Low-cost wireless electrooculography system for brain-computer interface applications - Hoi, Ka Hou (2018)
While communication is an innate ability to most of us, individuals with severe motor disability such as amyotrophic lateral sclerosis (ALS) have difficulty in daily communication. Nowadays, with the help of human-computer interface (HCI), they can communicate using bio-signal which can be measured from the human body and monitored. Electrooculography (EOG) is one type of bio-signal, it can be measured as the electrical potential difference generated by eye movement. This project aims to develop a low-cost EOG based speller. The EOG signal acquisition used 5 surface electrodes, which enable the capture of horizontal and vertical eye movement. An EOG signal acquisition circuit was designed and implemented. It consists of amplifiers and filters to condition the signal. Filters were used to filter out unwanted noises from the environment, power line (50Hz) and from the human body. The EOG signal ranges between 15 microvolts to 200 microvolts, hence, amplifier is needed to amplify the signal to a usable range. The horizontal and vertical EOG signal is digitised by the Arduino. A real-time EOG classifying algorithm was developed on the Arduino to classify the signal. The algorithm can classify up to 10 different types of eye movement. This classified information is transmitted wirelessly to a computer. A standard qwerty keyboard and a self-design keyboard were developed using Java to respond to the classified signal. A test was conducted on eight subjects to compare the accuracy and efficiency of both keyboards. It was observed that the self-design has higher performance as compared to the standard qwerty keyboard. The results from the test were also compared with other research, some research featured a commercially available EOG device and some research featured a self-design EOG acquisition circuit.