Cargando…

Study of driving skill level discrimination based on human physiological signal characteristics

The primary purpose of the study is to distinguish the differences in driving skill between novice and experienced drivers from the viewpoint of human cognitive behavior. Firstly, EEG (electroencephalogram) signals were collected using EEG acquisition equipment called Neuroscan. The δ sub-band and E...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Fuwang, Xu, Qing, Fu, Rongrong, Sun, Guangbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9092114/
https://www.ncbi.nlm.nih.gov/pubmed/35558811
http://dx.doi.org/10.1039/c8ra08523d
_version_ 1784705074924093440
author Wang, Fuwang
Xu, Qing
Fu, Rongrong
Sun, Guangbin
author_facet Wang, Fuwang
Xu, Qing
Fu, Rongrong
Sun, Guangbin
author_sort Wang, Fuwang
collection PubMed
description The primary purpose of the study is to distinguish the differences in driving skill between novice and experienced drivers from the viewpoint of human cognitive behavior. Firstly, EEG (electroencephalogram) signals were collected using EEG acquisition equipment called Neuroscan. The δ sub-band and EOG (electrooculogram) signals were extracted from the EEG. Furthermore, the eye movement rate and the sample entropy (SampEn) values of δ sub-bands were calculated. Finally, the heart rate variability (HRV) characteristics, calculated using the SampEn algorithm, were used to analyze driving skill. The final result showed that human physiological signals (EEG, EOG and ECG (electrocardiogram)) could effectively distinguish different driving skills.
format Online
Article
Text
id pubmed-9092114
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher The Royal Society of Chemistry
record_format MEDLINE/PubMed
spelling pubmed-90921142022-05-11 Study of driving skill level discrimination based on human physiological signal characteristics Wang, Fuwang Xu, Qing Fu, Rongrong Sun, Guangbin RSC Adv Chemistry The primary purpose of the study is to distinguish the differences in driving skill between novice and experienced drivers from the viewpoint of human cognitive behavior. Firstly, EEG (electroencephalogram) signals were collected using EEG acquisition equipment called Neuroscan. The δ sub-band and EOG (electrooculogram) signals were extracted from the EEG. Furthermore, the eye movement rate and the sample entropy (SampEn) values of δ sub-bands were calculated. Finally, the heart rate variability (HRV) characteristics, calculated using the SampEn algorithm, were used to analyze driving skill. The final result showed that human physiological signals (EEG, EOG and ECG (electrocardiogram)) could effectively distinguish different driving skills. The Royal Society of Chemistry 2018-12-18 /pmc/articles/PMC9092114/ /pubmed/35558811 http://dx.doi.org/10.1039/c8ra08523d Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Chemistry
Wang, Fuwang
Xu, Qing
Fu, Rongrong
Sun, Guangbin
Study of driving skill level discrimination based on human physiological signal characteristics
title Study of driving skill level discrimination based on human physiological signal characteristics
title_full Study of driving skill level discrimination based on human physiological signal characteristics
title_fullStr Study of driving skill level discrimination based on human physiological signal characteristics
title_full_unstemmed Study of driving skill level discrimination based on human physiological signal characteristics
title_short Study of driving skill level discrimination based on human physiological signal characteristics
title_sort study of driving skill level discrimination based on human physiological signal characteristics
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9092114/
https://www.ncbi.nlm.nih.gov/pubmed/35558811
http://dx.doi.org/10.1039/c8ra08523d
work_keys_str_mv AT wangfuwang studyofdrivingskillleveldiscriminationbasedonhumanphysiologicalsignalcharacteristics
AT xuqing studyofdrivingskillleveldiscriminationbasedonhumanphysiologicalsignalcharacteristics
AT furongrong studyofdrivingskillleveldiscriminationbasedonhumanphysiologicalsignalcharacteristics
AT sunguangbin studyofdrivingskillleveldiscriminationbasedonhumanphysiologicalsignalcharacteristics