Performance analysis of different feature-classifier binomials in motor-imagering BCIs: Preliminary results

Abstract

Brain Computer Interface Systems (BCIs) allow the identification of volitive brain activity patterns. This allows their use as input channels for alternative communication and computer access systems by patients suffering from severe motor disabilities. This paper presents preliminary results obtained after extracting four different features from EEG signals in order to recognize the activity patterns by means of four different classifiers. The final goal is to determine the proper "feature -classifier" binomial for each user in order to increase system reliability and satisfaction in use.

A concept-environment for computer-based augmentative and alternative communication founded on a systematic review

“…Paper Category (Bermúdez et al, 2010), (Cabrera et al, 2008), (Chin et al, 2010), (Deepa et al, 2010), (Okasaka and Hoshino, 2012), (Schalk et al, 2008), (Sorger et al, 2009), (Sun et al, 2010, (Thomas et al, 2008), (Thompson et al, 2013), (Ortner et al, 2011), (Al-Abdullatif et al, 2013), , , (Ming et al, 2009) BCI (Hanson et al, 2010) Speech generator device (Keegan et al, 2009) EOG (Joubert et al, 2011) Exploratory study (Ann and Theng, 2011b) Facial expression (Park et al, 2012), (Cipresso et al, 2011) Eyetracking (AlJa 'am et al, 2008), (Ann and Theng, 2011b), (Friginal et al, 2013), , (Sorna et al, 2009), (Hsieh et al, 2009) Software modeling , , , (Silva and Pereira, 2011), (Tsai, 2013) Communication board (Belani, 2012), (Arnott and Alm, 2013), (Deepa et al, 2010), (Hill, 2010), (McCoy et al, 2013), (Mak and Wolpaw, 2009), Conceptual review (Alwell and Cobb, 2009), (Finke et al, 2008) Systematic review , (Prabhu and Prasad, 2011), Alternative virtual keyboard…”

“…For example, in BCI the brain signals can be encoded in many different mental images. Then, a computer classifies those images as a pattern and, for each one, a distinct computational command may be generated (Bermúdez et al, 2010). Furthermore, this method can be used in BCI data input, facial expression recognition and combination of eye movement patterns.…”