Research on Mental Fatigue Detecting Method Based on Sleep Deprivation Models / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 497-502, 2015.
Artigo
em Chinês
| WPRIM
| ID: wpr-359618
ABSTRACT
Mental fatigue is an important factor of human health and safety. It is important to achieve dynamic mental fatigue detection by using electroencephalogram (EEG) signals for fatigue prevention and job performance improvement. We in our study induced subjects' mental fatigue with 30 h sleep deprivation (SD) in the experiment. We extracted EEG features, including relative power, power ratio, center of gravity frequency (CGF), and basic relative power ratio. Then we built mental fatigue prediction model by using regression analysis. And we conducted lead optimization for prediction model. Result showed that R2 of prediction model could reach to 0.932. After lead optimization, 4 leads were used to build prediction model, in which R' could reach to 0.811. It can meet the daily applicatioi accuracy of mental fatigue prediction.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Privação do Sono
/
Eletroencefalografia
/
Fadiga Mental
/
Modelos Biológicos
Tipo de estudo:
Estudo prognóstico
Limite:
Humanos
Idioma:
Chinês
Revista:
Journal of Biomedical Engineering
Ano de publicação:
2015
Tipo de documento:
Artigo
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