One Light Touch: A Simulation of the Sensory Cell Network in the Finger

Abstract

While studies of the mechanical properties of the human hand advances, the exploration of the sensory properties of the hand is lacking. In the light of the advancements in robotic hand models, the sensory properties of the hand prove to be as important as its mechanical counterparts in order to fully develop a well-rounded prosthetic hand. As a basis of further exploration of the sensory mechanisms of the hand, this thesis aims to simulate the response mechanisms and behaviors of sensory cells in the human hand. Although the human hand contains a variety of cells sensitive to different stimuli, the model presented in this thesis focuses on the sensory responses to touch. These cells are mechanoreceptors and are divided into four main types: Merkel cell, Meissner cell, Ruffinin cell, and Pacinian cell. Each of the cells has unique response patterns to different stimuli, and has unique influences on the response behaviors of other receptors in the neural network. This model seeks to reproduce both the individual firing patterns of each cell to different stimuli and the interactions between the cells in the neural network. The simulation presented in this thesis produces the response patterns of each mechanoreceptor located in a 1-cm by 1-cm by 0.2-cm patch of skin when stimulated by an input of a pinpoint skin displacement on the finger pad of the human index finger.