Continuous finger gesture recognition based on flex sensors

Wei Chieh Chuang, Wen Jyi Hwang, Tsung Ming Tai, De Rong Huang, Yun Jie Jhang

Research output: Contribution to journalArticle

Abstract

The goal of this work is to present a novel continuous finger gesture recognition system based on flex sensors. The system is able to carry out accurate recognition of a sequence of gestures. Wireless smart gloves equipped with flex sensors were implemented for the collection of the training and testing sets. Given the sensory data acquired from the smart gloves, the gated recurrent unit (GRU) algorithm was then adopted for gesture spotting. During the training process for the GRU, the movements associated with different fingers and the transitions between two successive gestures were taken into consideration. On the basis of the gesture spotting results, the maximum a posteriori (MAP) estimation was carried out for the final gesture classification. Because of the effectiveness of the proposed spotting scheme, accurate gesture recognition was achieved even for complicated transitions between successive gestures. From the experimental results, it can be observed that the proposed system is an effective alternative for robust recognition of a sequence of finger gestures.

Original languageEnglish
Article number3986
JournalSensors (Switzerland)
Volume19
Issue number18
DOIs
Publication statusPublished - 2019 Sep 2

Keywords

  • Artificial intelligence
  • Gated recurrent unit
  • Hand gesture recognition
  • Human machine interface
  • Wireless smart gloves

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

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