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.
Article
en Zh
| WPRIM
| ID: wpr-359618
Biblioteca responsable:
WPRO
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:
1
Base de datos:
WPRIM
Asunto principal:
Privación de Sueño
/
Electroencefalografía
/
Fatiga Mental
/
Modelos Biológicos
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
Zh
Revista:
Journal of Biomedical Engineering
Año:
2015
Tipo del documento:
Article