Review of capacitive touchscreen technologies: Overview, research trends, and machine learning approaches

Hyoungsik Nam, Ki Hyuk Seol, Junhee Lee, Hyeonseong Cho, Sang Won Jung

Research output: Contribution to journalReview articlepeer-review

44 Citations (Scopus)

Abstract

Touchscreens have been studied and developed for a long time to provide user-friendly and intuitive interfaces on displays. This paper describes the touchscreen technologies in four categories of resistive, capacitive, acoustic wave, and optical methods. Then, it addresses the main studies of SNR improvement and stylus support on the capacitive touchscreens that have been widely adopted in most consumer electronics such as smartphones, tablet PCs, and notebook PCs. In addition, the machine learning approaches for capacitive touchscreens are explained in four applications of user identification/authentication, gesture detection, accuracy improvement, and input discrimination.

Original languageEnglish
Article number4776
JournalSensors
Volume21
Issue number14
DOIs
Publication statusPublished - 2 Jul 2021

Bibliographical note

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Capacitive
  • Display
  • Machine learning
  • SNR
  • Stylus
  • Touchscreen

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