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vehicle collisions due to fatigue and inattention (Table 1).
DFD systems are complex systems because many factors
may influence drowsiness (Figure 1). However, the technologies required in their design have faced the challenge with a
variety of intelligent approaches, as shown in Figure 5.
From Figure 5, it is clear that two main approaches in the
DFD design are followed by developers, intrusive and nonintrusive. Although intrusive systems may yield a more accurate detection of drowsiness, drivers are more reluctant to use
this type of systems. Among the nonintrusive systems, those
focusing on eye features are the most investigated, followed
by head-movement detection (Table 4). However, new and
future DFD system design paradigms are proposed. For
example, a promising hybrid approach is reported in [93].
Driver fatigue-detection methods based on the driver's state,
including eye state, mouth shape, and head pose, are reported
in [94]-[96]. New research on DFD derived from the European project Advanced Sensor Development for Attention,
Stress, Vigilance, and Sleep/Wakefulness Monitoring (SENSATION) is expected in the coming years, including the use
of nanotechnology to monitor human physiological conditions as well as the use of results from the fields of brainsensing, neurosensing, computational neuroscience, signal
processing, materials science, optoelectronics, microelectronics, intelligent user interfaces, telematics, data fusion, sleep
research, human physiological measurements, and clinical/
medical research [96].
In summary, the literature shows that the efforts of companies, universities, and government agencies have started to
yield important results on the design of DFD systems. Some
developed systems have been tested with promising results.
The synergy implied in this research topic will boost the
design of DFD systems such that they will play an important
role in drivers' security in years to come.

ABOUT THE AUTHORS
Mario I. Chacon-Murguia (mchacon@ieee.org) earned his
B.Sc. degree in 1982 and his M.Sc. degree in 1985 in electrical engineering from the Chihuahua Institute of Technology,
Mexico, and his Ph.D. degree in electrical engineering in
1998 from New Mexico State University, Las Cruces. He is
currently a professor-researcher for the Chihuahua Institute
of Technology. He is the founder of the Digital Signal Processing-Vision Laboratory and the Visual Perception Application on Robotic Laboratory, 1999 and 2010. He is a member
of the IEEE Signal Processing Society, the IEEE Computational Intelligence Society, and the National Research System
in Mexico.
Claudia Prieto-Resendiz (claudia.prieto@honeywell.com)
earned her B.Sc. degree in 2004 in electronic systems engineering at Instituto Tecnologico de Estudios Superiores de
Monterrey (ITESM), Campus Chihuahua, Mexico, and her
M.Sc. degree in electronics engineering at ITESM Campus
Toluca, Mexico, in 2009. She has worked in the automotive
industry for five years in the product development area as an
electrical applications engineer.

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