FingerFlex: Shape Memory Alloy-based Actuation on Fingers for Kinesthetic Haptic Feedback

Takuro Nakao, Kai Kunze, Megumi Isogai, Shinya Shimizu, Yun Suen Pai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The tactile and kinesthetic sensation of pushing a button is usually lost when interacting with modern devices like touchscreens and/or virtual reality platforms. We present FingerFlex, a standalone glove wearable actuating the metacarpophalangeal joint (MCP) of each finger via shape memory alloy (SMA). SMA actuation is subtle, silent, and light, making it ideal for actuation of the fingers which we use to simulate the sensation of pressing a button. For our first study, we evaluated the engineering performance of FingerFlex by altering the current and triggering different levels of stimuli to the user's fingers. We show that users can perceive at least 3 levels of actuation with an accuracy of 73%. For our second study, we found FingerFlex to perform significantly better in terms of input error on a virtual numblock of a keyboard with no significant change in perceived workload.

Original languageEnglish
Title of host publicationMUM 2020 - 19th International Conference on Mobile and Ubiquitous Multimedia, Proceedings
EditorsJessica Cauchard, Markus Lochtefeld
PublisherAssociation for Computing Machinery
Pages240-244
Number of pages5
ISBN (Electronic)9781450388702
DOIs
Publication statusPublished - 2020 Nov 22
Event19th International Conference on Mobile and Ubiquitous Multimedia, MUM 2020 - Virtual, Online, Germany
Duration: 2020 Nov 222020 Nov 25

Publication series

NameACM International Conference Proceeding Series

Conference

Conference19th International Conference on Mobile and Ubiquitous Multimedia, MUM 2020
Country/TerritoryGermany
CityVirtual, Online
Period20/11/2220/11/25

Keywords

  • Subtle haptics
  • finger actuation
  • kinesthetic feedback
  • shape memory alloy

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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