Dataset Information

Contact geometry and mechanics predict friction forces during tactile surface exploration.

ABSTRACT: When we touch an object, complex frictional forces are produced, aiding us in perceiving surface features that help to identify the object at hand, and also facilitating grasping and manipulation. However, even during controlled tactile exploration, sliding friction forces fluctuate greatly, and it is unclear how they relate to the surface topography or mechanics of contact with the finger. We investigated the sliding contact between the finger and different relief surfaces, using high-speed video and force measurements. Informed by these experiments, we developed a friction force model that accounts for surface shape and contact mechanical effects, and is able to predict sliding friction forces for different surfaces and exploration speeds. We also observed that local regions of disconnection between the finger and surface develop near high relief features, due to the stiffness of the finger tissues. Every tested surface had regions that were never contacted by the finger; we refer to these as "tactile blind spots". The results elucidate friction force production during tactile exploration, may aid efforts to connect sensory and motor function of the hand to properties of touched objects, and provide crucial knowledge to inform the rendering of realistic experiences of touch contact in virtual reality.

SUBMITTER: Janko M

PROVIDER: S-EPMC5861050 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Contact geometry and mechanics predict friction forces during tactile surface exploration.

Janko Marco M Wiertlewski Michael M Visell Yon Y

Scientific reports 20180320 1

When we touch an object, complex frictional forces are produced, aiding us in perceiving surface features that help to identify the object at hand, and also facilitating grasping and manipulation. However, even during controlled tactile exploration, sliding friction forces fluctuate greatly, and it is unclear how they relate to the surface topography or mechanics of contact with the finger. We investigated the sliding contact between the finger and different relief surfaces, using high-speed vid ...[more]

PMID: 29559728

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Project description:BackgroundWhen scanning surfaces, humans perceive some of their physical attributes. These percepts are frequently accompanied by a sensation of (un)pleasantness. We therefore hypothesized that aspects of the mechanical activity induced by scanning surfaces with fingertips could be objectively associated with a pleasantness sensation. Previously, we developed a unidimensional measure of pleasantness, the Pleasant Touch Scale, quantifying the pleasantness level of 37 different materials. Findings of this study suggested that the sensation of pleasantness was influenced by the average magnitude of the frictional forces brought about by sliding the finger on the surface, and by the surface topography. In the present study, we correlated (i) characteristics of the fluctuations of frictional forces resulting from the interaction between the finger and the surface asperities as well as (ii) the average friction with the sensation of pleasantness.ResultsEight blindfolded participants tactually explored twelve materials of the Pleasant Touch Scale through lateral sliding movements of their index fingertip. During exploration, the normal and tangential interaction force components, fN and fT , as well as the fingertip trajectory were measured. The effect of the frictional force on pleasantness sensation was investigated through the analysis of the ratio fT to fN , i.e. the net coefficient of kinetic friction, ?. The influence of the surface topographies was investigated through analysis of rapid fT fluctuations in the spatial frequency domain. Results showed that high values of ? were anticorrelated with pleasantness. Furthermore, surfaces associated with fluctuations of fT having higher amplitudes in the low frequency range than in the high one were judged to be less pleasant than the surfaces yielding evenly distributed amplitudes throughout the whole spatial frequency domain.ConclusionCharacteristics of the frictional force fluctuations and of the net friction taking place during scanning can reliably be correlated with the pleasantness sensation of surfaces.

Project description:Inverse dynamics problems are usually solved in the analysis of human gait to obtain reaction forces and moments at the joints. However, these actions are not the actual forces and moments supported by the joint structure, because they do not consider the forces of the muscles acting across the joint. Therefore, to analyse bone-on bone forces it is necessary to estimate those muscle forces. Usually, this problem is addressed by means of optimization algorithms. One of the parameters required to solve this problem is the musculotendon geometry. These data are usually taken from cadavers or MRI data from several subjects, different from the analysed subject. Then, the model is scaled to the subject morphology. This procedure constitutes a source of error. The goals of this work were two. First, to perform a sensitivity analysis of the influence of muscle insertion locations on the muscle forces acting on the hip joint and on the hip joint bone-on-bone forces. Second, to compare the hip joint bone-on-bone forces during gait cycle obtained through muscle insertion locations taken from a musculoskeletal model template and a scaling procedure to those obtained from a subject-specific model using an MRI of the subject. The problem was solved using OpenSim. Results showed that anatomical variability should be analysed from two perspectives. One the one hand, throughout the gait cycle, in a global way. On the other hand, at a characteristic instant of the gait cycle. Variations of ±1 cm in the position of the attachment points of certain muscles caused variations of up to 14.21% in averaged deviation of the muscle forces and 58.96% in the peak force in the modified muscle and variations up to 57.23% in the averaged deviation of the muscle force and up to 117.23% in the peak force in the rest of muscles. Then, the influence of that variability on muscle activity patterns and hip bone-on-bone forces could be described more precisely. A biomechanical analysis of a subject-specific musculoskeletal model was carried out. Using MRI data, variations up to 5 cm in the location of the insertion points were introduced. These modifications showed significant differences between the baseline model and the customized model: within the range [-12%, 10%] for muscle forces and around 35% of body weight for hip bone-on-bone forces.

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Contact geometry and mechanics predict friction forces during tactile surface exploration.

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Contact geometry and mechanics predict friction forces during tactile surface exploration.

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