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

Biomechanical determinants of running economy

Running economy (RE) defined as the submaximal rate of oxygen consumption during running, has been correlated with better performance. Biomechanical factors such as spatiotemporal parameters and lower extremity mechanics play a significant role in influencing RE. However, the relationship between RE and biomechanical variables in middle-distance running shoes is still unclear. In this study, twenty-one healthy male runners (age: 32.5 ± 5.6 years, height: 1.70 ± 0.10 m, body mass: 69.9 ± 7.3 kg) performed running trials on the treadmill. Physiological and biomechanical variables, including joint angles, moments, angular velocities, powers, ground reaction forces, and spatiotemporal parameters were analyzed. Multiple linear regression and backward stepwise regression analyses were employed to identify key biomechanical determinants of RE. The final regression model identified that the hip positive power, knee extension angular velocity, ankle plantarflexion angular velocity and negative power, and metatarsophalangeal extension angular velocity explained 73% of RE variability. Therefore, focus on optimizing these biomechanical variables, possible with specific shoe properties, could lead to enhanced RE in middle-distance running shoes.

The effects of different shoe stack heights and running speeds on full-body running coordination: An uncontrolled manifold analysis

Stack height is a highly discussed key design feature of running shoes but its effects are not well understood. This study analyzed how shoe stack height and running speed influence full-body running coordination and motor variability structure using an uncontrolled manifold (UCM) analysis. The joint angle variability (i.e. elementary variables) was analyzed in terms of its effects on a synergy stabilizing the center of mass (CoM, i.e. performance variable). A total of 17 healthy experienced runners participated and ran at 10 and 15 km/h on a treadmill with three running shoes differing in stack height (H: 50 mm, M: 35 mm, L: 27 mm). The UCM components (UCM||, UCM Ʇ & UCMratio) were compared with statistical parametric mapping rmANOVAs for different shoes and speeds. The shoes did not show significant effects for the three UCM components. With increasing speed from 10 to 15 km/h, the joint angle coordination variability affecting the CoM (UCMꞱ) increased and UCMratio decreased independent of the shoe condition. This indicated that stack height did not influence the motor variability structure. However, independent of the shoes, the variability affecting CoM increased which led to a weakened synergy stabilizing CoM (UCMratio). It can be suggested that the variations in the tested running speeds had a greater impact on the running coordination than those of the tested shoes within the UCM framework.

Exploring the Relations Between Running Variability and Injury Susceptibility: A Scoping Review

BACKGROUND

Variability in running mechanics, termed running variability, reflects the adaptability of the locomotor system to dynamic environments. Due to inconsistent findings in the literature, there is a research gap in understanding its role in injury.

OBJECTIVES

This scoping review explores running variability's influence on injury susceptibility, examining studies across various injury types, skill levels, methods, and analysis adhering to the guidelines outlined in the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist (PRISMA-ScR). Eligibility criteria and sources of evidence: Twenty-one studies illustrating the complexity of running variability in relation to running-related injuries were selected from Web of Science, ScienceDirect, Google Scholar, and PubMed databases during December 2022 to June 2024.

RESULTS

There are significant differences in running variability between injured and healthy runners, with variability influenced by injury type, stage, and individual differences with varying levels of evidence. Out of 21 studies, 8 (38%) found no group differences, 11 (52%) noted higher running variability in injured participants, and 5 (24%) reported lower variability in injured than healthy subjects. The review was constrained by the diverse subjects, methods, tasks, and outcome variables across the studies.

CONCLUSIONS

Currently, there is no standard normal range for running variability and abnormal variability is defined relative to control groups, though healthy controls can also show abnormal variability without injury in some study designs. Despite the absence of standardized running variability norms, wearable sensors offer insights into real-world running mechanics, presenting running variability as a potential predictor of running-related injuries. The review highlights the need for standardized protocols and further research to clarify running variability's role in injury prediction and prevention, emphasizing the necessity of individualized approaches in training and rehabilitation. Future studies should aim to establish a causal relationship between running variability and injury susceptibility, focusing on identifying variability patterns that precede or follow an injury. This review sets the stage for developing evidence-based strategies to optimize running performance and minimize injury risks.

Comparative kinematic analysis of high-speed treadmill vs. overground sprinting across athletic levels and sex

BACKGROUND

This investigation aimed to dissect the kinematic differences in sprinting between high-speed treadmill and overground conditions, examining how these variations are influenced by the athlete's training status and biological sex.

METHODS

A total of 40 participants, 20 NCAA Division 1 sprinters and 20 recreational runners, performed a series of maximal sprints on a high-speed treadmill and on a standardized competition overground track. Sprinting kinematic variables such as stride length, stride frequency, contact time, and flight time were collected via photoelectric sensors. Maximal sprinting kinematics were analyzed by linear mixed-effects models, considering the impacts of sprinting environment (treadmill vs. overground), training level, and sex, with leg length as fixed factors and individual athletes as random effects. Statistical significance was set at a significance level of 0.05.

RESULTS

The statistical analysis revealed that high-speed treadmill sprinting significantly affects all measured kinematic variables, leading to increased stride frequency and contact time. Elite sprinters demonstrated enhanced kinematic efficiency over recreational runners, characterized by increased stride length and frequency and reduced contact time. Sex-based kinematic distinctions also emerged, with male athletes exhibiting superior stride length and frequency compared to female athletes. Leg length significantly influenced stride frequency, and an interaction effect was observed for flight time between sprint type and athletic group.

CONCLUSIONS

These findings elucidate the distinct biomechanical profiles across sprinting modalities and athlete demographics, emphasizing the need for sprint training customization. This study's insights offer a valuable reference for coaches and athletes to refine training and performance assessment in varied sprinting environments.

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.

Biomechanical differences and variability during sustained motorized treadmill running versus outdoor overground running using wearable sensors

This study aimed to compare running biomechanics and biomechanical variability across 3 run segments and between conditions for 5-km outdoor overground and indoor treadmill running. Seventy-one recreationally-active adults (31F, 40 M; age: 37 ± 11 years; body mass index: 22.9 ± 2.5 kg/m2) completed aerobic fitness assessments at baseline (VO2max), outdoor overground 5 km runs on a standardized route, and indoor treadmill 5 km runs on a motorized system (12.6 ± 4.9 days apart). Wearable sensors recorded step-by-step spatiotemporal, kinetic, and kinematic biomechanics. Repeated measures analyses of covariance were used to compare mean and coefficient of variation (CV) of sensor-derived metrics across run segments, conditions, and limbs (covariates: pace, VO2max). Tukey's post-hoc tests with mean differences and Cohen's d effect sizes were used to determine the difference magnitudes across comparisons. Most biomechanical measures significantly differed between running conditions (p < 0.001); contact time (mean difference and standard error: 8 ± 3 ms; d = 0.20), stride length (0.20 ± 0.12 m; d: 0.31), kinetics (shock, impact, braking; 0.17-1.30 g; d-range: 0.36-0.57), and pronation velocity (138 ± 16°/s; d: 0.61) were all higher during indoor treadmill running. Indoor treadmill running biomechanics CV were significantly higher for most measures compared to outdoor overground running (p < 0.001; d-range: 0.18-0.52). Only spatiotemporal measures and CV significantly differed across run segments (d-range: 0.16-0.68). Clinicians should expect that indoor treadmill biomechanics, particularly kinetic and pronation, will be significantly higher than patients' outdoor overground running biomechanics and tailor subsequent recommendations accordingly. Furthermore, clinicians should expect that indoor treadmill running analyses may result in more variable biomechanics, potentially attributed to consistent speed and surface, and tailor assessments to preferred run environments.

Pattern analysis using lower body human walking data to identify the gaitprint

All people have a fingerprint that is unique to them and persistent throughout life. Similarly, we propose that people have a gaitprint, a persistent walking pattern that contains unique information about an individual. To provide evidence of a unique gaitprint, we aimed to identify individuals based on basic spatiotemporal variables. 81 adults were recruited to walk overground on an indoor track at their own pace for four minutes wearing inertial measurement units. A total of 18 trials per participant were completed between two days, one week apart. Four methods of pattern analysis, a) Euclidean distance, b) cosine similarity, c) random forest, and d) support vector machine, were applied to our basic spatiotemporal variables such as step and stride lengths to accurately identify people. Our best accuracy (98.63%) was achieved by random forest, followed by support vector machine (98.40%), and the top 10 most similar trials from cosine similarity (98.40%). Our results clearly demonstrate a persistent walking pattern with sufficient information about the individual to make them identifiable, suggesting the existence of a gaitprint.

Running Gait Complexity During an Overground, Mass-Participation Five-Kilometre Run

Human locomotion contains innate variability which may provide health insights. Detrended fluctuation analysis (DFA) has been used to quantify the temporal structure of variability for treadmill running, although it has been less commonly applied to uncontrolled overground running. This study aimed to determine how running gait complexity changes in response to gradient and elapsed exercise duration during uncontrolled overground running. Sixty-eight participants completed an overground, mass-participation five-kilometre run (a parkrun). Stride times were recorded using an inertial measurement unit mounted on the distal shank. Data were divided into four consecutive intervals (uphill lap 1, downhill lap 1, uphill lap 2, downhill lap 2). The magnitude (SD) and structure (DFA) of stride time variability were compared across elapsed exercise duration and gradient using a repeated-measures ANOVA. Participants maintained consistent stride times throughout the run. Stride time DFA-α displayed a moderate decrease (d = |0.39| ± 0.13) during downhill running compared to uphill running. DFA-α did not change in response to elapsed exercise duration, although a greater stride time SD was found during the first section of lap 1 (d = |0.30| ± 0.12). These findings suggest that inter- and intra-run changes in gait complexity should be interpreted in the context of course elevation profiles before conclusions on human health are drawn.

The effects of nature-based vs. indoor settings on the adaptability, performance and affect of calisthenics exercisers. A registered report

Comparisons of the beneficial effects of nature-based versus indoor physical activity have been extensively reported, but existing research addresses mainly aerobic activity (running, jogging), not resistance or mixed (aerobic and resistance) exercise. It is unclear if the psychological benefits extend to functionality, i.e., if participants perform their activities better in nature, and how movement is expressed in nature-based and indoor environments, during similar exercise. The present registered report was a randomized controlled trial investigating how engaging in similar resistance-based exercise (calisthenics) in nature-based and indoor settings differed in affective valence, perceived exertion, visual attention, movement adaptability, heart rate variability, and performance. Nature-based exercisers (N = 51) showed increased performance output than indoor exercisers (N = 53) (p < 0.001). There were no group differences in affective valence, perceived exertion, or visual attention. However, psychological states of nature-based exercisers showed stronger associations to performance output (r < 0.33) than those of indoor exercisers (r < 0.03). Nature-based exercisers' movement variability and structure, measured with non-linear and fractal techniques (Sample Entropy and Detrended Fluctuation Analysis), were more regular (p < 0.001) and more functionally adaptive (long-term Detrended Fluctuation Analysis, p = 0.022) to achieve better performance output. Heart rate variability measures were not different between groups. Distinct environments can influence movement adaptability in a calisthenics exercise routine, and ultimately contribute to better performance. These results show how action is specific to task environment, and how action implies not only the task, but also the characteristics of the environment. TRIAL REGISTRATION: NCT05090501 (Clinicaltrials.gov). Registered October 21, 2021.

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.

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.

Stride-to-stride variability and fluctuations at intensities around lactate threshold in distance runners

Stride-to-stride variability and fluctuations in running have been widely investigated in relation to fatigue, injury, and other factors. However, no studies have examined the relationship of stride-to-stride variability and fluctuations with lactate threshold (LT), a well-known performance indicator for distance runners that represents the threshold at which fast-twitch muscle fibers are activated and the glycolytic system is hyperactivated. In this study, we examined a relationship between LT and stride-to-stride variability and fluctuations in trained middle- and long-distance runners (n = 33). All runners were asked to perform multistage graded exercise tests while wearing accelerometers on the upper surface of their shoes. The LT was determined by measuring blood lactate concentrations after each stage. Three gait parameters for each step were calculated based on the acceleration data: stride time (ST), ground contact time (CT), and peak acceleration (PA). The coefficient of variation (CV) and the long-range correlations (α) for each parameter were also calculated. The effects of the runner's group and the relative intensity for CV and α on gait parameters were evaluated using a two-way repeated measures analysis of variance. Although no significant effect was observed in the CV and α of ST, significant intensity main effects were observed for the CV and α of CT and PA. The lack of significant changes in ST might be the result of runners' adequate control of ST to minimize energy cost. All the parameters showing significant changes with increasing intensity decreased dramatically when they were close to LT. This might have been caused by an increase in physiological load near LT and be interpreted as a variation in motor control because of alternations in the mobilized muscle fibers and physiological changes around the LT. The α should be useful for non-invasive LT detection.

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.

The Application of non-linear methods to quantify changes to movement dynamics during running: A scoping review

The aim of this scoping review was to evaluate research approaches that quantify changes to non-linear movement dynamics during running in response to fatigue, different speeds, and fitness levels. PubMed and Scopus were used to identify appropriate research articles. After the selection of eligible studies, study details and participant characteristics were extracted and tabulated to identify methodologies and findings. Twenty-seven articles were included in the final analysis. To evaluate non-linearities in the time series, a range of approaches were identified including motion capture, accelerometery, and foot switches. Common methods of analysis included measures of fractal scaling, entropy, and local dynamic stability. Conflicting findings were evident when studies examined non-linear features in fatigued states when compared to non-fatigued. More pronounced alterations to movement dynamics are evident when running speed is changed markedly. Greater fitness levels resulted in more stable and predictable running patterns. The mechanisms by which these changes are underpinned require further examination. These could include the physiological demand of running, biomechanical constraints of the runner, and the attentional demands of the task. Moreover, the practical implications are yet to be elucidated. This review has identified gaps in the literature which should be addressed for further understanding of the field.

Comparison of EMG Activity in Leg Muscles between Overground and Treadmill Running

INTRODUCTION

Treadmills have been widely used for training and performance testing during which the treadmill grade is usually set to 0%-2% grade. The purpose of our study was to compare the level of activation of lower body muscles when running at two speeds in an overground condition and on a treadmill at 0%, 1%, and 2% grades.

METHODS

We recorded EMG data of eight lower body muscles from 13 recreationally active individuals during overground and treadmill running at 2.92 and 4.58 m·s -1 . Maximal voluntary contraction (MVC) tests were performed (3 × 6 s) to identify maximal torque and EMG values. The stride cycles, from one foot strike to the next, were identified using a pair of triaxial accelerometers. A two-way repeated-measures ANOVA was used to examine the differences in EMG activity across running conditions and speeds. Cohen's d effect size was calculated to indicate the difference between the overground and the treadmill running conditions.

RESULTS

The effect sizes were moderate to negligible for differences between the EMG integral values for overground running and the three treadmill grades. The coefficient of variation for stride time during overground running was significantly larger than that of the treadmill running at 4.58 m·s -1 .

CONCLUSIONS

The results showed that the overall EMG profiles of the thigh and shank muscles were similar for the overground and treadmill conditions, but the similarity was greatest for thigh muscles when running on the treadmill at 1% grade and for shank muscles at 2% grade. The variability in stride time was greater during overground running than when running on a treadmill and was associated with elevated EMG activity of some muscles.

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.

Drift-Free 3D Orientation and Displacement Estimation for Quasi-Cyclical Movements Using One Inertial Measurement Unit: Application to Running

A Drift-Free 3D Orientation and Displacement estimation method (DFOD) based on a single inertial measurement unit (IMU) is proposed and validated. Typically, body segment orientation and displacement methods rely on a constant- or zero-velocity point to correct for drift. Therefore, they are not easily applicable to more proximal segments than the foot. DFOD uses an alternative single sensor drift reduction strategy based on the quasi-cyclical nature of many human movements. DFOD assumes that the quasi-cyclical movement occurs in a quasi-2D plane and with an approximately constant cycle average velocity. DFOD is independent of a constant- or zero-velocity point, a biomechanical model, Kalman filtering or a magnetometer. DFOD reduces orientation drift by assuming a cyclical movement, and by defining a functional coordinate system with two functional axes. These axes are based on the mean acceleration and rotation axes over multiple complete gait cycles. Using this drift-free orientation estimate, the displacement of the sensor is computed by again assuming a cyclical movement. Drift in displacement is reduced by subtracting the mean value over five gait cycle from the free acceleration, velocity, and displacement. Estimated 3D sensor orientation and displacement for an IMU on the lower leg were validated with an optical motion capture system (OMCS) in four runners during constant velocity treadmill running. Root mean square errors for sensor orientation differences between DFOD and OMCS were 3.1 ± 0.4° (sagittal plane), 5.3 ± 1.1° (frontal plane), and 5.0 ± 2.1° (transversal plane). Sensor displacement differences had a root mean square error of 1.6 ± 0.2 cm (forward axis), 1.7 ± 0.6 cm (mediolateral axis), and 1.6 ± 0.2 cm (vertical axis). Hence, DFOD is a promising 3D drift-free orientation and displacement estimation method based on a single IMU in quasi-cyclical movements with many advantages over current methods.

Monitoring Gait Complexity as an Indicator for Running-Related Injury Risk in Collegiate Cross-Country Runners: A Proof-of-Concept Study

Dynamical systems theory suggests that studying the complexity of biological signals could lead to a single gait metric that reliably predicts risk of running-related injury (RRI). The purposes of this pilot study were to examine center of mass (COM) acceleration complexity at baseline, prior to RRI, and the change between timepoints between collegiate runners who developed RRI during a competitive season and those who remained uninjured, and to determine if complexity at these timepoints was associated with increased odds of RRI. Twenty-two collegiate runners from the same cross-country team wore a waist-mounted triaxial accelerometer (100 Hz) during easy-intensity runs throughout the competitive season. RRIs requiring medical attention were reported via an online survey. Control entropy was used to estimate the complexity of the resultant COM acceleration recorded during each run. Associations between complexity and RRI were assessed using a frequency-matching strategy where uninjured participants were paired with injured participants using complexity from the most time-proximal run prior to RRI. Seven runners sustained an RRI. No significant differences were observed between injured and uninjured groups for baseline complexity (p = 0.364, d = 0.405), pre-injury complexity (p = 0.258, d = 0.581), or change from baseline to pre-injury (p = 0.101, d = 0.963). There were no statistically significant associations found between complexity and RRI risk. Although no significant associations were found, the median effect from the models indicated that an increase in baseline complexity, pre-injury complexity, and change in complexity from baseline each corresponded to an increased odds of sustaining an RRI [baseline: odds ratio (OR) = 1.560, 95% CI = 0.587-4.143, p = 0.372; pre-injury: OR = 1.926, 95% CI: 0.689-5.382, p = 0.211; change from baseline: OR = 1.119; 95% CI: 0.839-1.491, p = 0.445). Despite non-significance and wide confidence intervals that included both positive and negative associations, the point estimates for >98% of the 10,000 frequency-case-control-matched model fits indicated that matching strategy did not influence the directionality of the association estimates between complexity and RRI risk (i.e., odds ratio >1.0). This pilot study demonstrates initial feasibility that additional research may support COM acceleration complexity as a useful single-metric monitoring system for RRI risk during real-world training. Follow-up work should assess longitudinal associations between gait complexity and running-related injury in larger cohorts.

Is Motorized Treadmill Running Biomechanically Comparable to Overground Running? A Systematic Review and Meta-Analysis of Cross-Over Studies

BACKGROUND

Treadmills are often used in research, clinical practice, and training. Biomechanical investigations comparing treadmill and overground running report inconsistent findings.

OBJECTIVE

This study aimed at comparing biomechanical outcomes between motorized treadmill and overground running.

METHODS

Four databases were searched until June 2019. Crossover design studies comparing lower limb biomechanics during non-inclined, non-cushioned, quasi-constant-velocity motorized treadmill running with overground running in healthy humans (18-65 years) and written in English were included. Meta-analyses and meta-regressions were performed where possible.

RESULTS

33 studies (n = 494 participants) were included. Most outcomes did not differ between running conditions. However, during treadmill running, sagittal foot-ground angle at footstrike (mean difference (MD) - 9.8° [95% confidence interval: - 13.1 to - 6.6]; low GRADE evidence), knee flexion range of motion from footstrike to peak during stance (MD 6.3° [4.5 to 8.2]; low), vertical displacement center of mass/pelvis (MD - 1.5 cm [- 2.7 to - 0.8]; low), and peak propulsive force (MD - 0.04 body weights [- 0.06 to - 0.02]; very low) were lower, while contact time (MD 5.0 ms [0.5 to 9.5]; low), knee flexion at footstrike (MD - 2.3° [- 3.6 to - 1.1]; low), and ankle sagittal plane internal joint moment (MD - 0.4 Nm/kg [- 0.7 to - 0.2]; low) were longer/higher, when pooled across overground surfaces. Conflicting findings were reported for amplitude of muscle activity.

CONCLUSIONS

Spatiotemporal, kinematic, kinetic, muscle activity, and muscle-tendon outcome measures are largely comparable between motorized treadmill and overground running. Considerations should, however, particularly be given to sagittal plane kinematic differences at footstrike when extrapolating treadmill running biomechanics to overground running. Protocol registration CRD42018083906 (PROSPERO International Prospective Register of Systematic Reviews).

Performance determinants, running energetics and spatiotemporal gait parameters during a treadmill ultramarathon

Purpose

The objective of this study was to investigate the changes in metabolic variables, running energetics and spatiotemporal gait parameters during an 80.5 km treadmill ultramarathon and establish which key predictive variables best determine ultramarathon performance.

Methods

Twelve participants (9 male and 3 female, age 34 ± 7 years, and maximal oxygen uptake (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O_2max) 60.4 ± 5.8 ml·kg⁻¹·min⁻¹) completed an 80.5 km time trial on a motorised treadmill in the fastest possible time. Metabolic variables: oxygen consumption (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂), carbon dioxide production (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙CO₂) and pulmonary ventilation (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙_E) were measured via indirect calorimetry every 16.1 km at a controlled speed of 8 km·h⁻¹ and used to calculate respiratory exchange ratio (RER), the energy cost of running (Cr) and fractional utilisation of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O_2max (F). Spatiotemporal gait parameters: stride length (SL) and cadence (SPM) were calculated via tri-axial accelerometery.

Results

Trial completion time was 09:00:18 ± 01:14:07 (hh:mm:ss). There were significant increases in \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙O₂, Cr, F, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{V}$$\end{document}V˙_E and heart rate (HR) (p < 0.01); a significant decrease in RER (p < 0.01) and no change in SL and SPM (p > 0.05) across the measured timepoints. F and Cr accounted for 61% of the variance in elapsed finish time (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{{{\text{adj}}}}^{{2}}$$\end{document}Radj2 = 0.607, p < 0.01).

Conclusion

A treadmill ultramarathon elicits significant changes in metabolic variables, running energetics and spatiotemporal gait parameters. With F and Cr explaining 61% of variance in finish time. Therefore, those able to maintain a higher F, while adopting strategies to minimise an increase in Cr may be best placed to maximise ultramarathon performance.

Entropy Analysis in Gait Research: Methodological Considerations and Recommendations

The usage of entropy analysis in gait research has grown considerably the last two decades. The present paper reviews the application of different entropy analyses in gait research and provides recommendations for future studies. While single-scale entropy analysis such as approximate and sample entropy can be used to quantify regularity/predictability/probability, they do not capture the structural richness and component entanglement characterized by a complex system operating across multiple spatial and temporal scales. Thus, for quantification of complexity, either multiscale entropy or refined composite multiscale entropy is recommended. For both single- and multiscale-scale entropy analyses, care should be made when selecting the input parameters of tolerance window r, vector length m, time series length N and number of scales. This selection should be based on the proposed research question and the type of data collected and not copied from previous studies. Parameter consistency should be investigated and published along with the main results to ensure transparency and enable comparisons between studies. Furthermore, since the interpretation of the absolute size of both single- and multiscale entropy analyses outcomes is not straightforward, comparisons should always be made with a control condition or group.

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.

A comparison of coordination and its variability in lower extremity segments during treadmill and overground running at different speeds

BACKGROUND

Recently, the use of treadmills for walking and running has increased due to lifestyle changes. However, biomechanical differences in coordination between running on a treadmill or overground have not been adequately addressed.

RESEARCH QUESTION

The purpose of this study was to compare coordination and its variability in lower limb segments during treadmill and overground running at different speeds.

METHODS

Twenty physically active university undergraduate students participated in this study. Each participant ran trials for both overground and treadmill running at slow and fast speeds. Three-dimensional kinematic data of the lower limb segments were captured. The continuous relative phase (CRP) was used to compute coordination and its variability (VCRP) for foot, shank, and thigh segments of the dominant side of the participants.

RESULTS

A vector analysis using statistical parametric mapping (SPM) revealed that there were statistically significant differences in the calculated CRPs for treadmill and overground running in the stance phase of running and for different running speeds in the late stance and swing phases. However, the VCRPs calculated for the two locations and speeds did not exhibit any statistically significant differences.

CONCLUSION

The findings of this study suggest differences in segment coupling between treadmill and overground running may affect lower extremity biomechanics. In addition, changes in the coupling patterns for different running speeds suggest that segment coordination is not stable in the range of training speeds used by runners. Finally, the lack of differences in the variability of segment couplings during treadmill and overground conditions at different speeds potentially demonstrates similar dynamic neuromuscular control and degrees of freedom at these different running locations and speeds.

Motor style at rest and during locomotion in human

Humans exhibit various motor styles that reflect their intra- and interindividual variability when implementing sensorimotor transformations. This opens important questions, such as, At what point should they be readjusted to maintain optimal motor control? Do changes in motor style reveal the onset of a pathological process and can these changes help rehabilitation and recovery? To further investigate the concept of motor style, tests were carried out to quantify posture at rest and motor control in 18 healthy subjects under four conditions: walking at three velocities (comfortable walking, walking at 4 km/h, and race walking) and running at maximum velocity. The results suggest that motor control can be conveniently decomposed into a static component (a stable configuration of the head and column with respect to the gravitational vertical) and dynamic components (head, trunk, and limb movements) in humans, as in quadrupeds, and both at rest and during locomotion. These skeletal configurations provide static markers to quantify the motor style of individuals because they exhibit large variability among subjects. Also, using four measurements (jerk, root mean square, sample entropy, and the two-thirds power law), it was shown that the dynamics were variable at both intra- and interindividual levels during locomotion. Variability increased following a head-to -toe gradient. These findings led us to select dynamic markers that could define, together with static markers, the motor style of a subject. Finally, our results support the view that postural and motor control are subserved by different neuronal networks in frontal, sagittal, and transversal planes.NEW & NOTEWORTHY During human locomotion, motor control can be conveniently decomposed into a static and dynamic components. Variable dynamics were observed at both the intra- and interindividual levels during locomotion. Variability increased following a head-to-toe gradient. Finally, our results support the view that postural and motor control are subserved by different neuronal networks in the frontal, sagittal, and transversal planes.

New Considerations for Collecting Biomechanical Data Using Wearable Sensors: The Effect of Different Running Environments

Traditionally, running biomechanics analyses have been conducted using 3D motion capture during treadmill or indoor overground running. However, most runners complete their runs outdoors. Since changes in running terrain have been shown to influence running gait mechanics, the purpose of this study was to use a machine learning approach to objectively determine relevant accelerometer-based features to discriminate between running patterns in different environments and determine the generalizability of observed differences in running patterns. Center of mass accelerations were recorded for recreational runners in treadmill-only (n = 28) and sidewalk-only (n = 25) environments, and an independent group (n = 16) ran in both treadmill and sidewalk environments. A feature selection algorithm was used to develop a training dataset from treadmill-only and sidewalk-only running. A binary support vector machine model was trained to classify treadmill and sidewalk running. Classification accuracy was determined using 10-fold cross-validation of the training dataset and an independent testing dataset from the runners that ran in both environments. Nine features related to the consistency and variability of center of mass accelerations were selected. Specifically, there was greater ratio of vertical acceleration during treadmill running and a greater ratio of anterior-posterior acceleration during sidewalk running in both the training and testing dataset. Step and stride regularity were significantly greater in the treadmill condition for the vertical axis in both the training and testing dataset, and in the medial-lateral axis for the testing dataset. During sidewalk running, there was significantly greater variability in the magnitude of the vertical and anterior-posterior accelerations for both datasets. The classification accuracy based on 10-fold cross-validation of the training dataset (M = 93.17%, SD = 2.43%) was greater than the classification accuracy of the independent testing dataset (M = 83.81%, SD = 3.39%). This approach could be utilized in future analyses to identify relevant differences in running patterns using wearable technology.

Setting, Age, and Intensity Influence Responses to Exercise in Young Endurance Runners

We investigated the effects of exercise setting (indoor treadmill vs. outdoor trail), age (17 middle school, 18 high school, and 13 college participants), and level of exertion (Borg Ratings of Perceived Exertion of 10, 12, and 16 on a 22-point scale) on young male endurance runners’ heart rate (HR), running speed, attentive focus, and affect. Three-way analyses of variance revealed that on the outdoor trail (vs. indoor treadmill), HR and speed were higher ( p < .001) and attentive focus was more dissociative ( p = .047). There were significant Age × Setting interactions for HR ( p = .047), speed ( p = .023), and attentive focus ( p = .002), with older participants exhibiting a greater increase in speed and HR and a greater shift toward dissociative focus on the outdoor trail. Three-way analyses of variance also yielded significant Age × Time interactions on components of the Physical Activity Affect Scale in that younger participants exhibited larger declines in positive affect ( p = .003) and tranquility ( p < .001) and larger increases in fatigue ( p < .001) as a result of the running session. Our data suggest that either runners develop more positive responses to exercise as they mature or those young runners who experience running more negatively tend to drop out of running so that the remaining older participants continuing to run are those who experience exercise positively.

Variability of running coordination in experts and novices: A 3D uncontrolled manifold analysis

The uncontrolled manifold (UCM) approach has been widely used in recent studies to examine variability in daily tasks; however, it has not yet been used to study running or the effects of expertise. Therefore, the aim of this study was to analyse the synergy structure stabilizing the centre of mass (CoM) trajectory in experts compared to novices during running at two different speeds using a subject-specific 3D model. A total of 25 healthy young adults (13 experts, 12 novices) participated in the study. All subjects ran at 10 and 15 km h^-1 on a treadmill. In each case, kinematics of 20 consecutive gait cycles were recorded and the effects of expertise and gait cycle phase on the synergy structure were investigated at both speeds. Specifically, the variance affecting the CoM ( U C M ⊥ ) , the variance not affecting the CoM ( U C M ∥ ) , and their ratio ( U C M R a t i o ) were analysed. Descriptively, in both groups there was a synergy stabilizing the CoM trajectory in running. However, the ANOVA showed no differences in U C M R a t i o between the two groups. In novices, U C M ⊥ and U C M ∥ were significantly higher compared to experts at the 15 km h^-1 condition. In both groups, there was more variability in the stance phase compared to the flight phase in the majority of cases. The results indicate that experts adopted a more consistent running style. The stride-to-stride variability was diminished but not abolished. This difference was only visible at the 15 km h^-1 condition. Furthermore, variability was less constrained in the stance phase compared to the flight phase.

Analysis of center of mass acceleration and muscle activation in hemiplegic paralysis during quiet standing

Hemiplegic paralysis after stroke may augment postural instability and decrease the balance control ability for standing. The center of mass acceleration (COMacc) is considered to be an effective indicator of postural stability for standing balance control. However, it is less studied how the COMacc could be affected by the muscle activities on lower-limbs in post-stroke hemiplegic patients. This study aimed to examine the effects of hemiplegic paralysis in post-stroke individuals on the amplitude and structural variabilities of COMacc and surface electromyography (sEMG) signals during quiet standing. Eleven post-stroke hemiplegic patients and the same number of gender- and age-matched healthy volunteers participated in the experiment. The sEMG signals of tibialis anterior (TA) and lateral gastrocnemius (LG) muscles of the both limbs, and the COMacc in the anterior-posterior direction with and without visual feedback (VF vs. NVF) were recorded simultaneously during quiet standing. The sEMG and COMacc were analyzed using root mean square (RMS) or standard deviation (SD), and a modified detrended fluctuation analysis based on empirical mode decomposition (EMD-DFA). Results showed that the SD and the scale exponent α of EMD-DFA of the COMacc from the patients were significantly higher than the values from the controls under both VF (p < 0.01) and NVF (p < 0.001) conditions. The RMSs of TA and LG on the non-paretic limbs were significantly higher than those on paretic limbs (p < 0.05) for both the patients and controls (p < 0.05). The TA of both the paretic and non-paretic limbs of the patients showed augmented α values than the TA of the controls (p < 0.05). The α of the TA and LG of non-paretic limbs, and the α of COMacc were significantly increased after removing visual feedback in patients (p < 0.05). These results suggested an increased amplitude variability but decreased structural variability of COMacc, associated with asymmetric muscle contraction between the paretic and the non-paretic limbs in hemiplegic paralysis, revealing a deficiency in integration of sensorimotor information and a loss of flexibility of postural control due to stroke.

The effect of running speed on joint coupling coordination and its variability in recreational runners

The purpose of this study was to examine the effect of speed on coordination and its variability in running gait using vector coding analysis. Lower extremity kinematic data were collected for thirteen recreational runners while running at three different speeds in random order: preferred speed, 15% faster and 15% lower than preferred speed. A dynamical systems approach, using vector coding and circular statistics, were used to quantify coordination and its variability for selected hip-knee and knee-ankle joint couplings. The influence of running speed was calculated from the continuous data sets of the running cycle, allowing for the identification of time percentages where differences existed. Results indicate that increases in running speed produced moderate alterations in the frequency of movement patterns which were not enough to alter classification of coordination. No effects of speed on coordination variability were observed. This study has demonstrated that coordination and coordination variability is generally stable in the range of ±15% around of preferred speed in recreational runners.

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

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

On the choice of multiscale entropy algorithm for quantification of complexity in gait data

The present study aimed at identifying a suitable multiscale entropy (MSE) algorithm for assessment of complexity in a stride-to-stride time interval time series. Five different algorithms were included (the original MSE, refine composite multiscale entropy (RCMSE), multiscale fuzzy entropy, generalized multiscale entropy and intrinsic mode entropy) and applied to twenty iterations of white noise, pink noise, or a sine wave with added white noise. Based on their ability to differentiate the level of complexity in the three different generated signal types, and their sensitivity and parameter consistency, MSE and RCMSE were deemed most appropriate. These two algorithms were applied to stride-to-stride time interval time series recorded from fourteen healthy subjects during one hour of overground and treadmill walking. In general, acceptable sensitivity and good parameter consistency were observed for both algorithms; however, they were not able to differentiate the complexity of the stride-to-stride time interval time series between the two walking conditions. Thus, the present study recommends the use of either MSE or RCMSE for quantification of complexity in stride-to-stride time interval time series.

Comparison of Different Algorithms for Calculating Velocity and Stride Length in Running Using Inertial Measurement Units

Running has a positive impact on human health and is an accessible sport for most people. There is high demand for tracking running performance and progress for amateurs and professionals alike. The parameters velocity and distance are thereby of main interest. In this work, we evaluate the accuracy of four algorithms, which calculate the stride velocity and stride length during running using data of an inertial measurement unit (IMU) placed in the midsole of a running shoe. The four algorithms are based on stride time, foot acceleration, foot trajectory estimation, and deep learning, respectively. They are compared using two studies: a laboratory-based study comprising 2377 strides from 27 subjects with 3D motion tracking as a reference and a field study comprising 12 subjects performing a 3.2-km run in a real-world setup. The results show that the foot trajectory estimation algorithm performs best, achieving a mean error of 0.032 ± 0.274 m/s for the velocity estimation and 0.022 ± 0.157 m for the stride length. An interesting alternative for systems with a low energy budget is the acceleration-based approach. Our results support the implementation decision for running velocity and distance tracking using IMUs embedded in the sole of a running shoe.

An Assessment of Running Power as a Training Metric for Elite and Recreational Runners

Aubry, RL, Power, GA, and Burr, JF. An assessment of running power as a training metric for elite and recreational runners. J Strength Cond Res 32(8): 2258-2264, 2018-Power, as a testing and training metric to quantify effort, is well accepted in cycling, but is not commonly used in running to quantify effort or performance. This study sought to investigate a novel training tool, the Stryd Running Power Meter, and the applicability of running power (and its individually calculated run mechanics) to be a useful surrogate of metabolic demand (V[Combining Dot Above]O2), across different running surfaces, within different caliber runners. Recreational (n = 13) and elite (n = 11) runners completed a test assessing V[Combining Dot Above]O2 at 3 different paces, while wearing a Stryd Power Meter on both an indoor treadmill and an outdoor track, to investigate relationships between estimated running power and metabolic demand. A weak but significant relationship was found between running power and V[Combining Dot Above]O2 considering all participants as a homogenous group (r = 0.29); however, when assessing each population individually, no significant relationship was found. Examination of the individual mechanical components of power revealed that a correlative decrease in V[Combining Dot Above]O2 representing improved efficiency was associated with decreased ground contact time (r = 0.56), vertical oscillation (r = 0.46), and cadence (r = 0.37) on the treadmill in the recreational group only. Although metabolic demand differed significantly between surfaces at most speeds, run power did not accurately reflect differences in metabolic cost between the 2 surfaces. Running power, calculated via the Stryd Power Meter, is not sufficiently accurate as a surrogate of metabolic demand, particularly in the elite population. However, in a recreational population, this training tool could be useful for feedback on several running dynamics known to influence running economy.

Lower between-limb asymmetry during running on treadmill compared to overground in subjects with laterally pronounced knee osteoarthritis

Subjects with knee osteoarthritis (KOA) show gait asymmetries evidenced by lower knee flexion and shorter contact times for the affected leg. Interestingly, running on a treadmill compared to running overground is also associated with lower knee flexion and shorter contact times. Thus, it is of particular interest how gait patterns are influenced by the type of ground in subjects with KOA. The aim of the current study was therefore to measure the overground asymmetry of kinematic parameters in KOA subjects while running and to investigate whether this asymmetry is altered on a treadmill. Nine patients diagnosed with KOA underwent overground and treadmill running with 3D-motion analysis. The symmetry analysis was performed using Symmetry Angles for five selected gait parameters: contact and step time, heel-toe delay, maximal knee flexion during stance and vertical speed variance. For all parameters, the values were significantly lower for the affected compared to the non-affected leg (p≤0.023). Post-hoc analyses revealed significant differences between legs only overground and not on the treadmill. The asymmetry was lower on the treadmill, as indicated by significant Symmetry Angle reductions for contact time (p = 0.033), knee flexion (p = 0.001) and vertical speed variance (p = 0.002). The symmetry increase on the treadmill was mainly due to changes of the non-affected leg towards the affected leg values leading to smaller steps and less impact load in general. The present results suggest therefore that a) an assessment of symmetry may differ depending on the ground type (treadmill versus overground) and b) treadmill running may be more suitable for patients with KOA related gait asymmetries.

Effects of upper and lower body wearable resistance on spatio-temporal and kinetic parameters during running

Wearable resistance training involves added load attached directly to the body during sporting movements. The effects of load position during running are not yet fully established. Therefore, the purpose of this research was to determine spatio-temporal and kinetic characteristics during submaximal running using upper, lower and whole-body wearable resistance (1-10% body mass (BM)). Twelve trained male runners completed eight 2-min treadmill running bouts at 3.9 m/s with and without wearable resistance. The first and last bouts were unloaded, while the middle 6 were randomised wearable resistance conditions: upper body (UB) 5% BM, lower body (LB) 1%, 3%, 5% BM and whole body (WB) 5%, 10% BM. Wearable resistance of 1-10% BM resulted in a significant increase in heart rate (5.40-8.84%), but minimal impact on spatio-temporal variables. Loads of 5% BM and greater caused changes in vertical stiffness, vertical and horizontal force, and impulse. Functional and effective propulsive force (2.95%, 2.88%) and impulse (3.40%, 3.38%) were significantly (p < 0.05) greater with LB5% than UB5%. Wearable resistance may be used to increase muscular kinetics during running without negatively impacting spatio-temporal variables. The application of these findings will vary depending on athlete goals. Future longitudinal studies are required to validate training contentions.

Stride-to-stride variability and complexity between novice and experienced runners during a prolonged run at anaerobic threshold speed

BACKGROUND

Motor control, related to running performance and running related injuries, is affected by progression of fatigue during a prolonged run. Distance runners are usually recommended to train at or slightly above anaerobic threshold (AT) speed for improving performance. However, running at AT speed may result in accelerated fatigue. It is not clear how one adapts running gait pattern during a prolonged run at AT speed and if there are differences between runners with different training experience.

PURPOSES

To compare characteristics of stride-to-stride variability and complexity during a prolonged run at AT speed between novice runners (NR) and experienced runners (ER).

METHODS

Both NR (n = 17) and ER (n = 17) performed a treadmill run for 31 min at his/her AT speed. Stride interval dynamics was obtained throughout the run with the middle 30 min equally divided into six time intervals (denoted as T1, T2, T3, T4, T5 and T6). Mean, coefficient of variation (CV) and scaling exponent alpha of stride intervals were calculated for each interval of each group.

RESULTS

This study revealed mean stride interval significantly increased with running time in a non-linear trend (p<0.001). The stride interval variability (CV) maintained relatively constant for NR (p = 0.22) and changed nonlinearly for ER (p = 0.023) throughout the run. Alpha was significantly different between groups at T2, T5 and T6, and nonlinearly changed with running time for both groups with slight differences.

SIGNIFICANCE

These findings provided insights into how the motor control system adapts to progression of fatigue and evidences that long-term training enhances motor control. Although both ER and NR could regulate gait complexity to maintain AT speed throughout the prolonged run, ER also regulated stride interval variability to achieve the goal.

Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review

Recent technological developments have led to the production of inexpensive, non-invasive, miniature magneto-inertial sensors, ideal for obtaining sport performance measures during training or competition. This systematic review evaluates current evidence and the future potential of their use in sport performance evaluation. Articles published in English (April 2017) were searched in Web-of-Science, Scopus, Pubmed, and Sport-Discus databases. A keyword search of titles, abstracts and keywords which included studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes (excluding risk of injury, physical activity, and energy expenditure) resulted in 2040 papers. Papers and reference list screening led to the selection of 286 studies and 23 reviews. Information on sport, motor-tasks, participants, device characteristics, sensor position and fixing, experimental setting and performance indicators was extracted. The selected papers dealt with motor capacity assessment (51 papers), technique analysis (163), activity classification (19), and physical demands assessment (61). Focus was placed mainly on elite and sub-elite athletes (59%) performing their sport in-field during training (62%) and competition (7%). Measuring movement outdoors created opportunities in winter sports (8%), water sports (16%), team sports (25%), and other outdoor activities (27%). Indications on the reliability of sensor-based performance indicators are provided, together with critical considerations and future trends.

Effect of parameter selection on entropy calculation for long walking trials

It is sometimes difficult to obtain uninterrupted data sets that are long enough to perform nonlinear analysis, especially in pathological populations. It is currently unclear as to how many data points are needed for reliable entropy analysis. The aims of this study were to determine the effect of changing parameter values of m, r, and N on entropy calculations for long gait data sets using two different modes of walking (i.e., overground versus treadmill). Fourteen young adults walked overground and on a treadmill at their preferred walking speed for one-hour while step time was collected via heel switches. Approximate (ApEn) and sample entropy (SampEn) were calculated using multiple parameter combinations of m, N, and r. Further, r was tested under two cases r*standard deviation and r constant. ApEn differed depending on the combination of r, m, and N. ApEn demonstrated relative consistency except when m=2 and the smallest r values used (rSD=0.015*SD, 0.20*SD; rConstant=0 and 0.003). For SampEn, as r increased, SampEn decreased. When r was constant, SampEn demonstrated excellent relative consistency for all combinations of r, m, and N. When r constant was used, overground walking was more regular than treadmill. However, treadmill walking was found to be more regular when using rSD for both ApEn and SampEn. For greatest relative consistency of step time data, it was best to use a constant r value and SampEn. When using entropy, several r values must be examined and reported to ensure that results are not an artifact of parameter choice.

Dynamics of Stride Interval Characteristics during Continuous Stairmill Climbing

It has been shown that statistical persistence in stride intervals characteristics exist during walking, running and cycling and were speed-dependent among healthy young adults. The purpose of this study was to determine if such statistical persistence in stride time interval, stride length and stride speed also exists during self-paced continuous stairmill climbing and if the strength is dependent on stepping rate. Stride time, stride length, and stride speed were collected from nine healthy participants during 3 min of stairmill climbing at 100, 110, and 120% of their preferred stepping rate (PSR) and 5 min of treadmill walking at preferred walking speed (PWS). The amount of variability (assessed by standard deviation and coefficient of variation) and dynamics (assessed by detrended fluctuation analysis and sample entropy) of the stride time, stride length, and stride speed time series were investigated. The amounts of variability were significantly higher during stairmill climbing for the stride time, stride length, and stride speed and did only change with increased stepping rate for stride speed. In addition to a more irregular pattern during stairmill climbing, the detrended fluctuation analysis (DFA) revealed that the stride length fluctuations were statistical anti-persistent for all subjects. On a group level both stride time and stride speed fluctuations were characterized by an uncorrelated pattern which was more irregular compared to that during treadmill walking. However, large inter-participant differences were observed for these two variables. In addition, the dynamics did not change with increase in stepping rate.

Imposed Faster and Slower Walking Speeds Influence Gait Stability Differently in Parkinson Fallers

OBJECTIVE

To evaluate the effect of imposed faster and slower walking speeds on postural stability in people with Parkinson disease (PD).

DESIGN

Cross-sectional cohort study.

SETTING

General community.

PARTICIPANTS

Patients with PD (n=84; 51 with a falls history; 33 without) and age-matched controls (n=82) were invited to participate via neurology clinics and preexisting databases. Of those contacted, 99 did not respond (PD=36; controls=63) and 27 were not interested (PD=18; controls=9). After screening, a further 10 patients were excluded; 5 had deep brain stimulation surgery and 5 could not accommodate to the treadmill. The remaining patients (N=30) completed all assessments and were subdivided into PD fallers (n=10), PD nonfallers (n=10), and age-matched controls (n=10) based on falls history.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Three-dimensional accelerometers assessed head and trunk accelerations and allowed calculation of harmonic ratios and root mean square (RMS) accelerations to assess segment control and movement amplitude.

RESULTS

Symptom severity, balance confidence, and medical history were established before participants walked on a treadmill at 70%, 100%, and 130% of their preferred speed. Head and trunk control was lower for PD fallers than PD nonfallers and older adults. Significant interactions indicated head and trunk control increased with speed for PD nonfallers and older adults, but did not improve at faster speeds for PD fallers. Vertical head and trunk accelerations increased with walking speed for PD nonfallers and older adults, while the PD fallers demonstrated greater anteroposterior RMS accelerations compared with both other groups.

CONCLUSIONS

The results suggest that improved gait dynamics do not necessarily represent improved walking stability, and this must be respected when rehabilitating gait in patients with PD.

Coordination of digit force variability during dominant and non-dominant sustained precision pinch

This study examined the effects of handedness on the inter-digit coordination of force variability with and without concurrent visual feedback during sustained precision pinch. Twenty-four right-handed subjects were instructed to pinch an instrumented apparatus with their dominant and non-dominant hands, separately. During the pinch, the subjects were required to maintain a stable force output at 5 N for 1 min. Visual feedback was given for the first 30 s and removed for the second 30 s. Coefficient of variation and detrended fluctuation analysis were employed to examine the amount and structural variability of the thumb and index finger forces. Similarly, correlation coefficient and detrended cross-correlation analysis were applied to quantify the inter-digit correlation of force amount and structural variability. Results showed that, compared to the non-dominant hand, the dominant hand had higher inter-digit difference in the amount of digit force variability. Without visual feedback, the dominant hand exhibited lower digit force structural variability but higher inter-digit force structural correlation than the non-dominant hand. These results implied that the dominant hand would be more independent, less flexible and with lower dynamic degrees of freedom than the non-dominant hand in coordination of the thumb and index finger forces during sustained precision pinch. The effects of handedness on inter-digit force coordination were dependent on sensory condition, which shed light on higher-level sensorimotor mechanisms that may be responsible for the asymmetries in coordination of digit force variability.

The influence of auditory-motor coupling on fractal dynamics in human gait

Humans exhibit an innate ability to synchronize their movements to music. The field of gait rehabilitation has sought to capitalize on this phenomenon by invoking patients to walk in time to rhythmic auditory cues with a view to improving pathological gait. However, the temporal structure of the auditory cue, and hence the temporal structure of the target behavior has not been sufficiently explored. This study reveals the plasticity of auditory-motor coupling in human walking in relation to 'complex' auditory cues. The authors demonstrate that auditory-motor coupling can be driven by different coloured auditory noise signals (e.g. white, brown), shifting the fractal temporal structure of gait dynamics towards the statistical properties of the signals used. This adaptive capability observed in whole-body movement, could potentially be harnessed for targeted neuromuscular rehabilitation in patient groups, depending on the specific treatment goal.