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An energy harvesting wearable ring platform for gesture input on surfaces

  • Jeremy Gummeson
  • , Bodhi Priyantha
  • , Jie Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a remote gesture input solution for interacting indirectly with user interfaces on mobile and wearable devices. The proposed solution uses a wearable ring platform worn on users index finger. The ring detects and interprets various gestures performed on any available surface, and wirelessly transmits the gestures to the remote device. The ring opportunistically harvests energy from an NFC-enabled phone for perpetual operation without explicit charging. We use a finger-tendon pressure-based solution to detect touch, and a light-weight audio based solution for detecting finger motion on a surface. The two level energy efficient classification algorithms identify 23 unique gestures that include tapping, swipes, scrolling, and strokes for hand written text entry. The classification algorithms have an average accuracy of 73% with no explicit user training. Our implementation supports 10 hours of interactions on a surface at 2 Hz gesture frequency. The prototype was built with off-the-shelf components has a size similar to a large ring.

Original languageEnglish
Title of host publicationMobiSys 2014 - Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services
PublisherAssociation for Computing Machinery
Pages162-175
Number of pages14
ISBN (Print)9781450327930
DOIs
StatePublished - 2 Jun 2014
Externally publishedYes
Event12th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 2014 - Bretton Woods, NH, United States
Duration: 16 Jun 201419 Jun 2014

Publication series

NameMobiSys 2014 - Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services

Conference

Conference12th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 2014
Country/TerritoryUnited States
CityBretton Woods, NH
Period16/06/1419/06/14

Keywords

  • energy harvesting
  • gesture input
  • machine learning
  • near field communications
  • wearable computing

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