loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock
Sampling Frequency Evaluation on Recurrent Neural Networks Architectures for IoT Real-time Fall Detection Devices

Topics: Applications: Image Processing and Artificial Vision, Pattern Recognition, Decision Making, Industrial and Real World Applications, Financial Applications, Neural Prostheses and Medical Applications, Neural Based Data Mining and Complex Information Process; Deep Learning; Recurrent Neural Networks

Authors: F. Luna-Perejon ; J. P. Civit-Masot ; L. Muñoz-Saavedra ; L. Duran-Lopez ; I. Amaya-Rodriguez ; J. P. Dominguez-Morales ; S. Vicente-Diaz ; A. Linares-Barranco ; A. Civit-Balcells and M. J. Dominguez-Morales

Affiliation: Robotics and Computer Technology Lab., University of Seville, Seville 41012 and Spain

Keyword(s): Fall Detection, Recurrent Neural Network, Deep Learning, Internet of Things.

Abstract: Falls are one of the most frequent causes of injuries in elderly people. Wearable Fall Detection Systems provided a ubiquitous tool for monitoring and alert when these events happen. Recurrent Neural Networks (RNN) are algorithms that demonstrates a great accuracy in some problems analyzing sequential inputs, such as temporal signal values. However, their computational complexity are an obstacle for the implementation in IoT devices. This work shows a performance analysis of a set of RNN architectures when trained with data obtained using different sampling frequencies. These architectures were trained to detect both fall and fall hazards by using accelerometers and were tested with 10-fold cross validation, using the F1-score metric. The results obtained show that sampling with a frequency of 25Hz does not affect the effectiveness, based on the F1-score, which implies a substantial increase in the performance in terms of computational cost. The architectures with two RNN layers and without a first dense layer had slightly better results than the smallest architectures. In future works, the best architectures obtained will be integrated in an IoT solution to determine the effectiveness empirically. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.191.223.123

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Luna-Perejon, F.; Civit-Masot, J.; Muñoz-Saavedra, L.; Duran-Lopez, L.; Amaya-Rodriguez, I.; Dominguez-Morales, J.; Vicente-Diaz, S.; Linares-Barranco, A.; Civit-Balcells, A. and Dominguez-Morales, M. (2019). Sampling Frequency Evaluation on Recurrent Neural Networks Architectures for IoT Real-time Fall Detection Devices. In Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - NCTA; ISBN 978-989-758-384-1; ISSN 2184-3236, SciTePress, pages 536-541. DOI: 10.5220/0008494805360541

@conference{ncta19,
author={F. Luna{-}Perejon. and J. P. Civit{-}Masot. and L. Muñoz{-}Saavedra. and L. Duran{-}Lopez. and I. Amaya{-}Rodriguez. and J. P. Dominguez{-}Morales. and S. Vicente{-}Diaz. and A. Linares{-}Barranco. and A. Civit{-}Balcells. and M. J. Dominguez{-}Morales.},
title={Sampling Frequency Evaluation on Recurrent Neural Networks Architectures for IoT Real-time Fall Detection Devices},
booktitle={Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - NCTA},
year={2019},
pages={536-541},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008494805360541},
isbn={978-989-758-384-1},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - NCTA
TI - Sampling Frequency Evaluation on Recurrent Neural Networks Architectures for IoT Real-time Fall Detection Devices
SN - 978-989-758-384-1
IS - 2184-3236
AU - Luna-Perejon, F.
AU - Civit-Masot, J.
AU - Muñoz-Saavedra, L.
AU - Duran-Lopez, L.
AU - Amaya-Rodriguez, I.
AU - Dominguez-Morales, J.
AU - Vicente-Diaz, S.
AU - Linares-Barranco, A.
AU - Civit-Balcells, A.
AU - Dominguez-Morales, M.
PY - 2019
SP - 536
EP - 541
DO - 10.5220/0008494805360541
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic