level of community involvement and physical independence, being able to walk is the primary aim of many stroke survivors. It is therefore one of the most important goals during rehabilitation. Falls are common in all stages after stroke. Reported fall rates in the chronic stage after stroke range from 43 to 70% during one year follow up. Moreover, stroke survivors are more likely to become repeated fallers as compared to healthy older adults. Considering the devastating effects of falls in stroke survivors, adequate fall risk assessment is of paramount importance, as it is a first step in targeted fall prevention. As the majority of all falls occur during dynamic activities such as walking, fall risk could be assessed using gait analysis. It is only recent that technology enables us to monitor gait over several consecutive days, thereby allowing us to assess quality of gait in daily life. This thesis studies a variety of gait assessments with respect to their ability to assess fall risk in ambulatory chronic stroke survivors, and explores whether stroke survivors can improve their gait stability through PBT.
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