Modular design of fatigue detection in naturalistic driving environments.

Al-Libawy, Hilal; Al-Ataby, Ali; Al-Nuaimy, Waleed; Al-Taee, Majid A

Al-Libawy, Hilal; Al-Ataby, Ali; Al-Nuaimy, Waleed; Al-Taee, Majid A.

Afiliación

Al-Libawy H; Department of Electrical Engineering and Electronics, University of Liverpool, Brownlow Hill, Liverpool L69 3GJ, UK; Department of Electrical Engineering, University of Babylon, Iraq. Electronic address: eng.hilal_al-libawy@uobabylon.edu.iq.
Al-Ataby A; Department of Electrical Engineering and Electronics, University of Liverpool, Brownlow Hill, Liverpool L69 3GJ, UK.
Al-Nuaimy W; Department of Electrical Engineering and Electronics, University of Liverpool, Brownlow Hill, Liverpool L69 3GJ, UK.
Al-Taee MA; Department of Electrical Engineering and Electronics, University of Liverpool, Brownlow Hill, Liverpool L69 3GJ, UK.

Accid Anal Prev ; 120: 188-194, 2018 Nov.

Article en En | MEDLINE | ID: mdl-30170293

Asunto(s)

Conducción de Automóvil; Fatiga Mental/diagnóstico; Adulto; Algoritmos; Teorema de Bayes; Femenino; Humanos; Masculino; Fatiga Mental/fisiopatología; Redes Neurales de la Computación; Reproducibilidad de los Resultados

Palabras clave

Bayesian combiner; Driver fatigue; Machine learning; Modular structure; Particle swarm optimisation; Performance optimisation

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Conducción de Automóvil / Fatiga Mental Tipo de estudio: Diagnostic_studies / Prognostic_studies / Screening_studies Límite: Adult / Female / Humans / Male Idioma: En Revista: Accid Anal Prev Año: 2018 Tipo del documento: Article

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