Soft and Integrable Multimodal Artificial Mechanoreceptors Toward Human Sensor of Skin

Abstract

Herein, the development and characterization of three distinct artificial mechanoreceptor sensors meticulously engineered is reported to emulate human skin. By mimicking the morphology, structure, and response characteristics (including preferential sensitivity, adaptation profile, and frequency response) of biological mechanoreceptors, artificial Meissner, Merkel, and Ruffini sensors capable of detecting pressure, shear, and tensile deformations with high fidelity are successfully fabricated. In situ experiments, designed to mimic physiological conditions, demonstrate that the integrated sensor array, mimicking human fingertips, can accurately discriminate seven Braille characters, five distinct surface textures, a grating with ridges, and four-step delivery stages of an object. Furthermore, a woolen glove incorporating 15 multimodal sensors are developed, which exhibits enhanced classification capabilities for eight objects of varying sizes and surface roughness. Notably, the trimodal sensor integration demonstrates superior recognition speed and precision compared to uni- or bimodal configurations, while also improving tactile identification intuition. This biomimetic mechanoreceptor sensor system demonstrates comprehensive and synergistic recognition of diverse stimuli and objects, potentially overcoming technological limitations in applications requiring human-like tactile perception, such as advanced prosthetics, robotics, and immersive augmented and virtual reality interfaces.