research-article

Unsupervised online activity discovery using temporal behaviour assumption

Authors:

Hristijan Gjoreski,

Daniel RoggenAuthors Info & Claims

ISWC '17: Proceedings of the 2017 ACM International Symposium on Wearable Computers

Pages 42 - 49

https://doi.org/10.1145/3123021.3123044

Published: 11 September 2017 Publication History

Abstract

We present a novel unsupervised approach, UnADevs, for discovering activity clusters corresponding to periodic and stationary activities in streaming sensor data. Such activities usually last for some time, which is exploited by our method; it includes mechanisms to regulate sensitivity to brief outliers and can discover multiple clusters overlapping in time to better deal with deviations from nominal behaviour. The method was evaluated on two activity datasets containing large number of activities (14 and 33 respectively) against online agglomerative clustering and DBSCAN. In a multi-criteria evaluation, our approach achieved significantly better performance on majority of the measures, with the advantages that: (i) it does not require to specify the number of clusters beforehand (it is open ended); (ii) it is online and can find clusters in real time; (iii) it has constant time complexity; (iv) and it is memory efficient as it does not keep the data samples in memory. Overall, it has managed to discover 616 of the total 717 activities. Because it discovers clusters of activities in real time, it is ideal to work alongside an active learning system.

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Cited By

Gunthermann L(2023)Application for Doctoral Consortium IUI 2023Companion Proceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581754.3584112(233-236)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1145/3581754.3584112
Zhou BGeissler DFaulhaber MGleiss CZahn ERay LGamarra DRey VSuh SBian SJoost GLukowicz P(2023)MoCaPoseProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35808837:1(1-40)Online publication date: 28-Mar-2023
https://dl.acm.org/doi/10.1145/3580883
Kann BCastellanos-Paez SLalanda P(2023)Evaluation of Regularization-based Continual Learning Approaches: Application to HAR2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops56833.2023.10150281(460-465)Online publication date: 13-Mar-2023
https://doi.org/10.1109/PerComWorkshops56833.2023.10150281
Show More Cited By

Index Terms

Unsupervised online activity discovery using temporal behaviour assumption
1. Computing methodologies
  1. Machine learning
2. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

ISWC '17: Proceedings of the 2017 ACM International Symposium on Wearable Computers

September 2017

276 pages

ISBN:9781450351881

DOI:10.1145/3123021

General Chairs:
Seungyon "Claire" Lee
Google
,
Leila Takayama
UC Santa Cruz
,
Khai Truong
University of Toronto
,
Program Chairs:
Jennifer Healey
Intel Labs
,
Thomas Ploetz
Georgia Tech

Copyright © 2017 ACM.

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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Publication History

Published: 11 September 2017

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Engineering and Physical Sciences Research Council

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UbiComp '17

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UbiComp '17: The 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 11 - 15, 2017

Hawaii, Maui

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Overall Acceptance Rate 38 of 196 submissions, 19%

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Cited By

Gunthermann L(2023)Application for Doctoral Consortium IUI 2023Companion Proceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581754.3584112(233-236)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1145/3581754.3584112
Zhou BGeissler DFaulhaber MGleiss CZahn ERay LGamarra DRey VSuh SBian SJoost GLukowicz P(2023)MoCaPoseProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35808837:1(1-40)Online publication date: 28-Mar-2023
https://dl.acm.org/doi/10.1145/3580883
Kann BCastellanos-Paez SLalanda P(2023)Evaluation of Regularization-based Continual Learning Approaches: Application to HAR2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops56833.2023.10150281(460-465)Online publication date: 13-Mar-2023
https://doi.org/10.1109/PerComWorkshops56833.2023.10150281
Adaimi RThomaz E(2022)Lifelong Adaptive Machine Learning for Sensor-Based Human Activity Recognition Using Prototypical NetworksSensors10.3390/s2218688122:18(6881)Online publication date: 12-Sep-2022
https://doi.org/10.3390/s22186881
Hiremath SNishimura YChernova SPlötz T(2022)Bootstrapping Human Activity Recognition Systems for Smart Homes from ScratchProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35502946:3(1-27)Online publication date: 7-Sep-2022
https://dl.acm.org/doi/10.1145/3550294
Ahmed AHaresamudram HPloetz T(2022)Clustering of Human Activities from Wearables by Adopting Nearest NeighborsProceedings of the 2022 ACM International Symposium on Wearable Computers10.1145/3544794.3558477(1-5)Online publication date: 11-Sep-2022
https://dl.acm.org/doi/10.1145/3544794.3558477
Ghosh MChoudhury S(2022)An Online Activity Monitoring for Geriatric Care Using Ambient SensorsSN Computer Science10.1007/s42979-022-01224-83:5Online publication date: 17-Jun-2022
https://doi.org/10.1007/s42979-022-01224-8
Hossen MHong OCaesarendra W(2022)Investigation of the Unsupervised Machine Learning Techniques for Human Activity DiscoveryProceedings of the 2nd International Conference on Electronics, Biomedical Engineering, and Health Informatics10.1007/978-981-19-1804-9_38(499-514)Online publication date: 25-Jun-2022
https://doi.org/10.1007/978-981-19-1804-9_38
Hwang YPark SLee HKo SLee B(2021)Deep Learning for Human Activity Recognition Based on Causality Feature ExtractionIEEE Access10.1109/ACCESS.2021.31032119(112257-112275)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3103211
Ye JCallus E(2020)Evolving models for incrementally learning emerging activitiesJournal of Ambient Intelligence and Smart Environments10.3233/AIS-20056612:4(313-325)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.3233/AIS-200566
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