title: Analysis of Different Classification Techniques for Two-Class Functional Near-Infrared Spectroscopy-Based Brain-Computer Interface.
abstract: We analyse and compare the classification accuracies of six different classifiers for a two-class mental task (mental arithmetic and rest) using functional near-infrared spectroscopy (fNIRS) signals. The signals of the mental arithmetic and rest tasks from the prefrontal cortex region of the brain for seven healthy subjects were acquired using a multichannel continuous-wave imaging system. After removal of the physiological noises, six features were extracted from the oxygenated hemoglobin (HbO) signals. Two- and three-dimensional combinations of those features were used for classification of mental tasks. In the classification, six different modalities, linear discriminant analysis (LDA), quadratic discriminant analysis (QDA),k-nearest neighbour (kNN), the Naïve Bayes approach, support vector machine (SVM), and artificial neural networks (ANN), were utilized. With these classifiers, the average classification accuracies among the seven subjects for the 2- and 3-dimensional combinations of features were 71.6, 90.0, 69.7, 89.8, 89.5, and 91.4% and 79.6, 95.2, 64.5, 94.8, 95.2, and 96.3%, respectively. ANN showed the maximum classification accuracies: 91.4 and 96.3%. In order to validate the results, a statistical significance test was performed, which confirmed that thepvalues were statistically significant relative to all of the other classifiers (p< 0.005) using HbO signals.
authors.affiliation: Department of Mechatronics Engineering, Air University, Sector E-9, Islamabad 44000, Pakistan.
authors.forename: Noman
authors.identifier: 0000-0002-2680-6403
authors.initials: N
authors.lastname: Naseer
authors.affiliation: Department of Mechatronics Engineering, Air University, Sector E-9, Islamabad 44000, Pakistan.
authors.forename: Nauman Khalid
authors.initials: NK
authors.lastname: Qureshi
authors.affiliation: Department of Mechatronics Engineering, Air University, Sector E-9, Islamabad 44000, Pakistan.
authors.forename: Farzan Majeed
authors.initials: FM
authors.lastname: Noori
authors.affiliation: School of Mechanical Engineering and Department of Cogno-Mechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea.
authors.forename: Keum-Shik
authors.initials: KS
authors.lastname: Hong
mesh_terms: D001499:Bayes Theorem; D062207:Brain-Computer Interfaces; D016002:Discriminant Analysis; D006801:Humans; D009483:Neuropsychological Tests; D010108:Oxyhemoglobins / Q000378:metabolism*; D017397:Prefrontal Cortex / Q000378:metabolism*; D012815:Signal Processing, Computer-Assisted; D019265:Spectroscopy, Near-Infrared / Q000145:classification / Q000295:instrumentation; D060388:Support Vector Machine
chemical_list: D010108:Oxyhemoglobins