The University of Southampton
University of Southampton Institutional Repository

161 - a machine learning multi-class approach for fall detection systems based on wearable sensors with a study on sampling rates selection

161 - a machine learning multi-class approach for fall detection systems based on wearable sensors with a study on sampling rates selection
161 - a machine learning multi-class approach for fall detection systems based on wearable sensors with a study on sampling rates selection
Data preprocessing, Fall detection, Feature extraction, Machine learning, Sampling rate, Wearable sensors
Wilde, Adriana Gabriela
4f9174fe-482a-4114-8e81-79b835946224
Zurbuchen, Nicolas
843a9cdc-a272-40a2-b1c5-4477a1f8857a
Bruegger, Pascal
7a458037-1032-4361-b011-70d3c9b20599
Wilde, Adriana Gabriela
4f9174fe-482a-4114-8e81-79b835946224
Zurbuchen, Nicolas
843a9cdc-a272-40a2-b1c5-4477a1f8857a
Bruegger, Pascal
7a458037-1032-4361-b011-70d3c9b20599

Wilde, Adriana Gabriela, Zurbuchen, Nicolas and Bruegger, Pascal (2023) 161 - a machine learning multi-class approach for fall detection systems based on wearable sensors with a study on sampling rates selection. Conferencia Latinoamericana de Informática, Universidad del Quindío, Armenia, Colombia. 17 - 21 Oct 2022.

Record type: Conference or Workshop Item (Other)

This record has no associated files available for download.

More information

Published date: 18 October 2023
Venue - Dates: Conferencia Latinoamericana de Informática, Universidad del Quindío, Armenia, Colombia, 2022-10-17 - 2022-10-21
Keywords: Data preprocessing, Fall detection, Feature extraction, Machine learning, Sampling rate, Wearable sensors

Identifiers

Local EPrints ID: 478133
URI: http://eprints.soton.ac.uk/id/eprint/478133
PURE UUID: 2c1d725c-a59b-4f79-81df-8b11bc05f781
ORCID for Adriana Gabriela Wilde: ORCID iD orcid.org/0000-0002-1684-1539

Catalogue record

Date deposited: 22 Jun 2023 16:37
Last modified: 12 Nov 2024 02:46

Export record

Contributors

Author: Adriana Gabriela Wilde ORCID iD
Author: Nicolas Zurbuchen
Author: Pascal Bruegger

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×