Cargando…
Drowsiness Detection System Based on PERCLOS and Facial Physiological Signal †
Accidents caused by fatigue occur frequently, and numerous scholars have devoted tremendous efforts to investigate methods to reduce accidents caused by fatigued driving. Accordingly, the assessment of the spirit status of the driver through the eyes blinking frequency and the measurement of physiol...
Autores principales: | Chang, Robert Chen-Hao, Wang, Chia-Yu, Chen, Wei-Ting, Chiu, Cheng-Di |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9323611/ https://www.ncbi.nlm.nih.gov/pubmed/35891065 http://dx.doi.org/10.3390/s22145380 |
Ejemplares similares
-
PERCLOS-based technologies for detecting drowsiness: current evidence and future directions
por: Abe, Takashi
Publicado: (2023) -
A Field Study of Work Type Influence on Air Traffic Controllers’ Fatigue Based on Data-Driven PERCLOS Detection
por: Zhang, Jianping, et al.
Publicado: (2021) -
Non-Invasive Driver Drowsiness Detection System
por: Siddiqui, Hafeez Ur Rehman, et al.
Publicado: (2021) -
A Hybrid Approach to Detect Driver Drowsiness Utilizing Physiological Signals to Improve System Performance and Wearability
por: Awais, Muhammad, et al.
Publicado: (2017) -
Presenting a model for dynamic facial expression changes in detecting drivers’ drowsiness
por: Karchani, Mohsen, et al.
Publicado: (2015)