Incorporating Machine Learning Strategies to Smart Gloves Enabled by Dual-Network Hydrogels for Multitask Control and User Identification

ACS Sens. 2024 Apr 26;9(4):1886-1895. doi: 10.1021/acssensors.3c02609. Epub 2024 Mar 26.

Abstract

Smart gloves are often used in human-computer interaction scenarios due to their portability and ease of integration. However, their application in the field of information security has been less studied. Herein, we propose a smart glove using an iontronic capacitive sensor with significant pressure-sensing performance. Besides, an operator interface has been developed to match the smart glove, which is capable of multitasking integration of mouse movement, music playback, game control, and message typing in Internet chat rooms by capturing and encoding finger-tapping movements. In addition, by integrating machine learning, we can mine the characteristics of individual behavioral habits contained in the sensor signals and, based on this, achieve a deep binding of the user to the smart glove. The proposed smart glove can greatly facilitate people's lives, as well as explore a new strategy in research on the application of smart gloves in data security.

Keywords: hydrogel; machine learning; multitask integration; pressure sensing; smart glove.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Security
  • Gloves, Protective
  • Humans
  • Hydrogels* / chemistry
  • Machine Learning*
  • User-Computer Interface

Substances

  • Hydrogels