The emergence of Body Sensor Networks (BSNs) constitutes a new and fast growing trend for the development of daily routine applications. However, in the case of heterogeneous BSNs integration with Vehicular ad hoc Networks (VANETs) a large number of difficulties remain, that must be solved, especially when talking about the detection of human state factors that impair the driving of motor vehic...

In a randomized controlled design, 100 healthy, term neonates in the first week of life, undergoing heel prick for routine screening were randomized to receive a heel prick in either the drowsy/sleeping state or the awake (but not fussy or crying) state. 48 babies in sleeping or drowsy states and 47 in the awake states were analyzed. Infants in the drowsy/sleeping states scored significantly lo...

Drowsy driving is among the most critical causes of fatal crashes. Thus, the development of an effective algorithm for detecting a driver’s cognitive state demands immediate attention. For decades, studies have observed clear evidence using electroencephalography that the brain’s rhythmic activities fluctuate from alertness to drowsiness. Recognition of this physiological signal is the major co...

As technology scales down, leakage energy accounts for a greater proportion of total energy. Applying the drowsy technique to a cache, is regarded as one of the most efficient techniques for reducing leakage energy. However, it increases the Soft Error Rate (SER), thus, many researchers doubt the reliability of the drowsy technique. In this paper, we show several reasons why the instruction cac...

This paper aims to provide reliable indications of driver drowsiness based on the characteristics of driver–vehicle interaction. A test bed was built under a simulated driving environment, and a total of 12 subjects participated in two experiment sessions requiring different levels of sleep (partial sleepdeprivation versus no sleep-deprivation) before the experiment. The performance of the subj...

Accurate classification of eye state is a prerequisite for preventing automobile accidents due to driver drowsiness. Previous methods of classification, based on features extracted for a single eye, are vulnerable to eye localization errors and visual obstructions, and most use a fixed threshold for classification, irrespective of variations in the driver’s eye shape and texture. To address the...