An efficient words typing P300-BCI system using a modified T9 interface and random forest classifier

The conventional P300-based character spelling BCI system consists of a character presentation paradigm and a classification system. In this paper, we propose modifications to both in order to increase the word typing speed and accuracy. In the paradigm part, we have modified the T9 (Text on Nine keys) interface which is similar to the keypad of mobile phones being used for text messaging. Then we have integrated a custom-built dictionary to give word suggestions to a user while typing. The user can select one out of the given suggestions to complete word typing. Our proposed paradigms significantly reduce the word typing time and make words typing more convenient by typing complete words with only few initial character spellings. In the classification part we have adopted a Random Forest (RF) classifier. The RF improves classification accuracy by combining multiple decision trees. We conducted experiments with five subjects using the proposed BCI system. Our results demonstrate that our system increases typing speed significantly: our proposed system took an average time of 1.83 minutes per word, while typing ten random words, whereas the conventional spelling required 3.35 minutes for the same words under the same conditions, decreasing the typing time by 45.37%.