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A Smart Robotic Walker With Intelligent Close-Proximity Interaction Capabilities for Elderly Mobility Safety

The elderly population has rapidly increased in past years, bringing huge demands for elderly serving devices, especially for those with mobility impairment. Present assistant walkers designed for elderly users are primitive with limited user interactivity and intelligence. We propose a novel smart...

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Detalles Bibliográficos
Autores principales: Zhao, Xiaoyang, Zhu, Zhi, Liu, Mingshan, Zhao, Chongyu, Zhao, Yafei, Pan, Jia, Wang, Zheng, Wu, Chuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7642877/
https://www.ncbi.nlm.nih.gov/pubmed/33192437
http://dx.doi.org/10.3389/fnbot.2020.575889
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author Zhao, Xiaoyang
Zhu, Zhi
Liu, Mingshan
Zhao, Chongyu
Zhao, Yafei
Pan, Jia
Wang, Zheng
Wu, Chuan
author_facet Zhao, Xiaoyang
Zhu, Zhi
Liu, Mingshan
Zhao, Chongyu
Zhao, Yafei
Pan, Jia
Wang, Zheng
Wu, Chuan
author_sort Zhao, Xiaoyang
collection PubMed
description The elderly population has rapidly increased in past years, bringing huge demands for elderly serving devices, especially for those with mobility impairment. Present assistant walkers designed for elderly users are primitive with limited user interactivity and intelligence. We propose a novel smart robotic walker that targets a convenient-to-use indoor walking aid for the elderly. The walker supports multiple modes of interactions through voice, gait or haptic touch, and allows intelligent control via learning-based methods to achieve mobility safety. Our design enables a flexible, initiative and reliable walker due to the following: (1) we take a hybrid approach by combining the conventional mobile robotic platform with the existing rollator design, to achieve a novel robotic system that fulfills expected functionalities; (2) our walker tracks users in front by detecting lower limb gait, while providing close-proximity walking safety support; (3) our walker can detect human intentions and predict emergency events, e.g., falling, by monitoring force pressure on a specially designed soft-robotic interface on the handle; (4) our walker performs reinforcement learning-based sound source localization to locate and navigate to the user based on his/her voice signals. Experiment results demonstrate the sturdy mechanical structure, the reliability of multiple novel interactions, and the efficiency of the intelligent control algorithms implemented. The demonstration video is available at: https://sites.google.com/view/smart-walker-hku.
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spelling pubmed-76428772020-11-13 A Smart Robotic Walker With Intelligent Close-Proximity Interaction Capabilities for Elderly Mobility Safety Zhao, Xiaoyang Zhu, Zhi Liu, Mingshan Zhao, Chongyu Zhao, Yafei Pan, Jia Wang, Zheng Wu, Chuan Front Neurorobot Neuroscience The elderly population has rapidly increased in past years, bringing huge demands for elderly serving devices, especially for those with mobility impairment. Present assistant walkers designed for elderly users are primitive with limited user interactivity and intelligence. We propose a novel smart robotic walker that targets a convenient-to-use indoor walking aid for the elderly. The walker supports multiple modes of interactions through voice, gait or haptic touch, and allows intelligent control via learning-based methods to achieve mobility safety. Our design enables a flexible, initiative and reliable walker due to the following: (1) we take a hybrid approach by combining the conventional mobile robotic platform with the existing rollator design, to achieve a novel robotic system that fulfills expected functionalities; (2) our walker tracks users in front by detecting lower limb gait, while providing close-proximity walking safety support; (3) our walker can detect human intentions and predict emergency events, e.g., falling, by monitoring force pressure on a specially designed soft-robotic interface on the handle; (4) our walker performs reinforcement learning-based sound source localization to locate and navigate to the user based on his/her voice signals. Experiment results demonstrate the sturdy mechanical structure, the reliability of multiple novel interactions, and the efficiency of the intelligent control algorithms implemented. The demonstration video is available at: https://sites.google.com/view/smart-walker-hku. Frontiers Media S.A. 2020-10-22 /pmc/articles/PMC7642877/ /pubmed/33192437 http://dx.doi.org/10.3389/fnbot.2020.575889 Text en Copyright © 2020 Zhao, Zhu, Liu, Zhao, Zhao, Pan, Wang and Wu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Zhao, Xiaoyang
Zhu, Zhi
Liu, Mingshan
Zhao, Chongyu
Zhao, Yafei
Pan, Jia
Wang, Zheng
Wu, Chuan
A Smart Robotic Walker With Intelligent Close-Proximity Interaction Capabilities for Elderly Mobility Safety
title A Smart Robotic Walker With Intelligent Close-Proximity Interaction Capabilities for Elderly Mobility Safety
title_full A Smart Robotic Walker With Intelligent Close-Proximity Interaction Capabilities for Elderly Mobility Safety
title_fullStr A Smart Robotic Walker With Intelligent Close-Proximity Interaction Capabilities for Elderly Mobility Safety
title_full_unstemmed A Smart Robotic Walker With Intelligent Close-Proximity Interaction Capabilities for Elderly Mobility Safety
title_short A Smart Robotic Walker With Intelligent Close-Proximity Interaction Capabilities for Elderly Mobility Safety
title_sort smart robotic walker with intelligent close-proximity interaction capabilities for elderly mobility safety
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7642877/
https://www.ncbi.nlm.nih.gov/pubmed/33192437
http://dx.doi.org/10.3389/fnbot.2020.575889
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