research-article

Feature based random forest nurse care activity recognition using accelerometer data

Authors:

Carolin Lübbe,

Björn Friedrich,

Sebastian Fudickar,

Sandra Hellmers,

Andreas HeinAuthors Info & Claims

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

Pages 408 - 413

https://doi.org/10.1145/3410530.3414340

Published: 12 September 2020 Publication History

Abstract

The The 2nd Nurse Care Activity Recognition Challenge Using Lab and Field Data addresses the important issue about care and the need for assistance systems in the nursing profession like automatic documentation systems. Data of 12 different care activities were recorded with an accelerometer attached to the right arm of the nurses. Both, laboratory and field data were taken into account. The task was to classify each activity based on the accelerometer data. We participated as team Gudetama in the challenge. We trained a Random Forest classifier and achieved an accuracy of 61.11% on our internal test set.

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Cited By

Alam GMcChesney INicholl PRafferty J(2023)Open Datasets in Human Activity Recognition Research—Issues and Challenges: A ReviewIEEE Sensors Journal10.1109/JSEN.2023.331764523:22(26952-26980)Online publication date: 15-Nov-2023
https://doi.org/10.1109/JSEN.2023.3317645
Wang AZhao SChen G(2021)Human Activity Recognition from Accelerometer Data: Axis-Wise Versus Axes-Resultant Feature ExtractionProceedings of the 5th International Conference on Computer Science and Application Engineering10.1145/3487075.3487152(1-5)Online publication date: 19-Oct-2021
https://dl.acm.org/doi/10.1145/3487075.3487152
Rahman AHassan IAhad M(2021)Nurse Care Activity Recognition: A Cost-Sensitive Ensemble Approach to Handle Imbalanced Class Problem in the WildAdjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers10.1145/3460418.3479389(440-445)Online publication date: 21-Sep-2021
https://dl.acm.org/doi/10.1145/3460418.3479389
Show More Cited By

Index Terms

Feature based random forest nurse care activity recognition using accelerometer data
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Neural networks
2. Human-centered computing
  1. Ubiquitous and mobile computing

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Published In

cover image ACM Conferences

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

September 2020

732 pages

ISBN:9781450380768

DOI:10.1145/3410530

General Chairs:
Monica Tentori
CICESE, Mexico
,
Nadir Weibel
UC San Diego
,
Kristof Van Laerhoven
University of Siegen, Germany
,
Program Chairs:
Gregory Abowd
Georgia Tech
,
Flora Salim
RMIT, Australia

Copyright © 2020 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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Association for Computing Machinery

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Publication History

Published: 12 September 2020

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Lower Saxony Ministry of Science and Culture

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UbiComp/ISWC '20

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UbiComp/ISWC '20: 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2020 ACM International Symposium on Wearable Computers

September 12 - 17, 2020

Virtual Event, Mexico

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

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Cited By

Alam GMcChesney INicholl PRafferty J(2023)Open Datasets in Human Activity Recognition Research—Issues and Challenges: A ReviewIEEE Sensors Journal10.1109/JSEN.2023.331764523:22(26952-26980)Online publication date: 15-Nov-2023
https://doi.org/10.1109/JSEN.2023.3317645
Wang AZhao SChen G(2021)Human Activity Recognition from Accelerometer Data: Axis-Wise Versus Axes-Resultant Feature ExtractionProceedings of the 5th International Conference on Computer Science and Application Engineering10.1145/3487075.3487152(1-5)Online publication date: 19-Oct-2021
https://dl.acm.org/doi/10.1145/3487075.3487152
Rahman AHassan IAhad M(2021)Nurse Care Activity Recognition: A Cost-Sensitive Ensemble Approach to Handle Imbalanced Class Problem in the WildAdjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers10.1145/3460418.3479389(440-445)Online publication date: 21-Sep-2021
https://dl.acm.org/doi/10.1145/3460418.3479389
Alia SLago PAdachi KHossain TGoto HOkita TInoue STentori MWeibel NVan Laerhoven KAbowd GSalim F(2020)Summary of the 2 nurse care activity recognition challenge using lab and field dataAdjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers10.1145/3410530.3414611(378-383)Online publication date: 10-Sep-2020
https://dl.acm.org/doi/10.1145/3410530.3414611

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