Task Dynamics of Prior Training Influence Visual Force Estimation Ability During Teleoperation

The lack of haptic feedback in Robot-assisted Minimally Invasive Surgery (RMIS) is a potential barrier to safe tissue handling during surgery. Bayesian modeling theory suggests that surgeons with experience in open or laparoscopic surgery can develop priors of tissue stiffness that translate to better force estimation abilities during RMIS compared to surgeons with no experience. To test if prior haptic experience leads to improved force estimation ability in teleoperation, 33 participants were assigned to one of three training conditions: manual manipulation, teleoperation with force feedback, or teleoperation without force feedback, and learned to tension a silicone sample to a set of force values. They were then asked to perform the tension task, and a previously unencountered palpation task, to a different set of force values under teleoperation without force feedback. Compared to the teleoperation groups, the manual group had higher force error in the tension task outside the range of forces they had trained on, but showed better speed-accuracy functions in the palpation task at low force levels. This suggests that the dynamics of the training modality affect force estimation ability during teleoperation, with the prior haptic experience accessible if formed under the same dynamics as the task.Comment: 12 pages, 8 figure

Look but don't touch:Visual cues to surface structure drive somatosensory cortex

When planning interactions with nearby objects, our brain uses visual information to estimate shape, material composition, and surface structure before we come into contact with them. Here we analyse brain activations elicited by different types of visual appearance, measuring fMRI responses to objects that are glossy, matte, rough, or textured. In addition to activation in visual areas, we found that fMRI responses are evoked in the secondary somatosensory area (S2) when looking at glossy and rough surfaces. This activity could be reliably discriminated on the basis of tactile-related visual properties (gloss, rough, and matte), but importantly, other visual properties (i.e., coloured texture) did not substantially change fMRI activity. The activity could not be solely due to tactile imagination, as asking explicitly to imagine such surface properties did not lead to the same results. These findings suggest that visual cues to an object's surface properties evoke activity in neural circuits associated with tactile stimulation. This activation may reflect the a-priori probability of the physics of the interaction (i.e., the expectation of upcoming friction) that can be used to plan finger placement and grasp force.</p

The neural basis of visual material properties in the human brain

Three independent studies with human functional magnetic resonance imaging (fMRI) measurements were designed to investigate the neural basis of visual glossiness processing in the human brain. The first study is to localize brain areas preferentially responding to glossy objects defined by specular reflectance. We found activations related to gloss in the posterior fusiform (pFs) and in area V3B/KO. The second study is to investigate how the visual-induced haptic sensation is achieved in our brain. We found that in secondary somatosensory area (S2) was distinguishable between glossy and rough surfaces, suggesting that visual information about object surfaces may be transformed into tactile information in S2. In the third study we investigate how the brain processes surface gloss information conveyed by disparity of specular reflections on stereo mirror objects and compared it with the processing of specular reflectance. We found that both dorsal and ventral areas were involving in this processing. The result implicates that in this region the processing of stereoscopic gloss information has a pattern of activation that is additional to the representation of specular reflectance. Overall, the three studies contribute to our understanding about the neural basis of visual glossiness and material processing in the human brain

Computational Aspects of Softness Perception

Di Luca M, Ernst MO. Computational Aspects of Softness Perception. In: Di Luca M, ed. Multisensory Softness. Perceived Compliance from Multiple Sources of Information. Touch and Haptic Systems. Vol 11. London: Springer; 2014: 85-106