Quantifying workload using nonlinear dynamical measures of biomechanical parameters during cycling on a roller trainer.

The aim of the present study was to determine the effectiveness of nonlinear parameters in distinguishing individual workload in cycling by using bike-integrated sensor data. The investigation focused on two nonlinear parameters: The ML1, which analyzes the geometric median in phase space, and the maximum Lyapunov exponent as nonlinear measure of local system stability. We investigated two hypothesis: 1. ML1α, derived from kinematic crank data, is as good as ML1F, derived from force crank data, at distinguishing between individual load levels. 2. Increasing load during cycling leads to decreasing local system stability evidenced by linearly increasing maximal Lyapunov exponents generated from kinematic data. A maximal incremental cycling step test was conducted on an ergometer, generating complete datasets from 10 participants in a laboratory setting. Pedaling torque and kinematic data of the crank were recorded. ML1F, ML1α, and Lyapunov parameters (λst, λlt, ιst, ιlt) were calculated for each participant at comparable load levels. The results showed a significant linear increase in ML1α across three individual load levels, with a lower but still large effect compared to ML1F. The contrast analysis also confirmed a linearly increasing trend for λst across three load levels, but this was not confirmed for λlt. However, the intercepts ιst and ιlt of the short- and longterm divergence showed a statistically significant linear increase across the load levels. In summary, nonlinear parameters seem fundamentally suitable to distinguish individual load levels in cycling. It is concluded that higher load during cycling is associated with decreasing local system stability. These findings may aid in developing improved e-bike propulsion algorithms. Further research is needed to determine the impact of factors occurring in field application.

Comparison of statistical models for characterizing continuous differences between two biomechanical measurement systems.

Most biomechanical processes are continuous in nature. Measurement systems record this continuous behavior as curve data, which is often treated inappropriately in validation studies. The current paper compares different statistical models for analyzing the agreement of curves from two measurement systems. All models were evaluated in various error scenarios (simulated and real-world data). Excellent results were obtained using a functional method, with coverage probabilities close to the desired level in all data sets. Pointwise constructed bands had a lower coverage probability, but still contained most of the curve points and may thus be an option in scenarios where assumptions of functional models are violated (e.g., when curves are much noisier than those presented here, or in the presence of drift). Models that account for within-subject variation showed a higher coverage probability and less uncertainty about the variation of band limits. We hope this study, along with the provided research code, will inspire researchers to use methods for curve data more frequently and appropriately.

Effects of an active hand exoskeleton on forearm muscle activity in industrial assembly grips.

BACKGROUND: The Bioservo Ironhand® is a commercially available active hand exoskeleton for reducing grip-induced stress. OBJECTIVES: The study aimed at quantifying the effect of the Ironhand® exoskeleton on the myoelectric muscle activity of forearm flexor and extensor muscles in three relevant assembly grip tasks: 2-Finger-grip (2Finger), 5-Finger-grip (5Finger) and Full grip (FullGrip). METHODS: Twenty-two subjects were tested in three different exoskeleton conditions for each grip task (overall 3×3×10 = 90 repetitions in randomized order): Exoskeleton off (Off), Exoskeleton on, "locking tendency" 0% (On_LT0), and Exoskeleton on, "locking tendency" 85% (On_LT85). Muscle activity was measured at 25% of the participant's maximum grip force using two EMG sensors at the M. flexor digitorum superficialis (M.FDS) and one at the M. extensor digitorum (M.ED). RESULTS: The effect of the Ironhand® exoskeleton varied depending on the grip task and the participant's sex. A statistically significant reduction in muscle activity of the M.FDS was found only for male subjects in the FullGrip condition. No reduction of muscular activity in the M.FDS was found for the other grip tasks (2Finger, 5Finger). For the females in the 2Finger condition, mean muscle activity of M.FDS even increased significantly in On_LT0 compared to Off. Besides differences between grip tasks and sex, the current study revealed substantial individual differences. CONCLUSIONS: In addition to testing for statistical significance, a detailed exploratory analysis of exoskeleton effects at subject level should be performed to evaluate these from a safety and regulatory perspective.

Icy road ahead-rapid adjustments of gaze-gait interactions during perturbed naturalistic walking.

Most humans can walk effortlessly across uniform terrain even when they do not pay much attention to it. However, most natural terrain is far from uniform, and we need visual information to maintain stable gait. Recent advances in mobile eye-tracking technology have made it possible to study, in natural environments, how terrain affects gaze and thus the sampling of visual information. However, natural environments provide only limited experimental control, and some conditions cannot safely be tested. Typical laboratory setups, in contrast, are far from natural settings for walking. We used a setup consisting of a dual-belt treadmill, 240\(^\circ\) projection screen, floor projection, three-dimensional optical motion tracking, and mobile eye tracking to investigate eye, head, and body movements during perturbed and unperturbed walking in a controlled yet naturalistic environment. In two experiments (N = 22 each), we simulated terrain difficulty by repeatedly inducing slipping through accelerating either of the two belts rapidly and unpredictably (Experiment 1) or sometimes following visual cues (Experiment 2). We quantified the distinct roles of eye and head movements for adjusting gaze on different time scales. While motor perturbations mainly influenced head movements, eye movements were primarily affected by the presence of visual cues. This was true both immediately following slips and-to a lesser extent-over the course of entire 5-min blocks. We find adapted gaze parameters already after the first perturbation in each block, with little transfer between blocks. In conclusion, gaze-gait interactions in experimentally perturbed yet naturalistic walking are adaptive, flexible, and effector specific.

Phase space methods for non-linear analysis of pedalling forces in cycling.

INTRODUCTION: From the perspective of dynamic systems theory, stability and variability of biological signals are both understood as a functional adaptation to variable environmental conditions. In the present study, we examined whether this theoretical perspective is applicable to the pedalling movement in cycling. Non-linear measures were applied to analyse pedalling forces with varying levels of subjective load. MATERIALS AND METHODS: Ten subjects completed a 13-sector virtual terrain profile of 15 km total length on a roller trainer with varying degrees of virtual terrain inclination (resistance). The test was repeated two times with different instructions on how to alter the bikes gearing. During the experiment, pedalling force and heart rate were measured. Force-time curves were sequenced into single cycles, linearly interpolated in the time domain, and z-score normalised. The established time series was transferred into a two-dimensional phase space with limit cycle properties given the applied 25% phase shift. Different representations of the phase space attractor were calculated within each sector and used as non-linear measures assessing pedalling forces. RESULTS AND DISCUSSION: A contrast analysis showed that changes in pedalling load were strongly associated to changes in non-linear phase space attractor variables. For the subjects investigated in this study, this association was stronger than that between heart rate and resistance level. The results indicate systematic changes of the pedalling movement as an adaptive response to an externally determined increase in workload. Future research may utilise the findings from this study to investigate possible relationships between subjective measures of exhaustion, comfort, and discomfort with biomechanic characteristics of the pedalling movement and to evaluate connections with dynamic stability measures.

Validation of an inertial measurement unit for the quantification of rearfoot kinematics during running.

BACKGROUND: The popular protocol used to study running motion suffers from problems that lead to a limited ability to generalize the obtained results. Inertial measurement units (IMU) appear to be promising in increasing ecological validity of the collected data. However, quantifying running kinematics utilizing IMU signals is complex and potentially affected by several well-established and less well-known errors. RESEARCH QUESTION: The purpose of this study was to examine the validity of kinematic variables obtained from a single, shoe-mounted IMU using an opto-electronic motion analysis reference system. METHODS: 51 recreational runners were analyzed, performing a single continuous run at three different speeds (10, 12, 15 km/h) on a treadmill. Descriptive statistics (Bland & Altman analysis, box plots, scatter plots) were employed to analyze the agreement between the two instruments. RESULTS: The findings of this study revealed considerable systematic and large random disagreement, which, in turn, is characterized by substantial inter-individual differences in the error distribution. These discrepancies may partly be explained by differences in foot strike behavior, resulting in varying degrees of vibration impact acting on the IMU. SIGNIFICANCE: Advances in IMU technology, as well as exploring new application approaches and signal processing strategies, might enhance the usability of IMUs in analyzing running kinematics.