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2019 | OriginalPaper | Buchkapitel

Automatic Exercise Assistance for the Elderly Using Real-Time Adaptation to Performance and Affect

verfasst von : Ramin Tadayon, Antonio Vega Ramirez, Swagata Das, Yusuke Kishishita, Masataka Yamamoto, Yuichi Kurita

Erschienen in: Universal Access in Human-Computer Interaction. Multimodality and Assistive Environments

Verlag: Springer International Publishing

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Abstract

This work presents the design of a system and methodology for reducing risk of locomotive syndrome among the elderly through the delivery of real-time at-home exercise assistance via intensity modulation of a worn soft exoskeleton. An Adaptive Neural Network (ANN) is proposed for the prediction of locomotive risk based on squat exercise performance. A preliminary pilot evaluation was conducted to determine how well these two performance metrics relate by training the ANN to predict test scores among three standard tests for locomotive risk with features from joint tracking data. The promising initial results of this evaluation are presented with discussions for future implementation of affective classification and a combined adaptation strategy.

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Vorheriges Kapitel The Contribution of Social Networks to the Technological Experience of Elderly Users

Nächstes Kapitel EEG Systems for Educational Neuroscience

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Titel: Automatic Exercise Assistance for the Elderly Using Real-Time Adaptation to Performance and Affect
verfasst von: Ramin Tadayon
Antonio Vega Ramirez
Swagata Das
Yusuke Kishishita
Masataka Yamamoto
Yuichi Kurita
Verlag: Springer International Publishing
Buch: Universal Access in Human-Computer Interaction. Multimodality and Assistive Environments
Print ISBN: 978-3-030-23562-8

Electronic ISBN: 978-3-030-23563-5

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-23563-5_44

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