IoT system for human activity recognition using bioharness 3 and smartphone

Camilo Rodriguez; Diego M. Castro; William Coral; Jose L. Cabra; Nicolas Velasquez; Julian Colorado; Diego Mendez; Luis C. Trujillo

doi:10.1145/3102304.3105828

IoT system for human activity recognition using bioharness 3 and smartphone

Camilo Rodriguez
, Diego M. Castro
, William Coral
, Jose L. Cabra
, Nicolas Velasquez
, Julian Colorado
, Diego Mendez
, Luis C. Trujillo

Universidad Javeriana
Center of Excellence in IoT (CEA-IoT)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

17 Scopus citations

Abstract

This paper presents an Internet of fiings (IoT) approach to Human Activity Recognition (HAR) using remote monitoring of vital signs in the context of a healthcare system for self-managed chronic heart patients. Our goal is to create a HAR-IoT system using learning algorithms to infer the activity done within 4 categories (lie, sit, walk and run) as well as the time consumed performing these activities and, finally giving feedback during and a?er the activity. Alike in thiswork, we provide a comprehensive insight on the cloudbased system implemented and the conclusions after implementing two different learning algorithms and the results of the overall system for larger implementations.

Original language	English
Title of host publication	Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450348447
DOIs	https://doi.org/10.1145/3102304.3105828
State	Published - 19 Jul 2017
Externally published	Yes
Event	2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017 - Cambridge, United Kingdom Duration: 19 Jul 2017 → 20 Jul 2017

Publication series

Name	ACM International Conference Proceeding Series
Volume	Part F130522

Conference

Conference	2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017
Country/Territory	United Kingdom
City	Cambridge
Period	19/07/17 → 20/07/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Bayesian classifier
CS5-Structural function
Human activity recognition (HAR)
IoT
W-Health

Access to Document

10.1145/3102304.3105828

Cite this

Rodriguez, C., Castro, D. M., Coral, W., Cabra, J. L., Velasquez, N., Colorado, J., Mendez, D., & Trujillo, L. C. (2017). IoT system for human activity recognition using bioharness 3 and smartphone. In Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017 Article 3105828 (ACM International Conference Proceeding Series; Vol. Part F130522). Association for Computing Machinery. https://doi.org/10.1145/3102304.3105828

@inproceedings{b55b22bb7c0c42b1965673c06c71a199,

title = "IoT system for human activity recognition using bioharness 3 and smartphone",

abstract = "This paper presents an Internet of fiings (IoT) approach to Human Activity Recognition (HAR) using remote monitoring of vital signs in the context of a healthcare system for self-managed chronic heart patients. Our goal is to create a HAR-IoT system using learning algorithms to infer the activity done within 4 categories (lie, sit, walk and run) as well as the time consumed performing these activities and, finally giving feedback during and a?er the activity. Alike in thiswork, we provide a comprehensive insight on the cloudbased system implemented and the conclusions after implementing two different learning algorithms and the results of the overall system for larger implementations.",

keywords = "Bayesian classifier, CS5-Structural function, Human activity recognition (HAR), IoT, W-Health",

author = "Camilo Rodriguez and Castro, \{Diego M.\} and William Coral and Cabra, \{Jose L.\} and Nicolas Velasquez and Julian Colorado and Diego Mendez and Trujillo, \{Luis C.\}",

note = "Publisher Copyright: {\textcopyright} 2017 Association for Computing Machinery.; 2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017 ; Conference date: 19-07-2017 Through 20-07-2017",

year = "2017",

month = jul,

day = "19",

doi = "10.1145/3102304.3105828",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

booktitle = "Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017",

}

Rodriguez, C, Castro, DM, Coral, W, Cabra, JL, Velasquez, N, Colorado, J , Mendez, D & Trujillo, LC 2017, IoT system for human activity recognition using bioharness 3 and smartphone. in Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017., 3105828, ACM International Conference Proceeding Series, vol. Part F130522, Association for Computing Machinery, 2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017, Cambridge, United Kingdom, 19/07/17. https://doi.org/10.1145/3102304.3105828

IoT system for human activity recognition using bioharness 3 and smartphone. / Rodriguez, Camilo; Castro, Diego M.; Coral, William et al.
Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017. Association for Computing Machinery, 2017. 3105828 (ACM International Conference Proceeding Series; Vol. Part F130522).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - IoT system for human activity recognition using bioharness 3 and smartphone

AU - Rodriguez, Camilo

AU - Castro, Diego M.

AU - Coral, William

AU - Cabra, Jose L.

AU - Velasquez, Nicolas

AU - Colorado, Julian

AU - Mendez, Diego

AU - Trujillo, Luis C.

PY - 2017/7/19

Y1 - 2017/7/19

N2 - This paper presents an Internet of fiings (IoT) approach to Human Activity Recognition (HAR) using remote monitoring of vital signs in the context of a healthcare system for self-managed chronic heart patients. Our goal is to create a HAR-IoT system using learning algorithms to infer the activity done within 4 categories (lie, sit, walk and run) as well as the time consumed performing these activities and, finally giving feedback during and a?er the activity. Alike in thiswork, we provide a comprehensive insight on the cloudbased system implemented and the conclusions after implementing two different learning algorithms and the results of the overall system for larger implementations.

AB - This paper presents an Internet of fiings (IoT) approach to Human Activity Recognition (HAR) using remote monitoring of vital signs in the context of a healthcare system for self-managed chronic heart patients. Our goal is to create a HAR-IoT system using learning algorithms to infer the activity done within 4 categories (lie, sit, walk and run) as well as the time consumed performing these activities and, finally giving feedback during and a?er the activity. Alike in thiswork, we provide a comprehensive insight on the cloudbased system implemented and the conclusions after implementing two different learning algorithms and the results of the overall system for larger implementations.

KW - Bayesian classifier

KW - CS5-Structural function

KW - Human activity recognition (HAR)

KW - IoT

KW - W-Health

UR - https://www.scopus.com/pages/publications/85030481865

U2 - 10.1145/3102304.3105828

DO - 10.1145/3102304.3105828

M3 - Conference contribution

AN - SCOPUS:85030481865

T3 - ACM International Conference Proceeding Series

BT - Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017

PB - Association for Computing Machinery

T2 - 2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017

Y2 - 19 July 2017 through 20 July 2017

ER -

Rodriguez C, Castro DM, Coral W, Cabra JL, Velasquez N, Colorado J et al. IoT system for human activity recognition using bioharness 3 and smartphone. In Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017. Association for Computing Machinery. 2017. 3105828. (ACM International Conference Proceeding Series). doi: 10.1145/3102304.3105828

IoT system for human activity recognition using bioharness 3 and smartphone

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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