Barcoding, linear and nonlinear analysis of full-day leg movements in infants with typical development and infants at risk of developmental disabilities: Cross-sectional study.

Traditional methods do not capture the multidimensional domains and dynamic nature of infant behavioral patterns. We aim to compare full-day, in-home leg movement data between infants with typical development (TD) and infants at risk of developmental disabilities (AR) using barcoding and nonlinear analysis. Eleven infants with TD (2-10 months) and nine infants AR (adjusted age: 2-14 months) wore a sensor on each ankle for 7 days. We calculated the standard deviation for linear variability and sample entropy (SampEn) of leg acceleration and angular velocity for nonlinear variability. Movements were also categorized into 16 barcoding states, and we calculated the SampEn and proportions of the barcoding. All variables were compared between the two groups using independent-samples t-test or Mann-Whitney U test. The AR group had larger linear variability compared to the TD group. SampEn was lower in the AR group compared to TD group for both acceleration and angular velocity. Two barcoding states' proportions were significantly different between the two groups. The results showed that nonlinear analysis and barcoding could be used to identify the difference of dynamic multidimensional movement patterns between infants AR and infants with TD. This information may help early diagnosis of developmental disabilities in the future.

Detection of Parkinson's Disease Using Wrist Accelerometer Data and Passive Monitoring.

Parkinson's disease is a neurodegenerative disorder impacting patients' movement, causing a variety of movement abnormalities. It has been the focus of research studies for early detection based on wearable technologies. The benefit of wearable technologies in the domain rises by continuous monitoring of this population's movement patterns over time. The ubiquity of wrist-worn accelerometry and the fact that the wrist is the most common and acceptable body location to wear the accelerometer for continuous monitoring suggests that wrist-worn accelerometers are the best choice for early detection of the disease and also tracking the severity of it over time. In this study, we use a dataset consisting of one-week wrist-worn accelerometry data collected from individuals with Parkinson's disease and healthy elderlies for early detection of the disease. Two feature engineering methods, including epoch-based statistical feature engineering and the document-of-words method, were used. Using various machine learning classifiers, the impact of different windowing strategies, using the document-of-words method versus the statistical method, and the amount of data in terms of number of days were investigated. Based on our results, PD was detected with the highest average accuracy value (85% ± 15%) across 100 runs of SVM classifier using a set of features containing features from every and all windowing strategies. We also found that the document-of-words method significantly improves the classification performance compared to the statistical feature engineering model. Although the best performance of the classification task between PD and healthy elderlies was obtained using seven days of data collection, the results indicated that with three days of data collection, we can reach a classification performance that is not significantly different from a model built using seven days of data collection.

Role of Specialized Pro-resolving Mediators in Reducing Neuroinflammation in Neurodegenerative Disorders.

Alzheimer's disease (AD) and Parkinson's disease (PD) are neurodegenerative disorders that affect millions of individuals worldwide. As incidence of these conditions increases with age, there will undoubtedly be an increased prevalence of cases in the near future. Neuroinflammation is a hallmark in the development and progression of neurodegenerative diseases and prevention or resolution of chronic neuroinflammation may represent a novel approach to treatment. The present review highlights the potential of the anti-inflammatory and pro-resolving effects of polyunsaturated fatty acid (PUFA)-derived mediators (Specialized Pro-resolving Mediators-SPM) in neurodegenerative disorders. PUFA-derived SPM are biosynthesized in response to chemicals produced from acute inflammatory responses. Preclinical studies from both AD and PD models suggest a dysregulation of SPM and their receptors in neurological disorders. Decreased SPM may be due to inadequate substrate, an imbalance between SPM and pro-inflammatory mediators or a disruption in SPM synthesis. SPMs hold great promise for neuroprotection in AD by altering expression of pro-inflammatory genes, modulating macrophage function, serving as a biomarker for AD status, and promoting resolution of neuroinflammation. In PD, data suggest SPM are able to cross the blood-brain barrier, inhibit microglial activation and decrease induced markers of inflammation, possibly as a result of their ability to downregulate NFκB signaling pathways. Several in vivo and in vitro studies suggest a benefit from administration of SPMs in both neurodegenerative disorders. However, extrapolation of these outcomes to humans is difficult as no models are able to replicate all features of AD or PD. Minimal data evaluating these PUFA-derived metabolites in humans with neurodegenerative disorders are available and a gap in knowledge exists regarding behavior of SPM and their receptors in patients with these conditions. There is also large gap in our knowledge regarding which lipid mediator would be most effective in which model of AD or PD and how dietary intake or supplementation can impact SPM levels. Future direction should include focused, translational efforts to investigate SPM as an add-on (in addition to standard treatment) or as standalone agents in patients with neurodegenerative disorders.

A Narrative Review Examining the Utility of Interpersonal Synchrony for the Caregiver-Care Recipient Relationship in Alzheimer's Disease and Related Dementias.

The stressful nature of caring for an older adult with a chronic disease, such as Alzheimer's disease (AD), can create barriers between the caregiver-care recipient, as they try to navigate their continuously changing social relationship. Interpersonal synchrony (i.e., matching or similarity of movement, emotions, hormones, or brain activity), is an innovative approach that could help to sustain caregiving relationship dynamics by promoting feelings of connection and empathy through shared behavior and experiences. This review investigates the current literature on interpersonal synchrony from an interdisciplinary perspective by examining interpersonal synchrony through psychological, neural, and hormonal measures across the adult lifespan. We then present a case for examining the degree to which interpersonal synchrony can be used to facilitate affiliation and well-being in the caregiver-care recipient relationship. We find that there is significant evidence in healthy adult populations that interpersonal synchrony can support affiliative feelings, prosocial behavior, and well-being. Characterizing the psychological, neural, and hormonal mechanisms of interpersonal synchrony is a first step towards laying the groundwork for the development of tools to support relational closeness and empathy in the caregiving context. Finally, we explore the strengths and limitations of using interpersonal synchrony to support relational well-being, and discuss possible avenues for future research.

The effects of visual biofeedback and visual biofeedback scale size on single limb balance.

BACKGROUND: Controlling postural sway relies on the assessment and integration of external sensory stimuli by the central nervous system. When there is a loss of one or more of the sensory stimuli, there is often a decrease in balance performance. Visual biofeedback (VBF) has become a popular method to improve balance because of the supplementation to natural visual information with visual cues of the center of pressure. It is also possible to improve balance even further by increasing the scale of VBF. The aim of this investigation was to determine the effects of VBF and increasing VBF scale on single-limb balance in healthy adults. METHODS: Twenty healthy young adults were recruited. Participants underwent 24, 20-s single limb balance trials on both the right and the left leg. These trials were collected under 4 conditions: 1) eyes-open (EO) with no VBF, 2) EO with 1:1 scale VBF, 3) EO with 2:1 scale VBF, 4) EO with 5:1 scale VBF. Force plate outcomes included resultant, anterior-posterior, and medial-lateral Sway. A two-way repeated measures ANOVA was performed and a Bonferonni post-hoc test was used to determine the effects of VBF and VBF scale size on balance. RESULTS: Differences were noted in AP Sway and Resultant Sway when VBF was present and the scale size was increased (p < 0.05). CONCLUSION: Providing VBF decreases Sway in single-limb stance for young healthy adults, especially when the scale was increased beyond 1:1 VBF. These results may be clinically applicable for balance rehabilitation and training.

Assessing the Temporal Organization of Walking Variability: A Systematic Review and Consensus Guidelines on Detrended Fluctuation Analysis.

Human physiological signals are inherently rhythmic and have a hallmark feature in that even distant intrasignal measurements are related to each other. This relationship is termed long-range correlation and has been recognized as an indicator of the optimal state of the observed physiological systems, among which the locomotor system. Loss of long-range correlations has been found as a result of aging as well as disease, which can be evaluated with detrended fluctuation analysis (DFA). Recently, DFA and the scaling exponent α have been employed for understanding the degeneration of temporal regulation of human walking biorhythms in, for example, Parkinson disease (PD). However, heterogeneous evidence on scaling exponent α values reported in the literature across different population groups has put into question what constitutes a healthy physiological pattern. Therefore, the purpose of this systematic review was to investigate the functional thresholds of scaling exponent α in young vs. older adults, as well as between patients with PD and age-matched asymptomatic controls. Aging and PD exhibited a negative effect size (i.e., led to decreased long-range correlations) of -0.20 and -0.53, respectively. Our meta-analysis based on 14 studies provides evidence that a mean scaling exponent α threshold of 0.86 [2 standard error (0.76, 0.96)] is able to optimally discriminate temporal organization of stride interval between young and old, whereas 0.82 (0.72, 0.92) differentiates patients with PD and age-matched asymptomatic controls. The optimal thresholds presented in this review together with the consensus guidelines for using DFA might allow a more sensitive and reliable application of this metric for understanding human walking physiology than has been achieved to date.

Fractal auditory stimulation has greater benefit for people with Parkinson's disease showing more random gait pattern.

BACKGROUND: Healthy gait dynamics are characterized by the presence of fractal, persistent stride-to-stride variations, which become more random with Parkinson's disease (PD). Rhythmic auditory stimulation with fractal beat-to-beat variations can change gait dynamics in people with PD toward more persistence. RESEARCH QUESTION: How does gait in people with PD change when synchronizing steps with fractal melodic metronomes with different step-to-beat ratios, and which stimulus do they prefer? METHODS: In this cross-sectional study, 15 people with PD and 15 healthy older adults walked over-ground in three conditions: self-paced, paced by a fractal auditory stimulus with a 1:1 step-to-beat ratio ('metronome'), and fractal auditory stimulus with a 1:2 step-to-beat ratio ('music'). Gait dynamics were recorded with instrumented insoles, and detrended fluctuation analysis (DFA) was applied to the series of stride time intervals. Stimuli preference was assessed using Likert-like scales and open-ended questions. ANOVAs were used to compare mean, coefficient of variation, α-DFA, and the responses from the continuous Likert scales. Pearson correlations were used to assess the relationship between 'music' and 'metronome' enjoyment or difficulty with gait outcomes, and to determine the association between baseline α-DFA and changes due to the stimuli. RESULTS: Our major findings are that (i) stride-to-stride variations were more persistent with the 'metronome' compared to baseline for both groups, (ii) the effect was greater for people with lower α-DFA at baseline (i.e., more random stride-to-stride variations), and (iii) both groups found the 'metronome' less difficult to synchronize with. SIGNIFICANCE: This study showed that people with PD and healthy older adults walk with higher statistical persistence in their stride-to-stride variations when instructed to synchronize their steps with a fractal stimulus. Participants with lower persistence at baseline benefited the most from the fractal 'metronome', highlighting the importance to develop patient-centered tests and interventions.

Comparison of a portable balance board for measures of persistence in postural sway.

Measuring postural sway is important for determining functional ability or risk of falling. Gathering postural sway measures outside of controlled environments is desirable for reaching populations with limited mobility. Previous studies have confirmed the accuracy of the magnitude of postural sway using the Nintendo Wii Balance Board (WBB). However, it is unclear if the WBB can accurately measure persistence of postural sway, i.e., the pattern of center-of-pressure fluctuations over time. The purpose of this study was to compare measures of persistence of postural sway (through detrended fluctuation analysis) using WBB and a force platform (FP). Seventeen healthy individuals performed three standing conditions: eyes open, eyes closed, and one-leg standing. The WBB (30 Hz) was placed on top on the FP (600 Hz) to collect data simultaneously, then the FP data were downsampled to 100 Hz and 30 Hz. The agreement between WBB and FP for measures of postural sway were influenced by the sampling rate and postural sway direction. Intraclass correlation coefficient was excellent (range: 0.953-0.998) for long-term scaling regions in the anterior-posterior direction, but lower (range: 0.352-0.877) and inconsistent for medial-lateral direction and short-term scaling regions. The three comparison groups (WBB at 30 Hz, FP at 30 Hz, and FP at 100 Hz) showed dissimilar abilities in detecting differences in persistence of postural sway. In summary, the WBB is accurate for quantifying persistence of postural sway measurements in long-term scaling regions in the AP direction, but has limitations for short-term scaling regions and the ML direction.

Effect of sampling frequency on fractal fluctuations during treadmill walking.

The temporal dynamics of stride-to-stride fluctuations in steady-state walking reveal important information about locomotor control and can be quantified using so-called fractal analyses, notably the detrended fluctuation analysis (DFA). Gait dynamics are often collected during treadmill walking using 3-D motion capture to identify gait events from kinematic data. The sampling frequency of motion capture systems may impact the precision of event detection and consequently impact the quantification of stride-to-stride variability. This study aimed i) to determine if collecting multiple walking trials with different sampling frequency affects DFA values of spatiotemporal parameters during treadmill walking, and ii) to determine the reliability of DFA values across downsampled conditions. Seventeen healthy young adults walked on a treadmill while their gait dynamics was captured using different sampling frequency (60, 120 and 240 Hz) in each condition. We also compared data from the highest sampling frequency to downsampled versions of itself. We applied DFA to the following time series: step length, time and speed, and stride length, time and speed. Reliability between experimental conditions and between downsampled conditions were measured with 1) intraclass correlation estimates and their 95% confident intervals, calculated based on a single-measurement, absolute-agreement, two-way mixed-effects model (ICC 3,1), and 2) Bland-Altman bias and limits of agreement. Both analyses revealed a poor reliability of DFA results between conditions using different sampling frequencies, but a relatively good reliability between original and downsampled spatiotemporal variables. Collectively, our results suggest that using sampling frequencies of 120 Hz or 240 Hz provide similar results, but that using 60 Hz may alter DFA values. We recommend that gait kinematics should be collected at around 120 Hz, which provides a compromise between event detection accuracy and processing time.

Complexity matching and coordination in individual and dyadic performance.

Complexity matching is a measure of coordination based on information exchange between complex networks. To date, studies have focused mainly on interpersonal coordination, but complexity matching may generalize to interacting networks within individuals. The present study examined complexity matching in a double, coordinated Fitts' perceptual-motor task with comparable individual and dyadic conditions. Participants alternated touching targets with their left and right hands in the individual condition, or analogously with the left hand of one partner and the right hand of another in the dyadic condition. In Experiment 1, response coupling was manipulated by making targets drift either randomly or contingently based on prior responses. Here, drift refers to the variability in the target movements between response locations. Long-range correlations in time series of inter-response intervals exhibited complexity matching between the left and right hands of dyads and individuals. Response coupling was necessary for complexity matching in dyads but not individuals. When response coupling was absent in the dyadic condition, the degree of complexity matching was significantly reduced. Experiment 2 showed that the effect of coupling was due to interactions between left and right responses. Results also showed a weak, negative relationship between complexity matching and performance as measured by total response time. In conclusion, principles and measures of complexity matching apply similarly within and between individuals, and perceptual-motor performance can be facilitated by loose response coupling.

Fractal analysis of gait in people with Parkinson's disease: three minutes is not enough.

BACKGROUND: The fractal dynamics of gait variability in people with Parkinson's disease has been studied by applying the detrended fluctuation analysis (DFA) to short time series (<200 strides). However, DFA is sensitive to time series length, and it is unclear if DFA results from short time series are reliable and if they reflect the fractal dynamics of longer time series. RESEARCH QUESTION: Is DFA reliable when applied to short time series? METHODS: We applied DFA to stride time series from five 3-min trials and one 15-min trial in 12 people with Parkinson's disease, 14 healthy older adults and 14 healthy young adults walking overground. Within each group, intraclass correlations (ICC 3,1) were performed to assess the reliability of i) the five 3-min trials together, ii) each 3-min trials to the 15-min trial, and iii) the first 150 strides from the 15-min trial to the full 15-min trial. RESULTS: Our three main findings are that 1) stride time α-DFA values are not consistent from trial-to-trial for short stride time series, 2) stride time α-DFA values from each 3-min trials are not consistent when compared to stride time α-DFA values from a 15-min trial, and 3) stride time α-DFA values from the first 150 strides of the 15-min trial are not consistent when compared to α-DFA values from the full 15-min trial. SIGNIFICANCE: Our results confirm that α-DFA values from 3-min walking trials are not reliable, and that they do not reflect the scale invariant properties of longer time series. This suggests that previous studies assessing the fractal dynamics of gait variability from about 3-min walking must be interpreted with caution. A major clinical implication is that DFA cannot be used to study gait in people unable to perform 500 strides continuously.

Walking speed and spatiotemporal step mean measures are reliable during feedback-controlled treadmill walking; however, spatiotemporal step variability is not reliable.

The purpose of the study was to compare the effects of a feedback-controlled treadmill (FeedbackTM) to a traditional fixed-speed treadmill (FixedTM) on spatiotemporal gait means, variability, and dynamics. The study also examined inter-session reliability when using the FeedbackTM. Ten young adults walked on the FeedbackTM for a 5-minute familiarization followed by a 16-minute experimental trial. They returned within one week and completed a 5-minute familiarization followed by a 16-minute experimental trial each for FeedbackTM and FixedTM conditions. Mean walking speed and step time, length, width, and speed means and coefficient of variation were calculated from all experimental conditions. Step time, length, width, and speed gait dynamics were analyzed using detrended fluctuation analysis. Mean differences between experimental trials were determined using ANOVAs and reliability between FeedbackTM sessions was determined by intraclass correlation coefficient. No difference was found in mean walking speed nor spatiotemporal variables, with the exception of step width, between the experimental trials. All mean spatiotemporal variables demonstrated good to excellent reliability between sessions, while coefficient of variation was not reliable. Gait dynamics of step time, length, width, and speed were significantly more persistent during the FeedbackTM condition compared to FixedTM, especially step speed. However, gait dynamics demonstrated fair to poor reliability between FeedbackTM sessions. When walking on the FeedbackTM, users maintain a consistent set point, yet the gait dynamics around the mean are different when compared to walking on a FixedTM. In addition, spatiotemporal gait dynamics and variability may not be consistent across separate days when using the FeedbackTM.

Interaction between step-to-step variability and metabolic cost of transport during human walking.

Minimizing the metabolic cost of transport can affect selection of the preferred walking speed. While many factors can affect metabolic cost of transport during human walking, its interaction with step-to-step variability is unclear. Here, we aimed to determine the interaction between metabolic cost of transport and step length variability during human walking at different speeds. In particular, two aspects of step length variability were analyzed: the amount of variations ('variations') and the organization of the step-to-step fluctuations ('fluctuations'). Ten healthy, young participants walked on a treadmill at five speeds, ranging from 0.75 to 1.75 m s-1 Metabolic cost of transport, step length variations (coefficient of variation) and step length fluctuations (quantified via detrended fluctuation analysis) were calculated. A mixed-model ANOVA revealed that variations and walking speed were strong predictors of metabolic cost of transport (R2=0.917, P<0.001), whereas fluctuations were not. Preferred walking speed (1.05±0.20 m s-1) was not significantly different from the speed at which metabolic cost of transport was minimized (1.04±0.05 m s-1; P=0.792), nor from the speed at which fluctuations were most persistent (1.00±0.41 m s-1; P=0.698). The minimization of variations occurred at a faster speed (1.56±0.17 m s-1) than the preferred walking speed (P<0.001). Step length variations likely affect metabolic cost of transport because greater variations are indicative of suboptimal, mechanically inefficient steps. Fluctuations have little or no effect on metabolic cost of transport, but still may relate to preferred walking speed.

Gait Dynamics in Parkinson's Disease: Short Gait Trials "Stitched" Together Provide Different Fractal Fluctuations Compared to Longer Trials.

The fractal analysis of stride-to-stride fluctuations in walking has become an integral part of human gait research. Fractal analysis of stride time intervals can provide insights into locomotor function and dysfunction, but its application requires a large number of strides, which can be difficult to collect from people with movement disorders such as Parkinson's disease. It has recently been suggested that "stitching" together short gait trials to create a longer time series could be a solution. The objective of this study was to determine if scaling exponents from "stitched" stride time series were similar to those from continuous, longer stride time series. Fifteen young adults, fourteen older adults, and thirteen people with Parkinson's disease walked around an indoor track in three blocks: one time 15 min, five times 3 min, and thirty times 30 s. Stride time intervals were determined from gait events recorded with instrumented insoles, and the detrended fluctuation analysis was applied to each stride time series of 512 strides. There was no statistically significant difference between scaling exponents in the three blocks, but intra-class correlation revealed very low between-blocks reliability of scaling exponents. This result challenges the premise that the stitching procedure could provide reliable information about gait dynamics, as it suggests that fractal analysis of stitched time series does not capture the same dynamics as gait recorded continuously. The stitching procedure cannot be considered as a valid alternative to the collection of continuous, long trials. Further studies are recommended to determine if the application of fractal analysis is limited by its own methodological considerations (i.e., long time series), or if other solutions exists to obtain reliable scaling exponents in populations with movement disorders.

Multiscale coordination between athletes: Complexity matching in ergometer rowing.

Complex systems applications in human movement sciences have increased our understanding of emergent coordination patterns between athletes. In the current study, we take a novel step and propose that movement coordination between athletes is a multiscale phenomenon. Specifically, we investigated so-called "complexity matching" of performance measured in the context of rowing. Sixteen rowers participated in two sessions on rowing ergometers: One individual session of 550 strokes and one dyadic session of 550 strokes side-by-side with a team member. We used evenly-spaced detrended fluctuation analysis (DFA) to calculate the complexity indices (DFA exponents) of the force-peak interval series for each rower in each session. The DFA exponents between team members were uncorrelated in the individual sessions (r = 0.06), but were strongly and significantly correlated when team members rowed together (r = 0.87). Furthermore, we found that complexity matching could not be attributed to the rowers mimicking or locally adapting to each other. These findings contribute to the current theoretical understanding of coordination dynamics in sports.

Reliability of a Feedback-Controlled Treadmill Algorithm Dependent on the User's Behavior.

The reliability of the treadmill belt speed using a feedback-controlled treadmill algorithm was analyzed in this study. Using biomechanical factors of the participant's walking behavior, an estimated walking speed was calculated and used to adjust the speed of the treadmill. Our proposed algorithm expands on the current hypotheses of feedback-controlled treadmill algorithms and is presented below. Nine healthy, young adults walked on a treadmill controlled by the algorithm for three trials over two days. Each participant walked on the feedback-controlled treadmill for one 16-minute and one five-minute trial during day one and one 16-minute trial during day two. Mean, standard deviation, interclass correlation coefficient (ICC), and standard error of measurement (SEM) were analyzed on the treadmill belt speed mean, standard deviation, and coefficient of variation. There were significantly high ICC for mean treadmill speed within- and between-days. Treadmill speed standard deviation and coefficient of variation were significantly reliable within-day. These results suggest the algorithm will reliably produce the same treadmill belt speed mean, but may only produce a similar treadmill belt speed standard deviation and coefficient of variation if the trials are performed in the same day. A feedback-controlled treadmill algorithm that accounts for the user's behavior provides a greater level of control and minimizes any possible constraints of walking on a conventional treadmill.

Multifractal signatures of complexity matching.

The complexity matching effect supposes that synchronization between complex systems could emerge from multiple interactions across multiple scales and has been hypothesized to underlie a number of daily-life situations. Complexity matching suggests that coupled systems tend to share similar scaling properties, and this phenomenon is revealed by a statistical matching between the scaling exponents that characterize the respective behaviors of both systems. However, some recent papers suggested that this statistical matching could originate from local adjustments or corrections, rather than from a genuine complexity matching between systems. In the present paper, we propose an analysis method based on correlation between multifractal spectra, considering different ranges of time scales. We analyze several datasets collected in various situations (bimanual coordination, interpersonal coordination, and walking in synchrony with a fractal metronome). Our results show that this method is able to distinguish between situations underlain by genuine statistical matching and situations where statistical matching results from local adjustments.

How to Sync to the Beat of a Persistent Fractal Metronome without Falling Off the Treadmill?

In rehabilitation, rhythmic acoustic cues are often used to improve gait. However, stride-time fluctuations become anti-persistent with such pacing, thereby deviating from the characteristic persistent long-range correlations in stride times of self-paced walking healthy adults. Recent studies therefore experimented with metronomes with persistence in interbeat intervals and successfully evoked persistent stride-time fluctuations. The objective of this study was to examine how participants couple their gait to a persistent metronome, evoking persistently longer or shorter stride times over multiple consecutive strides, without wandering off the treadmill. Twelve healthy participants walked on a treadmill in self-paced, isochronously paced and non-isochronously paced conditions, the latter with anti-persistent, uncorrelated and persistent correlations in interbeat intervals. Stride-to-stride fluctuations of stride times, stride lengths and stride speeds were assessed with detrended fluctuation analysis, in conjunction with an examination of the coupling between stride times and stride lengths. Stride-speed fluctuations were anti-persistent for all conditions. Stride-time and stride-length fluctuations were persistent for self-paced walking and anti-persistent for isochronous pacing. Both stride times and stride lengths changed from anti-persistence to persistence over the four non-isochronous metronome conditions, accompanied by an increasingly stronger coupling between these gait parameters, with peak values for the persistent metronomes. These results revealed that participants were able to follow the beat of a persistent metronome without falling off the treadmill by strongly coupling stride-length fluctuations to the stride-time fluctuations elicited by persistent metronomes, so as to prevent large positional displacements along the treadmill. For self-paced walking, in contrast, this coupling was very weak. In combination, these results challenge the premise that persistent metronomes in gait rehabilitation would evoke stride-to-stride dynamics reminiscent of self-paced walking healthy adults. Future studies are recommended to include an analysis of the interrelation between stride times and stride lengths in addition to the correlational structure of either one in isolation.

Persistent fluctuations in stride intervals under fractal auditory stimulation.

Stride sequences of healthy gait are characterized by persistent long-range correlations, which become anti-persistent in the presence of an isochronous metronome. The latter phenomenon is of particular interest because auditory cueing is generally considered to reduce stride variability and may hence be beneficial for stabilizing gait. Complex systems tend to match their correlation structure when synchronizing. In gait training, can one capitalize on this tendency by using a fractal metronome rather than an isochronous one? We examined whether auditory cues with fractal variations in inter-beat intervals yield similar fractal inter-stride interval variability as isochronous auditory cueing in two complementary experiments. In Experiment 1, participants walked on a treadmill while being paced by either an isochronous or a fractal metronome with different variation strengths between beats in order to test whether participants managed to synchronize with a fractal metronome and to determine the necessary amount of variability for participants to switch from anti-persistent to persistent inter-stride intervals. Participants did synchronize with the metronome despite its fractal randomness. The corresponding coefficient of variation of inter-beat intervals was fixed in Experiment 2, in which participants walked on a treadmill while being paced by non-isochronous metronomes with different scaling exponents. As expected, inter-stride intervals showed persistent correlations similar to self-paced walking only when cueing contained persistent correlations. Our results open up a new window to optimize rhythmic auditory cueing for gait stabilization by integrating fractal fluctuations in the inter-beat intervals.

'Human paced' walking: followers adopt stride time dynamics of leaders.

Isochronous cueing is widely used in gait rehabilitation even though it alters the stride-time dynamics toward anti-persistent rather than the persistent, fractal fluctuations characteristic of human walking. In the present experiment we tested an alternative cueing method: pacing by a human. To this end, we formed sixteen pairs of walkers based on their preferred stride frequency. Each pair consisted of a designated "leader" and a "follower" who was instructed to synchronize his or her steps to those of the leader. Heel strike times were detected with tiny footswitches, and Detrended Fluctuation Analysis (DFA) was applied to estimate fractal exponents of stride-time series. To ensure that the stride-time dynamics of the follower matched those of the leader, the latter was structurally modified by artificial cueing via either an isochronous metronome or a fractal metronome, in contrast to self-paced walking. Mean relative phases between followers and leaders were close to 0°, confirming that followers effectively synchronized their footfalls with those of the leaders. Mean fractal exponents were not statistically different between followers and leaders in any condition and highly correlated, suggesting that followers matched their stride-time structure to that of leaders. Our results open perspectives for alternative, more natural cueing protocols for gait rehabilitation.