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Mobile Robotic Balance Assistant (MRBA): a gait assistive and fall intervention robot for daily living
BACKGROUND: Aging degrades the balance and locomotion ability due to frailty and pathological conditions. This demands balance rehabilitation and assistive technologies that help the affected population to regain mobility, independence, and improve their quality of life. While many overground gait r...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9979429/ https://www.ncbi.nlm.nih.gov/pubmed/36859286 http://dx.doi.org/10.1186/s12984-023-01149-0 |
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author | Li, Lei Foo, Ming Jeat Chen, Jiaye Tan, Kuan Yuee Cai, Jiaying Swaminathan, Rohini Chua, Karen Sui Geok Wee, Seng Kwee Kuah, Christopher Wee Keong Zhuo, Huiting Ang, Wei Tech |
author_facet | Li, Lei Foo, Ming Jeat Chen, Jiaye Tan, Kuan Yuee Cai, Jiaying Swaminathan, Rohini Chua, Karen Sui Geok Wee, Seng Kwee Kuah, Christopher Wee Keong Zhuo, Huiting Ang, Wei Tech |
author_sort | Li, Lei |
collection | PubMed |
description | BACKGROUND: Aging degrades the balance and locomotion ability due to frailty and pathological conditions. This demands balance rehabilitation and assistive technologies that help the affected population to regain mobility, independence, and improve their quality of life. While many overground gait rehabilitation and assistive robots exist in the market, none are designed to be used at home or in community settings. METHODS: A device named Mobile Robotic Balance Assistant (MRBA) is developed to address this problem. MRBA is a hybrid of a gait assistive robot and a powered wheelchair. When the user is walking around performing activities of daily living, the robot follows the person and provides support at the pelvic area in case of loss of balance. It can also be transformed into a wheelchair if the user wants to sit down or commute. To achieve instability detection, sensory data from the robot are compared with a predefined threshold; a fall is identified if the value exceeds the threshold. The experiments involve both healthy young subjects and an individual with spinal cord injury (SCI). Spatial Parametric Mapping is used to assess the effect of the robot on lower limb joint kinematics during walking. The instability detection algorithm is evaluated by calculating the sensitivity and specificity in identifying normal walking and simulated falls. RESULTS: When walking with MRBA, the healthy subjects have a lower speed, smaller step length and longer step time. The SCI subject experiences similar changes as well as a decrease in step width that indicates better stability. Both groups of subjects have reduced joint range of motion. By comparing the force sensor measurement with a calibrated threshold, the instability detection algorithm can identify more than 93% of self-induced falls with a false alarm rate of 0%. CONCLUSIONS: While there is still room for improvement in the robot compliance and the instability identification, the study demonstrates the first step in bringing gait assistive technologies into homes. We hope that the robot can encourage the balance-impaired population to engage in more activities of daily living to improve their quality of life. Future research includes recruiting more subjects with balance difficulty to further refine the device functionalities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12984-023-01149-0. |
format | Online Article Text |
id | pubmed-9979429 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-99794292023-03-03 Mobile Robotic Balance Assistant (MRBA): a gait assistive and fall intervention robot for daily living Li, Lei Foo, Ming Jeat Chen, Jiaye Tan, Kuan Yuee Cai, Jiaying Swaminathan, Rohini Chua, Karen Sui Geok Wee, Seng Kwee Kuah, Christopher Wee Keong Zhuo, Huiting Ang, Wei Tech J Neuroeng Rehabil Research BACKGROUND: Aging degrades the balance and locomotion ability due to frailty and pathological conditions. This demands balance rehabilitation and assistive technologies that help the affected population to regain mobility, independence, and improve their quality of life. While many overground gait rehabilitation and assistive robots exist in the market, none are designed to be used at home or in community settings. METHODS: A device named Mobile Robotic Balance Assistant (MRBA) is developed to address this problem. MRBA is a hybrid of a gait assistive robot and a powered wheelchair. When the user is walking around performing activities of daily living, the robot follows the person and provides support at the pelvic area in case of loss of balance. It can also be transformed into a wheelchair if the user wants to sit down or commute. To achieve instability detection, sensory data from the robot are compared with a predefined threshold; a fall is identified if the value exceeds the threshold. The experiments involve both healthy young subjects and an individual with spinal cord injury (SCI). Spatial Parametric Mapping is used to assess the effect of the robot on lower limb joint kinematics during walking. The instability detection algorithm is evaluated by calculating the sensitivity and specificity in identifying normal walking and simulated falls. RESULTS: When walking with MRBA, the healthy subjects have a lower speed, smaller step length and longer step time. The SCI subject experiences similar changes as well as a decrease in step width that indicates better stability. Both groups of subjects have reduced joint range of motion. By comparing the force sensor measurement with a calibrated threshold, the instability detection algorithm can identify more than 93% of self-induced falls with a false alarm rate of 0%. CONCLUSIONS: While there is still room for improvement in the robot compliance and the instability identification, the study demonstrates the first step in bringing gait assistive technologies into homes. We hope that the robot can encourage the balance-impaired population to engage in more activities of daily living to improve their quality of life. Future research includes recruiting more subjects with balance difficulty to further refine the device functionalities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12984-023-01149-0. BioMed Central 2023-03-01 /pmc/articles/PMC9979429/ /pubmed/36859286 http://dx.doi.org/10.1186/s12984-023-01149-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Li, Lei Foo, Ming Jeat Chen, Jiaye Tan, Kuan Yuee Cai, Jiaying Swaminathan, Rohini Chua, Karen Sui Geok Wee, Seng Kwee Kuah, Christopher Wee Keong Zhuo, Huiting Ang, Wei Tech Mobile Robotic Balance Assistant (MRBA): a gait assistive and fall intervention robot for daily living |
title | Mobile Robotic Balance Assistant (MRBA): a gait assistive and fall intervention robot for daily living |
title_full | Mobile Robotic Balance Assistant (MRBA): a gait assistive and fall intervention robot for daily living |
title_fullStr | Mobile Robotic Balance Assistant (MRBA): a gait assistive and fall intervention robot for daily living |
title_full_unstemmed | Mobile Robotic Balance Assistant (MRBA): a gait assistive and fall intervention robot for daily living |
title_short | Mobile Robotic Balance Assistant (MRBA): a gait assistive and fall intervention robot for daily living |
title_sort | mobile robotic balance assistant (mrba): a gait assistive and fall intervention robot for daily living |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9979429/ https://www.ncbi.nlm.nih.gov/pubmed/36859286 http://dx.doi.org/10.1186/s12984-023-01149-0 |
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