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Perspectives in Wearable Systems in the Human–Robot Interaction (HRI) Field
Due to the advantages of ease of use, less motion disturbance, and low cost, wearable systems have been widely used in the human–machine interaction (HRI) field. However, HRI in complex clinical rehabilitation scenarios has further requirements for wearable sensor systems, which has aroused the inte...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575189/ https://www.ncbi.nlm.nih.gov/pubmed/37837147 http://dx.doi.org/10.3390/s23198315 |
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author | Liu, Tao Liu, Xiangzhi |
author_facet | Liu, Tao Liu, Xiangzhi |
author_sort | Liu, Tao |
collection | PubMed |
description | Due to the advantages of ease of use, less motion disturbance, and low cost, wearable systems have been widely used in the human–machine interaction (HRI) field. However, HRI in complex clinical rehabilitation scenarios has further requirements for wearable sensor systems, which has aroused the interest of many researchers. However, the traditional wearable system has problems such as low integration, limited types of measurement data, and low accuracy, causing a gap with the actual needs of HRI. This paper will introduce the latest progress in the current wearable systems of HRI from four aspects. First of all, it introduces the breakthroughs of current research in system integration, which includes processing chips and flexible sensing modules to reduce the system’s volume and increase battery life. After that, this paper reviews the latest progress of wearable systems in electrochemical measurement, which can extract single or multiple biomarkers from biological fluids such as sweat. In addition, the clinical application of non-invasive wearable systems is introduced, which solves the pain and discomfort problems caused by traditional clinical invasive measurement equipment. Finally, progress in the combination of current wearable systems and the latest machine-learning methods is shown, where higher accuracy and indirect acquisition of data that cannot be directly measured is achieved. From the evidence presented, we believe that the development trend of wearable systems in HRI is heading towards high integration, multi-electrochemical measurement data, and clinical and intelligent development. |
format | Online Article Text |
id | pubmed-10575189 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105751892023-10-14 Perspectives in Wearable Systems in the Human–Robot Interaction (HRI) Field Liu, Tao Liu, Xiangzhi Sensors (Basel) Perspective Due to the advantages of ease of use, less motion disturbance, and low cost, wearable systems have been widely used in the human–machine interaction (HRI) field. However, HRI in complex clinical rehabilitation scenarios has further requirements for wearable sensor systems, which has aroused the interest of many researchers. However, the traditional wearable system has problems such as low integration, limited types of measurement data, and low accuracy, causing a gap with the actual needs of HRI. This paper will introduce the latest progress in the current wearable systems of HRI from four aspects. First of all, it introduces the breakthroughs of current research in system integration, which includes processing chips and flexible sensing modules to reduce the system’s volume and increase battery life. After that, this paper reviews the latest progress of wearable systems in electrochemical measurement, which can extract single or multiple biomarkers from biological fluids such as sweat. In addition, the clinical application of non-invasive wearable systems is introduced, which solves the pain and discomfort problems caused by traditional clinical invasive measurement equipment. Finally, progress in the combination of current wearable systems and the latest machine-learning methods is shown, where higher accuracy and indirect acquisition of data that cannot be directly measured is achieved. From the evidence presented, we believe that the development trend of wearable systems in HRI is heading towards high integration, multi-electrochemical measurement data, and clinical and intelligent development. MDPI 2023-10-08 /pmc/articles/PMC10575189/ /pubmed/37837147 http://dx.doi.org/10.3390/s23198315 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Perspective Liu, Tao Liu, Xiangzhi Perspectives in Wearable Systems in the Human–Robot Interaction (HRI) Field |
title | Perspectives in Wearable Systems in the Human–Robot Interaction (HRI) Field |
title_full | Perspectives in Wearable Systems in the Human–Robot Interaction (HRI) Field |
title_fullStr | Perspectives in Wearable Systems in the Human–Robot Interaction (HRI) Field |
title_full_unstemmed | Perspectives in Wearable Systems in the Human–Robot Interaction (HRI) Field |
title_short | Perspectives in Wearable Systems in the Human–Robot Interaction (HRI) Field |
title_sort | perspectives in wearable systems in the human–robot interaction (hri) field |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575189/ https://www.ncbi.nlm.nih.gov/pubmed/37837147 http://dx.doi.org/10.3390/s23198315 |
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