Information Technology Reference
In-Depth Information
Subjective measurement results gathered from all these tests greatly depend on
the quality of the asked questions as well as proper interpretation and understanding
of those questions by the subject. Due to the age and social diversity of subjects, it
might not be possible to formulate a questionnaire to accommodate every potential
problem. Moreover, the subjects' perspective plays a huge role on the quality of
the acquired data. Lastly, it is worth stating that it is very difficult to acquire
subjective drowsiness feedback from a driver in a real-world driving situation; all
the measurements are usually done in a simulated environment.
2.2
Physiological Methods
Physiological methods offer an objective, precise way to measure sleepiness.
They are based upon the fact that physiological signals start to change in earlier
stages of drowsiness [
3
,
30
], which could allow a potential driver drowsiness
detection system a little bit of extra time to alert a drowsy driver in a timely
manner and thereby prevent many road accidents. The idea of being able to
detect drowsiness at an early stage with very few false positives has motivated
many researchers to experiment with various electro-physiological signals of the
human body, such as electrocardiogram (ECG), electroencephalogram (EEG), and
electrooculogram (EOG). They are briefly defined and explained below.
Electrocardiogram (ECG)
records electrical activity of a human heart. This
system can very precisely tell which state the human body is in by detecting
minute changes in the behavior of the heart, such as increase or decrease of
heart rate [
28
,
50
]. Variability of a heart rate can be described using Heart
Rate Variability measure (HRV) [
28
,
50
], in which the low (LF) and high (HF)
frequencies of heartbeat are described. HRV is a measure of the beat-to-beat
(R-R intervals) changes in the heart rate. When a subject is awake, the heart rate
is much closer to the HF. The ECG can clearly show that when a subject starts
going into drowsy state, the heart rate starts slowing down and heading towards
the LF band.
Electroencephalogram (EEG)
records electrical activity of a human brain. It is
the most reliable and most commonly used signal that can precisely describe
humans alertness level [
3
,
27
,
36
,
37
,
40
]. The EEG signal is highly complex and
has various frequency bands. Frequency bands that can be measured to determine
if a subject is drowsy are: delta band—which corresponds to sleep activity; theta
band—which is related to drowsiness; and beta band—which corresponds to
alertness. A decrease in the power changes in the alpha frequency band and
an increase in the theta frequency band indicate drowsiness. The frequencies
measured using this method are very prone to errors and require very specific
conditions for being measured properly. Moreover, in order to measure them,
sensing devices would have to make physical contact with the subject. Clearly, in
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