Morphological Computation of Skin Focusing on Fingerprint Structure

When humans get tactile sensation, we touch an object with the skin and the stimuli are transmitted to the brain. The effect of the skin in tactile perception however has not been clarified yet, and sensors considering the skin functions are not introduced. In this research, we investigate the information processing performed by the skin against physical stimuli in touching an object from the viewpoint of morphological computation. We create a dynamical model that expresses the skin structure based on the spring and mass model, and show that the model contributes to the learning of temporal response against physical stimuli. In addition, we conduct an experiment to compare the learning performance of a finger model having fingerprints with a model without fingerprints. Frequency response against physical stimuli with different frequencies is examined, and the result shows that the performance of a model with fingerprints is better in the higher frequency range. The model with fingerprints also reflects the hardness of the human skin remarkably. These results are expected to help clarify the information processing ability of the human skin focusing on the fingerprint structure in response to external physical stimuli.