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.

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.