Weight Perception Analysis using Electroencephalographic Signals

Haptics is the study of coupling the human sense of touch and motion with computer systems. In this study, we analyze weight perception of the brain based on electroencephalographic signals, which is obtained using a pressure tactile as a stimulus. The state of weight perception is represented by the relative power of alpha and beta sub-bands of subjects. Independent Component Analysis is applied for post-processing. In the final stage, Linear Discriminant Analysis and Support Vector Machine techniques are utilized for classification of the brain signals as either holding a weight or being in a resting state. Our proposed method achieved satisfactory performance when Support Vector Machine with Radial Basis Function kernel classifier and relative power features, which are obtained from the alpha sub-band of four EEG channels, were used.