The temporal organization of stride duration variability for assessing gait stability : clinical application to Parkinson’s disease

Human movement is intrinsically dynamic and complex. Continuous integration of multiple sensory inputs and coordination of motor outputs are needed to achieve efficient, stable and adaptable locomotion. Both externally (e.g. environment) and/or internally (e.g. pathology) generated perturbations and the neuromechanical responses to them contribute to the fluctuating dynamics of human gait (assessed by long-range autocorrelations; LRA). Although the origin of this property is largely debated, LRA may provide important information about neuromechanical control of gait and potentially constitute a powerful marker of dysfunction. Influence of external and internal factors on human locomotion was investigated, which allowed further investigation on both possible neuromechanical origin of LRA and their potential clinical utility. The recent consideration of LRA gives rise to new way of thinking about variability, adaptability, health and motor rehabilitation.Le mouvement humain est intrinsèquement dynamique et complexe. Une locomotion efficace, stable et adaptée requiert à la fois l'intégration continue d’afférences sensorielles multiples et la coordination des sorties motrices. Le caractère fluctuant de la marche humaine (autocorrélations à long-terme, LRA) relève tant de perturbations externes (e.g., environnement) et/ou internes (e.g., pathologie) que des réponses neuromécaniques à celles-ci. Bien que l'origine de cette propriété soit largement débattue, l’analyse des LRA fournirait d’importantes informations sur le contrôle de la marche et pourrait constituer un marqueur de dysfonctionnement. L'influence des facteurs externes et internes sur la locomotion humaine a été étudiée, permettant d’approfondir l’étude de possibles origines neuromécaniques des LRA et de leur utilité clinique potentielle. La récente considération des LRA donne lieu à une nouvelle façon de penser la variabilité, l'adaptabilité, la santé et la rééducation motrice.(MOTR - Sciences de la motricité) -- UCL, 201

Gait Complexity and Regularity Are Differently Modulated by Treadmill Walking in Parkinson's Disease and Healthy Population

Variability raises considerable interest as a promising and sensitive marker of dysfunction in physiology, in particular in neurosciences. Both internally (e.g., pathology) and/or externally (e.g., environment) generated perturbations and the neuro-mechanical responses to them contribute to the fluctuating dynamics of locomotion. Defective internal gait control in Parkinson's disease (PD), resulting in typical timing gait disorders, is characterized by the breakdown of the temporal organization of stride duration variability. Influence of external cue on gait pattern could be detrimental or advantageous depending on situations (healthy or pathological gait pattern, respectively). As well as being an interesting rehabilitative approach in PD, treadmills are usually implemented in laboratory settings to perform instrumented gait analysis including gait variability assessment. However, possibly acting as an external pacemaker, treadmill could modulate the temporal organization of gait variability of PD patients which could invalidate any gait variability assessment. This study aimed to investigate the immediate influence of treadmill walking (TW) on the temporal organization of stride duration variability in PD and healthy population. Here, we analyzed the gait pattern of 20 PD patients and 15 healthy age-matched subjects walking on overground and on a motorized-treadmill (randomized order) at a self-selected speed. The temporal organization and regularity of time series of walking were assessed on 512 consecutive strides and assessed by the application of non-linear mathematical methods (i.e., the detrended fluctuation analysis and power spectral density; and sample entropy, for the temporal organization and regularity of gait variability, respectively). A more temporally organized and regular gait pattern seems to emerge from TW in PD while no influence was observed on healthy gait pattern. Treadmill could afford the necessary framework to regulate gait rhythmicity in PD. Overall, the results support the hypothesis of a greater dependence to regulatory inputs as an explanatory factor of treadmill influence observed in PD. Also, since treadmill misrepresents the gait as more healthy than it is, the present findings underline that gait analysis using treadmill devices should be cautiously considered in PD and especially for gait variability assessment in gait lab

Gait Complexity and Regularity Are Differently Modulated by Treadmill Walking in Parkinson's Disease and Healthy Population

Variability raises considerable interest as a promising and sensitive marker of dysfunction in physiology, in particular in neurosciences. Both internally (e.g., pathology) and/or externally (e.g., environment) generated perturbations and the neuro-mechanical responses to them contribute to the fluctuating dynamics of locomotion. Defective internal gait control in Parkinson’s disease (PD), resulting in typical timing gait disorders, is characterized by the breakdown of the temporal organization of stride duration variability. Influence of external cue on gait pattern could be detrimental or advantageous depending on situations (healthy or pathological gait pattern, respectively). As well as being an interesting rehabilitative approach in PD, treadmills are usually implemented in laboratory settings to perform instrumented gait analysis including gait variability assessment. However, possibly acting as an external pacemaker, treadmill could modulate the temporal organization of gait variability of PD patients which could invalidate any gait variability assessment. This study aimed to investigate the immediate influence of treadmill walking (TW) on the temporal organization of stride duration variability in PD and healthy population. Here, we analyzed the gait pattern of 20 PD patients and 15 healthy age-matched subjects walking on overground and on a motorized-treadmill (randomized order) at a self-selected speed. The temporal organization and regularity of time series of walking were assessed on 512 consecutive strides and assessed by the application of non-linear mathematical methods (i.e., the detrended fluctuation analysis and power spectral density; and sample entropy, for the temporal organization and regularity of gait variability, respectively). A more temporally organized and regular gait pattern seems to emerge from TW in PD while no influence was observed on healthy gait pattern. Treadmill could afford the necessary framework to regulate gait rhythmicity in PD. Overall, the results support the hypothesis of a greater dependence to regulatory inputs as an explanatory factor of treadmill influence observed in PD. Also, since treadmill misrepresents the gait as more healthy than it is, the present findings underline that gait analysis using treadmill devices should be cautiously considered in PD and especially for gait variability assessment in gait lab

Variability of Human Gait: Effect of Backward Walking and Dual-Tasking on the Presence of Long-Range Autocorrelations

Abstract—Information from the central and peripheral nervous systems is continuously integrated to produce a stable gait pattern. However, stride duration fluctuates in a complex manner in healthy subjects, exhibiting long-range autocorrelations that can span over hundreds of consecutive strides. The present study was conducted to explore the mechanisms controlling the long-term fluctuation dynamics of gait. In the first part of the study, stride duration variability was evaluated on a treadmill during forward (FW) and backward walking (BW). Despite the modification of the biomechanical constraints imposed on the locomotor system, the characteristics of the long-range autocorrelations remained unchanged in both modes of locomotion (FW: H = 0.79 ± 0.04 and a = 0.58 ± 0.13; BW: H = 0.79 ± 0.11 and a = 0.53 ± 0.25). In the second part of the study, stride duration variability was assessed while the subjects were performing a dual-task paradigm that combined gait and mental calculation. The long-term variability of stride duration was similar during usual walking (H = 0.80 ± 0.06 and a = 0.57 ± 0.13) and in dual-tasking (H = 0.77 ± 0.06 and a = 0.52 ± 0.16), whereas walking altered the performance of the cognitive task. Hence, the biomechanical and cognitive interferences imposed in the present study were not sufficient to induce a modification of the long-range autocorrelations highlighted in walking variability. These observations underline the robustness of the long-range autocorrelations

Effects of overground gait training assisted by a wearable exoskeleton in patients with Parkinson’s disease

Background In the recent past, wearable devices have been used for gait rehabilitation in patients with Parkinson’s disease. The objective of this paper is to analyze the outcome of a wearable hip orthosis whose assistance adapts in real time to the patient’s gait kinematics via adaptive oscillators. In particular, this study focuses on a metric characterizing natural gait variability, i.e., the level of long-range autocorrelations (LRA) in series of stride durations. Methods Eight patients with Parkinson’s disease (Hoehn and Yahr stages 1-2.5) performed overground gait training three times per week for four consecutive weeks, assisted by a wearable hip orthosis. Gait was assessed based on performance metrics such as the hip range of motion, speed, stride length and duration, and the level of LRA in inter-stride time series assessed using the Adaptive Fractal Analysis. These metrics were measured before, directly after, and 1 month after training. Results After training, patients increased their hip range of motion, their gait speed and stride length, and decreased their stride duration. These improvements were maintained 1 month after training. Regarding long-range autocorrelations, the population’s behavior was standardized towards a metric closer to the one of healthy individuals after training, but with no retention after 1 month. Conclusion This study showed that an overground gait training with adaptive robotic assistance has the potential to improve key gait metrics that are typically affected by Parkinson’s disease and that lead to higher prevalence of fall

Dynamics of Revolution Time Variability in Cycling Pattern: Voluntary Intent Can Alter the Long-Range Autocorrelations

Long-range dependency has been found in most rhythmic motor signals. The origin of this property is unknown and largely debated. There is a controversy on the influence of voluntary control induced by requiring a predetermined pace such as asking subjects to step to a metronome. We studied the cycle duration variability of 15 men pedaling on an ergometer at free pace and at an imposed pace (60 rpm). Revolution time was determined based on accelerometer signals (sample frequency 512 Hz). Revolution time variability was assessed by coefficient of variation (CV). The presence of long-range autocorrelations was based on scaling properties of the series variability (Hurst exponent) and the shape of the power spectral density (a exponent).Mean revolution time was significantly lower at freely chosen cadence, while values of CV were similar between both sessions. Long-range autocorrelations were highlighted in all series of cycling patterns. However, Hurst and a exponents were significantly lower at imposed cadence. This study demonstrates the presence of long-range autocorrelations during cycling and that voluntary intent can modulate the interdependency between consecutive cycles. Therefore, cycling may constitute a powerful paradigm to investigate the influence of central control mechanisms on the longrange interdependency characterizing rhythmic motor tasks

Impact of series length on statistical precision and sensitivity of autocorrelation assessment in human locomotion

Long-range autocorrelations (LRA) are a robust feature of rhythmic movements, which may provide important information about neural control and potentially constitute a powerful marker of dysfunction. A clear difficulty associated with the assessment of LRA is that it requires a large number of cycles to generate reliable results. Here we investigate how series length impacts the reliability of LRA assessment. A total of 94 time series extracted from walking or cycling tasks were re-assessed with series length varying from 64 to 512 data points. LRA were assessed using an approach combining the rescaled range analysis or the detrended fluctuation analysis (Hurst exponent, H), along with the shape of the power spectral density (α exponent). The statistical precision was defined as the ability to obtain estimates for H and α that are consistent with their theoretical relationship, irrespective of the series length. The sensitivity consisted of testing whether significant differences between experimental conditions found in the original studies when considering 512 data points persisted with shorter series. We also investigate the use of evenly-spaced diffusion plots as a methodological improvement of original version of methods for short series. Our results show that the reliable assessment of LRA requires 512 data points, or no shorter than 256 data points provided that more robust methods are considered such as the evenly-spaced algorithms. Such series can be reasonably obtained in clinical populations with moderate, or even more severe, gait impairments and open the perspective to extend the use of LRA assessment as a marker of gait stability applicable to a broad range of locomotor disorders