Title :
Development of Assistive Technology Devices Using an EEG Headset
Author :
Sicheng Wang ; Yih-Choung Yu ; Jouny, Ismail ; Gabel, Lisa
Author_Institution :
Dept. of Electr. & Comput. Eng., Lafayette Coll., Easton, PA, USA
Abstract :
Two signal-processing algorithms have been developed to detect the head movements from a human subject. The head movement was measured by two signals from a gyroscope (representing x- and y-axis) integrated in an EEG headset (EEG neuroheadset, Emotiv Systems). These signals were acquired into a PC wirelessly to determine four possible head movements: left, right, up, and down using two different algorithms based on cross-correlation and clipping. A series of tests was conducted with two subjects to evaluate the performance of both algorithms. The results showed that the cross-correlation method detected head movements with 75% accuracy while the clipping method performed slightly better than the cross-correlation method with 81% accuracy. These algorithms will be further improved and integrated with a brain-computer interface for the purpose of assisting people with disabilities.
Keywords :
brain-computer interfaces; electroencephalography; gyroscopes; handicapped aids; medical signal detection; medical signal processing; EEG neuroheadset; Emotiv Systems; assistive technology device development; brain-computer interface; clipping algorithms; cross-correlation algorithms; disabilities; gyroscope; head movements; human subject; signal acquisition; signal processing algorithms; wireless PC; Accuracy; Assistive technology; Electrodes; Electroencephalography; Headphones; Signal processing algorithms; Turning; Signal processing; assist technology; brain-computer interface; clipping; cross-correlation; gyroscope;
Conference_Titel :
Bioengineering Conference (NEBEC), 2013 39th Annual Northeast
Conference_Location :
Syracuse, NY
Print_ISBN :
978-1-4673-4928-4
DOI :
10.1109/NEBEC.2013.169