Personal protective gloves with objects recognizing for rescuing in disaster

Abstract

Tactile sensing ability of human hands were the unique critical way to feel diverse objects and infer material properties which remains challenging tasks for intelligent personal protective glove, especially for salvager rescuing in disaster in some extreme environment such as earthquake, fire, avalanche or the night without light. Tactile maps of hands have been precisely recorded and analyzed by smart gloves with film-based sensor arrays, however, the comfortable and breathable performance of film-decorated gloves can’t be satisfied with long wearing time. Herein, a flexible knitted-based protective tactile sensing glove with low cost (about US$1.383) is fabricated by seamlessly stitching tiny micro-patterned (400 μm) sensors through 3D two-photon femtosecond laser direct writing strategy. The proposed tactile sensors exhibited a tunable sensing detection (0.002 kPa ∼ 300 kPa) and tunable sensitivities (0.011 kPa−1 ∼ 0.082 kPa−1). Our protective tactile sensing gloves are developed by distributing numbers of tiny tactile sensors on the glove to recognize diverse objects enabled by learning the signatures through an artificial neural network of the fully connect neural network, which can work in air, water, low temperature (−40 °C) and high temperature (116 °C) for protecting hands. Additionally, demonstrations of the protective tactile sensing glove for recognizing different hardness and different shape objects which can be used for salvager rescuing in disaster.