A Wavelet-Based Approach to Fall Detection

Palmerini, Luca ; Bagalà, Fabio ; Zanetti, Andrea ; Klenk, Jochen ; Becker, Clemens ; Cappello, Angelo (2015) A Wavelet-Based Approach to Fall Detection. Sensors, 15 (5). pp. 11575-11586. ISSN 1424-8220
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Abstract

Falls among older people are a widely documented public health problem. Automatic fall detection has recently gained huge importance because it could allow for the immediate communication of falls to medical assistance. The aim of this work is to present a novel wavelet-based approach to fall detection, focusing on the impact phase and using a dataset of real-world falls. Since recorded falls result in a non-stationary signal, a wavelet transform was chosen to examine fall patterns. The idea is to consider the average fall pattern as the “prototype fall”.In order to detect falls, every acceleration signal can be compared to this prototype through wavelet analysis. The similarity of the recorded signal with the prototype fall is a feature that can be used in order to determine the difference between falls and daily activities. The discriminative ability of this feature is evaluated on real-world data. It outperforms other features that are commonly used in fall detection studies, with an Area Under the Curve of 0.918. This result suggests that the proposed wavelet-based feature is promising and future studies could use this feature (in combination with others considering different fall phases) in order to improve the performance of fall detection algorithms.

Abstract
Tipologia del documento
Articolo
Autori
AutoreAffiliazioneORCID
Palmerini, LucaDepartment of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”,University of Bologna0000-0003-4758-662X
Bagalà, FabioDepartment of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”,University of Bologna
Zanetti, AndreaDepartment of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”,University of Bologna
Klenk, JochenDepartment of Clinical Gerontology, Robert-Bosch-Hospital, Stuttgart, Germany0000-0002-5987-447X
Becker, ClemensDepartment of Clinical Gerontology, Robert-Bosch-Hospital, Stuttgart, Germany0000-0003-1624-8353
Cappello, AngeloDepartment of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”,University of Bologna
Parole chiave
fall detection; wavelet; accelerometers; pattern recognition
Settori scientifico-disciplinari
ISSN
1424-8220
DOI
Data di deposito
05 Apr 2017 13:00
Ultima modifica
05 Apr 2017 13:02
Nome del Progetto
FARSEEING - FAll Repository for the design of Smart and sElf-adaptive Environments prolonging INdependent livinG
Programma di finanziamento
EC - FP7
URI

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