research-article

Reducing user intervention in incremental activityrecognition for assistive technologies

Authors:

Julien Rebetez,

Héctor F. Satizábal,

Andres Perez-UribeAuthors Info & Claims

ISWC '13: Proceedings of the 2013 International Symposium on Wearable Computers

Pages 29 - 32

https://doi.org/10.1145/2493988.2494350

Published: 08 September 2013 Publication History

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Abstract

Activity recognition has recently gained a lot of interest and there already exist several methods to detect human activites based on wearable sensors. Most of the existing methods rely on a database of labelled activities that is used to train an offline activity recognition system. This paper presents an approach to build an online activity recognition system that do not require any a priori labelled data. The system incrementally learns activities by actively querying the user for labels. To choose when the user should be queried, we compare a method based on random sampling and another that uses a Growing Neural Gas (GNG). The use of GNG helps reducing the number of user queries by 20% to 30%.

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Cited By

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Akram AFarhan ABasharat A(2023)Less is more: Efficient behavioral context recognition using Dissimilarity-Based Query StrategyPLOS ONE10.1371/journal.pone.028691918:6(e0286919)Online publication date: 7-Jun-2023
https://doi.org/10.1371/journal.pone.0286919
Adaimi RThomaz E(2019)Leveraging Active Learning and Conditional Mutual Information to Minimize Data Annotation in Human Activity RecognitionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/33512283:3(1-23)Online publication date: 9-Sep-2019
https://dl.acm.org/doi/10.1145/3351228
Ao BWang YLiu HLi DSong LLi J(2018)Context Impacts in Accelerometer-Based Walk Detection and Step CountingSensors10.3390/s1811360418:11(3604)Online publication date: 24-Oct-2018
https://doi.org/10.3390/s18113604
Show More Cited By

Index Terms

Reducing user intervention in incremental activityrecognition for assistive technologies
1. Human-centered computing

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Information & Contributors

Information

Published In

ISWC '13: Proceedings of the 2013 International Symposium on Wearable Computers

September 2013

160 pages

ISBN:9781450321273

DOI:10.1145/2493988

General Chair:
Kristof Van Laerhoven
TU Darmstadt, Germany
,
Program Chairs:
Daniel Roggen
Newcastle University, UK
,
Daniel Gatica-Perez
Idiap and EPFL, Switzerland
,
Masaaki Fukumoto
Microsoft Research Asia, China

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 September 2013

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UbiComp '13

Sponsor:

SIGMOBILE
University of Florida
SIGCHI

UbiComp '13: The 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 8 - 12, 2013

Zurich, Switzerland

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ISWC '13 Paper Acceptance Rate 20 of 101 submissions, 20%;

Overall Acceptance Rate 38 of 196 submissions, 19%

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Cited By

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Akram AFarhan ABasharat A(2023)Less is more: Efficient behavioral context recognition using Dissimilarity-Based Query StrategyPLOS ONE10.1371/journal.pone.028691918:6(e0286919)Online publication date: 7-Jun-2023
https://doi.org/10.1371/journal.pone.0286919
Adaimi RThomaz E(2019)Leveraging Active Learning and Conditional Mutual Information to Minimize Data Annotation in Human Activity RecognitionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/33512283:3(1-23)Online publication date: 9-Sep-2019
https://dl.acm.org/doi/10.1145/3351228
Ao BWang YLiu HLi DSong LLi J(2018)Context Impacts in Accelerometer-Based Walk Detection and Step CountingSensors10.3390/s1811360418:11(3604)Online publication date: 24-Oct-2018
https://doi.org/10.3390/s18113604
Cook DKrishnan N(2015)BibliographyActivity Learning10.1002/9781119010258.biblio(237-251)Online publication date: 20-Feb-2015
https://doi.org/10.1002/9781119010258.biblio
Miu TPlötz TMissier PRoggen DBrush AFriday AKientz JScott JSong J(2014)On strategies for budget-based online annotation in human activity recognitionProceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication10.1145/2638728.2641300(767-776)Online publication date: 13-Sep-2014
https://dl.acm.org/doi/10.1145/2638728.2641300
Satizábal HPerez-Uribe A(2014)Unsupervised template discovery in activity recognition using the Gamma Growing Neural Gas algorithmSoft Computing10.1007/s00500-014-1499-y19:9(2435-2445)Online publication date: 2-Nov-2014
https://doi.org/10.1007/s00500-014-1499-y

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