research-article

Nurse care activity recognition challenge: summary and results

Authors:

Sayeda Shamma Alia,

Tittaya Mairittha,

Nattaya Mairittha,

Yusuke Nishimura,

Tsuyoshi Okita,

François Charpillet,

Sozo InoueAuthors Info & Claims

UbiComp/ISWC '19 Adjunct: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers

Pages 746 - 751

https://doi.org/10.1145/3341162.3345577

Published: 09 September 2019 Publication History

Abstract

Although activity recognition has been studied for a long time now, research and applications have focused on physical activity recognition. Even if many application domains require the recognition of more complex activities, research on such activities has attracted less attention. One reason for this gap is the lack of datasets to evaluate and compare different methods. To promote research in such scenarios, we organized the Open Lab Nursing Activity Recognition Challenge focusing on the recognition of complex activities related to the nursing domain. Nursing domain is one of the domains that can benefit enormously from activity recognition but has not been researched due to lack of datasets. The competition used the CARE-COM Nurse Care Activity Dataset, featuring 7 activities performed by 8 subjects in a controlled environment with accelerometer sensors, motion capture and indoor location sensor. In this paper, we summarize the results of the competition.

References

[1]

Stefano Abbate, Marco Avvenuti, Francesco Bonatesta, Guglielmo Cola, Paolo Corsini, and Alessio Vecchio. 2012. A smartphone-based fall detection system. Pervasive and Mobile Computing 8, 6 (2012), 883 -- 899. Special Issue on Pervasive Healthcare.

Digital Library

[2]

Ling Bao and Stephen S. Intille. 2004. Activity Recognition from User-Annotated Acceleration Data. In Pervasive Computing. Pervasive 2004. Lecture Notes in Computer Science, vol 3001., A. Ferscha and F. Mattern (Eds.). Springer, Berlin, Heidelberg, Berlin, Heidelberg. arXiv:9780201398298

[3]

Xin Cao, Wataru Kudo, Chihiro Ito, Masaki Shuzo, and Eisaku Maeda. 2019. Activity Recognition with ST-GCN for 3D Motion Data. In HASCA '19 (Ubicomp '19).

Digital Library

[4]

Macarena Espinilla, Javier Medina, and Chris Nugent. 2018. UCAmI Cup. Analyzing the UJA Human Activity Recognition Dataset of Activities of Daily Living. Proceedings 2, 19 (2018).

[5]

J. Favela. 2013. Behavior-Aware Computing: Applications and Challenges. IEEE Pervasive Computing 12, 3 (July 2013), 14--17.

Digital Library

[6]

H. Gjoreski, M. Ciliberto, L. Wang, F. J. Ordonez Morales, S. Mekki, S. Valentin, and D. Roggen. 2018. The University of Sussex-Huawei Locomotion and Transportation Dataset for Multimodal Analytics With Mobile Devices. IEEE Access 6 (2018), 42592--42604.

[7]

Nazmul Haque, Mahir Mahbub, Hasan Tarek, Lutfun Nahar Lota, and Amin Assan Ali. 2019. Nurse Care Activity Recognition: A GRU-based approach with attention mechanism. In HASCA '19 (Ubicomp '19).

Digital Library

[8]

Sozo Inoue, Paula Lago, Tahera Hossein, Tittaya Mairittha, and Nattaya Mairittha. 2019. Integrating Activity Recognition and Nursing Care Records: the System, Deployment, and a Verification Study. IMWUT (2019). In Press.

Digital Library

[9]

Sozo Inoue, Paula Lago, Shingo Takeda, AliaShamma, Farina Faiz, Nattaya Mairittha, and Tittaya Mairittha. 2019. Nurse Care Activity Recognition Challenge.

[10]

Sozo Inoue, Naonori Ueda, Yasunobu Nohara, and Naoki Nakashima. 2015. Mobile Activity Recognition for a Whole Day: Recognizing Real Nursing Activities with Big Dataset. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '15). ACM, New York, NY, USA, 1269--1280.

Digital Library

[11]

Eusha Kadir, Pritom Saha Akash, Sadia Sharmin, Amin Ahsan Ali, and Mohammad Shoyaib. 2019. Can a Simple Approach Identify Complex Nurse Care Activity?. In HASCA '19 (Ubicomp '19).

Digital Library

[12]

Paula Lago, Fréderic Lang, Claudia Roncancio, Claudia Jiménez-Guarín, Radu Mateescu, and Nicolas Bonnefond. 2017. The ContextAct@A4H Real-Life Dataset of Daily-Living Activities. In Modeling and Using Context, Patrick Brézillon, Roy Turner, and Carlo Penco (Eds.). Springer International Publishing, Cham, 175--188.

[13]

Jonathan Lester, Tanzeem Choudhury, and Gaetano Borriello. 2006. A Practical Approach to Recognizing Physical Activities. In Pervasive Computing, Kenneth P. Fishkin, Bernt Schiele, Paddy Nixon, and Aaron Quigley (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 1--16.

Digital Library

[14]

Nazmus Sakib Patwary, Protap Kumar Saha, and Ifthakhar Ahmed. 2019. Nurse Care Activity Recognition Challenge Using A Supervised Methodology. In HASCA '19 (Ubicomp '19).

[15]

Lago Paula, Takeda Shingo, Sayeda Shamma Alia, Mairittha Tittaya, Mairittha Nattaya, and Inoue Sozo. 2019. Open Lab Nursing Activity Recognition Challenge. Technical Report 12. Kyushu Institute of Technology. https://ipsj.ixsq.nii.ac.jp/ej/index.php?active_action=repository_view_main_item_detail&page_id=13&block_id=8&item_id=196715&item_no=1

[16]

M. Stikic, D. Larlus, S. Ebert, and B. Schiele. 2011. Weakly Supervised Recognition of Daily Life Activities with Wearable Sensors. IEEE Transactions on Pattern Analysis and Machine Intelligence 33, 12 (Dec 2011), 2521--2537.

Digital Library

Cited By

Arrotta LCivitarese GChen XCumin JBettini C(2025)Multi-subject human activities: A survey of recognition and evaluation methods based on a formal frameworkExpert Systems with Applications10.1016/j.eswa.2024.126178267(126178)Online publication date: Apr-2025
https://doi.org/10.1016/j.eswa.2024.126178
Fukushi KNozaki YNishihara KNakahara K(2024)Few-shot generative model for skeleton-based human action synthesis using cross-domain adversarial learning2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV57701.2024.00390(3934-3943)Online publication date: 3-Jan-2024
https://doi.org/10.1109/WACV57701.2024.00390
Li XLiu JWang YKato J(2024)Spatio-Temporal Transformer with Hypergraph in Nursing Activity Recognition2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)10.1109/EMBC53108.2024.10781545(1-4)Online publication date: 15-Jul-2024
https://doi.org/10.1109/EMBC53108.2024.10781545
Show More Cited By

Index Terms

Nurse care activity recognition challenge: summary and results
1. Applied computing
  1. Life and medical sciences
    1. Health care information systems
2. Computing methodologies
  1. Machine learning

Recommendations

Nurse care activity recognition: a GRU-based approach with attention mechanism
UbiComp/ISWC '19 Adjunct: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers

Human activity recognition is a challenging task due to complexity and variations of human movements while performing activities by different subjects. Extracting features to model the temporal evolution of different movements plays an important role in ...
Can a simple approach identify complex nurse care activity?
UbiComp/ISWC '19 Adjunct: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers

For the last two decades, more and more complex methods have been developed to identify human activities using various types of sensors, e.g., data from motion capture, accelerometer, and gyroscopes sensors. To date, most of the researches mainly focus ...
Summary of the 2^nd nurse care activity recognition challenge using lab and field data
UbiComp/ISWC '20 Adjunct: Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers

2^nd Nurse Care Activity Recognition Challenge using Lab and Field Data is organized as a part of HASCA workshop and is continuation of Nurse Care Activity Recognition Challenge [7]. We give the description of the dataset and summarize the approaches ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

UbiComp/ISWC '19 Adjunct: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers

September 2019

1234 pages

ISBN:9781450368698

DOI:10.1145/3341162

General Chairs:
Robert Harle
Cambridge University
,
Katayoun Farrahi
University Of Southampton
,
Nicholas Lane
University Of Oxford And Samsung Ai

Copyright © 2019 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].

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 September 2019

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

UbiComp '19

Sponsor:

UbiComp '19: The 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 9 - 13, 2019

London, United Kingdom

Acceptance Rates

Overall Acceptance Rate 764 of 2,912 submissions, 26%

Upcoming Conference

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

29
Total Citations
View Citations
458
Total Downloads

Downloads (Last 12 months)29
Downloads (Last 6 weeks)2

Reflects downloads up to 02 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Arrotta LCivitarese GChen XCumin JBettini C(2025)Multi-subject human activities: A survey of recognition and evaluation methods based on a formal frameworkExpert Systems with Applications10.1016/j.eswa.2024.126178267(126178)Online publication date: Apr-2025
https://doi.org/10.1016/j.eswa.2024.126178
Fukushi KNozaki YNishihara KNakahara K(2024)Few-shot generative model for skeleton-based human action synthesis using cross-domain adversarial learning2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV57701.2024.00390(3934-3943)Online publication date: 3-Jan-2024
https://doi.org/10.1109/WACV57701.2024.00390
Li XLiu JWang YKato J(2024)Spatio-Temporal Transformer with Hypergraph in Nursing Activity Recognition2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)10.1109/EMBC53108.2024.10781545(1-4)Online publication date: 15-Jul-2024
https://doi.org/10.1109/EMBC53108.2024.10781545
Staab SAbt VSchmid HLuderschmidt JWetter MMartin L(2024)Classification of Nursing Care Activities Using Smartwatches2024 International Conference on Activity and Behavior Computing (ABC)10.1109/ABC61795.2024.10652176(1-10)Online publication date: 29-May-2024
https://doi.org/10.1109/ABC61795.2024.10652176
Rahman ANahid NSchuller BAhad M(2024)A stacked CNN and random forest ensemble architecture for complex nursing activity recognition and nurse identificationScientific Reports10.1038/s41598-024-81228-x14:1Online publication date: 30-Dec-2024
https://doi.org/10.1038/s41598-024-81228-x
Bruns FPauls AKoppelin FWallhoff F(2024)Activity Recognition of Nursing Tasks in a Hospital: Requirements and ChallengesPervasive Computing Technologies for Healthcare10.1007/978-3-031-59717-6_16(235-243)Online publication date: 4-Jun-2024
https://doi.org/10.1007/978-3-031-59717-6_16
Jeyakumar JSarker AGarcia LSrivastava M(2023)X-CHARProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35808047:1(1-28)Online publication date: 28-Mar-2023
https://dl.acm.org/doi/10.1145/3580804
Solimullah ARahman ASadik MPatwary NAlam MIslam A(2023)A comprehensive analysis of nurse care activity recognition using machine learning algorithmsPROCEEDINGS OF THE TIM20-21 PHYSICS CONFERENCE10.1063/5.0149094(050001)Online publication date: 2023
https://doi.org/10.1063/5.0149094
Ijaz MDiaz RChen C(2022)Multimodal Transformer for Nursing Activity Recognition2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW56347.2022.00224(2064-2073)Online publication date: Jun-2022
https://doi.org/10.1109/CVPRW56347.2022.00224
Rakib Sayem FSheikh MAhad M(2022)Bento Packaging Activity Recognition Based on Statistical FeaturesSensor- and Video-Based Activity and Behavior Computing10.1007/978-981-19-0361-8_13(207-216)Online publication date: 4-May-2022
https://doi.org/10.1007/978-981-19-0361-8_13
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten