A MEMS-based tactile sensor to study human digital touch: mechanical transduction of the tactile information and role of fingerprints

Abstract

We present recent results showing that human epidermal ridges (fingerprints) could play a central role in fine texture discrimination tasks by spatially modulating the contact stress field between the fingertip and the substrate. Using an original biomimetic finger whose surface is patterned with parallel ridges, we demonstrate that the subsurface stress signals elicited by continuous rubbing of randomly textured substrates is dominated by fluctuations at a frequency defined by the inter-ridge distance divided by the rubbing velocity. In natural exploratory conditions, this frequency matches the best frequency of one type of mechanoreceptors, namely the Pacinian corpuscles, which are specifically involved in the tactile coding of fine textures. The use of white-noise patterned stimuli has alloowed us to extract, using a reverse-correlation analysis, the stimulus-signal response function associated with roughness modality. Its shape could provides spectral, spatial and directional selectivity to the digital tactile system. It offers a physiological basis for the recently proposed hypothesis of a dual-coding (spatio-temporal and vibratory) of tactile information.