Kinematic variability, fractal dynamics and local dynamic stability of treadmill walking

Gait variability predicts post-fatigue obstacle course performance among military cadets: An exploratory study

We explored the extent to which pre-fatigue gait variability during load carriage is associated with the ability of an individual to perform an obstacle course post-fatigue. Twenty-four military cadets were monitored during treadmill gait and completed an obstacle course before and after a full-body fatigue protocol. Gait variability measures were determined from spatiotemporal stride characteristics, joint angle trajectories, and inter-joint coordination. These measures were then used in multiple linear regression models to predict three measures of post-fatigue performance (i.e., hurdle completion time, maximum jump height, and maximum jump distance). Measures of joint kinematic variability predicted 73-89% of the variance in post-fatigue performance. Specifically, the significant predictors were sagittal plane variability of 1) hip angle and hip-knee coordination during swing phase; and 2) knee-ankle coordination during both stance and swing phase. Measures of joint kinematic variability obtained from gait thus appear relevant for predicting individual differences in adapting to fatigue, and such measures could aid in predicting post-fatigue performance in diverse dynamic tasks.

Differences in the stride time and lower limb joint angles and their variability during distance running between treadmill and over-ground: a crossover study

BACKGROUND

Treadmills have been used in laboratories to assess various measures related to walking and running. However, there has been some skepticism regarding their reliability as a representation of outdoor running. While marathon running has gained popularity as a form of physical activity, there have been few studies examining stride-to-stride variability after distance running, especially in relation to the duration and surface of running. This study compared stride time and lower limb joint angles during distance treadmill running and running over-ground. The hypothesis was that stride-to-stride variability would be influenced by running duration and surface, with greater variability observed during outdoor running.

METHODS

Eleven runners participated in the study, running on a treadmill and over-ground for 31 minutes at their preferred speed. Inertial measurement units were used to measure stride time, total range of motion, and joint angles of the hip, knee, and ankle in different phases of the gait cycle in the sagittal plane movements. Mean and coefficient of variation of each parameter were compared between the initial and final 5 minutes of running on the treadmill and over-ground.

RESULTS

There were no significant differences in stride time or its variability based on running duration or surface. However, mean and variability of certain lower limb joint angles were higher during outdoor running, supporting the hypothesis. Variability was higher in the initial duration of running as compared to final phase of running.

CONCLUSIONS

These findings suggest that treadmill may not fully reflect the dynamics of running over-ground. It is important to consider variability in gait analysis and research, as well as the potential impact on training and clinical practice.

NONAN GaitPrint: An IMU gait database of healthy older adults

The continued effort to study gait kinematics and the increased interest in identifying individuals based on their gait patterns could be strengthened by the inclusion of data from older groups. To address this need and complement our previous database on healthy young adults, we present an addition to the Nonlinear Analysis Core (NONAN) GaitPrint database. We offer full-body inertial measurement data during self-paced overground walking on a 200 m indoor track of 41 older adults (56 + years old; 20 men and 21 women; age: 64.7 ± 7.5 years; height: 1.7 ± 0.1 m; body mass: 81.1 ± 17.8 kg) across 18 four-minute trials conducted over two days. The multiple recordings are supported by a range of pre-calculated spatiotemporal variables, a list of each subject's anthropometrics, notes for each walking trial, and template scripts for easier application of our data to classroom assignments or laboratory research. In addition, a preliminary Bayesian analysis found a range of evidence supporting age-related gait changes between this database and our database on young adults.

Evaluating the Reliability and Consistency of Treadmill Gait Analysis Using an RGB-D Camera: Effects of Assistance and No Assistance

This study aimed to assess the intraday reliability of markerless gait analysis using an RGB-D camera versus a traditional three-dimensional motion analysis (3DMA) system with and without a simulated walking assistant. Gait assessments were conducted on 20 healthy adults walking on a treadmill with a focus on spatiotemporal parameters gathered using the RGB-D camera and 3DMA system. The intraday reliability of the RGB-D camera was evaluated using intraclass correlation coefficients (ICC 1, 1), while its consistency with the 3DMA system was determined using ICC (2, 1). The results demonstrated that the RGB-D camera provided high intraday reliability and showed strong consistency with 3DMA measurements regardless of the presence of an assistant. The Bland-Atman analysis indicated no significant systematic bias, with the minimum detectable change remaining within acceptable clinical ranges. These findings highlight the potential of the RGB-D camera for reliable markerless gait analysis in clinical environments in which walking assistance may be needed, thereby expanding its applicability in patients with various impairment degrees. Future research should validate these results in patient populations and explore their utility for measuring kinematic parameters.

Leveraging feature selection for enhanced fall risk prediction in elderly using gait analysis

There is no effective fall risk screening tool for the elderly that can be integrated into clinical practice. Developing a system that can be easily used in primary care services is a current need. Current studies focus on the use of multiple sensors or activities to achieve higher accuracy. However, multiple sensors and activities reduce the availability of these systems. This study aims to develop a system to perform fall prediction for the elderly by using signals recorded from a single sensor during a short-term activity. A total of 168 features in the time and frequency domains were created using acceleration signals obtained from 71 elderly people. The features were weighted based on the ReliefF algorithm, and the artificial neural networks model was developed using the most important features. The best classification result was obtained using the 17 most important features of those weighted for K = 20 nearest neighbors. The highest accuracy was 82.2% (82.9% Sensitivity, 81.6% Specificity). The partially high accuracy obtained in our study shows that falling can be detected early with a sensor and a simple activity by determining the right features and can be easily applied in the assessment of the elderly during routine follow-ups.

Self-selected speed provides more accurate human gait kinematics and spatiotemporal parameters than overground simulated speed on a treadmill: a cross-sectional study

BACKGROUND

Walking speed, a key element of gait analysis, is essential for evaluating the biomechanics of the musculoskeletal system and is typically assessed on flat surfaces, such as walkways or treadmills. While many authors have compared the differences and similarities between treadmill and overground walking, no studies have yet investigated the differences between treadmill gait analysis at self-selected speed (SS) and overground simulated speed (OS). The hypothesis is that accurate kinematic measurements depend on selecting the correct gait speed; however, a mismatch between the perceived comfortable treadmill speed and actual overground speed may affect the accuracy of treadmill gait analyses. This study aimed to assess treadmill gait in healthy young adults by comparing the SS with the OS. The objectives were to determine whether participants could match SS with OS on a treadmill, examine sex differences in gait kinematics and spatiotemporal parameters (KSP) at different speeds, and identify which speed better reflects natural gait kinematics.

METHODS

A total of 60 healthy men and 70 healthy women, aged 22-35 years, participated in this cross-sectional study to investigate the gait kinematics and spatiotemporal differences between the SS and OS. Student's t-test, Bonferroni adjustment, Cohen's effect size, and quadratic regression were employed to analyse differences across walking speeds and groups.

RESULTS

A discrepancy between OS and SS was observed in 66.4% of the participants. Our findings revealed that the adjusted R² values for KSP at SS were consistently greater than those at OS, suggesting that SS offers a more robust and accurate representation of gait kinematics, whereas OS is less reliable.

CONCLUSIONS

These findings underscore the importance of individualized speed selection in gait analysis, as it significantly impacts the accuracy of kinematic and spatiotemporal measurements. This insight is pivotal for clinicians and researchers to develop more effective rehabilitation strategies and comprehensively understand gait dynamics.

Validation of Linear and Nonlinear Gait Variability Measures Derived From a Smartphone System Compared to a Gold-Standard Footswitch System During Overground Walking

Smartphones, with embedded accelerometers, may be a viable method to monitor gait variability in the free-living environment. However, measurements estimated using smartphones must first be compared to known quantities to ensure validity. This study assessed the validity and reliability of smartphone-derived gait measures compared to a gold-standard footswitch system during overground walking. Seventeen adults completed three 8-minute overground walking trials during 3 separate visits. The stride time series was calculated as the time difference between consecutive right heel contact events within the footswitch and smartphone-accelerometry signals. Linear (average stride time, stride time standard deviation, and stride time coefficient of variation) and nonlinear (fractal scaling index, approximate entropy, and sample entropy) measures were calculated for each stride time series. Bland-Altman plots with 95% limits of agreement assessed agreement between systems. Intraclass correlation coefficients assessed reliability across visits. Bland-Altman plots revealed acceptable limits of agreement for all measures. Intraclass correlation coefficients revealed good-to-excellent reliability for both systems, except for fractal scaling index, which was moderate. The smartphone system is a valid method and performs similarly to gold-standard research equipment. These findings suggest the development and implementation of an inexpensive, easy-to-use, and ubiquitous telehealth instrument that may replace traditional laboratory equipment for use in the free-living environment.

The repeatability of stride time variability, regularity, and long-range correlations

BACKGROUND

Detrended fluctuation analysis (DFA) and sample entropy (SE) measure the long-term correlations and regularity of gait patterns, respectively, having previously been used to identify participants at risk of falling, previous history of injury, or patients with motor diseases. Since these measures are more sensitive to gait impairment than linear measures (e.g., the standard deviation [SD] of stride time), they can be potentially used in military medicine to identify soldiers at risk of injury. However, clinometric properties are yet to be established.

RESEARCH QUESTION

What is the repeatability of DFA, SE, and traditional linear measures of stride time variability (SD and coefficient of variation [CV]) under various load and speed constraints?

METHODS

Fourteen Australian Army trainee soldiers (age: 25.6 ± 5.9 y, height: 1.74 ± 0.08 m, body mass: 77.2 ± 15.1 kg, service: 1.5 ± 1.8 y) attended three sessions over two weeks, completing four 12-minute walking trials on an instrumented treadmill in each session. Participants walked with a combination of 0 kg or 23 kg loads at a self-selected or 5.5 km/h speed. Heel contacts from the right foot were identified using treadmill-embedded force plates. From 512 stride time intervals, linear (SD and CV), and non-linear (DFA and SE) measures were obtained. To assess the between-session repeatability, intraclass correlations (ICC 2,1) were employed.

RESULTS AND SIGNIFICANCE

There was poor-to-moderate repeatability for the SD (ICC: 0.357-0.545) and CV (ICC: 0.371-0.529). DFA showed poor-to-moderate repeatability (ICC: 0.013-0.504), while SE had poor repeatability (ICC: 0.133-0.226). Previous studies have shown that differences of > 0.19 in DFA and > 0.66 in SE can differentiate between healthy and pathological gait. These values are greater than this study's reported standard error of measurement, indicating that clinically meaningful changes may still be detectable despite low repeatability.

The Cumulative Impacts of Fatigue during Overload Training Can Be Tracked Using Field-Based Monitoring of Running Stride Interval Correlations

Integrating running gait coordination assessment into athlete monitoring systems could provide unique insight into training tolerance and fatigue-related gait alterations. This study investigated the impact of an overload training intervention and recovery on running gait coordination assessed by field-based self-testing. Fifteen trained distance runners were recruited to perform 1-week of light training (baseline), 2 weeks of heavy training (high intensity, duration, and frequency) designed to overload participants, and a 10-day light taper to allow recovery and adaptation. Field-based running assessments using ankle accelerometry and online short recovery and stress scale (SRSS) surveys were completed daily. Running performance was assessed after each training phase using a maximal effort multi-stage running test-to-exhaustion (RTE). Gait coordination was assessed using detrended fluctuation analysis (DFA) of a stride interval time series. Two participants withdrew during baseline training due to changed personal circumstances. Four participants withdrew during heavy training due to injury. The remaining nine participants completed heavy training and were included in the final analysis. Heavy training reduced DFA values (standardised mean difference (SMD) = -1.44 ± 0.90; p = 0.004), recovery (SMD = -1.83 ± 0.82; p less than 0.001), performance (SMD = -0.36 ± 0.32; p = 0.03), and increased stress (SMD = 1.78 ± 0.94; p = 0.001) compared to baseline. DFA values (p = 0.73), recovery (p = 0.77), and stress (p = 0.73) returned to baseline levels after tapering while performance trended towards improvement from baseline (SMD = 0.28 ± 0.37; p = 0.13). Reduced DFA values were associated with reduced performance (r2 = 0.55) and recovery (r2 = 0.55) and increased stress (r2 = 0.62). Field-based testing of running gait coordination is a promising method of monitoring training tolerance in running athletes during overload training.

Smartphone usage during walking decreases the positive persistency in gait cycle variability

Gait cycle variability during steady walking, described by the stride interval time series, has been used as a gait-stability-related measure. In particular, the positive persistency in the stride intervals with 1/f-like fluctuation and reduction of the persistency are the well-documented metrics that can characterize gait patterns of healthy young adults and elderly including patients with neurological diseases, respectively. Here, we examined effects of a dual task on gait cycle variability in healthy young adults, based on the mean and standard deviation statistics as well as the positive persistency of the stride intervals during steady walking on a treadmill. Specifically, three gait conditions were examined: control condition, non-cognitive task with holding a smartphone in front of the chest using their dominant hand and looking fixedly at a blank screen of the smartphone, and cognitive motor task with holding a smartphone as in the non-cognitive task and playing a puzzle game displayed on the smartphone by one-thumb operation. We showed that only the positive persistency, not the mean and standard deviation statistics, was affected by the cognitive and motor load of smartphone usage in the cognitive condition. More specifically, the positive persistency exhibited in the control and the non-cognitive conditions was significantly reduced in the cognitive condition. Our results suggest that the decrease in the positive persistency during the cognitive task, which might represent the deterioration of healthy gait pattern, is caused endogenously by the cognitive and motor load, not necessarily by the reduction of visual field as often hypothesized.

Effects of metronome walking on long-term attractor divergence and correlation structure of gait: a validation study in older people

This study investigates the effects of metronome walking on gait dynamics in older adults, focusing on long-range correlation structures and long-range attractor divergence (assessed by maximum Lyapunov exponents). Sixty older adults participated in indoor walking tests with and without metronome cues. Gait parameters were recorded using two triaxial accelerometers attached to the lumbar region and to the foot. We analyzed logarithmic divergence of lumbar acceleration using Rosenstein's algorithm and scaling exponents for stride intervals from foot accelerometers using detrended fluctuation analysis (DFA). Results indicated a concomitant reduction in long-term divergence exponents and scaling exponents during metronome walking, while short-term divergence remained largely unchanged. Furthermore, long-term divergence exponents and scaling exponents were significantly correlated. Reliability analysis revealed moderate intrasession consistency for long-term divergence exponents, but poor reliability for scaling exponents. Our results suggest that long-term divergence exponents could effectively replace scaling exponents for unsupervised gait quality assessment in older adults. This approach may improve the assessment of attentional involvement in gait control and enhance fall risk assessment.

Exploring harmonic walking development in children with unilateral cerebral palsy and typically developing toddlers: Insights from walking experience

This longitudinal study investigated the impact of the first independent steps on harmonic gait development in unilateral cerebral palsy (CP) and typically developing (TD) children. We analysed the gait ratio values (GR) by comparing the duration of stride/stance, stance/swing and swing/double support phases. Our investigation focused on identifying a potential trend towards the golden ratio value of 1.618, which has been observed in the locomotion of healthy adults as a characteristic of harmonic walking. Locomotor ability was assessed in both groups at different developmental stages: before and after the emergence of independent walking. Results revealed that an exponential fit was observed only after the first unsupported steps were taken. TD children achieved harmonic walking within a relatively short period (approximately one month) compared to children with CP, who took about seven months to develop harmonic walking. Converging values for stride/stance and stance/swing gait ratios, averaged on the two legs, closely approached the golden ratio in TD children (R2 = 0.9) with no difference in the analysis of the left vs right leg separately. In contrast, children with CP exhibited a trend for stride/stance and stance/swing (R2 = 0.7), with distinct trends observed for the most affected leg which did not reach the golden ratio value for the stride/stance ratio (GR = 1.5), while the least affected leg exceeded it (GR = 1.7). On the contrary, the opposite trend was observed for the stance/swing ratio. These findings indicate an overall harmonic walking in children with CP despite the presence of asymmetry between the two legs. These results underscore the crucial role of the first independent steps in the progressive development of harmonic gait over time.

Gait variability, fractal dynamics, and statistical regularity of treadmill and overground walking recorded with a smartphone

BACKGROUND

The nonlinear variability present during steady-state gait may provide a signature of health and showcase one's walking adaptability. Although treadmills can capture vast amounts of walking data required for estimating variability within a small space, gait patterns may be misrepresented compared to an overground setting. Smartphones may provide a low-cost and user-friendly estimate of gait patterns among a variety of walking settings. However, no study has investigated differences in gait patterns derived from a smartphone between treadmill walking (TW) and overground walking (OW).

RESEARCH QUESTION

This study implemented a smartphone accelerometer to compare differences in temporal gait variability and gait dynamics between TW and OW.

METHODS

Sixteen healthy adults (8F; 24.7 ± 3.8 years) visited the laboratory on three separate days and completed three 8-minute OW and three TW trials, at their preferred speed, during each visit. The inter-stride interval was calculated as the time difference between right heel contact events located within the vertical accelerometery signals recorded from a smartphone while placed in participants front right pant pocket during walking trials. The inter-stride interval series was used to calculate stride time standard deviation (SD) and coefficient of variation (COV), statistical persistence (fractal scaling index), and statistical regularity (sample entropy). Two-way analysis of variance compared walking condition and laboratory visits for each measure.

RESULTS

Compared to TW, OW displayed significantly (p < 0.01) greater stride time SD (0.014 s, 0.020 s), COV (1.26 %, 1.82 %), fractal scaling index (0.70, 0.79) and sample entropy (1.43, 1.63). No differences were found between visits for all measures.

SIGNIFICANCE

Smartphone-based assessment of gait provides the ability to distinguish between OW and TW conditions, similar to previously established methodologies. Furthermore, smartphones may be a low-cost and user-friendly tool to estimate gait patterns outside the laboratory to improve ecological validity, with implications for free-living monitoring of gait among various populations.

Biomechanical Assessment Methods Used in Chronic Stroke: A Scoping Review of Non-Linear Approaches

Non-linear and dynamic systems analysis of human movement has recently become increasingly widespread with the intention of better reflecting how complexity affects the adaptability of motor systems, especially after a stroke. The main objective of this scoping review was to summarize the non-linear measures used in the analysis of kinetic, kinematic, and EMG data of human movement after stroke. PRISMA-ScR guidelines were followed, establishing the eligibility criteria, the population, the concept, and the contextual framework. The examined studies were published between 1 January 2013 and 12 April 2023, in English or Portuguese, and were indexed in the databases selected for this research: PubMed®, Web of Science®, Institute of Electrical and Electronics Engineers®, Science Direct® and Google Scholar®. In total, 14 of the 763 articles met the inclusion criteria. The non-linear measures identified included entropy (n = 11), fractal analysis (n = 1), the short-term local divergence exponent (n = 1), the maximum Floquet multiplier (n = 1), and the Lyapunov exponent (n = 1). These studies focused on different motor tasks: reaching to grasp (n = 2), reaching to point (n = 1), arm tracking (n = 2), elbow flexion (n = 5), elbow extension (n = 1), wrist and finger extension upward (lifting) (n = 1), knee extension (n = 1), and walking (n = 4). When studying the complexity of human movement in chronic post-stroke adults, entropy measures, particularly sample entropy, were preferred. Kinematic assessment was mainly performed using motion capture systems, with a focus on joint angles of the upper limbs.

Stride-to-stride fluctuations and temporal patterns of muscle activity exhibit similar responses during walking to variable visual cues

Incorporating variability within gait retraining approaches has been proposed and shown to lead to positive changes. Specifically, submitting the individuals to walk in synchrony to cues that are temporally organized with a fractal-like patterns, promotes changes at the stride-to-stride fluctuations closer to those typically find in young adults. However, there is still a need to understand the underlying neuromuscular mechanisms associated to such improvement. Thus, this study aimed to investigate whether changes in the temporal structure of the variability in gait patterns are accompanied by changes in muscle activity patterns. Fourteen young individuals walked synchronized to one uncued (UNC) and three cued conditions: isochronous (ISO), fractal (FRC) and random (RND). Inter-stride intervals were determined from an accelerometer placed on the lateral malleoli. Inter-muscle peak intervals were obtained from the electromyographic signal from the gastrocnemius muscle. Fractal scaling, obtained through detrended fluctuation analysis, and coefficient of variation were calculated. Repeated measures ANOVAs were used to identify differences between conditions. Significant main effect was observed for both fractal scaling and coefficient of variation. Both shown no differences between UNC and FRC conditions, while ISO and RND were significantly lower compared to UNC and FRC conditions. In addition, a Pearson's Correlation was used to test the correlation between variables. A strong correlation was found the temporal structure of gait and muscle activity patterns. These findings strengthen the current literature regarding the incorporation of variability within cued approaches. Specifically, it shows that such an approach allows the modification of the neuromuscular processes underlying the stride-to-stride fluctuations.

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.

NONAN GaitPrint: An IMU gait database of healthy young adults

An ongoing thrust of research focused on human gait pertains to identifying individuals based on gait patterns. However, no existing gait database supports modeling efforts to assess gait patterns unique to individuals. Hence, we introduce the Nonlinear Analysis Core (NONAN) GaitPrint database containing whole body kinematics and foot placement during self-paced overground walking on a 200-meter looping indoor track. Noraxon Ultium MotionTM inertial measurement unit (IMU) sensors sampled the motion of 35 healthy young adults (19-35 years old; 18 men and 17 women; mean ± 1 s.d. age: 24.6 ± 2.7 years; height: 1.73 ± 0.78 m; body mass: 72.44 ± 15.04 kg) over 18 4-min trials across two days. Continuous variables include acceleration, velocity, position, and the acceleration, velocity, position, orientation, and rotational velocity of each corresponding body segment, and the angle of each respective joint. The discrete variables include an exhaustive set of gait parameters derived from the spatiotemporal dynamics of foot placement. We technically validate our data using continuous relative phase, Lyapunov exponent, and Hurst exponent-nonlinear metrics quantifying different aspects of healthy human gait.

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

BACKGROUND

In the recent past, wearable devices have been used for gait rehabilitation in patients with Parkinson's disease. The objective of this paper is to analyze the outcome of a wearable hip orthosis whose assistance adapts in real time to the patient's gait kinematics via adaptive oscillators. In particular, this study focuses on a metric characterizing natural gait variability, i.e., the level of long-range autocorrelations (LRA) in series of stride durations.

METHODS

Eight patients with Parkinson's disease (Hoehn and Yahr stages 1[Formula: see text]2.5) performed overground gait training three times per week for four consecutive weeks, assisted by a wearable hip orthosis. Gait was assessed based on performance metrics such as the hip range of motion, speed, stride length and duration, and the level of LRA in inter-stride time series assessed using the Adaptive Fractal Analysis. These metrics were measured before, directly after, and 1 month after training.

RESULTS

After training, patients increased their hip range of motion, their gait speed and stride length, and decreased their stride duration. These improvements were maintained 1 month after training. Regarding long-range autocorrelations, the population's behavior was standardized towards a metric closer to the one of healthy individuals after training, but with no retention after 1 month.

CONCLUSION

This study showed that an overground gait training with adaptive robotic assistance has the potential to improve key gait metrics that are typically affected by Parkinson's disease and that lead to higher prevalence of fall.

TRIAL REGISTRATION

ClinicalTrials.gov Identifer NCT04314973. Registered on 11 April 2020.

Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running

Introduction: The seemingly periodic human gait exhibits stride-to-stride variations as it adapts to the changing task constraints. The optimal movement variability hypothesis (OMVH) states that healthy stride-to-stride variations exhibit "fractality"-a specific temporal structure in consecutive strides that are ordered, stable but also variable, and adaptable. Previous research has primarily focused on a single fractality measure, "monofractality." However, this measure can vary across time; strideto-stride variations can show "multifractality." Greater multifractality in stride-tostride variations would highlight the ability to tune and adjust movements more. Methods: We investigated monofractality and multifractality in a cohort of eight healthy adults during self-paced walking and running trials, both on a treadmill and overground. Footfall data were collected through force-sensitive sensors positioned on their heels and feet. We examined the effects of self-paced walking vs. running and treadmill vs. overground locomotion on the measure of monofractality, α-DFA, in addition to the multifractal spectrum width, W, and the asymmetry in the multifractal spectrum, WAsym, of stride interval time series. Results: While the α-DFA was larger than 0.50 for almost all conditions, α-DFA was higher in running and locomoting overground than walking and locomoting on a treadmill. Similarly, W was greater while locomoting overground than on a treadmill, but an opposite trend indicated that W was greater in walking than running. Larger WAsym values in the negative direction suggest that walking exhibits more variation in the persistence of shorter stride intervals than running. However, the ability to tune and adjust movements does not differ between treadmill and overground, although both exhibit more variation in the persistence of shorter stride intervals. Discussion: Hence, greater heterogeneity in shorter than longer stride intervals contributed to greater multifractality in walking compared to running, indicated by larger negative WAsym values. Our results highlight the need to incorporate multifractal methods to test the predictions of the OMVH.

Can handling a weapon make soldiers more unstable?

Gait stability in soldiers can be affected by task constraints that may lead to injuries. This study determined the effects of weapon handling and speed on gait stability in seventeen soldiers walking on a treadmill with and without a replica weapon at self-selected (SS), 3.5 km·h-1, 5.5 km·h-1, and 6.5 km·h-1 while carrying a 23-kg load. Local dynamic stability was measured using accelerometry at the sacrum (LDESAC) and sternum (LDESTR). No significant weapon and speed interaction were found. A significant effect of speed for the LDESAC, and a significant effect of speed and weapon for the LDESTR were found. Per plane analyses showed that the weapon effect was consistent across all directions for the LDESTR but not for LDESAC. Weapon handling increased trunk but did not affect pelvis stability. Speed decreased stability when walking slower than SS and increased when faster. These findings can inform injury prevention strategies in the military. Practitioner summary: We determined the effects of two constraints in soldier's walking stability, weapon handling and speed, measured at the trunk and sacrum. No constraints interactions were found, however, lower stability when walking slow and greater stability with the weapon at the trunk can inform preventive strategies in military training.

Adaptive walking assistance does not impact long-range stride-to-stride autocorrelations in healthy people

Many studies have demonstrated in the past that the level of long-range autocorrelations in series of stride durations, characterizing natural gait variability, is impacted by external constraints, such as treadmill or metronome, or by pathologies, such as Parkinson's or Huntington's disease. Nevertheless, no one has analyzed the effects on this metric of a gait constrained by a robot-mediated walking assistance, which intrinsically tends to normalize the gait pattern. This paper focuses on the influence of a wearable active pelvis orthosis on the level of long-range autocorrelations in series of stride durations. Ten healthy participants, aged between 55 and 77 yr, performed four overground walking sessions, wearing this orthosis, and with different assistive parameters. This study showed that the adaptive assistance provided by this device has the potential of improving gait metrics that are typically affected by aging, such as the hip range of motion, walking speed, stride length, and stride duration, without impacting natural gait variability, i.e., the level of long-range autocorrelations in series of stride durations. This combination is virtuous toward the design of an assistive device for people with locomotion disorders resulting in deteriorated levels of long-range autocorrelations, such as patients with Parkinson's disease.NEW & NOTEWORTHY This study is the first that investigates the effects of a wearable active pelvis orthosis using an oscillator-based adaptive assistance on the level of long-range autocorrelations in series of stride durations during overground walking. It is also the first to compare the effects of different assistance settings on spatiotemporal gait metrics.

Indoor running temporal variability for different running speeds, treadmill inclinations, and three different estimation strategies

Inertial measurement units (IMU) constitute a light and cost-effective alternative to gold-standard measurement systems in the assessment of running temporal variables. IMU data collected on 20 runners running at different speeds (80, 90, 100, 110 and 120% of preferred running speed) and treadmill inclination (±2, ±5, and ±8%) were used here to predict the following temporal variables: stride frequency, duty factor, and two indices of running variability such as the detrended fluctuation analysis alpha (DFA-α) and the Higuchi's D (HG-D). Three different estimation methodologies were compared: 1) a gold-standard optoelectronic device (which provided the reference values), 2) IMU placed on the runner's feet, 3) a single IMU on the runner's thorax used in conjunction with a machine learning algorithm with a short 2-second or a long 120-second window as input. A two-way ANOVA was used to test the presence of significant (p<0.05) differences due to the running condition or to the estimation methodology. The findings of this study suggest that using both IMU configurations for estimating stride frequency can be effective and comparable to the gold-standard. Additionally, the results indicate that the use of a single IMU on the thorax with a machine learning algorithm can lead to more accurate estimates of duty factor than the strategy of the IMU on the feet. However, caution should be exercised when using these techniques to measure running variability indices. Estimating DFA-α from a short 2-second time window was possible only in level running but not in downhill running and it could not accurately estimate HG-D across all running conditions. By taking a long 120-second window a machine learning algorithm could improve the accuracy in the estimation of DFA-α in all running conditions. By taking these factors into account, researchers and practitioners can make informed decisions about the use of IMU technology in measuring running biomechanics.

Running gait produces long range correlations: A systematic review

BACKGROUND

Walking and running are common forms of locomotion, both of which exhibit variability over many gait cycles. Many studies have investigated the patterns generated from that ebb and flow, and a large proportion suggests human gait exhibits Long Range Correlations (LRCs). LRCs refer to the observation that healthy gait characteristic, like stride times, are positively correlated to themselves over time. Literature on LRCs in walking gait is well known but less attention has been given to LRCs in running gait.

RESEARCH QUESTION

What is the state of the art concerning LRCs in running gait?

METHODS

We conducted a systematic review to identify the typical LRC patterns present in human running gait, in addition to disease, injury, and running surface effects on LRCs. Inclusion criteria were human subjects, running related experiments, computed LRCs, and experimental design. Exclusion criteria were studies on animals, non-humans, walking only, non-running, non-LRC analysis, and non-experiments.

RESULTS

The initial search returned 536 articles. After review and deliberation, our review included 26 articles. Almost every article produced strong evidence for LRCs apparent in running gait and in all running surfaces. Additionally, LRCs tended to decrease due to fatigue, past injury, increased load carriage and seem to be lowest at preferred running speed on a treadmill. No studies investigated disease effects on LRCs in running gait.

SIGNIFICANCE

LRCs seem to increase with deviations away from preferred running speed. Previously injured runners produced decreased LRCs compared to non-injured runners. LRCs also tended to decrease due to an increase in fatigue rate, which has been associated with increased injury rate. Lastly, there is a need for research on the typical LRCs in an overground environment, for which the typical LRCs found in a treadmill environment may or may not transfer.

Evaluation of a smartphone accelerometer system for measuring nonlinear dynamics during treadmill walking: Concurrent validity and test-retest reliability

The accelerometers embedded within smartphones may be a promising tool to capture gait patterns outside the laboratory and for extended periods of time. The current study evaluated the agreement and reliability of gait measures derived from a smartphone accelerometer system, compared to reference motion capture and footswitch systems during treadmill walking. Seventeen healthy young adults visited the laboratory on three separate days and completed three 8-minute treadmill walking trials, during each visit, at their preferred walking speed. The inter-stride interval series was calculated as the time difference between consecutive right heel contacts, located within the signals of the smartphone accelerometer, motion capture, and footswitch systems. The inter-stride interval series was used to estimate common linear gait measures and nonlinear measures, including fractal scaling index, approximate entropy, and sample entropy. Bland Altman plots with 95% limits of agreement and intraclass correlation coefficients assessed agreement and reliability, respectively. The smartphone system was found to be within the acceptable limits of agreement when compared to either reference system. The intraclass correlation coefficients values revealed moderate-to-excellent reliability for the smartphone system, with greater reliability found for linear compared to nonlinear measures and were similar to both reference systems, except for the fractal scaling index. These findings suggest the smartphone accelerometer system is a valid and reliable method for estimating linear and nonlinear gait measures during treadmill walking.

Optimal sensor location and direction to accurately classify people with early-stage multiple sclerosis using gait stability

BACKGROUND

The local divergence exponent (LDE) has been used to assess gait stability in people with multiple sclerosis (pwMS). Although previous studies have consistently found that stability is lower in pwMS, inconsistent methodologies have been used to assess patients with a broad range of disability levels.

QUESTIONS

What sensor location and movement direction(s) are better able to classify pwMS at early stages of the disease?

METHODS

49 pwMS with EDSS ≤ 2.5 and 24 healthy controls walked overground for 5 min while 3D acceleration data was obtained from sensors placed at the sternum (STR) and lumbar (LUM) areas. Unidirectional (vertical [VT], mediolateral [ML], and anteroposterior [AP]) and 3-dimensional (3D) LDEs were calculated using STR and LUM data over 150 strides. ROC analyses were performed to assess classification models using single and combined LDEs, with and without velocity per lap (VEL_LAP) as a covariate.

RESULTS

Four models performed equally well by using combinations of VEL_LAP, LUM_3D, LUM_VT, LUM_ML, LUM_AP, STR_ML, and STR_AP (AUC = 0.879). The best model using single sensor LDEs included VEL_LAP, STR_3D, STR_ML, and STR_AP (AUC = 0.878), whereas using VEL_LAP + STR_VT (AUC = 0.869) or VEL_LAP + STR_3D (AUC=0.858) performed best using a single LDE.

SIGNIFICANCE

The LDE offers an alternative to currently insensitive tests of gait impairment in pwMS at early stages, when deterioration is not clinically evident. For clinical purposes, the implementation of this measure can be simplified using a single sensor at the sternum and a single LDE measure, but speed should be considered. Longitudinal studies to determine the predictive power and responsiveness of the LDE to MS progression are still needed.

Better than DFA? A Bayesian Method for Estimating the Hurst Exponent in Behavioral Sciences

Detrended Fluctuation Analysis (DFA) is the most popular fractal analytical technique used to evaluate the strength of long-range correlations in empirical time series in terms of the Hurst exponent, H. Specifically, DFA quantifies the linear regression slope in log-log coordinates representing the relationship between the time series' variability and the number of timescales over which this variability is computed. We compared the performance of two methods of fractal analysis-the current gold standard, DFA, and a Bayesian method that is not currently well-known in behavioral sciences: the Hurst-Kolmogorov (HK) method-in estimating the Hurst exponent of synthetic and empirical time series. Simulations demonstrate that the HK method consistently outperforms DFA in three important ways. The HK method: (i) accurately assesses long-range correlations when the measurement time series is short, (ii) shows minimal dispersion about the central tendency, and (iii) yields a point estimate that does not depend on the length of the measurement time series or its underlying Hurst exponent. Comparing the two methods using empirical time series from multiple settings further supports these findings. We conclude that applying DFA to synthetic time series and empirical time series during brief trials is unreliable and encourage the systematic application of the HK method to assess the Hurst exponent of empirical time series in behavioral sciences.

Stride-to-stride time intervals are independently affected by the temporal pattern and probability distribution of visual cues

The temporal structure of the variability of the stride-to-stride time intervals during paced walking is affected by the underlying autocorrelation function (ACF) of the pacing signal. This effect could be accounted for by differences in the underlying probability distribution function (PDF) of the pacing signal. We investigated the isolated and combined effect of the ACF and PDF of the pacing signals on the temporal structure of the stride-to-stride time intervals during visually guided paced overground walking. Ten young, healthy participants completed four walking trials while synchronizing their footstep to a visual pacing signal with a temporal pattern of either pink or white noise (different ACF) and either a Gaussian or normal probability distribution (different PDF). The scaling exponent from the Detrended Fluctuation Analysis was used to quantify the temporal structure of the stride-to-stride time intervals. The ACF and PDF of the pacing signals had independent effects on the scaling exponent of the stride-to-stride time intervals. The scaling exponent was higher during the pink noise pacing trials compared to the white noise pacing trials and higher during the trials with the Gaussian probability distribution compared to the uniform distribution. The results suggest that the sensorimotor system in healthy young individuals has an affinity towards external cues with a pink noise pattern and a Gaussian probability distribution during paced walking.

Ankle strategy assistance to improve gait stability using controllers based on in-shoe center of pressure in 2 degree-of-freedom powered ankle-foot orthoses: a clinical study

Background

Although the ankle strategy is important for achieving frontal plane stability during one-leg stance, previously developed powered ankle–foot orthoses (PAFOs) did not involve ankle strategies because of hardware limitations. Weakness of movement in frontal plane is a factor that deteriorates gait stability and increases fall risk so it should not be overlooked in rehabilitation. Therefore, we used PAFO with subtalar joint for frontal plane movement and tried to confirm that the existence of it is important in balancing through clinical experiments.

Methods

We developed a proportional CoP controller to assist ankle strategy or stabilizing moment and enhance eversion to compensate for the tilting moment with 2 dof PAFO. It was true experimental study, and we recruited seven healthy subjects (30 ± 4 years) who did not experience any gait abnormality participated in walking experiments for evaluating the immediate effect of subtalar joint of PAFO on their gait stability. They walked on the treadmill with several cases of controllers for data acquisitions. Indices of gait stability and electromyography for muscle activity were measured and Wilcoxon signed-rank tests were used to identify meaningful changes.

Results

We found that subjects were most stable during walking (in terms of largest Lyapunov exponents, p < 0.008) with the assistance of the PAFO when their electromyographic activity was the most reduced (p < 0.008), although postural sway increased when a proportional CoP controller was used to assist the ankle strategy (p < 0.008). Other indices of gait stability, kinematic variability, showed no difference between the powered and unpowered conditions (p > 0.008). The results of the correlation analysis indicate that the actuator of the PAFO enhanced eversion and preserved the location of the CoP in the medial direction so that gait stability was not negatively affected or improved.

Conclusions

We verified that the developed 2 dof PAFO assists the ankle strategy by compensating for the tilting moment with proportional CoP controller and that wearer can walk in a stable state when the orthosis provides power for reducing muscle activity. This result is meaningful because an ankle strategy should be considered in the development of PAFOs for enhancing or even rehabilitating proprioception.

Trial registration 7001988-202003-HR-833-03

Nonlinear Dynamic Measures of Walking in Healthy Older Adults: A Systematic Scoping Review

BACKGROUND

Maintaining a healthy gait into old age is key to preserving the quality of life and reducing the risk of falling. Nonlinear dynamic analyses (NDAs) are a promising method of identifying characteristics of people who are at risk of falling based on their movement patterns. However, there is a range of NDA measures reported in the literature. The aim of this review was to summarise the variety, characteristics and range of the nonlinear dynamic measurements used to distinguish the gait kinematics of healthy older adults and older adults at risk of falling.

METHODS

Medline Ovid and Web of Science databases were searched. Forty-six papers were included for full-text review. Data extracted included participant and study design characteristics, fall risk assessment tools, analytical protocols and key results.

RESULTS

Among all nonlinear dynamic measures, Lyapunov Exponent (LyE) was most common, followed by entropy and then Fouquet Multipliers (FMs) measures. LyE and Multiscale Entropy (MSE) measures distinguished between older and younger adults and fall-prone versus non-fall-prone older adults. FMs were a less sensitive measure for studying changes in older adults' gait. Methodology and data analysis procedures for estimating nonlinear dynamic measures differed greatly between studies and are a potential source of variability in cross-study comparisons and in generating reference values.

CONCLUSION

Future studies should develop a standard procedure to apply and estimate LyE and entropy to quantify gait characteristics. This will enable the development of reference values in estimating the risk of falling.

Comparing adaptive fractal and detrended fluctuation analyses of stride time variability: Tests of equivalence

BACKGROUND

Fractal analyses quantify self-similarities in stride-to-stride fluctuations over different time scales. Fractal exponents can be measured with adaptive fractal analysis (AFA) or detrended fluctuation analysis (DFA), though measurements obtained with the algorithms have not been directly compared.

RESEARCH QUESTION

Are stride time fractal exponents measured with AFA and DFA algorithms equivalent?

METHODS

Data from 50 participants with Parkinson's Disease (n = 15), age-similar healthy adults (n = 15) and healthy young adults (n = 20) were analyzed in this cross-sectional, observational study. Participants completed 6-min walks at self-selected speeds overground on a straight walkway and on a treadmill. Stride times were measured with inertial measurement units. Fractal exponents in stride time data were processed using AFA and DFA algorithms and compared with two one-sided tests of equivalence. Mixed ANOVAs were used to compare exponents between groups and conditions.

RESULTS

Fractal exponents computed with AFA and DFA were equivalent neither in the overground (0.796 & 0.830, respectively, p = .587) nor treadmill conditions (0.806 & 0.882, respectively, p = .122). Fractal exponents measured with DFA were higher than when measured with AFA. Standard errors were 22% lower when measured with AFA. Additionally, a group × condition interaction was statistically significant when fractal exponents were processed with the AFA algorithm (F(2,47) = 11.696, p < .001), whereas the group × condition interaction was not statistically significant when DFA exponents were compared (F(2, 47) = 2.144, p = .129).

SIGNIFICANCE

AFA and DFA do not produce equivalent estimates of the fractal exponent α in stride time dynamics. Estimates of the fractal exponent α obtained with AFA or DFA algorithms therefore should not be used interchangeably. Standard errors were lower when derived with AFA. Fractal exponents calculated with AFA may be more sensitive to conditions that influence stride time fractal dynamics than are measures calculated with DFA.

Self-paced and fixed speed treadmill walking yield similar energetics and biomechanics across different speeds

BACKGROUND

Treadmill assessments are often performed at a fixed speed. Feedback-controlled algorithms allow users to adjust the treadmill speed, hereby potentially better resembling natural self-paced locomotion. However, it is currently unknown whether the energetics and biomechanics of self-paced differ from fixed-paced treadmill walking. Such information is important for clinicians and researchers using self-paced locomotion for assessing gait.

RESEARCH QUESTION

To investigate whether energy cost and biomechanics are different between self-paced and matched-speed fixed-paced locomotion.

METHODS

18 healthy participants (9 males/9 females, mean ± standard deviation age 24.8 ± 3.3 years, height 1.71 ± 0.81 m, weight 65.9 ± 8.1 kg) walked at four different self-paced speeds (comfortable, slow, very slow, fast) in randomized order on an instrumented treadmill while three-dimensional motion capture and gas exchange were measured continuously. The average walking speed during the last 2 min of the self-paced trials was used to match the speed in fixed-paced conditions. Linear mixed models were used to assess differences in mean values and within-subject variations between conditions (self-paced and fixed-paced) and speeds. Statistical Parametric Mapping was used to assess differences in kinematics of the lower limb between conditions.

RESULTS

Although self-paced walking consistently resulted in a 4-6% higher net cost of walking, there were no significant differences in the net cost of walking between conditions. Further, there were also no differences of clinical relevance in spatiotemporal outcomes and sagittal-plane lower-limb kinematics between the self-paced and fixed-paced conditions. Within-trial variability was also not significantly different between conditions.

SIGNIFICANCE

Self-paced and fixed-paced treadmill walking yield similar energetics and kinematics in healthy young individuals when mean values or linear measures of variation are of interest.

Is treadmill walking biomechanically comparable to overground walking? A systematic review

BACKGROUND

The equivalency of treadmill and overground walking has been investigated in a large number of studies. However, no systematic review has been performed on this topic.

RESEARCH QUESTION

The aim of this study was to compare the biomechanical, electromyographical and energy consumption outcomes of motorized treadmill and overground walking.

METHODS

Five databases, ScienceDirect, SpringerLink, Web of Science, PubMed, and Scopus, were searched until January 13, 2021. Studies written in English comparing lower limb biomechanics, electromyography and energy consumption during treadmill and overground walking in healthy young adults (20-40 years) were included.

RESULTS

Twenty-two studies (n = 409 participants) were included and evaluated via the Cochrane Collaboration's tool. These 22 studies showed that some kinematic (reduced pelvic ROM, maximum hip flexion angle for females, maximum knee flexion angle for males and cautious gait pattern), kinetic (sagittal plane joint moments: dorsiflexor moments, knee extensor moments and hip extensor moments and sagittal plane joint powers at the knee and hip joints, peak backwards, lateral and medial COP velocities and propulsive forces during late stance) and electromyographic (lower limbs muscles activities) outcome measures were significantly different for motorized treadmill and overground walking.

SIGNIFICANCE

Spatiotemporal, kinematic, kinetic, electromyographic and energy consumption outcome measures were largely comparable for motorized treadmill and overground walking. However, the differences in kinematic, kinetic and electromyographic parameters should be taken into consideration by clinicians, trainers, and researchers when working on new protocols related to patient rehabilitation, fitness rooms or research as to be as close as possible to the outcome measures of overground walking. The protocol registration number is CRD42021236335 (PROSPERO International Prospective Register of Systematic Reviews).

Self-paced treadmills do not allow for valid observation of linear and nonlinear gait variability outcomes in patients with Parkinson's disease

BACKGROUND

Due to the imposed constant belt speed, motorized treadmills are known to affect linear and nonlinear gait variability outcomes. This is particularly true of patients with Parkinson's Disease where the treadmill can act as an external pacemaker. Self-paced treadmills update the belt speed in response to the subject's walking speed and might, therefore, be a useful tool for measurement of gait variability in this patient population. This study aimed to compare gait variability during walking at self-paced and constant treadmill speeds with overground walking in individuals with PD and individuals with unimpaired gait.

METHODS

Thirteen patients with Parkinson's Disease and thirteen healthy controls walked under three conditions: overground, on a treadmill at a constant speed, and using three self-paced treadmill modes. Gait variability was assessed with coefficient of variation (CV), sample entropy (SampEn), and detrended fluctuation analysis (DFA) of stride time and length. Systematic and random error between the conditions was quantified.

RESULTS

For individuals with PD, error in variability measurement was less during self-paced modes compared with constant treadmill speed for stride time but not for stride length. However, there was substantial error for stride time and length variability for all treadmill conditions. For healthy controls the error in measurement associated with treadmill walking was substantially less.

SIGNIFICANCE

The large systematic and random errors between overground and treadmill walking prohibit meaningful gait variability observations in patients with Parkinson's Disease using self-paced or constant-speed treadmills.

Differences in Gait Stability and Acceleration Characteristics Between Healthy Young and Older Females

Our aim was to evaluate differences in gait acceleration intensity, variability, and stability of feet and trunk between older females (OF) and young females (YF) using inertial sensors. Twenty OF (mean age 68.4, SD 4.1 years) and 18 YF (mean age 22.3, SD 1.7 years) were asked to walk straight for 100 meters at their preferred speed, while wearing inertial sensors on their heels and lower back. We calculated spatiotemporal measures, foot and trunk acceleration characteristics, their variability, and trunk stability using the local divergence exponent (LDE). Two-way ANOVA (such as the factors foot and age), Student's t-test and Mann–Whitney U test were used to compare statistical differences of measures between groups. Cohen's d effects were calculated for each variable. Foot maximum vertical (VT) acceleration and amplitude, trunk-foot VT acceleration attenuation, and their variability were significantly smaller in OF than in YF. In contrast, trunk mediolateral (ML) acceleration amplitude, maximum VT acceleration, amplitude, and their variability were significantly larger in OF than in YF. Moreover, OF showed lower stability (i.e., higher LDE values) in ML acceleration, ML, and VT angular velocity of the trunk. Even though we measured healthy OF, these participants showed lower VT foot accelerations with higher VT trunk acceleration, lower trunk-foot VT acceleration attenuation, less gait stability, and more variability of the trunk, and hence, were more likely to fall. These findings suggest that instrumented gait measurements may help for early detection of changes or impairments in gait performance, even before this can be observed by clinical eye or gait speed.

Revisiting the lumbosacral orthosis from the perspective of dynamical systems theory: a preliminary randomized clinical trial on patients with chronic low back pain

BACKGROUND

The prevalent method for investigating the effect of therapeutic interventions on walking in the individuals with chronic low back pain (CLBP) is component-level approach in which all measurements focus on the spine component alone. However, this approach cannot disclose information about the overall function of the movement system such as complex walking patterns, which, in turn, reveal the underlying movement control.

OBJECTIVES

To compare the effect of 3-week wearing of lumbosacral orthosis (LSO) along with routine physical therapy with routine physical therapy alone on walking complexity in the individuals with nonspecific CLBP on the basis of the systems approach.

STUDY DESIGN

Preliminary randomized clinical trial.

METHODS

Twenty-four subjects were randomly allocated to two groups. The control group received the routine physical therapy for 3 weeks. The intervention group received the same program plus an LSO. Nonlinear analysis was used to quantify walking complexity, as behavior of the entire movement system, before and after the intervention and at 1-month follow-up.

RESULTS

An average of 496 strides during ten minutes of walking was used for analysis. There was no significant difference (p > 0.05) in degree of walking complexity between two groups during all evaluation periods.

CONCLUSIONS

The administered orthotic intervention did not alter walking complexity. This suggests that therapeutic goal of current LSOs, which is not based on the systems approach, cannot recover the emergent behavior of the movement system. This may be a potential source of controversies.

CLINICAL RELEVANCE

To achieve an effective treatment, orthotists should focus on the individuals themselves, not only on their CLBP symptoms. Although the component-level approach aims to decrease the symptoms, the systems approach focuses on the whole context that fosters LBP symptoms.

Intra-subject sample size effects in plantar pressure analyses

Background

Recent work using large datasets (>500 records per subject) has demonstrated seemingly high levels of step-to-step variation in peak plantar pressure within human individuals during walking. One intuitive consequence of this variation is that smaller sample sizes (e.g., 10 steps per subject) may be quantitatively and qualitatively inaccurate and fail to capture the variance in plantar pressure of individuals seen in larger data sets. However, this remains quantitatively unexplored reflecting a lack of detailed investigation of intra-subject sample size effects in plantar pressure analysis.

Methods

Here we explore the sensitivity of various plantar pressure metrics to intra-subject sample size (number of steps per subject) using a random subsampling analysis. We randomly and incrementally subsample large data sets (>500 steps per subject) to compare variability in three metric types at sample sizes of 5–400 records: (1) overall whole-record mean and maximum pressure; (2) single-pixel values from five locations across the foot; and (3) the sum of pixel-level variability (measured by mean square error, MSE) from the whole plantar surface.

Results

Our results indicate that the central tendency of whole-record mean and maximum pressure within and across subjects show only minor sensitivity to sample size >200 steps. However, <200 steps, and particularly <50 steps, the range of overall mean and maximum pressure values yielded by our subsampling analysis increased considerably resulting in potential qualitative error in analyses of pressure changes with speed within-subjects and in comparisons of relative pressure magnitudes across subjects at a given speed. Our analysis revealed considerable variability in the absolute and relative response of the single pixel centroids of five regions to random subsampling. As the number of steps analysed decreased, the absolute value ranges were highest in the areas of highest pressure (medial forefoot and hallux), while the largest relative changes were seen in areas of lower pressure (the midfoot). Our pixel-level measure of variability by MSE across the whole-foot was highly sensitive to our manipulation of sample size, such that the range in MSE was exponentially larger in smaller subsamples. Random subsampling showed that the range in pixel-level MSE only came within 5% of the overall sample size in subsamples of >400 steps. The range in pixel-level MSE at low subsamples (<50) was 25–75% higher than that of the full datasets of >500 pressure records per subject. Overall, therefore, we demonstrate a high probability that the very small sample sizes (n < 20 records), which are routinely used in human and animal studies, capture a relatively low proportion of variance evident in larger plantar pressure data set, and thus may not accurately reflect the true population mean.

Aging Liver: Can Exercise be a Better Way to Delay the Process than Nutritional and Pharmacological Intervention? Focus on Lipid Metabolism

BACKGROUND & AIMS

Nowadays, the world is facing a common problem that the population aging process is accelerating. How to delay metabolic disorders in middle-aged and elderly people, has become a hot scientific and social issue worthy of attention. The liver plays an important role in lipid metabolism, and abnormal lipid metabolism may lead to liver diseases. Exercise is an easily controlled and implemented intervention, which has attracted extensive attention in improving the health of liver lipid metabolism in the elderly. This article reviewed the body aging process, changes of lipid metabolism in the aging liver, and the mechanism and effects of different interventions on lipid metabolism in the aging liver, especially focusing on exercise intervention.

METHODS

A literature search was performed using PubMed-NCBI, EBSCO Host and Web of Science, and also a report from WHO. In total, 143 studies were included from 1986 to 15 February 2020.

CONCLUSION

Nutritional and pharmacological interventions can improve liver disorders, and nutritional interventions are less risky relatively. Exercise intervention can prevent and improve age-related liver disease, especially the best high-intensity interval training intensity and duration is expected to be one of the research directions in the future.

Acceleration Gait Measures as Proxies for Motor Skill of Walking: A Narrative Review

In adults 65 years or older, falls or other neuromotor dysfunctions are often framed as walking-related declines in motor skill; the frequent occurrence of such decline in walking-related motor skill motivates the need for an improved understanding of the motor skill of walking. Simple gait measurements, such as speed, do not provide adequate information about the quality of the body motion's translation during walking. Gait measures from accelerometers can enrich measurements of walking and motor performance. This review article will categorize the aspects of the motor skill of walking and review how trunk-acceleration gait measures during walking can be mapped to motor skill aspects, satisfying a clinical need to understand how well accelerometer measures assess gait. We will clarify how to leverage more complicated acceleration measures to make accurate motor skill decline predictions, thus furthering fall research in older adults.

A non-linear analysis of running in the heavy and severe intensity domains

PURPOSE

Altered movement complexity, indicative of system dysfunction, has been demonstrated with increased running velocity and neuromuscular fatigue. The critical velocity (CV) denotes a metabolic and neuromuscular fatigue threshold. It remains unclear whether changes to complexity during running are coupled with the exercise intensity domain in which it is performed. The purpose of this study was to examine whether movement variability and complexity differ exclusively above the CV intensity during running.

METHODS

Ten endurance-trained participants ran at 95%, 100%, 105% and 115% CV for 20 min or to task failure, whichever occurred first. Movement at the hip, knee, and ankle were sampled throughout using 3D motion analysis. Complexity of kinematics in the first and last 30 s were quantified using sample entropy (SampEn) and detrended fluctuation analysis (DFA-α). Variability was determined using standard deviation (SD).

RESULTS

SampEn decreased during all trials in knee flexion/extension and it increased in hip internal/external rotation, whilst DFA-α increased in knee internal/external rotation. SD of ankle plantar/dorsiflexion and inversion/eversion, knee internal/external rotation, and hip flexion/extension and abduction/adduction increased during trials. Hip flexion/extension SampEn values were lowest below CV. DFA-α was lower at higher velocities compared to velocities below CV in ankle plantar/dorsiflexion, hip flexion/extension, hip adduction/abduction, hip internal/external rotation. In hip flexion/extension SD was highest at 115% CV.

CONCLUSIONS

Changes to kinematic complexity over time are consistent between heavy and severe intensity domains. The findings suggest running above CV results in increased movement complexity and variability, particularly at the hip, during treadmill running.

Influence of Autocorrelated Rhythmic Auditory Stimulations on Parkinson's Disease Gait Variability: Comparison With Other Auditory Rhythm Variabilities and Perspectives

Parkinson's Disease patients suffer from gait impairments such as reduced gait speed, shortened step length, and deterioration of the temporal organization of stride duration variability (i.e., breakdown in Long-Range Autocorrelations). The aim of this study was to compare the effects on Parkinson's Disease patients' gait of three Rhythmic Auditory Stimulations (RAS), each structured with a different rhythm variability (isochronous, random, and autocorrelated). Nine Parkinson's Disease patients performed four walking conditions of 10-15 min each: Control Condition (CC), Isochronous RAS (IRAS), Random RAS (RRAS), and Autocorrelated RAS (ARAS). Accelerometers were used to assess gait speed, cadence, step length, temporal organization (i.e., Long-Range Autocorrelations computation), and magnitude (i.e., coefficient of variation) of stride duration variability on 512 gait cycles. Long-Range Autocorrelations were assessed using the evenly spaced averaged Detrended Fluctuation Analysis (α-DFA exponent). Spatiotemporal gait parameters and coefficient of variation were not modified by the RAS. Long-Range Autocorrelations were present in all patients during CC and ARAS although all RAS conditions altered them. The α-DFA exponents were significantly lower during IRAS and RRAS than during CC, exhibiting anti-correlations during IRAS in seven patients. α-DFA during ARAS was the closest to the α-DFA during CC and within normative data of healthy subjects. In conclusion, Isochronous RAS modify patients' Long-Range Autocorrelations and the use of Autocorrelated RAS allows to maintain an acceptable level of Long-Range Autocorrelations for Parkinson's Disease patients' gait.

Irregular Metronomes as Assistive Devices to Promote Healthy Gait Patterns

Older adults and people suffering from neurodegenerative disease often experience difficulty controlling gait during locomotion, ultimately increasing their risk of falling. To combat these effects, researchers and clinicians have used metronomes as assistive devices to improve movement timing in hopes of reducing their risk of falling. Historically, researchers in this area have relied on metronomes with isochronous interbeat intervals, which may be problematic because normal healthy gait varies considerably from one step to the next. More recently, researchers have advocated the use of irregular metronomes embedded with statistical properties found in healthy populations. In this paper, we explore the effect of both regular and irregular metronomes on many statistical properties of interstride intervals. Furthermore, we investigate how these properties react to mechanical perturbation in the form of a halted treadmill belt while walking. Our results demonstrate that metronomes that are either isochronous or random break down the inherent structure of healthy gait. Metronomes with statistical properties similar to healthy gait seem to preserve those properties, despite a strong mechanical perturbation. We discuss the future development of this work in the context of networked augmented reality metronome devices.

Test-Retest Reliability and the Effects of Walking Speed on Stride Time Variability During Continuous, Overground Walking in Healthy Young Adults

Studies have investigated the reliability and effect of walking speed on stride time variability during walking trials performed on a treadmill. The objective of this study was to investigate the reliability of stride time variability and the effect of walking speed on stride time variability, during continuous, overground walking in healthy young adults. Participants completed: (1) 2 walking trials at their preferred walking speed on 1 day and another trial 2 to 4 days later and (2) 1 trial at their preferred walking speed, 1 trial approximately 20% to 25% faster than their preferred walking speed, and 1 trial approximately 20% to 25% slower than their preferred walking speed on a separate day. Data from a waist-mounted accelerometer were used to determine the consecutive stride times for each trial. The reliability of stride time variability outcomes was generally poor (intraclass correlations: .167-.487). Although some significant differences in stride time variability were found between the preferred walking speed, fast, and slow trials, individual between-trial differences were generally below the estimated minimum difference considered to be a real difference. The development of a protocol to improve the reliability of stride time variability outcomes during continuous, overground walking would be beneficial to improve their application in research and clinical settings.

Virtual Reality Gait Training to Promote Balance and Gait Among Older People: A Randomized Clinical Trial

Falls are the leading cause of injury and injury-related death in the elderly. This study evaluated the effect of virtual reality gait training (VRGT) with non-motorized treadmill on balance and gait ability of elderly individuals who had experienced a fall. Fifty-six elderly individuals living in local communities participated in this study. Subjects who met the selection criteria were randomly divided into a VRGT group (n = 28) and a control group (n = 28). The VRGT group received VRGT with non-motorized treadmill for 50 min a day for 4 weeks and 5 days a week. The control group received non-motorized treadmill gait training without virtual reality for the same amount of time as the VRGT group. Before and after the training, the one-leg-standing test, Berg Balance Scale, Functional Reach test, and Timed Up and Go test were used to assess balance ability, and the gait analyzer system was used to evaluate the improvement in gait spatiotemporal parameters. In the VRGT group, the balance ability variable showed a significant decrease in the one-leg-standing test and a significant improvement in the Timed Up and Go test. With respect to spatiotemporal gait parameters, velocity and step width decreased significantly in the VRGT group (p < 0.05), and stride length and step length were significantly improved in the VRGT group (p < 0.05). VRGT with non-motorized treadmill has been shown to improve balance and gait ability in the elderly. This study is expected to provide basic data on exercise programs for the elderly to prevent falls.

[Trunk kinematics during walking in stroke patients: A systematic review]

The trunk and pelvis are affected after stroke, predisposing individuals to falls and dependency. The aim of this review was to describe the lineal and angular kinematics of the trunk and pelvis in patients with post-stroke sequels during walking. We included studies published up to June 2018 using a 2-3 D motion capture system during walking. We searched the Cochrane, Medline, PEDRo, Lilacs, Scielo, EBSCO, ClinicalKey and Elsevier databases. Twelve articles were selected. Linear kinematics showed greater lateral displacement and acceleration in all axes. Angular kinematics in the swing phase of the paretic segment showed the pelvis in posterior rotation, with elevation and lower velocity and the trunk in anterior flexion, with lateral inclination and ipsilateral rotation. The studies showed wide variability, making it impossible to establish of a common effect. However, the results allow description of the movement of the trunk and pelvis.

Mechanisms used to increase propulsive forces on a treadmill in older adults

Older adults typically demonstrate reductions in overground walking speeds and propulsive forces compared to young adults. These reductions in walking speeds are risk factors for negative health outcomes. Therefore, this study aimed to determine the effect of an adaptive speed treadmill controller on walking speed and propulsive forces in older adults, including the mechanisms and strategies underlying any change in propulsive force between conditions. Seventeen participants completed two treadmill conditions, one with a fixed comfortable walking speed and one with an adaptive speed controller. The adaptive speed treadmill controller utilized a set of inertial-force, gait parameters, and position-based controllers that respond to an instantaneous anterior inertial force. A biomechanical-based model previously developed for individuals post-stroke was implemented for older adults to determine the primary gait parameters that contributed to the change in propulsive forces when increasing speed. Participants walked at faster average speeds during the adaptive speed controller (1.20 m/s) compared to the fixed speed controller conditions (0.98 m/s); however, these speeds were not as fast as their overground speed (1.44 m/s). Although average trailing limb angle (TLA) (p < 0.001) and ankle moment (p = 0.020) increased when speed also increased between treadmill conditions, increasing TLA contributed more to the increased propulsive forces seen during faster treadmill speeds. Our findings show that older adults chose faster walking speeds and increased propulsive force when walking on an adaptive speed treadmill compared to a fixed speed treadmill, suggesting that an adaptive speed treadmill controller has the potential to be a beneficial alternative to current exercise interventions for older adults.

Immersive Virtual Reality to Restore Natural Long-Range Autocorrelations in Parkinson's Disease Patients' Gait During Treadmill Walking

Effects of treadmill walking on Parkinson’s disease (PD) patients’ spatiotemporal gait parameters and stride duration variability, in terms of magnitude [coefficient of variation (CV)] and temporal organization [long range autocorrelations (LRA)], are known. Conversely, effects on PD gait of adding an optic flow during treadmill walking using a virtual reality headset, to get closer to an ecological walk, is unknown. This pilot study aimed to compare PD gait during three conditions: Overground Walking (OW), Treadmill Walking (TW), and immersive Virtual Reality on Treadmill Walking (iVRTW). Ten PD patients completed the three conditions at a comfortable speed. iVRTW consisted in walking at the same speed as TW while wearing a virtual reality headset reproducing an optic flow. Gait parameters assessed were: speed, step length, cadence, magnitude (CV) and temporal organization (evenly spaced averaged Detrended Fluctuation Analysis, α exponent) of stride duration variability. Motion sickness was assessed after TW and iVRTW using the Simulator Sickness Questionnaire (SSQ). Step length was greater (p = 0.008) and cadence lower (p = 0.009) during iVRTW compared to TW while CV was similar (p = 0.177). α exponent was similar during OW (0.77 ± 0.07) and iVRTW (0.76 ± 0.09) (p = 0.553). During TW, α exponent (0.85 ± 0.07) was higher than during OW (p = 0.039) and iVRTW (p = 0.016). SSQ was similar between TW and iVRTW (p = 0.809). iVRTW is tolerable, could optimize TW effects on spatiotemporal parameters while not increasing CV in PD. Furthermore, iVRTW could help to capture the natural LRA of PD gait in laboratory settings and could potentially be a challenging second step in PD gait rehabilitation.

Biological and Functional Biomarkers of Aging: Definition, Characteristics, and How They Can Impact Everyday Cancer Treatment

Purpose of Review

Recognize which are the elements that predict why a person is aging faster or slower and which intervention we can arrange to slow down the process, which permits to prevent or delay the progression of multimorbidity and disability.

Recent Findings

Aging is a complex process that leads to changes in all the systems of the body and all the functions of the person; however, aging develops at different rates in different people, and chronological age is not always consistent with biological age.

Summary

Gerontologists are focused not only on finding the best theory able to explain aging but also on identifying one or more markers, which are able to describe aging processes. These biomarkers are necessary to better define the aging-related pathologies, manage multimorbidity, and improve the quality of life. The aim of this paper is to review the most recent evidence on aging biomarkers and the clusters related to them for personalization of treatments.

A comparison of variability and gait dynamics in spatiotemporal variables between different self-paced treadmill control modes

This study investigates the effects of treadmill control algorithms on spatiotemporal variables when walking on a self-paced (SP) treadmill. Ten healthy subjects walked at their preferred walking speed for 15 min under three different treadmill control modes. Stride time, stride length, and stride speed were measured using an inertial measurement unit. The mean, coefficient of variance, Poincaré descriptors, and gait dynamics were calculated for each parameter. The mean values of stride length and stride speed were significantly increased when the treadmill had a quick response speed to the user's walking behavior. The long-term variability of stride length and stride speed was significantly affected by the treadmill control algorithms. A reduced strength of long-range correlations of stride time and stride speed was found when walking on the SP treadmill with suppressed treadmill accelerations and small velocity variations. We suggest that the suppression of treadmill acceleration provides more adaptability and less constraint to the user during SP treadmill walking. Although further research is required, the present work provides a basis for interpreting the influence of treadmill control algorithms on human gait.

A Novel Functional Link Network Stacking Ensemble with Fractal Features for Multichannel Fall Detection

Falls are a major health concern and result in high morbidity and mortality rates in older adults with high costs to health services. Automatic fall classification and detection systems can provide early detection of falls and timely medical aid. This paper proposes a novel Random Vector Functional Link (RVFL) stacking ensemble classifier with fractal features for classification of falls. The fractal Hurst exponent is used as a representative of fractal dimensionality for capturing irregularity of accelerometer signals for falls and other activities of daily life. The generalised Hurst exponents along with wavelet transform coefficients are leveraged as input feature space for a novel stacking ensemble of RVFLs composed with an RVFL neural network meta-learner. Novel fast selection criteria are presented for base classifiers founded on the proposed diversity indicator, obtained from the overall performance values during the training phase. The proposed features and the stacking ensemble provide the highest classification accuracy of 95.71% compared with other machine learning techniques, such as Random Forest (RF), Artificial Neural Network (ANN) and Support Vector Machine. The proposed ensemble classifier is 2.3× faster than a single Decision Tree and achieves the highest speedup in training time of 317.7× and 198.56× compared with a highly optimised ANN and RF ensemble, respectively. The significant improvements in training times of the order of 100× and high accuracy demonstrate that the proposed RVFL ensemble is a prime candidate for real-time, embedded wearable device–based fall detection systems.

On the application of entropic half-life and statistical persistence decay for quantification of time dependency in human gait

Entropic half-life (ENT½) and statistical persistence decay (SPD) was recently introduced as measures of time dependency in stride time intervals during walking. The present study investigated the effect of data length on ENT½ and SPD and additionally applied these measures to stride length and stride speed intervals. First, stride times were collected from subjects during one hour of treadmill walking. ENT½ and SPD were calculated from a range of stride numbers between 250 and 2500. Secondly, stride times, stride lengths and stride speeds were collected from subjects during 16 min of treadmill walking. ENT½ and SPD were calculated from the stride times, stride lengths and stride speeds. The ENT½ values reached a plateau between 1000 and 2500 strides whereas the SPD increased linearly with the number of included strides. This suggests that ENT½ can be compared if 1000 strides or more are included, but only SPD obtained from same number of strides should be compared. The ENT½ and SPD of the stride times were significantly longer compared to that of the stride lengths and stride speeds. This indicates that the time dependency is greater in the motor control of stride time compared to that of stride lengths and stride speeds.