Biology subjects

O'Reilly, D.

Publications and source records attributed to O'Reilly, D..

21 records · Page 2Linked to original sources

bioRxiv2020

Identifying differences in gait adaptability across various speeds using movement synergy analysis

IntroductionThe aim of this study was to identify movement synergies during normal-walking that can differentiate healthy adults in terms of gait adaptability at various speeds. To this end, the association between movement synergies and lower-limb coordination variability or Deviation Phase (DP) was investigated. A secondary aim of this study included an investigation into the moderating effect of these movement synergies on the relationship between DP and the smoothness of arm-swing motion quantified as the normalised jerk index (NJI). MethodA principal component analysis of whole-body marker trajectories from normal-walking treadmill trials at 0.8m/s, 1.2m/s and 1.6m/s was undertaken. Both DP and NJI were derived from approx. 8 minutes of perturbed-walking treadmill trials. Principal movement components, PMk, were derived and the RMS of the 2nd-order differentiation of these PMk (PAkRMS) were included as independent variables representing the magnitude of neuromuscular control in each PMk. The PAkRMS were input into separate maximal linear mixed-effects regression models to explain the variance in DP and (DP x NJI). A stepwise elimination of terms and comparison of models using Anova identified optimal models for both aims. ResultsAmong the first 7 validated PMk, PA4RMS (double-support phase) was identified as an optimal model and demonstrated a significant negative effect on DP however this effect may differ considerably across walking-speeds. An optimal model for describing the variance in (DP x NJI) included a fixed-effect of PA6RMS (Left - Right side weight transfer). Within-participant clustering was prevalent within both optimal models. InterpretationThe hypotheses that individuals who exhibited greater control on specific kinematic synergies would exhibit variations during perturbed walking was substantiated. Supporting evidence for the role of movement synergies during the double-support phase of gait in proactively correcting balance was presented. The potential influence of leg dominance on gait adaptability was also discussed. Future studies should investigate further the role of walking-speed and leg dominance on movement synergies and look to generalize these findings to patient populations. HighlightsO_LIBaseline movement synergies representing terminal-swing and double-support phases of gait were found to have significant negative effects on lower-limb coordination variability during perturbed-walking trials at various speeds. C_LIO_LIMovement synergies related to the double-support phase and weight transfer events of gait were determined to have a negative moderating effect on the translation of lower-limb coordination variability into upper-limb postural corrections. C_LIO_LIEvidence was presented for the important role of the double-stance phase of gait in gait adaptability while leg dominance was shown to play a potential role in differentiating healthy adults in this study. C_LI

neuroscience↗

bioRxiv2020

Slow walking synergies reveal a functional role for arm swing asymmetry in healthy adults: a principal component analysis with relation to mechanical work.

IntroductionThe purpose of this study was to reveal a functional role for arm-swing asymmetry during gait in healthy adults. The primary aim was to identify differences in propulsive and collision work between sides at either end of the double-support phase of slow-walking (WDS). The secondary aim was to identify differences between sides in propulsive and collision work done at either end of the single-support phase (WSS) and the effect of arm-swing asymmetry on this difference. It was hypothesized that differences between sides would be evident during the double-support phase and that these differences would be coherent with differences in single-support control symmetry. It was also hypothesized that left-side dominant arm-swing would reduce the collision work done on the dominant lower-limb side. MethodsA secondary analysis of slow-walking trials of 25 healthy, uninjured adults was undertaken where a principal component analysis of kinematic data was carried out to generate the movement synergies (PMk). Independent variables included the tightness of neuromuscular control (Nk) which was formulated from the first PMk and arm-swing asymmetry which was quantified using the directional Arm-swing asymmetry index (dASI). Dependent variables included the difference between double-support collision and propulsive work (WDS) and a ratio consisting of the difference between single-support collision and propulsive work of both sides (WSS). A linear mixed-effects model was utilized for aim 1 while a multiple linear regression analysis was undertaken for aim 2. ResultsHealthy adult gait was accompanied by a left-side dominant arm-swing on average as seen elsewhere. For aim 1, Nk demonstrated a significant negative effect on WDS while sidedness had a direct negative effect and indirect positive effect through Nk on WDS. The most notable finding was the effect of a crossover interaction between dASI and Nk which demonstrated a highly significant positive effect on Wss. All main-effects in aim 2 were in the hypothesized direction but were insignificant. InterpretationThe aim 1 hypothesis was supported while the aim 2 hypothesis was not supported. Nk exhibited opposing signs between ipsilateral and contralateral WBAM regulation, revealing a differential control strategy while the effect of sidedness on WDS was evident. The findings from aim 2 describe a relationship between arm-swing asymmetry and the magnitude of lower-limb mechanical work asymmetry that is cohesive with the sidedness effect found in aim 1. Individuals with left-side dominant arm-swing had an increased collision work indicative of a lateralised preference for WBAM regulation. Evidence was therefore put forward that arm-swing asymmetry during gait is related to footedness. Future studies should look to formally confirm this finding. Implications for further research into dynamic balance control mechanisms are also discussed. HighlightsO_LILeft-side dominant arm-swing was found to be related to the degree of lower-limb mechanical work asymmetry. C_LIO_LIThe relationship between arm-swing asymmetry and lower-limb mechanical work symmetry was explained by a moderating effect of neuromuscular control. C_LIO_LIA differential control on single-and double-support phases was demonstrated by the neuromuscular system, supporting previous studies and this control may be heavily influenced by sidedness. C_LI

neuroscience↗

bioRxiv2019

Feature selection for the classification of fall-risk in older subjects: a combinational approach using static force-plate measures

IntroductionFeature selection prevents over-fitting in predictive models. This study aimed to present an effective feature selection method that leads to a reliable classification of fall-risk in older subjects using static force-platform data across four conditions only.\n\nMethod528 features were generated from a publicly available dataset of force-plate signals from 45 low-risk and 28 high-risk subjects. Subjects were classified as high- or low-risk if they recorded [≥]1 falls in the prior 12 months and/or were rated as high-risk on the FES. The feature selection protocol included SVM-RFE, GA and ReliefF and finally SAFE. Several machine-learning models were then used to evaluate classification performance.\n\nResults67 features were identified after the three-fold process which was further reduced to 18 features after SAFE. The MLP achieved the highest average classification accuracy of 80%. All classification models evaluating this final subset displayed high variance across all performance metrics, especially in terms of sensitivity to high-risk subjects.\n\nInterpretationAn optimal feature set of static force-plate measures was insufficient in creating a reliable classifier of fall-risk. This was due potentially to the limited information about fall-risk that could be provided by such measures leading to under-fitting/over-fitting being unavoidable and appeared to be centered around an insensitivity to high-risk subjects.\n\nConclusionStatic stability measures have shown some usability in fall-risk classification however feature sets limited to such measures are inadequately sensitive to high-risk subjects. The utilized feature selection methods demonstrated their ability to identify relevant stability measures and could be used successfully on dynamic measures.

bioinformatics↗