A Fatigue and Drowsiness Detection System Using Inertial Sensors and Electrocardiogram Signals
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://doi.org/10.34629/ipl.isel.i-ETC.85 |
Resumo: | The interest in monitoring a drivers conditions and performance has increased in the past years, to make the roads safer both for drivers and pedestrians. This raised the idea of developing a system to monitor the drivers conditions to prevent road disasters. In this paper, we propose a system to monitor the drivers fatigue and drowsiness, based on the Car- dioWheel system, developed by CardioID. The proposed system records both the persons ECG signal and the motion of the steering wheel during the driving session. The amount of data acquired demands a compression stage for transmission with the goal to reduce the required bandwidth. The transmission of the compressed data is done via Bluetooth Low Energy, with an exclusive profile developed for this system. To detect fatigue and drowsiness patterns, a machine learning approach was taken. Among the evaluated classifiers, the Support Vector Machines technique proved to be the best classification method with the highest accuracy. Thus, the developed prototype has the ability to warn the driver about his physiological and physical states, increasing the safety in the roads. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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A Fatigue and Drowsiness Detection System Using Inertial Sensors and Electrocardiogram SignalsComputers; Informatics; MultimediaECG; Fatigue Detection; Drowsiness Detection; Driver Assistant; CardioWheelThe interest in monitoring a drivers conditions and performance has increased in the past years, to make the roads safer both for drivers and pedestrians. This raised the idea of developing a system to monitor the drivers conditions to prevent road disasters. In this paper, we propose a system to monitor the drivers fatigue and drowsiness, based on the Car- dioWheel system, developed by CardioID. The proposed system records both the persons ECG signal and the motion of the steering wheel during the driving session. The amount of data acquired demands a compression stage for transmission with the goal to reduce the required bandwidth. The transmission of the compressed data is done via Bluetooth Low Energy, with an exclusive profile developed for this system. To detect fatigue and drowsiness patterns, a machine learning approach was taken. Among the evaluated classifiers, the Support Vector Machines technique proved to be the best classification method with the highest accuracy. Thus, the developed prototype has the ability to warn the driver about his physiological and physical states, increasing the safety in the roads.ISEL - High Institute of Engineering of Lisbon2022-07-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://doi.org/10.34629/ipl.isel.i-ETC.85oai:i-ETC.journals.isel.pt:article/85i-ETC : ISEL Academic Journal of Electronics Telecommunications and Computers; Vol 8, No 1 (2022): Volume 8i-ETC : ISEL Academic Journal of Electronics Telecommunications and Computers; Vol 8, No 1 (2022): Volume 82182-4010reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPenghttp://journals.isel.pt/index.php/i-ETC/article/view/ID-01https://doi.org/10.34629/ipl.isel.i-ETC.85http://journals.isel.pt/index.php/i-ETC/article/view/ID-01/75Copyright (c) 2022 Andre Ribeiro Lourencohttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessCerca, AntonioLourenco, Andre RibeiroFerreira, Artur2022-09-20T15:26:07Zoai:i-ETC.journals.isel.pt:article/85Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T15:51:12.677252Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
A Fatigue and Drowsiness Detection System Using Inertial Sensors and Electrocardiogram Signals |
title |
A Fatigue and Drowsiness Detection System Using Inertial Sensors and Electrocardiogram Signals |
spellingShingle |
A Fatigue and Drowsiness Detection System Using Inertial Sensors and Electrocardiogram Signals Cerca, Antonio Computers; Informatics; Multimedia ECG; Fatigue Detection; Drowsiness Detection; Driver Assistant; CardioWheel |
title_short |
A Fatigue and Drowsiness Detection System Using Inertial Sensors and Electrocardiogram Signals |
title_full |
A Fatigue and Drowsiness Detection System Using Inertial Sensors and Electrocardiogram Signals |
title_fullStr |
A Fatigue and Drowsiness Detection System Using Inertial Sensors and Electrocardiogram Signals |
title_full_unstemmed |
A Fatigue and Drowsiness Detection System Using Inertial Sensors and Electrocardiogram Signals |
title_sort |
A Fatigue and Drowsiness Detection System Using Inertial Sensors and Electrocardiogram Signals |
author |
Cerca, Antonio |
author_facet |
Cerca, Antonio Lourenco, Andre Ribeiro Ferreira, Artur |
author_role |
author |
author2 |
Lourenco, Andre Ribeiro Ferreira, Artur |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Cerca, Antonio Lourenco, Andre Ribeiro Ferreira, Artur |
dc.subject.por.fl_str_mv |
Computers; Informatics; Multimedia ECG; Fatigue Detection; Drowsiness Detection; Driver Assistant; CardioWheel |
topic |
Computers; Informatics; Multimedia ECG; Fatigue Detection; Drowsiness Detection; Driver Assistant; CardioWheel |
description |
The interest in monitoring a drivers conditions and performance has increased in the past years, to make the roads safer both for drivers and pedestrians. This raised the idea of developing a system to monitor the drivers conditions to prevent road disasters. In this paper, we propose a system to monitor the drivers fatigue and drowsiness, based on the Car- dioWheel system, developed by CardioID. The proposed system records both the persons ECG signal and the motion of the steering wheel during the driving session. The amount of data acquired demands a compression stage for transmission with the goal to reduce the required bandwidth. The transmission of the compressed data is done via Bluetooth Low Energy, with an exclusive profile developed for this system. To detect fatigue and drowsiness patterns, a machine learning approach was taken. Among the evaluated classifiers, the Support Vector Machines technique proved to be the best classification method with the highest accuracy. Thus, the developed prototype has the ability to warn the driver about his physiological and physical states, increasing the safety in the roads. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-07-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://doi.org/10.34629/ipl.isel.i-ETC.85 oai:i-ETC.journals.isel.pt:article/85 |
url |
https://doi.org/10.34629/ipl.isel.i-ETC.85 |
identifier_str_mv |
oai:i-ETC.journals.isel.pt:article/85 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://journals.isel.pt/index.php/i-ETC/article/view/ID-01 https://doi.org/10.34629/ipl.isel.i-ETC.85 http://journals.isel.pt/index.php/i-ETC/article/view/ID-01/75 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2022 Andre Ribeiro Lourenco http://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2022 Andre Ribeiro Lourenco http://creativecommons.org/licenses/by-nc/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
ISEL - High Institute of Engineering of Lisbon |
publisher.none.fl_str_mv |
ISEL - High Institute of Engineering of Lisbon |
dc.source.none.fl_str_mv |
i-ETC : ISEL Academic Journal of Electronics Telecommunications and Computers; Vol 8, No 1 (2022): Volume 8 i-ETC : ISEL Academic Journal of Electronics Telecommunications and Computers; Vol 8, No 1 (2022): Volume 8 2182-4010 reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799130375516061696 |