A Neuromorphic Model to Match the Spiking Activity of Merkel Mechanoreceptors With Biomimetic Tactile Sensors for Bioengineering Applications

A major challenge in upper limb neuroprostheses is to reproduce the tactile feedback as the one provided by the spiking activity of human mechanoreceptors. In this paper, we aim at emulating the firing behavior of Merkel mechanoreceptors, innervated by slowly adapting type I (SA1) receptors, in silico by means of a custom implementation of the Izhikevich spiking neuron model with a porting function of the sensors output. We matched the neuron model output with the sustained firing observed in neurophysiological experiments in response to constant stimuli to the skin. We compared different input transformation functions to find the proper trade-off between agreement with biological spiking activity and model leanness. We identified a porting function that converts the output of physical sensors into the input to artificial spiking models of mechanoreceptors. The porting function was then validated by comparing the firing rate-indentation curve of real mechanoreceptors with the one obtained from an MEMS-based biomimetic tactile sensor platform. From the analysis of the adjusted-residual variance, the two curves result coherent. Therefore, having applied the calibration inverse function to a sensor output, the proposed porting function allows obtaining the proper input to an artificial neuron model, enabling the generation of neuromorphic signals.