ROLE OF EEG SUGNALS FOR DIAGNOSIS OF NEUROLOGICAL DISORDER

Abstract

In this work, we use the same dataset as in previous studies. 14- Normally-sighted humans (7-Females, 7-male). The median age of all women and men taken into account is 26. The participants volunteered their services for the research. This decentralised sensor network consisted of the 32 electrodes on the EEG cap. The 10-20 system recommended by the American encephalographic society was used to determine where to insert the electrodes. These electrodes were separated into two groups, frontal and occipital. 1 kHz frequency was used for recording the data. In order to remove the artifacts, line noise etc. low pass filters were employed and input impedance was kept near 5 kΩ. The images shown to objects were dived into two groups: (i) distracters and (ii) objectives. Out of total 1000 pictures shown to objects, 500 were distracters type and rest 500 were objective type. The testing of blocks started immediately after the training mode. The participants were requested to memorize the pictures.