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Citation
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Poursadeghiyan M, Mazloumi A, Saraji GNASL, Niknezhad A, Akbarzadeh A, Ebrahimi MH. Iran. J. Public Health 2017; 46(1): 93-102. |
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Abstract
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BACKGROUND: We determined the levels of subjective and observer drowsiness and facial dynamics changes.
METHODS: This experimental study was done in the virtual reality laboratory of Khaje-Nasir Toosi University of Technology in 2015. Facial dynamics changes like changes in eyes, mouth and eyebrows were surveyed on twenty-five drivers in 2015byKSS (Karolinska Sleepiness Scale) and ORD (Observer Rating of Drowsiness). ANOVA Repeated Measure and MANOVA Repeated Measure tests were used for data analysis. Also, neural network and Viola-Jones were used to detect facial characteristics. PERCLOS (Percentage of Eye Closure), blink frequency and blink duration were inspected for eyes parameters. The size of open mouth during drowsiness was inspected for mouth parameter. During the inspection of eyebrow, the number 50 denoted eyebrow in normal position. For eyebrows above the normal position, a range of 50 to 55 was specified; in addition, 45-50 was found as the specified range for eyebrows under normal position.
RESULTS: Descriptive statistics of the dynamic changes in mouth and eyes illustrated that during the driving process, the level of sleepiness increased as well as changes of eyes and mouth. However, statistical findings during car driving revealed that dynamic changes in eyebrows had clear expression with a constant trend. Similar studies on data obtained from KSS and ORD showed that both of these parameters simultaneously increased as well as the level of drowsiness. In addition, a significant relationship existed between facial expression and drowsiness.
CONCLUSION: This research would be an effective and efficient tool for timely alarming and detecting the drowsiness quickly and precisely.
Language: en |