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Trends in Smart Helmets With Multimodal Sensing for Health and Safety: Scoping Review
BACKGROUND: As a form of the Internet of Things (IoT)–gateways, a smart helmet is one of the core devices that offers distinct functionalities. The development of smart helmets connected to IoT infrastructure helps promote connected health and safety in various fields. In this regard, we present a c...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709670/ https://www.ncbi.nlm.nih.gov/pubmed/36378505 http://dx.doi.org/10.2196/40797 |
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author | Lee, Peter Kim, Heepyung Zitouni, M Sami Khandoker, Ahsan Jelinek, Herbert F Hadjileontiadis, Leontios Lee, Uichin Jeong, Yong |
author_facet | Lee, Peter Kim, Heepyung Zitouni, M Sami Khandoker, Ahsan Jelinek, Herbert F Hadjileontiadis, Leontios Lee, Uichin Jeong, Yong |
author_sort | Lee, Peter |
collection | PubMed |
description | BACKGROUND: As a form of the Internet of Things (IoT)–gateways, a smart helmet is one of the core devices that offers distinct functionalities. The development of smart helmets connected to IoT infrastructure helps promote connected health and safety in various fields. In this regard, we present a comprehensive analysis of smart helmet technology and its main characteristics and applications for health and safety. OBJECTIVE: This paper reviews the trends in smart helmet technology and provides an overview of the current and future potential deployments of such technology, the development of smart helmets for continuous monitoring of the health status of users, and the surrounding environmental conditions. The research questions were as follows: What are the main purposes and domains of smart helmets for health and safety? How have researchers realized key features and with what types of sensors? METHODS: We selected studies cited in electronic databases such as Google Scholar, Web of Science, ScienceDirect, and EBSCO on smart helmets through a keyword search from January 2010 to December 2021. In total, 1268 papers were identified (Web of Science: 87/1268, 6.86%; EBSCO: 149/1268, 11.75%; ScienceDirect: 248/1268, 19.55%; and Google Scholar: 784/1268, 61.82%), and the number of final studies included after PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) study selection was 57. We also performed a self-assessment of the reviewed articles to determine the quality of the paper. The scoring was based on five criteria: test environment, prototype quality, feasibility test, sensor calibration, and versatility. RESULTS: Smart helmet research has been considered in industry, sports, first responder, and health tracking scenarios for health and safety purposes. Among 57 studies, most studies with prototype development were industrial applications (18/57, 32%), and the 2 most frequent studies including simulation were industry (23/57, 40%) and sports (23/57, 40%) applications. From our assessment-scoring result, studies tended to focus on sensor calibration results (2.3 out of 3), while the lowest part was a feasibility test (1.6 out of 3). Further classification of the purpose of smart helmets yielded 4 major categories, including activity, physiological and environmental (hazard) risk sensing, as well as risk event alerting. CONCLUSIONS: A summary of existing smart helmet systems is presented with a review of the sensor features used in the prototyping demonstrations. Overall, we aimed to explore new possibilities by examining the latest research, sensor technologies, and application platform perspectives for smart helmets as promising wearable devices. The barriers to users, challenges in the development of smart helmets, and future opportunities for health and safety applications are also discussed. In conclusion, this paper presents the current status of smart helmet technology, main issues, and prospects for future smart helmet with the objective of making the smart helmet concept a reality. |
format | Online Article Text |
id | pubmed-9709670 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-97096702022-12-01 Trends in Smart Helmets With Multimodal Sensing for Health and Safety: Scoping Review Lee, Peter Kim, Heepyung Zitouni, M Sami Khandoker, Ahsan Jelinek, Herbert F Hadjileontiadis, Leontios Lee, Uichin Jeong, Yong JMIR Mhealth Uhealth Review BACKGROUND: As a form of the Internet of Things (IoT)–gateways, a smart helmet is one of the core devices that offers distinct functionalities. The development of smart helmets connected to IoT infrastructure helps promote connected health and safety in various fields. In this regard, we present a comprehensive analysis of smart helmet technology and its main characteristics and applications for health and safety. OBJECTIVE: This paper reviews the trends in smart helmet technology and provides an overview of the current and future potential deployments of such technology, the development of smart helmets for continuous monitoring of the health status of users, and the surrounding environmental conditions. The research questions were as follows: What are the main purposes and domains of smart helmets for health and safety? How have researchers realized key features and with what types of sensors? METHODS: We selected studies cited in electronic databases such as Google Scholar, Web of Science, ScienceDirect, and EBSCO on smart helmets through a keyword search from January 2010 to December 2021. In total, 1268 papers were identified (Web of Science: 87/1268, 6.86%; EBSCO: 149/1268, 11.75%; ScienceDirect: 248/1268, 19.55%; and Google Scholar: 784/1268, 61.82%), and the number of final studies included after PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) study selection was 57. We also performed a self-assessment of the reviewed articles to determine the quality of the paper. The scoring was based on five criteria: test environment, prototype quality, feasibility test, sensor calibration, and versatility. RESULTS: Smart helmet research has been considered in industry, sports, first responder, and health tracking scenarios for health and safety purposes. Among 57 studies, most studies with prototype development were industrial applications (18/57, 32%), and the 2 most frequent studies including simulation were industry (23/57, 40%) and sports (23/57, 40%) applications. From our assessment-scoring result, studies tended to focus on sensor calibration results (2.3 out of 3), while the lowest part was a feasibility test (1.6 out of 3). Further classification of the purpose of smart helmets yielded 4 major categories, including activity, physiological and environmental (hazard) risk sensing, as well as risk event alerting. CONCLUSIONS: A summary of existing smart helmet systems is presented with a review of the sensor features used in the prototyping demonstrations. Overall, we aimed to explore new possibilities by examining the latest research, sensor technologies, and application platform perspectives for smart helmets as promising wearable devices. The barriers to users, challenges in the development of smart helmets, and future opportunities for health and safety applications are also discussed. In conclusion, this paper presents the current status of smart helmet technology, main issues, and prospects for future smart helmet with the objective of making the smart helmet concept a reality. JMIR Publications 2022-11-15 /pmc/articles/PMC9709670/ /pubmed/36378505 http://dx.doi.org/10.2196/40797 Text en ©Peter Lee, Heepyung Kim, M Sami Zitouni, Ahsan Khandoker, Herbert F Jelinek, Leontios Hadjileontiadis, Uichin Lee, Yong Jeong. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 15.11.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on https://mhealth.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Review Lee, Peter Kim, Heepyung Zitouni, M Sami Khandoker, Ahsan Jelinek, Herbert F Hadjileontiadis, Leontios Lee, Uichin Jeong, Yong Trends in Smart Helmets With Multimodal Sensing for Health and Safety: Scoping Review |
title | Trends in Smart Helmets With Multimodal Sensing for Health and Safety: Scoping Review |
title_full | Trends in Smart Helmets With Multimodal Sensing for Health and Safety: Scoping Review |
title_fullStr | Trends in Smart Helmets With Multimodal Sensing for Health and Safety: Scoping Review |
title_full_unstemmed | Trends in Smart Helmets With Multimodal Sensing for Health and Safety: Scoping Review |
title_short | Trends in Smart Helmets With Multimodal Sensing for Health and Safety: Scoping Review |
title_sort | trends in smart helmets with multimodal sensing for health and safety: scoping review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709670/ https://www.ncbi.nlm.nih.gov/pubmed/36378505 http://dx.doi.org/10.2196/40797 |
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