We investigated the propagation patterns of cutaneous vibration in the hand during interactions with touched objects. Prior research has highlighted the importance of vibrotactile signals during haptic interactions, but little is known of how vibrations propagate throughout the hand. Furthermore, the extent to which the patterns of vibrations reflect the nature of the objects that are touched, and how they are touched, is unknown. Using an apparatus comprised of an array of accelerometers, we mapped and analyzed spatial distributions of vibrations propagating in the skin of the dorsal region of the hand during active touch, grasping, and manipulation tasks. We found these spatial patterns of vibration to vary systematically with touch interactions and determined that it is possible to use these data to decode the modes of interaction with touched objects. The observed vibration patterns evolved rapidly in time, peaking in intensity within a few milliseconds, fading within 20-30 ms, and yielding interaction-dependent distributions of energy in frequency bands that span the range of vibrotactile sensitivity. These results are consistent with findings in perception research that indicate that vibrotactile information distributed throughout the hand can transmit information regarding explored and manipulated objects. The results may further clarify the role of distributed sensory resources in the perceptual recovery of object attributes during active touch, may guide the development of approaches to robotic sensing, and could have implications for the rehabilitation of the upper extremity.touch | haptics | vibration | cutaneous | skin W hen we touch an object, a cascade of mechanical events ensues, and through it, vibration is transmitted, not just to the fingertips, but broadly within the hard and soft tissues of the hand. Prior research has shed light on mechanical signals generated during object palpation or manipulation, the transduction of such signals into neural signals, and the salience of different contact-generated stimuli. It has been shown that the responses of somatosensory neurons should be understood in light of perceptual functions that integrate input from several tactile submodalities (1, 2).Tactile mechanics yield numerous perceptual cues that inform the brain about key properties of the external mechanical world such as the presence of an object through contact (3), slip against a surface (4), object deformation (5, 6), and object shape (7,8). Among these cues, touch-induced vibrations play important roles. Until recently, it has been assumed that perceptual information generated during haptic interaction is confined to the region of skin-object contact. It has subsequently been demonstrated, however, that perceptually meaningful mechanical energy can propagate away from the origin of contact, sometimes beyond the hand itself (9, 10), and that humans are capable of using this information to evaluate surface roughness (11). Recent measurements have demonstrated that skin vibrations reflect the fin...
A key problem in the study of the senses is to describe how sense organs extract perceptual information from the physics of the environment. We previously observed that dynamic touch elicits mechanical waves that propagate throughout the hand. Here, we show that these waves produce an efficient encoding of tactile information. The computation of an optimal encoding of thousands of naturally occurring tactile stimuli yielded a compact lexicon of primitive wave patterns that sparsely represented the entire dataset, enabling touch interactions to be classified with an accuracy exceeding 95%. The primitive tactile patterns reflected the interplay of hand anatomy with wave physics. Notably, similar patterns emerged when we applied efficient encoding criteria to spiking data from populations of simulated tactile afferents. This finding suggests that the biomechanics of the hand enables efficient perceptual processing by effecting a preneuronal compression of tactile information.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.