Measures of dynamic stability: Detecting differences between walking overground and on a compliant surface

The relationship between the local dynamic stability of gait to cognitive and physical performance in older adults: A scoping review

BACKGROUND

Local dynamic stability (LDS) has become accepted as a gait stability indicator. The deterioration of gait stability is magnified in older adults.

RESEARCH QUESTION

What is the current state in the field regarding rthe relationship between LDS and cognitive and/or physical function in older adults?

METHODS

A scoping review design was used to search for peer-reviewed literature or conference proceedings published through May 2023 for an association between LDS and cognitive (e.g., Montreal Cognitive Assessment) or physical performance (e.g., Timed Up & Go Test) in older adults. Only studies investigating gait stability via LDS during controlled walking, when dealing with a subject group consisting of healthy older adults, and quantifying LDS relationship to cognitive and/or physical measure were included. We analysed data from the studies in a descriptive manner.

RESULTS

In total, 814 potentially relevant articles were selected, of which 15 met the inclusion criteria. We identified 37 LDS quantifiers employed in LDS-cognition and/or LDS-physical performance relationship assessment. Nine measures of cognitive and 20 measures of physical performance were analysed. Most studies estimated LDS quantities using triaxial acceleration data. However, there was a variance in sensor placement and signal direction. Out of the 56 studied relationships of LDS to physical performance measures, sixteen were found to be relevant. Out of 22 studied relationships between LDS and cognitive measures, only two were worthwhile.

SIGNIFICANCE

Considering the heterogeneity of the utilized LDS (caused by different sensors locations, signals, and signal directions as well as variety of computational approaches to estimate LDS) and cognitive/physical measures, the results of this scoping review does not indicate a current need for a systematic review with meta-analysis. To assess the overall utility of LDS to reveal a relationship between LDS to cognitive and physical performance measures, an analysis of other subject groups would be appropriate.

From neural noise to co-adaptability: Rethinking the multifaceted architecture of motor variability

In the last decade, the source and the functional meaning of motor variability have attracted considerable attention in behavioral and brain sciences. This construct classically combined different levels of description, variable internal robustness or coherence, and multifaceted operational meanings. We provide here a comprehensive review of the literature with the primary aim of building a precise lexicon that goes beyond the generic and monolithic use of motor variability. In the pars destruens of the work, we model three domains of motor variability related to peculiar computational elements that influence fluctuations in motor outputs. Each domain is in turn characterized by multiple sub-domains. We begin with the domains of noise and differentiation. However, the main contribution of our model concerns the domain of adaptability, which refers to variation within the same exact motor representation. In particular, we use the terms learning and (social)fitting to specify the portions of motor variability that depend on our propensity to learn and on our largely constitutive propensity to be influenced by external factors. A particular focus is on motor variability in the context of the sub-domain named co-adaptability. Further groundbreaking challenges arise in the modeling of motor variability. Therefore, in a separate pars construens, we attempt to characterize these challenges, addressing both theoretical and experimental aspects as well as potential clinical implications for neurorehabilitation. All in all, our work suggests that motor variability is neither simply detrimental nor beneficial, and that studying its fluctuations can provide meaningful insights for future research.

The application of the Lyapunov Exponent to analyse human performance: A systematic review

Variability is a normal component of human movement, allowing one to adapt to environmental perturbations. It can be analysed from linear or non-linear perspectives. The Lyapunov Exponent (LyE) is a commonly used non-linear technique, which quantifies local dynamic stability. It has been applied primarily to walking gait and appears to be limited application in other movements. Therefore, this systematic review aims to summarise research methodologies applying the LyE to movements, excluding walking gait. Four databases were searched using keywords related to movement variability, dynamic stability, LyE and divergence exponent. Articles written in English, using the LyE to analyse movements, excluding walking gait were included for analysis. 31 papers were included for data extraction. Quality appraisal was conducted and information related to the movement, data capture method, data type, apparatus, sampling rate, body segment/joint, number of strides/steps, state space reconstruction, algorithm, filtering, surrogation and time normalisation were extracted. LyE values were reported in supplementary materials (Appendix 2). Running was the most prevalent non-walking gait movement assessed. Methodologies to calculate the LyE differed in various aspects resulting in different LyE values being generated. Additionally, test-retest reliability, was only conducted in one study, which should be addressed in future.

Reliability of Running Stability during Treadmill and Overground Running

Running stability is the ability to withstand naturally occurring minor perturbations during running. It is susceptible to external and internal running conditions such as footwear or fatigue. However, both its reliable measurability and the extent to which laboratory measurements reflect outdoor running remain unclear. This study aimed to evaluate the intra- and inter-day reliability of the running stability as well as the comparability of different laboratory and outdoor conditions. Competitive runners completed runs on a motorized treadmill in a research laboratory and overground both indoors and outdoors. Running stability was determined as the maximum short-term divergence exponent from the raw gyroscope signals of wearable sensors mounted to four different body locations (sternum, sacrum, tibia, and foot). Sacrum sensor measurements demonstrated the highest reliabilities (good to excellent; ICC = 0.85 to 0.91), while those of the tibia measurements showed the lowest (moderate to good; ICC = 0.55 to 0.89). Treadmill measurements depicted systematically lower values than both overground conditions for all sensor locations (relative bias = -9.8% to -2.9%). The two overground conditions, however, showed high agreement (relative bias = -0.3% to 0.5%; relative limits of agreement = 9.2% to 15.4%). Our results imply moderate to excellent reliability for both overground and treadmill running, which is the foundation of further research on running stability.

Centroidal Moment Pivot for ambulatory estimation of relative feet and CoM movement post stroke: Portable Gait Lab. IEEE Int Conf Rehabil Robot 2022;2022:1-6. [PMID: 36176085 DOI: 10.1109/icorr55369.2022.9896526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Measuring gait and balance recovery is necessary post stroke. In an earlier study, we developed a minimal three Inertial Measurement Units (IMUs) system called Portable Gait Lab (PGL). The PGL used the Centroidal Moment Pivot (CMP) assumption to estimate relative foot and centre of mass (CoM) positions, and thereby estimate gait parameters in healthy participants. In this study, we validate the feasibility of the PGL to track foot and CoM trajectory during gait in four persons with chronic stroke. Spatiotemporal gait and balance measures were estimated from the foot and CoM trajectories, and compared with the reference ForceShoes™. Each participant made at least 20 steps, and the PGL was able to track foot and CoM trajectories with a root mean square of the differences with the reference of 2.9 ± 0.2 cm and 4.6 ± 3.6 cm. The distances between either foot at the end of the walking task, and step lengths were estimated by PGL with an average error with the reference of 1.98 ± 2.2 cm and 7.8 ± 0.1 cm respectively across participants. We show that our approach was able to estimate spatiotemporal and balance parameters related to gait quality in a clinically useful manner. We recommend conducting further studies to study the feasibility of using the PGL system for variable gait patterns measured post stroke.

Effects of back-support exoskeleton use on gait performance and stability during level walking

BACKGROUND

Back-support exoskeletons (BSEs) are a promising intervention to mitigate physical demands at work. Although growing evidence indicates that BSEs can reduce low-back physical demands, there is limited understanding of potential unintended consequences of BSE use, including the risk of falls.

RESEARCH QUESTION

Does using a BSE adversely affect gait performance and stability, and are such effects dependent on specific BSE external torque characteristics?

METHODS

Twenty participants (10 M, 10 F) completed five level over-ground walking trials and a five-minute treadmill walking trial while wearing a BSE (backX™) with three different levels of external torque (i.e., no torque, low torque, and high torque) and in a control (no-exoskeleton) condition. Spatiotemporal gait patterns, stride-to-stride gait variability measures, required coefficient-of-friction (RCoF), and minimum foot clearance (MFC) were determined, to assess gait performance. Gait stability was quantified using the maximum Lyapunov exponent (MLE) of trunk kinematics and the margin-of-stability (MoS).

RESULTS

Using the backX™ with high supportive torque decreased slip risk (7% decrease in RCoF) and slightly improved trunk stability (3% decrease in MLE). However, it also decreased step length (1%), increased step width (10%) and increased gait variability (8-19%). Changes in MoS were complex: while MoS at heel strike decreased in the AP direction, it increased in the ML direction. There was a rather large decrease in MoS (26%) in the ML direction during the swing phase.

SIGNIFICANCE

This is the first study to quantify the effects of wearing a passive BSE with multiple supportive torque levels on gait performance and stability during level walking. Our results, showing that the external torque of the BSE may adversely affect gait step width, variability, and dynamic stability, can contribute to better design and practice guidelines to facilitate the safe adoption of BSEs in the workplace.

Gait Alterations in Adults after Ankle Fracture: A Systematic Review

(1) Background: Ankle fracture results in pain, swelling, stiffness and strength reduction, leading to an altered biomechanical behavior of the joint during the gait cycle. Nevertheless, a common pattern of kinematic alterations has still not been defined. To this end, we analyzed the literature on instrumental gait assessment after ankle fracture, and its correlation with evaluator-based and patient-reported outcome measures. (2) Methods: We conducted a systematic search, according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, of articles published from January 2000 to June 2021 in PubMed, Embase and PEDro on instrumental gait assessment after ankle fracture. (3) Results: Several changes in gait occur after ankle fracture, including a reduction in step length, swing time, single support time, stride length, cadence, speed and an earlier foot-off time in the affected side. Additionally, trunk movement symmetry (especially vertical) is significantly reduced after ankle fracture. The instrumental assessments correlate with different clinical outcome measures. (4) Conclusions: Instrumental gait assessment can provide an objective characterization of the gait alterations after ankle fracture. Such assessment is important not only in clinical practice to assess patients’ performance but also in clinical research as a reference point to evaluate existing or new rehabilitative interventions.

Gait Variability and Complexity during Single and Dual-Task Walking on Different Surfaces in Outdoor Environment

Nowadays, gait assessment in the real life environment is gaining more attention. Therefore, it is desirable to know how some factors, such as surfaces (natural, artificial) or dual-tasking, influence real life gait pattern. The aim of this study was to assess gait variability and gait complexity during single and dual-task walking on different surfaces in an outdoor environment. Twenty-nine healthy young adults aged 23.31 ± 2.26 years (18 females, 11 males) walked at their preferred walking speed on three different surfaces (asphalt, cobbles, grass) in single-task and in two dual-task conditions (manual task-carrying a cup filled with water, cognitive task-subtracting the number 7). A triaxial inertial sensor attached to the lower trunk was used to record trunk acceleration during gait. From 15 strides, sample entropy (SampEn) as an indicator of gait complexity and root mean square (RMS) as an indicator of gait variability were computed. The findings demonstrate that in an outdoor environment, the surfaces significantly impacted only gait variability, not complexity, and that the tasks affected both gait variability and complexity in young healthy adults.

A narrative review of potential measures of dynamic stability to be used during outdoor locomotion on different surfaces

Dynamic stability of locomotion plays an important role in running injuries, particularly during trail running where ankle injuries occur frequently. Several studies have investigated dynamic stability of locomotion using wearable accelerometer measurements. However, no study has reviewed how dynamic stability of locomotion is quantified using accelerometry. Therefore, the present review aims to synthetise the methods and findings of studies investigating stability related parameters measured by accelerometry, during locomotion on various surfaces, and among asymptomatic participants. A systematic search of studies associated with locomotion was conducted. Only studies including assessment of dynamic stability parameters based on accelerometry, including at least one group of asymptomatic participants, and conditions that occur during trail running were considered relevant for this review. Consequently, all retrieved studies used a non-obstructive portable accelerometer or an inertial measurement unit. Fifteen studies used a single tri-axial accelerometer placed above the lumbar region allowing outdoor recordings. From trunk accelerations, a combination of index of cycle repeatability and signal dispersion can adequately be used to assess dynamic stability. However, as most studies included indoor conditions, studies addressing the biomechanics of trail running in outdoor conditions are warranted.

Complexity of human walking: the attractor complexity index is sensitive to gait synchronization with visual and auditory cues

Background

During steady walking, gait parameters fluctuate from one stride to another with complex fractal patterns and long-range statistical persistence. When a metronome is used to pace the gait (sensorimotor synchronization), long-range persistence is replaced by stochastic oscillations (anti-persistence). Fractal patterns present in gait fluctuations are most often analyzed using detrended fluctuation analysis (DFA). This method requires the use of a discrete times series, such as intervals between consecutive heel strikes, as an input. Recently, a new nonlinear method, the attractor complexity index (ACI), has been shown to respond to complexity changes like DFA, while being computed from continuous signals without preliminary discretization. Its use would facilitate complexity analysis from a larger variety of gait measures, such as body accelerations. The aim of this study was to further compare DFA and ACI in a treadmill experiment that induced complexity changes through sensorimotor synchronization.

Methods

Thirty-six healthy adults walked 30 min on an instrumented treadmill under three conditions: no cueing, auditory cueing (metronome walking), and visual cueing (stepping stones). The center-of-pressure trajectory was discretized into time series of gait parameters, after which a complexity index (scaling exponent alpha) was computed via DFA. Continuous pressure position signals were used to compute the ACI. Correlations between ACI and DFA were then analyzed. The predictive ability of DFA and ACI to differentiate between cueing and no-cueing conditions was assessed using regularized logistic regressions and areas under the receiver operating characteristic curves (AUC).

Results

DFA and ACI were both significantly different among the cueing conditions. DFA and ACI were correlated (Pearson’s r = 0.86). Logistic regressions showed that DFA and ACI could differentiate between cueing/no cueing conditions with a high degree of confidence (AUC = 1.00 and 0.97, respectively).

Conclusion

Both DFA and ACI responded similarly to changes in cueing conditions and had comparable predictive power. This support the assumption that ACI could be used instead of DFA to assess the long-range complexity of continuous gait signals. However, future studies are needed to investigate the theoretical relationship between DFA and ACI.

The effect of shoe and floor characteristics on walking kinematics

It is common sense that walking on sand poses challenges to postural control. However, there are no studies quantifying the kinematics of sand walking compared to other types of postural perturbations such as unstable shoes. The aim of the study was to investigate differences in walking kinematics during walking on solid ground, in unstable shoes and on unstable surfaces. Nineteen healthy young adults (23.5 ± 1.5 years) performed three different walking tasks: 1) walking at preferred speed while wearing regular shoes; 2) Walking at preferred speed wearing Masai Barefoot Technology shoes and 3) barefoot walking at preferred speed on a large sand grave. Full-body kinematics were recorded during all conditions using an inertial motion capture system. Basic gait parameters (walking speed, stride length and duration), relative vertical center-of-mass position (rvCOM), and ankle, knee and hip joint angles in the sagittal plane were compared across the tasks through statistical parametric mapping over the course of full walking cycles. Participants presented similar walking speed, as well as stride length and duration across different conditions (p > 0.05). However, walking on sand reduced the rvCOM (p < 0.05), while also requiring greater ankle plantarflexion during stance phase (p < 0.05), as well as greater knee and hip flexion during leg swing and initial contact when compared to the other conditions (p < 0.05). It was concluded that walking on sand substantially changes walking kinematics, and may cause greater postural instability than unstable shoes. Therefore, walking on sand can be an alternative to improve postural control in patients undergoing walking rehabilitation.

Quantifying Dynamic Balance in Young, Elderly and Parkinson's Individuals: A Systematic Review

Introduction: Falling is one of the primary concerns for people with Parkinson's Disease and occurs predominately during dynamic movements, such as walking. Several methods have been proposed to quantify dynamic balance and to assess fall risk. However, no consensus has been reached concerning which method is most appropriate for examining walking balance during unperturbed and perturbed conditions, particularly in Parkinson's Disease individuals. Therefore, this systematic review aimed to assess the current literature on quantifying dynamic balance in healthy young, elderly and Parkinson's individuals during unperturbed and perturbed walking. Methods: The PubMed database was searched by title and abstract for publications quantifying dynamic balance during unperturbed and mechanically perturbed walking conditions in elderly adults and PD. Inclusion criteria required publications to be published in English, be available in full-text, and implement a dynamic balance quantification method. Exclusion criteria included clinical dynamic balance measures, non-mechanical perturbations, pathologies other than PD, and dual-tasking conditions. The initial database search yielded 280 articles, however, only 81 articles were included after title, abstract and full-text screening. Methodological quality and data were extracted from publications included in the final synthesis. Results: The dynamic balance articles included 26 Coefficient of Variation of Spatiotemporal Variability, 10 Detrended Fluctuation Analysis, 20 Lyapunov Exponent, 7 Maximum Floquet Multipliers, 17 Extrapolated Center of Mass, 11 Harmonic Ratios, 4 Center of Mass-Center of Pressure Separation, 2 Gait Stability Ratio, 1 Entropy, 3 Spatiotemporal Variables, 2 Center of Gravity and Center of Pressure, and 2 Root Mean Square in the final synthesis. Assessment of methodological quality determined that 58 articles had a low methodological rating, a 22 moderate rating, and 1 having a high rating. Conclusion: Careful consideration must be given when selecting a method to quantify dynamic balance because each method defines balance differently, reflects a unique aspect of neuromuscular stability mechanisms, and is dependent on the walking condition (unperturbed vs. perturbed). Therefore, each method provides distinct information into stability impairment in elderly and PD individuals.

Template-Based Step Detection with Inertial Measurement Units

This article presents a method for step detection from accelerometer and gyrometer signals recorded with Inertial Measurement Units (IMUs). The principle of our step detection algorithm is to recognize the start and end times of the steps in the signal thanks to a predefined library of templates. The algorithm is tested on a database of 1020 recordings, composed of healthy subjects and patients with various neurological or orthopedic troubles. Simulations on more than 40,000 steps show that the template-based method achieves remarkable results with a 98% recall and a 98% precision. The method adapts well to pathological subjects and can be used in a medical context for robust step estimation and gait characterization.

Maximum Lyapunov exponent revisited: Long-term attractor divergence of gait dynamics is highly sensitive to the noise structure of stride intervals

BACKGROUND

The local dynamic stability method (maximum Lyapunov exponent) can assess gait stability. Two variants of the method exist: the short-term divergence exponent (DE), and the long-term DE. Only the short-term DE can predict fall risk. However, the significance of long-term DE has been unclear so far. Some studies have suggested that the complex, fractal-like structure of fluctuations among consecutive strides correlates with long-term DE. The aim, therefore, was to assess whether the long-term DE is a gait complexity index.

METHODS

The study reanalyzed a dataset of trunk accelerations from 100 healthy adults walking at preferred speed on a treadmill for 10 min. By interpolation, the stride intervals were modified within the acceleration signals for the purpose of conserving the original shape of the signal, while imposing a known stride-to-stride fluctuation structure. Four types of hybrid signals with different noise structures were built: constant, anti-correlated, random, and correlated (fractal). Short- and long-term DEs were then computed.

RESULTS

The results show that long-term DEs, but not short-term DEs, are sensitive to the noise structure of stride intervals. For example, it was that observed that random hybrid signals exhibited significantly lower long-term DEs than hybrid correlated signals did (0.100 vs 0.144, i.e. a 44% difference). Long-term DEs from constant hybrid signals were close to zero (0.006). Conversely, short-term DEs of anti-correlated, random, and correlated hybrid signals were closely grouped (2.49, 2.50, and 2.51).

CONCLUSIONS

The short-term DE and the long-term DE, although they are both computed from divergence curves, should not be interpreted in a similar way. The long-term DE is very likely an index of gait complexity, which may be associated with gait automaticity or cautiousness. Consequently, to better differentiate between short- and long-term DEs, the use of the term attractor complexity index (ACI) is proposed for the latter.

Challenging human locomotion: stability and modular organisation in unsteady conditions

The need to move over uneven terrain is a daily challenge. In order to face unexpected perturbations due to changes in the morphology of the terrain, the central nervous system must flexibly modify its control strategies. We analysed the local dynamic stability and the modular organisation of muscle activation (muscle synergies) during walking and running on an even- and an uneven-surface treadmill. We hypothesized a reduced stability during uneven-surface locomotion and a reorganisation of the modular control. We found a decreased stability when switching from even- to uneven-surface locomotion (p < 0.001 in walking, p = 0.001 in running). Moreover, we observed a substantial modification of the time-dependent muscle activation patterns (motor primitives) despite a general conservation of the time-independent coefficients (motor modules). The motor primitives were considerably wider in the uneven-surface condition. Specifically, the widening was significant in both the early (+40.5%, p < 0.001) and late swing (+7.7%, p = 0.040) phase in walking and in the weight acceptance (+13.6%, p = 0.006) and propulsion (+6.0%, p = 0.041) phase in running. This widening highlighted an increased motor output’s robustness (i.e. ability to cope with errors) when dealing with the unexpected perturbations. Our results confirmed the hypothesis that humans adjust their motor control strategies’ timing to deal with unsteady locomotion.

Fractional Stability of Trunk Acceleration Dynamics of Daily-Life Walking: Toward a Unified Concept of Gait Stability

Over the last decades, various measures have been introduced to assess stability during walking. All of these measures assume that gait stability may be equated with exponential stability, where dynamic stability is quantified by a Floquet multiplier or Lyapunov exponent. These specific constructs of dynamic stability assume that the gait dynamics are time independent and without phase transitions. In this case the temporal change in distance, d(t), between neighboring trajectories in state space is assumed to be an exponential function of time. However, results from walking models and empirical studies show that the assumptions of exponential stability break down in the vicinity of phase transitions that are present in each step cycle. Here we apply a general non-exponential construct of gait stability, called fractional stability, which can define dynamic stability in the presence of phase transitions. Fractional stability employs the fractional indices, α and β, of differential operator which allow modeling of singularities in d(t) that cannot be captured by exponential stability. The fractional stability provided an improved fit of d(t) compared to exponential stability when applied to trunk accelerations during daily-life walking in community-dwelling older adults. Moreover, using multivariate empirical mode decomposition surrogates, we found that the singularities in d(t), which were well modeled by fractional stability, are created by phase-dependent modulation of gait. The new construct of fractional stability may represent a physiologically more valid concept of stability in vicinity of phase transitions and may thus pave the way for a more unified concept of gait stability.

Analysis of Big Data in Gait Biomechanics: Current Trends and Future Directions

The increasing amount of data in biomechanics research has greatly increased the importance of developing advanced multivariate analysis and machine learning techniques, which are better able to handle “big data”. Consequently, advances in data science methods will expand the knowledge for testing new hypotheses about biomechanical risk factors associated with walking and running gait-related musculoskeletal injury. This paper begins with a brief introduction to an automated three-dimensional (3D) biomechanical gait data collection system: 3D GAIT, followed by how the studies in the field of gait biomechanics fit the quantities in the 5 V’s definition of big data: volume, velocity, variety, veracity, and value. Next, we provide a review of recent research and development in multivariate and machine learning methods-based gait analysis that can be applied to big data analytics. These modern biomechanical gait analysis methods include several main modules such as initial input features, dimensionality reduction (feature selection and extraction), and learning algorithms (classification and clustering). Finally, a promising big data exploration tool called “topological data analysis” and directions for future research are outlined and discussed.

Monitoring of Gait Quality in Patients With Chronic Pain of Lower Limbs

Severe injuries of lower extremities often lead to chronic pain and reduced walking abilities. We postulated that measuring free-living gait can provide further information about walking ability in complement to clinical evaluations. We sought to validate a method that characterizes free gaits with a wearable sensor. Over one week, 81 healthy controls (HC) and 66 chronic lower limb pain patients (CLLPP) hospitalized for multidisciplinary rehabilitation wore a simple accelerometer (Actigraph). In the acceleration signals, steady 1-min walks detected numbered 7,835 (5,085 in CLLPP and 2,750 in HC). Five gait quality measures were assessed: movement intensity, cadence, stride regularity, and short-term and long-term local dynamic stability. Gait quality variables differed significantly between CLLPP and HC (4%-26%). Intraclass correlation coefficients revealed moderate to high repeatability (0.71-0.91), which suggests that seven days of measurement are sufficient to assess average gait patterns. Regression analyses showed significant association (R² = 0.44) between the gait quality variables and a clinical evaluation of walking ability, i.e., the 6-min walk test. Overall, the results show that the method is easy to implement, valid (high concurrent validity), and reliable to assess walking abilities ecologically.

Sudden changes in walking surface compliance evoke contralateral EMG in a hemiparetic walker: a case study of inter-leg coordination after neurological injury

Gait impairment due to neurological disorders is a significant problem around the world. Despite the growing interest in using robotic devices for gait rehabilitation, their widespread use remains limited as there is no clear evidence that robot-assisted gait therapy is superior to traditional treadmill-based therapy. This work is a case study that focuses on investigating the existence of mechanisms of inter-leg coordination after neurological injury, and based on that, proposing novel methods for gait rehabilitation. Using a novel robotic device, the Variable Stiffness Treadmill (VST), we apply perturbations to the compliance of the walking surface underneath the non-paretic leg, and analyze the response of the contralateral (paretic) leg. We show that muscle activity is evoked in the gastrocnemius of the paretic leg. From a clinical prospective, the results of this study can be disruptive because our methods provide a safe and targeted way to provide gait rehabilitation in hemiparesis since direct manipulation of the paretic side is not required. This work provides evidence for the first time that muscle activity can be evoked in the paretic leg of a hemiplegic walker in response to unilateral perturbations to the compliance of the walking surface, providing direction for targeted robot-assisted gait rehabilitation.

Is There a Correlation Between Static and Dynamic Postural Balance Among Young Male and Female Dancers?

Aimed to investigate whether young male and female dancers have different patterns of association between static and dynamic postural balance (PB), 60 dancers from the Australian Ballet School (14-19 years old) were tested for static and dynamic PB with head and lumbar accelerometers. Monotonic relationships between static and dynamic PB were found in head movements among young female dancers in all three directions, but were found for young male dancers in the mediolateral (ML) and anteroposterior (AP) directions only. In lumbar movements, monotonic relationships were found for young female dancers in the AP direction only. Comparing head with lumbar movements in static PB, young male dancers demonstrated monotonic relationships between head and lumbar movements in all 3 directions; however, young female dancers demonstrated monotonic relationships in the AP direction only. In the dynamic measurements, both male and female dancers demonstrated monotonic relationships between head and lumbar movements for all parameters measured in the ML and vertical directions (p < .05). In conclusions, among female dancers static PB ability is correlated with their dynamic ability, whereas among male dancers, no relationship between the static and dynamic PB in the AP direction exists. Male dancers showed head and lumbar coordination in the static PB movement, but both genders manifested no head and lumbar coordination in the AP direction measured for dynamic PB.

Walking on a compliant surface does not enhance kinematic gait asymmetries after unilateral total knee arthroplasty

PURPOSE

To investigate gait asymmetries and the effect of walking on compliant surfaces in individuals with unilateral total knee arthroplasty (TKA), hypothesizing that asymmetries would increase as an effect of the compliant surface.

METHODS

Individuals with unilateral TKA ~19 months post-operative (n = 23, median age 59 years) recruited from one orthopaedic clinic and age- and gender-matched healthy individuals without knee complaints (n = 23, median age 56 years) walked at comfortable speed on a hard surface and on a compliant surface. 3D kinematic analyses were made for knee and hip angles in sagittal and frontal planes, stance time, step length, and gait velocity.

RESULTS

Shorter stance time (p < 0.01) and less peak knee flexion (p < 0.001) at weight bearing acceptance was found in the prosthetic side compared with the contralateral side. Larger knee (p < 0.01) and hip (p < 0.001) adduction was found compared with healthy controls. Neither asymmetries between the prosthetic and the contralateral side nor differences compared with healthy controls were enhanced when walking on compliant surfaces compared with hard surfaces.

CONCLUSION

The TKA group adapted their gait to compliant surfaces similarly to healthy controls. Gait asymmetries in the TKA group observed on hard surface were not enhanced, and adduction in hip and knee joints did not increase further as an effect of walking on compliant surfaces. Thus, unfavourable knee joint loading did not increase when walking on a compliant surface. This implies that recommendations for walking on soft surfaces to reduce knee joint loading are not counteracted by increased gait asymmetries and unfavourable joint loading configurations.

LEVEL OF EVIDENCE

III.

A comparison study of local dynamic stability measures of daily life walking in older adult community-dwelling fallers and non-fallers

In the present study we compared the performance of three different estimations of local dynamic stability λ to distinguish between the dynamics of the daily-life walking of elderly fallers and non-fallers. The study re-analyses inertial sensor data of 3-days daily-life activity originally described by Weiss et al. (2013). The data set contains inertial sensor data from 39 older persons who reported less than 2 falls and 31 older persons who reported two or more falls the previous year. 3D-acceleration and 3D-velocity signals from walking epochs of 50s were used to reconstruct a state space using three different methods. Local dynamic stability was estimated with the algorithms proposed by Rosenstein et al. (1993), Kantz (1994), and Ihlen et al. (2012a). Median λs assessed by Ihlen׳s and Kantz׳ algorithms discriminated better between elderly fallers and non-fallers (highest AUC=0.75 and 0.73) than Rosenstein׳s algorithm (highest AUC=0.59). The present results suggest that the ability of λ to distinguish between fallers and non-fallers is dependent on the parameter setting of the chosen algorithm. Further replication in larger samples of community-dwelling older persons and different patient groups is necessary before including the suggested parameter settings in fall risk assessment and prediction models.

Extraction of stride events from gait accelerometry during treadmill walking

Objective: evaluating stride events can be valuable for understanding the changes in walking due to aging and neurological diseases. However, creating the time series necessary for this analysis can be cumbersome. In particular, finding heel contact and toe-off events which define the gait cycles accurately are difficult. Method: we proposed a method to extract stride cycle events from tri-axial accelerometry signals. We validated our method via data collected from 14 healthy controls, 10 participants with Parkinson’s disease, and 11 participants with peripheral neuropathy. All participants walked at self-selected comfortable and reduced speeds on a computer-controlled treadmill. Gait accelerometry signals were captured via a tri-axial accelerometer positioned over the L3 segment of the lumbar spine. Motion capture data were also collected and served as the comparison method. Results: our analysis of the accelerometry data showed that the proposed methodology was able to accurately extract heel and toe-contact events from both feet. We used t-tests, analysis of variance (ANOVA) and mixed models to summarize results and make comparisons. Mean gait cycle intervals were the same as those derived from motion capture, and cycle-to-cycle variability measures were within 1.5%. Subject group differences could be similarly identified using measures with the two methods. Conclusions: a simple tri-axial acceleromter accompanied by a signal processing algorithm can be used to capture stride events. Clinical impact: the proposed algorithm enables the assessment of stride events during treadmill walking, and is the first step toward the assessment of stride events using tri-axial accelerometers in real-life settings.

Tactile pavement for guiding walking direction: An assessment of heading direction and gait stability

For maintaining heading direction while walking we heavily rely on vision. Therefore, walking in the absence of vision or with visual attention directed elsewhere potentially leads to dangerous situations. Here we investigated whether tactile information from the feet can be used as a (partial) substitute for vision in maintaining a stable heading direction. If so, participants should be better able to keep a constant heading direction on tactile pavement that indicates directionality than on regular flat pavement. However, such a pavement may also be destabilizing. Thus we asked participants to walk straight ahead on regular pavement, and on tactile pavement (tiles with ridges along the walking direction) while varying the amount of vision. We assessed the effects of the type of pavement as well as the amount of vision on the variability of the heading direction as well as gait stability. Both of these measures were calculated from accelerations and angular velocities recorded from a smartphone attached to the participants trunk. Results showed that on tactile pavement participants had a less variations in their heading direction than on regular pavement. The drawback, however, was that the tactile pavement used in this study decreased gait stability. In sum, tactile pavement can be used as a partial substitute for vision in maintaining heading direction, but it can also decrease gait stability. Future work should focus on designing tactile pavement that does provided directional clues, but is less destabilizing.

The Discriminant Value of Phase-Dependent Local Dynamic Stability of Daily Life Walking in Older Adult Community-Dwelling Fallers and Nonfallers

The present study compares phase-dependent measures of local dynamic stability of daily life walking with 35 conventional gait features in their ability to discriminate between community-dwelling older fallers and nonfallers. The study reanalyzes 3D-acceleration data of 3-day daily life activity from 39 older people who reported less than 2 falls during one year and 31 who reported two or more falls. Phase-dependent local dynamic stability was defined for initial perturbation at 0%, 20%, 40%, 60%, and 80% of the step cycle. A partial least square discriminant analysis (PLS-DA) was used to compare the discriminant abilities of phase-dependent local dynamic stability with the discriminant abilities of 35 conventional gait features. The phase-dependent local dynamic stability λ at 0% and 60% of the step cycle discriminated well between fallers and nonfallers (AUC = 0.83) and was significantly larger (p < 0.01) for the nonfallers. Furthermore, phase-dependent λ discriminated as well between fallers and nonfallers as all other gait features combined. The present result suggests that phase-dependent measures of local dynamic stability of daily life walking might be of importance for further development in early fall risk screening tools.

Understanding the effects of pre-processing on extracted signal features from gait accelerometry signals

Gait accelerometry is an important approach for gait assessment. Previous contributions have adopted various pre-processing approaches for gait accelerometry signals, but none have thoroughly investigated the effects of such pre-processing operations on the obtained results. Therefore, this paper investigated the influence of pre-processing operations on signal features extracted from gait accelerometry signals. These signals were collected from 35 participants aged over 65years: 14 of them were healthy controls (HC), 10 had Parkinson׳s disease (PD) and 11 had peripheral neuropathy (PN). The participants walked on a treadmill at preferred speed. Signal features in time, frequency and time-frequency domains were computed for both raw and pre-processed signals. The pre-processing stage consisted of applying tilt correction and denoising operations to acquired signals. We first examined the effects of these operations separately, followed by the investigation of their joint effects. Several important observations were made based on the obtained results. First, the denoising operation alone had almost no effects in comparison to the trends observed in the raw data. Second, the tilt correction affected the reported results to a certain degree, which could lead to a better discrimination between groups. Third, the combination of the two pre-processing operations yielded similar trends as the tilt correction alone. These results indicated that while gait accelerometry is a valuable approach for the gait assessment, one has to carefully adopt any pre-processing steps as they alter the observed findings.

Fixed and self-paced treadmill walking for able-bodied and transtibial amputees in a multi-terrain virtual environment

A self-paced treadmill automatically adjusts speed in real-time to match the user's walking speed, potentially enabling more natural gait than fixed-speed treadmills. This research examined walking speed changes for able-bodied and transtibial amputee populations on a self-paced treadmill in a multi-terrain virtual environment and examined gait differences between fixed and self-paced treadmill speed conditions. Twelve able-bodied (AB) individuals and 12 individuals with unilateral transtibial amputation (TT) walked in a park-like virtual environment with level, slopes, and simulated uneven terrain scenarios. Temporal-spatial and range-of-motion parameters were analyzed. Within the self-paced condition, all participants significantly varied walking speed (p<0.001) across different walking activities. Compared to level walking, participants reduced speed for uphill and hilly activities (p<0.001). TT also reduced speed downhill (p<0.001). Generally, differences in temporal-spatial and range-of-motion parameters between fixed and self-paced speed conditions were no longer significantly different with a speed covariate. However, for uphill walking, both groups decreased stride length during self-paced trials, and increased stride length during fixed-speed trials to maintain the constant speed (p<0.01). The results from this study demonstrated self-paced treadmill mode is important for virtual reality systems with multiple movement scenarios in order to elicit more natural gait across various terrain. Fixed-speed treadmills may induce gait compensations to maintain the fixed speed.

Effect of treadmill versus overground running on the structure of variability of stride timing

Gait timing dynamics of treadmill and overground running were compared. Nine trained runners ran treadmill and track trials at 80, 100, and 120% of preferred pace for 8 min. each. Stride time series were generated for each trial. To each series, detrended fluctuation analysis (DFA), power spectral density (PSD), and multiscale entropy (MSE) analysis were applied to infer the regime of control along the randomness-regularity axis. Compared to overground running, treadmill running exhibited a higher DFA and PSD scaling exponent, as well as lower entropy at non-preferred speeds. This indicates a more ordered control for treadmill running, especially at non-preferred speeds. The results suggest that the treadmill itself brings about greater constraints and requires increased voluntary control. Thus, the quantification of treadmill running gait dynamics does not necessarily reflect movement in overground settings.

To What Extent Does Not Wearing Shoes Affect the Local Dynamic Stability of Walking?: Effect Size and Intrasession Repeatability

Local dynamic stability (stability) quantifies how a system responds to small perturbations. Several experimental and clinical findings have highlighted the association between gait stability and fall risk. Walking without shoes is known to slightly modify gait parameters. Barefoot walking may cause unusual sensory feedback to individuals accustomed to shod walking, and this may affect stability. The objective was therefore to compare the stability of shod and barefoot walking in healthy individuals and to analyze the intrasession repeatability. Forty participants traversed a 70 m indoor corridor wearing normal shoes in one trial and walking barefoot in a second trial. Trunk accelerations were recorded with a 3D-accelerometer attached to the lower back. The stability was computed using the finite-time maximal Lyapunov exponent method. Absolute agreement between the forward and backward paths was estimated with the intraclass correlation coefficient (ICC). Barefoot walking did not significantly modify the stability as compared with shod walking (average standardized effect size: +0.11). The intrasession repeatability was high (ICC: 0.73–0.81) and slightly higher in barefoot walking condition (ICC: 0.81–0.87). Therefore, it seems that barefoot walking can be used to evaluate stability without introducing a bias as compared with shod walking, and with a sufficient reliability.

Detrended fluctuation analysis and adaptive fractal analysis of stride time data in Parkinson's disease: stitching together short gait trials

Variability indicates motor control disturbances and is suitable to identify gait pathologies. It can be quantified by linear parameters (amplitude estimators) and more sophisticated nonlinear methods (structural information). Detrended Fluctuation Analysis (DFA) is one method to measure structural information, e.g., from stride time series. Recently, an improved method, Adaptive Fractal Analysis (AFA), has been proposed. This method has not been applied to gait data before. Fractal scaling methods (FS) require long stride-to-stride data to obtain valid results. However, in clinical studies, it is not usual to measure a large number of strides (e.g., [Formula: see text][Formula: see text] strides). Amongst others, clinical gait analysis is limited due to short walkways, thus, FS seem to be inapplicable. The purpose of the present study was to evaluate FS under clinical conditions. Stride time data of five self-paced walking trials ([Formula: see text] strides each) of subjects with PD and a healthy control group (CG) was measured. To generate longer time series, stride time sequences were stitched together. The coefficient of variation (CV), fractal scaling exponents [Formula: see text] (DFA) and [Formula: see text] (AFA) were calculated. Two surrogate tests were performed: A) the whole time series was randomly shuffled; B) the single trials were randomly shuffled separately and afterwards stitched together. CV did not discriminate between PD and CG. However, significant differences between PD and CG were found concerning [Formula: see text] and [Formula: see text]. Surrogate version B yielded a higher mean squared error and empirical quantiles than version A. Hence, we conclude that the stitching procedure creates an artificial structure resulting in an overestimation of true [Formula: see text]. The method of stitching together sections of gait seems to be appropriate in order to distinguish between PD and CG with FS. It provides an approach to integrate FS as standard in clinical gait analysis and to overcome limitations such as short walkways.

The effects of listening to music or viewing television on human gait

This paper presents a two-part study with walking conditions involving music and television (TV) to investigate their effects on human gait. In the first part, we observed seventeen able-bodied adults as they participated in three 15-minute walking trials: (1) without music, (2) with music and (3) without music again. In the second part, we observed fifteen able-bodied adults as they walked on a treadmill for 15 min while watching (1) TV with sound (2) TV without sound and (3) TV with subtitles but no sound. Gait timing was recorded via bilateral heel sensors and center-of-mass accelerations were measured by tri-axial accelerometers. Measures of statistical persistence, dynamic stability and gait variability were calculated. Our results showed that none of the considered gait measures were statistically different when comparing music with no-music trials. Therefore, walking to music did not appear to affect intrinsic walking dynamics in the able-bodied adult population. However, stride interval variability and stride interval dynamics were significantly greater in the TV with sound walking condition when compared to the TV with subtitles condition. Treadmill walking while watching TV with subtitles alters intrinsic gait dynamics but potentially offers greater gait stability.

Local dynamic stability as a responsive index for the evaluation of rehabilitation effect on fall risk in patients with multiple sclerosis: a longitudinal study

BACKGROUND

Gait and balance problems are common in patients with multiple sclerosis, leading to high risk for falls. Local Dynamic Stability (LDS), a non-linear gait stability index, has been advocated as an early indicator of risk for falls. With this longitudinal study over three weeks, we aimed to assess the responsiveness of Local Dynamic Stability to a rehabilitation program and to compare it to other measures.

METHODS

Eighteen patients (mean 54 years, median EDSS score: 5) participated. They were admitted to inpatient rehabilitation and received a three weeks individually tailored program. They performed a 3-minute walking test at the beginning and at the end of the stay, as well as pain, wellbeing, fatigue, and balance assessment. The Local Dynamic Stability was computed from the acceleration signals measured with a 3D-accelerometer.

RESULTS

At the end of the rehabilitation process, patients reported reduced pain (Effect Size: -0.7), fatigue (ES:-0.6), and increased wellbeing (ES: 1.1). A small positive effect on static balance was observed (ES: 0.3). LDS was improved (ES: 0.6), and the effect was higher than walking speed improvement (ES: 0.4).

CONCLUSIONS

The Local Dynamic Stability seemed responsive to assess rehabilitation effects in patients with multiple sclerosis. It could constitute a valuable gait quality index, which could evaluate potential effects of rehabilitation on fall risk.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN69803702.

A comprehensive assessment of gait accelerometry signals in time, frequency and time-frequency domains

Gait accelerometry is a promising tool to assess human walking and reveal deteriorating gait characteristics in patients and can be a rich source of clinically relevant information about functional declines in older adults. Therefore, in this paper, we present a comprehensive set of signal features that may be used to extract clinically valuable information from gait accelerometry signals. To achieve our goal, we collected tri-axial gait accelerometry signals from 35 adults 65 years of age and older. Fourteen subjects were healthy controls, 10 participants were diagnosed with Parkinson's disease, and 11 participants were diagnosed with peripheral neuropathy. The data were collected while the participants walked on a treadmill at a preferred walking speed. Accelerometer signal features in time, frequency and time-frequency domains were extracted. The results of our analysis showed that some of the extracted features were able to differentiate between healthy and clinical populations. Signal features in all three domains were able to emphasize variability among different groups, and also revealed valuable information about variability of the signals between anterior-posterior, mediolateral, and vertical directions within subjects. The current results imply that the proposed signal features can be valuable tools for the analysis of gait accelerometry data and should be utilized in future studies.

Assessing the stability of human locomotion: a review of current measures

Falling poses a major threat to the steadily growing population of the elderly in modern-day society. A major challenge in the prevention of falls is the identification of individuals who are at risk of falling owing to an unstable gait. At present, several methods are available for estimating gait stability, each with its own advantages and disadvantages. In this paper, we review the currently available measures: the maximum Lyapunov exponent (λS and λL), the maximum Floquet multiplier, variability measures, long-range correlations, extrapolated centre of mass, stabilizing and destabilizing forces, foot placement estimator, gait sensitivity norm and maximum allowable perturbation. We explain what these measures represent and how they are calculated, and we assess their validity, divided up into construct validity, predictive validity in simple models, convergent validity in experimental studies, and predictive validity in observational studies. We conclude that (i) the validity of variability measures and λS is best supported across all levels, (ii) the maximum Floquet multiplier and λL have good construct validity, but negative predictive validity in models, negative convergent validity and (for λL) negative predictive validity in observational studies, (iii) long-range correlations lack construct validity and predictive validity in models and have negative convergent validity, and (iv) measures derived from perturbation experiments have good construct validity, but data are lacking on convergent validity in experimental studies and predictive validity in observational studies. In closing, directions for future research on dynamic gait stability are discussed.

Do orthopaedic shoes improve local dynamic stability of gait? An observational study in patients with chronic foot and ankle injuries

Background

Complex foot and ankle fractures, such as calcaneum fractures or Lisfranc dislocations, are often associated with a poor outcome, especially in terms of gait capacity. Indeed, degenerative changes often lead to chronic pain and chronic functional limitations. Prescription footwear represents an important therapeutic tool during the rehabilitation process. Local Dynamic Stability (LDS) is the ability of locomotor system to maintain continuous walking by accommodating small perturbations that occur naturally during walking. Because it reflects the degree of control over the gait, LDS has been advocated as a relevant indicator for evaluating different conditions and pathologies. The aim of this study was to analyze changes in LDS induced by orthopaedic shoes in patients with persistent foot and ankle injuries. We hypothesised that footwear adaptation might help patients to improve gait control, which could lead to higher LDS:

Methods

Twenty-five middle-aged inpatients (5 females, 20 males) participated in the study. They were treated for chronic post-traumatic disabilities following ankle and/or foot fractures in a Swiss rehabilitation clinic. During their stay, included inpatients received orthopaedic shoes with custom-made orthoses (insoles). They performed two 30s walking trials with standard shoes and two 30s trials with orthopaedic shoes. A triaxial motion sensor recorded 3D accelerations at the lower back level. LDS was assessed by computing divergence exponents in the acceleration signals (maximal Lyapunov exponents). Pain was evaluated with Visual Analogue Scale (VAS). LDS and pain differences between the trials with standard shoes and the trials with orthopaedic shoes were assessed.

Results

Orthopaedic shoes significantly improved LDS in the three axes (medio-lateral: 10% relative change, paired t-test p < 0.001; vertical: 9%, p = 0.03; antero-posterior: 7%, p = 0.04). A significant decrease in pain level (VAS score -29%) was observed.

Conclusions

Footwear adaptation led to pain relief and to improved foot & ankle proprioception. It is likely that that enhancement allows patients to better control foot placement. As a result, higher dynamic stability has been observed. LDS seems therefore a valuable index that could be used in early evaluation of footwear outcome in clinical settings.

Kinematic measures for assessing gait stability in elderly individuals: a systematic review

Falls not only present a considerable health threat, but the resulting treatment and loss of working days also place a heavy economic burden on society. Gait instability is a major fall risk factor, particularly in geriatric patients, and walking is one of the most frequent dynamic activities of daily living. To allow preventive strategies to become effective, it is therefore imperative to identify individuals with an unstable gait. Assessment of dynamic stability and gait variability via biomechanical measures of foot kinematics provides a viable option for quantitative evaluation of gait stability, but the ability of these methods to predict falls has generally not been assessed. Although various methods for assessing gait stability exist, their sensitivity and applicability in a clinical setting, as well as their cost-effectiveness, need verification. The objective of this systematic review was therefore to evaluate the sensitivity of biomechanical measures that quantify gait stability among elderly individuals and to evaluate the cost of measurement instrumentation required for application in a clinical setting. To assess gait stability, a comparative effect size (Cohen's d) analysis of variability and dynamic stability of foot trajectories during level walking was performed on 29 of an initial yield of 9889 articles from four electronic databases. The results of this survey demonstrate that linear variability of temporal measures of swing and stance was most capable of distinguishing between fallers and non-fallers, whereas step width and stride velocity prove more capable of discriminating between old versus young (OY) adults. In addition, while orbital stability measures (Floquet multipliers) applied to gait have been shown to distinguish between both elderly fallers and non-fallers as well as between young and old adults, local stability measures (λs) have been able to distinguish between young and old adults. Both linear and nonlinear measures of foot time series during gait seem to hold predictive ability in distinguishing healthy from fall-prone elderly adults. In conclusion, biomechanical measurements offer promise for identifying individuals at risk of falling and can be obtained with relatively low-cost tools. Incorporation of the most promising measures in combined retrospective and prospective studies for understanding fall risk and designing preventive strategies is warranted.

Sensitivity of trunk variability and stability measures to balance impairments induced by galvanic vestibular stimulation during gait

For targeted prevention of falls, it is necessary to identify individuals with balance impairments. To test the sensitivity of measures of variability, local stability and orbital stability of trunk kinematics to balance impairments during gait, we used galvanic vestibular stimulation (GVS) to impair balance in 12 young adults while walking on a treadmill at different speeds. Inertial sensors were used to measure trunk accelerations, from which variability in the medio-lateral direction and local and orbital stability were calculated. The short-term Lyapunov exponent and variability reflected the destabilizing effect of GVS, while the long-term Lyapunov exponent and Floquet multipliers suggested increased stability. Therefore, we concluded that only short-term Lyapunov exponents and variability can be used to asses stability of gait. In addition, to investigate the feasibility of using these measures in screening for fall risk, the presence or absence of GVS was predicted with variability and the short-term Lyapunov exponent. Predictions were good at all walking speeds, but best at preferred walking speed, with a correct classification in 83.3% of the cases.