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
18 October 2023
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)
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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
Catalogue record
Date deposited: 22 Jun 2023 16:37
Last modified: 12 Nov 2024 02:46
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Contributors
Author:
Adriana Gabriela Wilde
Author:
Nicolas Zurbuchen
Author:
Pascal Bruegger
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