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Artigo em Inglês | MEDLINE | ID: mdl-24110852

RESUMO

Drowsiness is one of the major risk factors causing accidents that result in a large number of damage. Drivers and industrial workers probably have a large effect on several mishaps occurring from drowsiness. Therefore, advanced technology to reduce these accidental rates is a very challenging problem. Nowadays, there have been many drowsiness detectors using electroencephalogram (EEG), however, the cost is still high and the use of this is uncomfortable in long-term monitoring because most of them require wiring and conventional wet electrodes. The purpose of this paper is to develop a portable wireless device that can automatically detect the drowsiness in real time by using the EEG and electrooculogram (EOG). The silver (Ag) conducting fabric consolidated in a headband used as dry electrodes can acquire signal from the user's forehead. The signal was sent via the wireless communication of XBee® 802.15.4 to a standalone microcontroller to analyze drowsiness using the proposed algorithm. The alarm will ring when the drowsiness occurs. Besides, the automatic drowsiness detection and alarm device yields the real-time detection accuracy of approximately 81%.


Assuntos
Piscadela , Eletroencefalografia/instrumentação , Eletroculografia/instrumentação , Monitorização Ambulatorial/instrumentação , Fases do Sono , Algoritmos , Vestuário , Eletrodos , Eletroencefalografia/métodos , Eletroculografia/métodos , Desenho de Equipamento , Humanos , Monitorização Ambulatorial/métodos , Reprodutibilidade dos Testes , Fatores de Risco , Processamento de Sinais Assistido por Computador , Prata/química , Software , Fatores de Tempo , Tecnologia sem Fio
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