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Texture-induced vibrations in the forearm during tactile exploration

Institute of Neuroscience, Université Catholique de Louvain Brussels, Belgium.
Frontiers in Behavioral Neuroscience (Impact Factor: 4.16). 07/2012; 6:37. DOI: 10.3389/fnbeh.2012.00037
Source: PubMed

ABSTRACT Humans can detect and discriminate between fine variations of surface roughness using active touch. It is hitherto believed that roughness perception is mediated mostly by cutaneous and subcutaneous afferents located in the fingertips. However, recent findings have shown that following abolishment of cutaneous afferences resulting from trauma or pharmacological intervention, the ability of subjects to discriminate between textures roughness was not significantly altered. These findings suggest that the somatosensory system is able to collect textural information from other sources than fingertip afference. It follows that signals resulting of the interaction of a finger with a rough surface must be transmitted to stimulate receptor populations in regions far away from the contact. This transmission was characterized by measuring in the wrist vibrations originating at the fingertip and thus propagating through the finger, the hand and the wrist during active exploration of textured surfaces. The spectral analysis of the vibrations taking place in the forearm tissues revealed regularities that were correlated with the scanned surface and the speed of exploration. In the case of periodic textures, the vibration signal contained a fundamental frequency component corresponding to the finger velocity divided by the spatial period of the stimulus. This regularity was found for a wide range of textural length scales and scanning velocities. For non-periodic textures, the spectrum of the vibration did not contain obvious features that would enable discrimination between the different stimuli. However, for both periodic and non-periodic stimuli, the intensity of the vibrations could be related to the microgeometry of the scanned surfaces.

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    • " this study , we have only considered the strength and frequency composition of skin vibrations close to the location of contact with the texture on the fingertip . However , high - frequency skin vibrations elicited at the fingertip propagate the full length of the finger ( Manfredi et al . 2012 ) and have been recorded as far away as the wrist ( Delhaye et al . 2012 ) . Skin vibrations also decay in a frequency - dependent manner , a mechanism that , at least on the finger , amplifies frequencies in the PC response range ( Manfredi et al . 2012 ) . Given the exquisite sensitivity of PC fibers to high - frequency vibrations ( with thresholds below 1 ␮m around 250 Hz ) , texture - elicited vibrations"
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    ABSTRACT: Sensory systems are designed to extract behaviorally relevant information from the environment. In seeking to understand a sensory system, it is important to understand the environment within which it operates. In the present study, we seek to characterize the natural scenes of tactile texture perception. During tactile exploration, complex high-frequency vibrations are elicited in the fingertip skin, and these vibrations are thought to carry information about the surface texture of manipulated objects. How these texture-elicited vibrations depend on surface microgeometry and on the biomechanical properties of the fingertip skin itself remains to be elucidated. Here, we record skin vibrations, using a laser Doppler vibrometer, as various textured surfaces are scanned across the finger. We find that the frequency composition of elicited vibrations is texture-specific and highly repeatable. In fact, textures can be classified with high accuracy based on the vibrations they elicit in the skin. As might be expected, some aspects of surface microgeometry are directly reflected in the skin vibrations. However, texture vibrations are also determined in part by fingerprint geometry. This mechanism enhances textural features that are too small to be resolved spatially, given the limited spatial resolution of the neural signal. We conclude that it is impossible to understand the neural basis of texture perception without first characterizing the skin vibrations that drive neural responses, given the complex dependence of skin vibrations on both surface microgeometry and fingertip biomechanics.
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    ABSTRACT: The textures of surfaces are tactually perceived mostly from the vibrations generated when sliding our fingertips on them. Despite its prevalence in everyday behavior, the study of the interaction of a finger with a textured surface, for virtual reality purposes, has not been much studied.This thesis explores some factors that contribute to the mechanics of interaction between a bare finger and a surface with a view to their artificial reproduction. The recording and reproduction of tactual textures are first discussed, along with a specifically designed apparatus able to precisely measure the interaction force arising from the friction of a sliding finger. The same piezoelectric-based apparatus was employed to rapidly deform the fingertip during exploratory movement, in order to replicate the presence of a texture, resulting in a new approach to simulate the roughness and texture of virtual surfaces. The problem of recording-reproducing textured surfaces motivated the question of the determination of the mechanical behavior of the fingertip. Investigations revealed that fingertips behave like elastic springs at low frequencies, and that after a corner frequency of about 100 Hz, the response is dominated by viscous damping, something that was never directly shown before. Next, the features of the vibratory signals created by the friction of a finger on various textures were analyzed. Expressing the fluctuations of the frictional force as function of space, rather than of time, indicated a number of possible signal characteristics that could play a key role in the tactual perception textures. The thesis highlights the importance of the mechanics and biomechanics during the haptic exploration of surfaces and their possible contribution to perception. Collectively, the findings reported in this thesis are pertinent to the design of effective virtual reality systems and other applications.
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    ABSTRACT: Grasping is one of the most common forms of dexterity. So far, most research has focused on slow-varying loads which can be resisted by anticipatory grip adjustments. There are common cases, however, when a rapid, unexpected increase in the load occurs and where the central nervous system must re-adjust the grip dynamically to prevent slippage. During such events, the central nervous system reactively updates the grip force to minimize further escape of an object. While existing theories postulates that the shear strain of the finger pads caused by the load force is a primary source of information for detecting a new load condition, vibrations induced by even minute object slip in the hand might more effectively signal the occurrence of unwanted movement of the object relatively to the hand. With the help of a high-sensitivity force sensor interposed in the load-path of a fast traction-creating device, we recorded the fluctuations of the force projected onto the fingertip when a rapid perturbation was applied to a grasped object. These fluctuations are indicative of slip. The results highlight the existence of a correlation between the amplitude of the vibrations and the grip force modulation, when textural features are present. The study provides promising evidence that the central nervous system exploits vibrations to detect the onset of unwanted movement of an object relatively to the hand to optimally scale the grip force in response to unexpected, rapid load variations.
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