Drowsiness is one of the major risk factors causing accidents that result in a large number of damage. Drivers and industrial workers probably have a large effect on several mishaps occurring from drowsiness. Therefore, advanced technology to reduce these accidental rates is a very challenging problem. Nowadays, there have been many drowsiness detectors using electroencephalogram (EEG), however, the cost is still high and the use of this is uncomfortable in long-term monitoring because most of them require wiring and conventional wet electrodes. The purpose of this paper is to develop a portable wireless device that can automatically detect the drowsiness in real time by using the EEG and electrooculogram (EOG). The silver (Ag) conducting fabric consolidated in a headband used as dry electrodes can acquire signal from the user's forehead. The signal was sent via the wireless communication of XBee® 802.15.4 to a standalone microcontroller to analyze drowsiness using the proposed algorithm. The alarm will ring when the drowsiness occurs. Besides, the automatic drowsiness detection and alarm device yields the real-time detection accuracy of approximately 81%.

People who lost their limbs by injury or congenital missing need prosthesis to replace the missing body part to assist or enhance the motor ability or for cosmetic purpose. In this paper, brain-computer interface (BCI) technology is proposed to assist the person with disability who has no arm. The proposed system includes two BCI algorithms, i.e. ERD/ERS algorithm and hybrid EEG-EOG algorithm. The designed assistive robot arm is light weight, low power consumption, user friendly and pleasing aesthetic. The ERD/ERS algorithm can achieve the accuracy of approximately 66% with 3 commands. Moreover, the accuracy of the hybrid EEG-EOG algorithm yields nearly 96%.