TY - JOUR
T1 - The anterior contralateral response improves performance in a single trial auditory oddball BMI
AU - Guo, Miaomiao
AU - Xu, Guizhi
AU - Wang, Lei
AU - Masters, Matthew
AU - Milsap, Griffin
AU - Thakor, Nitish
AU - Soares, Alcimar Barbosa
N1 - Funding Information:
The authors would like to thank the National Natural Science Foundation of China (grant 50877023 ), Natural Science Foundation of Hebei Province , China (grant H2012202053 ) and CAPES and CNPq Brazil for the financial support.
Publisher Copyright:
© 2015 Elsevier Ltd.
PY - 2015/7/21
Y1 - 2015/7/21
N2 - Abstract Auditory Brain Machine Interfaces were designed for patients with severe neurofunctional disabilities, such as those suffering with late-stage amyotrophic lateral sclerosis (ALS), who have impaired eye movements or are unable to maintain gaze preventing them from using visual strategies for communication. This study explores the three-stimulus auditory oddball paradigm with binary choices (yes/no) associated with Empirical Mode Decomposition to extract features used to train and test a Support Vector Machine classifier. Data from standard EEG channels and from the N200-anterior-contralateral (N2ac) response signal were tested. Ten healthy male subjects, age 20 to 27 years, participated in the experiment. The best performance (average classification accuracy of 87.41% and information transfer ratio of 6.48 bit/min) was achieved when features extracted from the N2ac response were added to features extracted from the EEG channels. Also, the results showed that by using target stimuli with larger frequency separation helps the subjects focus better on the desired answer.
AB - Abstract Auditory Brain Machine Interfaces were designed for patients with severe neurofunctional disabilities, such as those suffering with late-stage amyotrophic lateral sclerosis (ALS), who have impaired eye movements or are unable to maintain gaze preventing them from using visual strategies for communication. This study explores the three-stimulus auditory oddball paradigm with binary choices (yes/no) associated with Empirical Mode Decomposition to extract features used to train and test a Support Vector Machine classifier. Data from standard EEG channels and from the N200-anterior-contralateral (N2ac) response signal were tested. Ten healthy male subjects, age 20 to 27 years, participated in the experiment. The best performance (average classification accuracy of 87.41% and information transfer ratio of 6.48 bit/min) was achieved when features extracted from the N2ac response were added to features extracted from the EEG channels. Also, the results showed that by using target stimuli with larger frequency separation helps the subjects focus better on the desired answer.
KW - Brain machine interface
KW - Empirical Mode Decomposition
KW - N200-anterior-contralateral
KW - Oddball auditory paradigm
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U2 - 10.1016/j.bspc.2015.06.014
DO - 10.1016/j.bspc.2015.06.014
M3 - Article
AN - SCOPUS:84937557297
SN - 1746-8094
VL - 22
SP - 74
EP - 84
JO - Biomedical Signal Processing and Control
JF - Biomedical Signal Processing and Control
M1 - 708
ER -