Mindful interruptions: A lightweight system for managing interruptibility onwearables

Claudio Forlivesi, Utku Günay Acer, Marc Van Den Broeck, Fahim Kawsar

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

We present the design, development, and evaluation of a personalised, privacy-aware and multi-modal wearable-only system to model interruptibility. Our system runs as a background service of a wearable OS and operates on two key techniques: i) online learning to recognise interruptible situation at a personal scale and ii) runtime inference of opportune moments for an interruption. .e former is realised by a set of fast and ecient algorithms to automatically discover and learn interruptible situations as a function of meaningful places, and physical and conversational activities with active user engagement. .e la.er is substantiated with a multiphased context sensing mechanics to identify moments which are then utilised to delivery noti€cations and interactive contents at the right moment. Early experimental evaluation of our system shows a sharp 46% increase in the response rate of noti€cations in wearable se.ings at the expense of negligible 6.3% resource cost.

Original languageEnglish
Title of host publicationWearSys 2018 - Proceedings of the 4th ACM Workshop on Wearable Systems and Applications
Place of PublicationNew York, NY, USA
PublisherAssociation for Computing Machinery (ACM)
Pages27-32
Number of pages6
ISBN (Electronic)978-1-4503-5842-2
DOIs
Publication statusPublished - 2018
Event4th ACM Workshop on Wearable Systems and Applications, WearSys 2018: The 4th ACM Workshop on Wearable Systems and Applications - Munich, Germany
Duration: 10 Jun 201810 Jun 2018
Conference number: 4th

Conference

Conference4th ACM Workshop on Wearable Systems and Applications, WearSys 2018
Abbreviated titleWearSys 2018
CountryGermany
CityMunich
Period10/06/1810/06/18

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