Automatic Electrooculogram Classification for Microcontroller Based Interface Design

Author

Trikha, M. ; Bhandari, A. ; Gandhi, T.

Author_Institution

Jaypee Inst. of Inf. Technol., Noida

fYear

2007

fDate

27-27 April 2007

Firstpage

1

Lastpage

6

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/SIEDS.2007.4373994

Filename

4373994