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

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

Producción: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

17 Citas (Scopus)

Resumen

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.

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017
Editorial	Association for Computing Machinery
ISBN (versión digital)	9781450348447
DOI	https://doi.org/10.1145/3102304.3105828
Estado	Publicada - 19 jul 2017
Publicado de forma externa	Sí
Evento	2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017 - Cambridge, Reino Unido Duración: 19 jul 2017 → 20 jul 2017

Serie de la publicación

Nombre	ACM International Conference Proceeding Series
Volumen	Part F130522

Conferencia

Conferencia	2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017
País/Territorio	Reino Unido
Ciudad	Cambridge
Período	19/07/17 → 20/07/17

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 3: Salud y bienestar

Acceder al documento

10.1145/3102304.3105828

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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. En Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017 Artículo 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. En 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, Reino Unido, 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).

Producción: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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. En 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

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