Can Gait Signatures Provide Quantitative Measures for Aiding Clinical Decision-Making? A Systematic Meta-Analysis of Gait Variability Behavior in Patients with Parkinson’s Disease

A disturbed, inconsistent walking pattern is a common feature of patients with Parkinson\u27s disease (PwPD). Such extreme variability in both temporal and spatial parameters of gait has been associated with unstable walking and an elevated prevalence of falls. However, despite their ability to discretise healthy from pathological function, normative variability values for key gait parameters are still missing. Furthermore, an understanding of each parameter\u27s response to pathology, as well as the inter-parameter relationships, has received little attention. The aim of this systematic literature review and meta-analysis was therefore to define threshold levels for pathological gait variability as well as to investigate whether all gait parameters are equally perturbed in PwPD. Based on a broader systematic literature search that included 13′195 titles, 34 studies addressed Parkinson\u27s disease, presenting 800 PwPD and 854 healthy subjects. Eight gait parameters were compared, of which six showed increased levels of variability during walking in PwPD. The most commonly reported parameter, coefficient of variation of stride time, revealed an upper threshold of 2.4% to discriminate the two groups. Variability of step width, however, was consistently lower in PwPD compared to healthy subjects, and therefore suggests an explicit sensory motor system control mechanism to prioritize balance during walking. The results provide a clear functional threshold for monitoring treatment efficacy in patients with Parkinson\u27s disease. More importantly, however, quantification of specific functional deficits could well provide a basis for locating the source and extent of the neurological damage, and therefore aid clinical decision-making for individualizing therapies

A Method to Concatenate Multiple Short Time Series for Evaluating Dynamic Behaviour During Walking

Gait variability is a sensitive metric for assessing functional deficits in individuals with mobility impairments. To correctly represent the temporal evolution of gait kinematics, nonlinear measures require extended and uninterrupted time series. In this study, we present and validate a novel algorithm for concatenating multiple time-series in order to allow the nonlinear analysis of gait data from standard and unrestricted overground walking protocols. The fullbody gait patterns of twenty healthy subjects were captured during five walking trials (at least 5 minutes) on a treadmill under different weight perturbation conditions. The collected time series were cut into multiple shorter time series of varying lengths and subsequently concatenated using a novel algorithm that identifies similar poses in successive time series in order to determine an optimal concatenation time point. After alignment of the datasets, the approach then concatenated the data to provide a smooth transition. Nonlinear measures to assess stability (Largest Lyapunov Exponent, LyE) and regularity (Sample Entropy, SE) were calculated in order to quantify the efficacy of the concatenation approach using intra-class correlation coefficients, standard error of measurement and paired effect sizes. Our results indicate overall good agreement between the full uninterrupted and the concatenated time series for LyE. However, SE was more sensitive to the proposed concatenation algorithm and might lead to false interpretation of physiological gait signals. This approach opens perspectives for analysis of dynamic stability of gait data from physiological overground walking protocols, but also the re-processing and estimation of nonlinear metrics from previously collected datasets

Extreme Levels of Noise Constitute a Key Neuromuscular Deficit in the Elderly

Fluctuations during isometric force production tasks occur due to the inability of musculature to generate purely constant submaximal forces and are considered to be an estimation of neuromuscular noise. The human sensori-motor system regulates complex interactions between multiple afferent and efferent systems, which results in variability during functional task performance. Since muscles are the only active component of the motor system, it therefore seems reasonable that neuromuscular noise plays a key role in governing variability during both standing and walking. Seventy elderly women (including 34 fallers) performed multiple repetitions of isometric force production, quiet standing and walking tasks. No relationship between neuromuscular noise and functional task performance was observed in either the faller or the nonfaller cohorts. When classified into groups with either nominal (group NOM, 25th –75th percentile) or extreme (either too high or too low, group EXT) levels of neuromuscular noise, group NOM demonstrated a clear association (r2.0.23, p,0.05) between neuromuscular noise and variability during task performance. On the other hand, group EXT demonstrated no such relationship, but also tended to walk slower, and had lower stride lengths, as well as lower isometric strength. These results suggest that neuromuscular noise is related to the quality of both static and dynamic functional task performance, but also that extreme levels of neuromuscular noise constitute a key neuromuscular deficit in the elderly

Cortical Contribution to Linear, Non-linear and Frequency Components of Motor Variability Control During Standing

Motor variability is an inherent feature of all human movements and reflects the quality of functional task performance. Depending on the requirements of the motor task, the human sensory-motor system is thought to be able to flexibly govern the appropriate level of variability. However, it remains unclear which neurophysiological structures are responsible for the control of motor variability. In this study, we tested the contribution of cortical cognitive resources on the control of motor variability (in this case postural sway) using a dual-task paradigm and furthermore observed potential changes in control strategy by evaluating Ia-afferent integration (H-reflex). Twenty healthy subjects were instructed to stand relaxed on a force plate with eyes open and closed, as well as while trying to minimize swaymagnitude and performing a “subtracting-sevens” cognitive task. In total 25 linear and non-linear parameters were used to evaluate postural sway, which were combined using a Principal Components procedure. Neurophysiological response of Ia-afferent reflex loop was quantified using the Hoffman reflex. In order to assess the contribution of the H-reflex on the sway outcome in the different standing conditions multiplemixed-model ANCOVAs were performed. The results suggest that subjects were unable to further minimize their sway, despite actively focusing to do so. The dual-task had a destabilizing effect on PS, which could partly (by 4%) be counter-balanced by increasing reliance on Ia-afferent information. The effect of the dual-task was larger than the protective mechanism of increasing Ia-afferent information. We, therefore, conclude that cortical structures, as compared to peripheral reflex loops, play a dominant role in the control of motor variability

Age-Related Modifications to the Magnitude and Periodicity of Neuromuscular Noise

Background: Evaluation of task related outcomes within geriatric and fall-prone populations is essential not only for identification of neuromuscular deficits, but also for effective implementation of fall prevention strategies. As most tasks and activities of daily living are performed at submaximal force levels, restoration of muscle strength often does not produce the expected benefit in functional capacity. However, it is known that muscular control plays a key role in the performance of functional tasks, but it remains unclear to what degree muscular control and the associated neuromuscular noise (NmN) is age-related, particularly in the lower-extremities. Objectives: The aim of this study was to determine the effects of age and fall-pathology on the magnitude as well as the frequency of NmN during lower extremity force production. Methods: Sixteen young healthy adults, as well as seventy elderly women (36 healthy, 34 elderly fallers), performed force production tests at moderate levels (15% of maximum voluntary isometric contractions). Results: Elderly fallers exhibited the highest magnitude of NmN, while the highest frequency components of NmN tended to occur in the healthy elderly. Young subjects exhibited significantly more power in the low frequency ranges than either of the elderly groups, and had the lowest levels of NmN. Conclusion: These data suggest increased degeneration of muscular control through greater NmN in elderly fallers compared to healthy elderly or young subjects. This could possibly be associated with muscle atrophy and lower levels of motor unit synchronisation

What Is the Contribution of Ia-Afference for Regulating Motor Output Variability During Standing?

Motor variability is an inherent feature of all human movements, and describes the system‘s stability and rigidity during the performance of functional motor tasks such as balancing. In order to ensure successful task execution, the nervous system is thought to be able to flexibly select the appropriate level of variability. However, it remains unknown which neurophysiological pathways are utilized for the control of motor output variability. In responding to natural variability (in this example sway), it is plausible that the neuro-physiological response to muscular elongation contributes to restoring a balanced upright posture. In this study, the postural sway of 18 healthy subjects was observed while their visual and mechano-sensory system was perturbed. Simultaneously, the contribution of Ia-afferent information for controlling the motor task was assessed by means of H-reflex. There was no association between postural sway and Ia-afference in the eyes open condition, however up to 4%of the effects of eye closure on themagnitude of sway can be compensated by increased reliance on Ia-afference. Increasing the biomechanical demands by adding up to 40% bodyweight around the trunk induced a specific sway response, such that the magnitude of sway remained unchanged but its dynamic structure became more regular and stable (by up to 18%). Such regular sway patterns have been associated with enhanced cognitive involvement in controlling motor tasks. It therefore appears that the nervous system applies different control strategies in response to the perturbations: The loss of visual information is compensated by increased reliance on other receptors; while the specific regular sway pattern associated with additional weight-bearing was independent of Ia-afferent information, suggesting the fundamental involvement of supraspinal centers for the control of motor output variability

Identification of Functional Parameters for the Classification of Older Female Fallers and Prediction of ‘First-Time’ Fallers

Falls remain a challenge for ageing societies. Strong evidence indicates that a previous fall is the strongest single screening indicator for a subsequent fall and the need for assessing fall risk without accounting for fall history is therefore imperative. Testing in three functional domains (using a total 92 measures) were completed in 84 older women (60–85 years of age), including muscular control, standing balance, and mean and variability of gait. Participants were retrospectively classified as fallers (n = 38) or non-fallers (n = 42) and additionally in a prospective manner to identify first-time fallers (FTFs) (n = 6) within a 12-month follow-up period. Principal component analysis revealed that seven components derived from the 92 functional measures are sufficient to depict the spectrum of functional performance. Inclusion of only three components, related to mean and temporal variability of walking, allowed classification of fallers and non-fallers with a sensitivity and specificity of 74% and 76%, respectively. Furthermore, the results indicate that FTFs show a tendency towards the performance of fallers, even before their first fall occurs. This study suggests that temporal variability and mean spatial parameters of gait are the only functional components among the 92 measures tested that differentiate fallers from non-fallers, and could therefore show efficacy in clinical screening programmes for assessing risk of first-time falling

Revealing the Quality of Movement: A Meta-Analysis Review to Quantify the Thresholds to Pathological Variability During Standing and Walking

Neuromotor processes are inherently noisy, which results in variability during movement and fluctu-ations in motor control. Although controversial, low levels of variability are traditionally considered healthy, while increased levels are thought to be pathological. This systematic review and meta-analysisof the literature investigates the thresholds between healthy and pathological task variability. After examining 13,195 publications, 109 studies were included. Results from over 3000 healthy sub-jects and 2775 patients revealed an overall positive effect size of pathology on variability of 0.59 forwalking and 0.80 for sway. For the coefficient of variation of stride time (ST) and sway area (SA), upperthresholds of 2.6% and 265 mm2discriminated pathological from asymptomatic performance, while 1.1%and 62 mm2identified the lower thresholds for pathological variability. This window of healthy perfor-mance now provides science based evidence for the discrimination of both extremely low and extremelyhigh levels of variability in the identification as well as standardised monitoring of functional status inneurological cases

Does Variability of Footfall Kinematics Correlate with Dynamic Stability of the Centre of Mass During Walking?

A stable walking pattern is presumably essential to avoid falls. Stability of walking is most accurately determined by the short-term local dynamic stability (maximum Lyapunov exponent) of the body centre of mass. In many studies related to fall risk, however, variability of step width is considered to be indicative of the stability of the centre of mass during walking. However, other footfall parameters, in particular variability of stride time, have also been associated with increased risk for falling. Therefore, the aim of this study was to investigate the association between short-term local dynamic stability of the body centre of mass and different measures of footfall variability. Twenty subjects performed unperturbed walking trials on a treadmill and under increased (addition of 40% body weight) and decreased (harness system) demands to stabilise the body centre of mass. Association between stability of the centre of mass and footfall parameters was established using a structural equation model. Walking with additional body weight lead to greater instability of the centre of mass and increased stride time variability, however had no effect on step width variability. Supported walking in the harness system did not increase centre of mass stability further, however, led to a significant decrease of step width and increase in stride time variability. A structural equation model could only predict 8% of the variance of the centre of mass stability after variability of step width, stride time and stride length were included. A model which included only step width variability as exogenous variable, failed to predict centre of mass stability. Because of the failure to predict centre of mass stability in this study, it appears, that the stability of the centre of mass is controlled by more complex interaction of sagittal and frontal plane temporal and spatial footfall parameters, than those observed by standard variability measures. Anyway, this study does not support the application of step width variability as indicator for medio-lateral stability of the centre of mass during walking

A Solution to Ambiguities in Position Estimation for Solenoid Actuators by Exploiting Eddy Current Variations

Position estimation techniques for solenoid actuators are successfully used in a wide field of applications requiring monitoring functionality without the need for additional sensors. Most techniques, which also include standstill condition, are based on the identification of the differential inductance, a parameter that exhibits high sensitivity towards position variations. The differential inductance of some actuators shows a non-monotonic dependency over the position. This leads to ambiguities in position estimation. Nevertheless, a unique position estimation in standstill condition without prior knowledge of the actuator state is highly desired. In this work, the eddy current losses inside the actuator are identified in terms of a parallel resistor and are exploited in order to solve the ambiguities in position estimation. Compared to other state-of-the-art techniques, the differential inductance and the parallel resistance are estimated online by approaches requiring low implementation and computation effort. Furthermore, a data fusion algorithm for position estimation based on a neural network is proposed. Experimental results involving a use case scenario of an end-position detection for a switching solenoid actuator prove the uniqueness, the precision and the high signal-to-noise ratio of the obtained position estimate. The proposed approach therefore allows the unique estimation of the actuator position including standstill condition suitable for low-cost applications demanding low implementation effort