scholarly journals Leg Dominance Effects on Postural Control When Performing Challenging Balance Exercises

2020 ◽  
Vol 10 (3) ◽  
pp. 128 ◽  
Author(s):  
Arunee Promsri ◽  
Thomas Haid ◽  
Inge Werner ◽  
Peter Federolf
Keyword(s):  
Motion Tracking ◽  
Motor Behavior ◽  
Time Derivative ◽  
Principal Component ◽  
Neuromuscular Control ◽  
Movement Component ◽  
Balance Exercises ◽  
Coordinative Structure ◽  
Diagonal Plane ◽  
Leg Dominance

Leg dominance reflects the preferential use of one leg over another and is typically attributed to asymmetries in the neural circuitry. Detecting leg dominance effects on motor behavior, particularly during balancing exercises, has proven difficult. The current study applied a principal component analysis (PCA) on kinematic data, to assess bilateral asymmetry on the coordinative structure (hypothesis H1) or on the control characteristics of specific movement components (hypothesis H2). Marker-based motion tracking was performed on 26 healthy adults (aged 25.3 ± 4.1 years), who stood unipedally on a multiaxial unstable board, in a randomized order, on their dominant and non-dominant leg. Leg dominance was defined as the kicking leg. PCA was performed to determine patterns of correlated segment movements (“principal movements” PMks). The control of each PMk was characterized by assessing its acceleration (second-time derivative). Results were inconclusive regarding a leg-dominance effect on the coordinative structure of balancing movements (H1 inconclusive); however, different control (p = 0.005) was observed in PM3, representing a diagonal plane movement component (H2 was supported). These findings supported that leg dominance effects should be considered when assessing or training lower-limb neuromuscular control and suggest that specific attention should be given to diagonal plane movements.

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

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244582
Author(s):  
David Ó’Reilly ◽  
Peter Federolf
Keyword(s):  
Principal Component ◽  
Neuromuscular Control ◽  
Whole Body ◽  
Supporting Evidence ◽  
Normal Walking ◽  
Optimal Model ◽  
Double Support ◽  
Leg Dominance ◽  
Perturbed Walking

Introduction The 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. This study also investigated the moderating effect of movement synergies on the relationship between DP and the smoothness of arm-swing motion (NJI). Method A 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. Each PAkRMS were input into maximal linear mixed-effects models against DP and (DP x NJI) respectively. A stepwise elimination of terms and comparison of models using Anova identified optimal models for both aims. Results The principal movement related to the push-off mechanism of gait (PA4RMS) 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 representing Right—Left side weight transfer was identified. Interpretation The 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 as well as the potential for this approach in targeted rehabilitation. 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.

Correlation of Neuropsychiatric Symptoms in Dementia with Brain Perfusion: A 99mTc-SPECT-HMPAO Study with Brodmann Areas Analysis

2021 ◽  
Vol 19 ◽  
Author(s):  
Varvara Valotassiou ◽  
Nikolaos Sifakis ◽  
Chara Tzavara ◽  
Evi Lykou ◽  
Niki Tsinia ◽  
...  
Keyword(s):  
Partial Correlation ◽  
Motor Behavior ◽  
Neuropsychiatric Symptoms ◽  
Correlation Coefficients ◽  
Principal Component ◽  
Lewy Body Dementia ◽  
Brain Perfusion ◽  
Neuropsychiatric Inventory ◽  
Different Types ◽  
Brodmann Areas

Background: Neuropsychiatric symptoms (NPSs) are common in dementia. Their evaluation is based on Neuropsychiatric Inventory (NPI). Neuroimaging studies have tried to elucidate the underlying neural circuits either in isolated NPSs or in specific forms of dementia. Objective: : The objective of this study is to evaluate the correlation of NPS in the NPI with Brodmann areas (BAs) perfusion, for revealing BAs involved in the pathogenesis of NPSs in dementia of various etiologies. Method: We studied 201 patients (82 with Alzheimer's disease, 75 with Frontotemporal dementia, 27 with Corticobasal Syndrome, 17 with Parkinson Disease/Lewy Body Dementia). Exploratory factor analysis was carried out to evaluate underlying groups of BAs, and Principal Component analysis was chosen as extraction method using Varimax rotation. Partial correlation coefficients were computed to explore the association of factors obtained from analysis and NPI items controlling for age, educational yeas, and ACE-R. Results: We found 6 BAs Factors(F); F1 (BAs 8,9,10,11,24,32,44,45,46,47, bilaterally), F2 (Bas 4,5,6,7,23,31, bilaterally), F3 (BAs 19,21,22,37,39,40, bilaterally), F4 (BAs 20,28,36,38, bilaterally), F5 (BAs 25, bilaterally) and F6 (BAs 17,18, bilaterally). Significant and negative correlation was found between NPI1 (delusions) and F3,F6, NPI2 (hallucinations) and F6, NPI7 (apathy) and F1,F4,F5, NPI3 (agitation) - NPI10 (aberrant motor behavior) - NPI12 (eating disorders) and F1. We did not find any significant correlation for NPI4,5,6,8,9,11 (depression, anxiety, euphoria, disinhibition, irritability, sleep disorders, respectively). Conclusion: Several NPSs share the same BAs among different types of dementia, while the manifestation of the rest may be attributed to different neural networks. These findings may have an impact on patients’ treatment.

Patterns of neuropsychiatric sub-syndromes in Brazilian and Norwegian patients with dementia

2012 ◽  
Vol 25 (2) ◽  
pp. 228-235 ◽  
Author(s):  
Annibal Truzzi ◽  
Ingun Ulstein ◽  
Letice Valente ◽  
Eliasz Engelhardt ◽  
Evandro Silva Freire Coutinho ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Factor Analysis ◽  
Motor Behavior ◽  
Neuropsychiatric Symptoms ◽  
Principal Component ◽  
Mixed Dementia ◽  
Cross Sectional ◽  
Brazilian Sample ◽  
Two Samples

ABSTRACTBackground: Neuropsychiatric symptoms (NPS) affect the majority of patients who have dementia. Neuropsychiatric sub-syndromes with symptoms that occur together and have common neurobiological correlates have been identified. There are scarce data regarding the comparison of the pattern of the neuropsychiatric sub-syndromes in distinct ethnical and cultural populations. We aim at comparing the pattern of the NPS, and the factor analysis of the Neuropsychiatric Inventory (NPI-10) in two samples of outpatients with dementia living in Brazil and Norway.Methods: This is a cross-sectional study. The sample consists of 168 Brazilian and 155 Norwegian demented patients from psychogeriatric facilities and community-based educational programs. Brazilian patients were diagnosed with Alzheimer's disease (63.7%), vascular dementia (15.5%), or mixed dementia (20.8%), whereas the diagnoses of Norwegian patients were Alzheimer's disease (97.4%) and mixed dementia (2.6%). Principal component analysis with the Varimax rotation was used for factor analysis of the NPI-10.Results: Apathy (80.4 %), agitation/aggression (45.8%), and aberrant motor behavior (45.8%) were the most common symptoms in the Brazilian sample. Apathy (72.3%), dysphoria (61.9%), and anxiety (52.3%) were the most frequent symptoms in the Norwegian sample. Factor analysis of the NPI-10 revealed three syndromes for the Brazilian (Psychosis, Mood, Psychomotor) and Norwegian (Psychosis, Mood, Frontal) groups.Conclusions: The frequency of individual NPS may differ among distinct populations. However, Psychosis and Depression are common sub-syndromes in diverse ethnical and cultural patients with dementia. Our findings support the syndromic approach for the clinical assessment of the patients with dementia.

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

2020 ◽  
Author(s):  
David Ó’ Reilly
Keyword(s):  
Lower Limb ◽  
Principal Component ◽  
Neuromuscular Control ◽  
Mechanical Work ◽  
Arm Swing ◽  
Double Support ◽  
Slow Walking ◽  
Negative Effect ◽  
The Difference ◽  
Support Phase

AbstractIntroductionThe 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.HighlightsLeft-side dominant arm-swing was found to be related to the degree of lower-limb mechanical work asymmetry.The relationship between arm-swing asymmetry and lower-limb mechanical work symmetry was explained by a moderating effect of neuromuscular control.A 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.

scholarly journals A PCA-based bio-motion generator to synthesize new patterns of human running

2016 ◽  
Vol 2 ◽  
pp. e102 ◽  
Author(s):  
José María Baydal-Bertomeu ◽  
Juan Vicente Durá-Gil ◽  
Ana Piérola-Orcero ◽  
Eduardo Parrilla Bernabé ◽  
Alfredo Ballester ◽  
...  
Keyword(s):  
Motion Tracking ◽  
Principal Component ◽  
Human Movement ◽  
Original Data ◽  
Main Body ◽  
Least Squares Regression ◽  
And Performance ◽  
Body Shapes ◽  
Body Joints ◽  
Future Work

Synthesizing human movement is useful for most applications where the use of avatars is required. These movements should be as realistic as possible and thus must take into account anthropometric characteristics (weight, height, etc.), gender, and the performance of the activity being developed. The aim of this study is to develop a new methodology based on the combination of principal component analysis and partial least squares regression model that can generate realistic motion from a set of data (gender, anthropometry and performance). A total of 18 volunteer runners have participated in the study. The joint angles of the main body joints were recorded in an experimental study using 3D motion tracking technology. A five-step methodology has been employed to develop a model capable of generating a realistic running motion. The described model has been validated for running motion, showing a highly realistic motion which fits properly with the real movements measured. The described methodology could be applied to synthesize any type of motion: walking, going up and down stairs, etc. In future work, we want to integrate the motion in realistic body shapes, generated with a similar methodology and from the same simple original data.

scholarly journals Changed Temporal Structure of Neuromuscular Control, Rather Than Changed Intersegment Coordination, Explains Altered Stabilographic Regularity after a Moderate Perturbation of the Postural Control System

Entropy ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 614 ◽  
Author(s):  
Felix Wachholz ◽  
Tove Kockum ◽  
Thomas Haid ◽  
Peter Federolf
Keyword(s):  
Control System ◽  
Postural Control ◽  
Center Of Pressure ◽  
Temporal Structure ◽  
Force Plate ◽  
Principal Component ◽  
Neuromuscular Control ◽  
Postural Control System ◽  
Temporal Regularity ◽  
Postural Movement

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.

FPGA-Based Object Detection and Motion Tracking in Micro- and Nanorobotics

2014 ◽  
pp. 251-261
Author(s):  
Claas Diederichs ◽  
Sergej Fatikow
Keyword(s):  
Image Processing ◽  
Object Detection ◽  
High Speed ◽  
Motion Tracking ◽  
Principal Component ◽  
Fpga Implementation ◽  
Connected Components ◽  
Connected Component ◽  
Connected Component Labeling ◽  
Labeling Approach

Object-detection and classification is a key task in micro- and nanohandling. The microscopic imaging is often the only available sensing technique to detect information about the positions and orientations of objects. FPGA-based image processing is superior to state of the art PC-based image processing in terms of achievable update rate, latency and jitter. A connected component labeling algorithm is presented and analyzed for its high speed object detection and classification feasibility. The features of connected components are discussed and analyzed for their feasibility with a single-pass connected component labeling approach, focused on principal component analysis-based features. It is shown that an FPGA implementation of the algorithm can be used for high-speed tool tracking as well as object classification inside optical microscopes. Furthermore, it is shown that an FPGA implementation of the algorithm can be used to detect and classify carbon-nanotubes (CNTs) during image acquisition in a scanning electron microscope, allowing fast object detection before the whole image is captured.

The association between cognitive impairment and neuropsychiatric symptoms in patients with Parkinson's disease dementia

2012 ◽  
Vol 24 (12) ◽  
pp. 1980-1987 ◽  
Author(s):  
Wei-Ju Lee ◽  
Chia-Fen Tsai ◽  
Serge Gauthier ◽  
Shuu-Jiun Wang ◽  
Jong-Ling Fuh
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Motor Behavior ◽  
Sleep Problems ◽  
Task Force ◽  
Mmse Score ◽  
Neuropsychiatric Symptoms ◽  
Principal Component ◽  
Principal Component Factor Analysis

ABSTRACTBackground: Neuropsychiatric symptoms (NPS) are common in patients with dementia associated with Parkinson's disease (PDD). The relationship between cognition and NPS in PDD has not been well studied.Methods: Patients diagnosed with PDD were assessed for cognitive function and NPS. The instruments used were the Neuropsychiatric Inventory (NPI), Mini-Mental State Examination (MMSE), and semantic verbal fluency according to the recommendation of the Movement Disorder Society Task Force.Results: We evaluated 127 PDD patients (76 males/51 females; mean age 77 ± 6.3 years). Their mean MMSE score was 17 ± 6.5 and the mean NPI score was 19 ± 20.4. The most prevalent NPI items were anxiety (57.5%), sleep problems (53.5%), and apathy (52.0%). Principal component factor analysis revealed that 12 items formed three factors, namely “mood and psychosis” (delusion, hallucination, agitation, depression, anxiety, apathy, and irritability), “vegetative” (sleep and appetite problems), and “frontal” (euphoria, disinhibition, and aberrant motor behavior). Symptoms of hallucination were significantly associated with MMSE score, even after controlling for the confounding variables.Conclusion: NPS are common and diverse among patients with PDD. Three specific subgroups of NPS were identified. Hallucination was significantly correlated with cognitive impairment, and could be a predictor of cognition in PDD patients.

scholarly journals Evaluation of Synergy Extrapolation for Predicting Unmeasured Muscle Excitations from Measured Muscle Synergies

2020 ◽  
Author(s):  
Di Ao ◽  
Mohammad S. Shourijeh ◽  
Carolynn Patten ◽  
Benjamin J. Fregly
Keyword(s):  
Inverse Dynamics ◽  
Principal Component ◽  
Evaluation Process ◽  
Neuromuscular Control ◽  
Stroke Survivor ◽  
Muscle Synergy ◽  
Joint Moments ◽  
Normalization Methods ◽  
Specific Muscle ◽  
Time Invariant

AbstractElectromyography (EMG)-driven musculoskeletal modeling relies on high-quality measurements of muscle electrical activity to estimate muscle forces. However, a critical challenge for practical deployment of this approach is missing EMG data from muscles that contribute substantially to joint moments. This situation may arise due to either the inability to measure deep muscles with surface electrodes or the lack of a sufficient number of EMG electrodes. Muscle synergy analysis is a dimensionality-reduction approach to decompose a large number of muscle excitations into a small number of time-varying synergy excitations along with time-invariant synergy weights that define the contribution of each corresponding synergy excitation to a specific muscle excitation. This study evaluates how accurately missing muscle excitations can be predicted using synergy excitations extracted from muscles with available EMGs (henceforth called “synergy extrapolation”). The results were reported on a gait dataset collected from a stroke survivor walking on an instrumented treadmill at self-selected and fastest-comfortable speeds. The evaluation process started with full calibration of a lower-body EMG-driven model using 16-channel EMGs (including surface and indwelling) in each leg. One indwelling EMG (either iliopsoas or adductor longus) was then treated as unmeasured at a time. The synergy weights associated with the unmeasured muscle were predicted through solving a nonlinear optimization problem where the errors between inverse dynamics and EMG-driven joint moments were minimized. We also quantitatively evaluated how synergy analysis algorithms (principal component analysis (PCA) and non-negative matrix factorization (NMF)), EMG normalization methods, and number of synergies affect the accuracy of the predicted unmeasured muscle excitation. Synergy extrapolation performance was most influenced by the choice of synergy analysis algorithm and number of synergies. PCA with 5 or 6 synergies consistently predicted unmeasured muscle excitations most accurately and with greatest robustness to choice of EMG normalization method. Furthermore, the associated joint moment matching accuracy was comparable to that produced by the full EMG-driven calibration. The synergy extrapolation method described in this study may facilitate the assessment of human neuromuscular control and biomechanics in response to surgical or rehabilitation treatment when important EMG signals are missing.

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