Abstract:The development of technologies that utilize eye movements as interface for motion detection has an important role in human-computer interaction especially as a medium for controlling automated device such as electrical wheelchair. The reliability of eye movement detection can determine the system performance which can be implemented into an automated device. By tracking the movement of the eyeball, communication between users and automated devices can take easily and may be used by people with hand-foot impairment. In this paper, we propose a method by using the division of the eye region and checking the eyeball midpoint position for detecting the direction of eyeball movement which can be used as a navigation in real time condition We also implement Haar Cascade method for detecting the eye region followed by tracking using Kernelized Correlation Filter to produce stable movement. This approach was proved reliable and could increase the precision and recall on eyeball movement detection significantly, reach the average to 0.93 and 0.84. Even, our proposed method enables a suitable level of sensitivity with low computational time.
The multiple crashes in Indonesia are categorized into a frequently occurring accident, which often causes death. The aim of this paper is to examine the driver psychophysiology during braking in response to the vehicle in the front, which is varied. The research was initiated with a literature review regarding the electrooculography (EEG), safe braking distance, Emotive Epoc+, and Central Nervous System (CNS).
The research was initiated with a literature review regarding the Electroencephalography (EEG), safe braking distance, Emotive Epoc+, and Central Nervous System (CNS). Research design with direct driving experiments on the road is used to analyze what happens to the driver's brain when braking at a certain distance (psychophysiology factor). The collected sampling data are from 4 male healthy drivers with the age between 20 - 40 years and average driving experience of more than 5 years. The measurement of brain activities into a spectrum of colors and Emotive BCI 16 electrodes through the performance matrices was conducted for the existing condition and condition suitable with the safety distance permitted. Experiments have been tested in 4 different road conditions of residential road (speed <30Km/h), city road (speed <50Km/h), rural road (speed <80Km/h) and motorway (speed <100Km/h). Safety distance measurement used standard data with residences road = 10m, city road = 29m, rural road 73m, and motorways = 115m. Results of brainwave signal have been recorded by Emotive Epoc Brain Activity map and Emotive BCI matrix and have been used to analyse the driver’s psychophysical.
The findings show that the level of stress in the existing condition is very wherein for the braking in the densely populated residence = 87, urban areas = 83, intercity = 76, and motorways = 60. In contrast, following the safety distance rules have successfully reduced mental stress to average 47 as proofed by lower beta signal especially on occipital lobe (vision function) and on frontal lobe (attention function). Improper infrastructure such as narrow road at heavy residential damaged driver relaxes and increased stress level as indicated by increasing brain signal significantly.
Meanwhile, driving while concerning the safety braking distance psychophysiologically through the identification of brain activity will be able to lower the driver’s stress and fatigue level.
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