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2020 | OriginalPaper | Buchkapitel

Assistive Smart Cane (ASCane) for Fall Detection: First Advances

verfasst von : Pedro Mouta, Nuno Ferrete Ribeiro, Cristina P. Santos, Rui Moreira

Erschienen in: XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019

Verlag: Springer International Publishing

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Abstract

The development of fall detection systems with the capability of real-time monitoring is necessary considering that a large amount of people die and suffer severe consequences from falls. Due to their advantages, daily life accessories can be a solution to embed fall-related systems, and canes are no exception. In this paper, it is presented a cane with fall detection abilities. The ASCane is instrumented with an inertial sensor which data will be tested with three different fixed multi-threshold fall detection algorithms, one dynamic multi-threshold and machine learning methods from the literature. They were tested and modified to account the use of a cane. The best performance resulted in a sensitivity and specificity of 96.90% and 98.98%, respectively.

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Vorheriges Kapitel Computational Intelligence Generation of Subject-Specific Knee and Hip Healthy Joint Angles Reference Curves

Nächstes Kapitel Multi-view Robust Gesture Recognition for Assistive Interfaces

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Titel: Assistive Smart Cane (ASCane) for Fall Detection: First Advances
verfasst von: Pedro Mouta
Nuno Ferrete Ribeiro
Cristina P. Santos
Rui Moreira
Verlag: Springer International Publishing
Buch: XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019
Print ISBN: 978-3-030-31634-1

Electronic ISBN: 978-3-030-31635-8

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-3-030-31635-8_204

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