Title :
Automatic Electrooculogram Classification for Microcontroller Based Interface Design
Author :
Trikha, M. ; Bhandari, A. ; Gandhi, T.
Author_Institution :
Jaypee Inst. of Inf. Technol., Noida
Abstract :
In this paper, we present a simple and novel technique for classification of multiple channel Electrooculogram signals (EOG). In particular, a viable real time EOG signal classifier for microcontrollers is proposed. The classifier is based on Deterministic Finite Automata (DFA). The system is capable of classifying sixteen different EOG signals. The viability of the system was tested by performing online experiments with able bodied subjects.
Keywords :
biology computing; deterministic automata; electro-oculography; finite automata; medical signal processing; microcontrollers; signal classification; user interfaces; EOG signal classifier; automatic electrooculogram classification; deterministic finite automata; microcontroller based interface design; multiple channel electrooculogram signal classification; Automata; Automatic control; Communication system control; Cornea; Doped fiber amplifiers; Electrodes; Electrooculography; Humans; Microcontrollers; Voltage;
Conference_Titel :
Systems and Information Engineering Design Symposium, 2007. SIEDS 2007. IEEE
Conference_Location :
Charlottesville, VA
Print_ISBN :
978-1-4244-1286-0
Electronic_ISBN :
978-1-4244-1286-0
DOI :
10.1109/SIEDS.2007.4373994
