Gregory J. Gerling, "SA-I Mechanoreceptor Position in Fingertip Skin May Impact Sensitivity to Edge Stimuli", Applied Bionics and Biomechanics, vol. 7, Article ID 874936, 11 pages, 2010. https://doi.org/10.1080/11762320903069992
SA-I Mechanoreceptor Position in Fingertip Skin May Impact Sensitivity to Edge Stimuli
Background: The skin plays a role in conditioning mechanical indentation into distributions of stress/strain that mechanoreceptors convert into neural signals. Solid mechanics methods have modelled the skin to predict the in vivo neural response from mechanoreceptors. Despite their promise, current models cannot explain the role that anatomical positioning and receptor organ morphology play in producing differences in neural response. This work hypothesises that the skin's intermediate ridges may help explain, in part, the sensitivity of slowly adapting type I (SA-I) mechanoreceptors to edge stimuli. Method: Two finite-element models of the fingertip were built, validated and used to analyse the functionality of the intermediate ridges. One of the two-dimensional, cross-sectional models included intermediate ridges, while the other did not. The analysis sought to determine if intermediate ridges (1) increase the magnitude of strain energy density (SED) near the SA-I location and (2) help differentiate one 2.0-mm indenter from two 0.5-mm wide indenters with a 1.0-mm gap. Results: Higher concentrations of SED were found near the tips of the intermediate ridges, the anatomical location that coincides with the SA-I receptors. This first result suggested that the location of the SA-Is in the stiffer epidermal tissue helps magnify their response to edge stimuli. The second result was that both models were equally capable of predicting the spatial structure within the in vivo neural responses, and therefore the addition of intermediate ridges did not help in differentiating the indenters. Conclusion: The finding, a 15%–35% increase in response when the sampling point lies within the stiffer tissue at the same depth, seeks to inform the positioning of force sensors in robotic skin substrates.
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