Fig 1.
When skiing down a slope, one may relax their legs to filter out perturbations in clear conditions (left panel), or stiffen them to better sense the terrain in low visibility, such as at dawn or in fog (right).
Original photographies from Unsplash, courtesy of Andri Klopfenstein (left) and Greg Rosenke (right).
Fig 2.
Experiment setup and protocol.
A: Participants were asked to track a randomly moving target with noisy visual feedback and in some conditions were connected to the human-like tracking controller of [33]. B,C: Experiment protocol of separate visual or haptic feedback experiment, with each block consisting of nine trials. The 13 participants received only visual/haptic feedback in random order and each with random noise level (B). Another 22 participants experienced nine integrated visual and haptic conditions presented in a random order (C). (D) illustrates the mechanical modeling scheme of the human-robot interaction with visual and haptic noise.
Fig 3.
Results of solely visual/haptic feedback experiment.
A&B: Evolution of tracking error and coactivation with visual and/or haptic feedback, where error bars represent standard error. C&D: The mean and standard error of tracking error and coactivation for all subjects during the last four trials. In the visual feedback condition (A&C), with increasing visual noise the tracking error increases while the coactivation decreases. In the haptic feedback condition (B&D), there is a decaying trend of both tracking error and coactivation over the trials and no clear difference among noise conditions.
Fig 4.
Results of tracking with combined visual and haptic noise.
A: Evolution of tracking error and coactivation with visual or haptic feedback, with error bars representing the standard error. The tracking error saturates in the initial solo trials, and increases with both visual and haptic noise during interactive trials. coactivation shows a slower decrease across trials. B: Mean and standard error of tracking error and coactivation for all subjects during the last four trials. Tracking error increases with either visual or haptic noise, while muscle coactivation increases with haptic noise and decreases with visual noise. C: Muscle coactivation and reciprocal activation waveforms along with their frequency spectrum. Muscle coactivation remains relatively constant, while reciprocal activation changes synchronized with the movement, as is confirmed by their spectra.
Fig 5.
Simulation results of normalized coactivation.
(A) Comparison between the tracking error minimization (TEM) model and our optimal information and effort (OIE) model across the nine experiment conditions. The OIE model predicted normalized coactivation values closely aligned with the experimental data, while the TEM model produced large prediction errors. (B) OIE model predictions of normalized coactivation as a function of visual and haptic noise levels. Black dots represent the recorded average coactivation of 20 participants in the final trial. Red dots represent the fitted data from the OIE model. The blue dots show the model’s predicted coactivation in unobserved noise conditions.
Table 1.
Identified effective visual and haptic noise values.