Author: Tuan Anh Vuong
Vuong, Tuan Anh, 2024 Towards vibrotactile mobility control using the P300 in a BCI, Flinders University, College of Science and Engineering
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With the brain-computer interface (BCI), besides using visual and auditory stimuli, the user could control the device using vibrotactile stimuli to utilise the P300 event-related potential. However, the effect of the location of vibrotactile stimuli on the body and its performance is unclear. This project investigated the correlation between the location of the tactors on the body and the accuracy of the participant in recognition of the target tactor. From there, recommendations for tactor location setup were derived for optimal extraction of P300. In the experiments, 4 tactors were used and set up in 5 configurations of tactor location. The EEG and EMG signals were recorded in each configuration using the EEG scalp and the EMG electrodes. The EMG signal was used to grade the participants' responses' accuracy. The P300 ERP analysis was performed to extract and average the EEG signal from the 300 to 500 ms range. The decision matrices built from the EMG data were used to validate the accuracy, precision and recall of each configuration of tactor locations. The project results were able to show the accuracy in focusing on the target tactor based on the locations through 5 tactor configurations. Then, the project provided recommendations for potential locations of vibrotactile stimuli setup for effective P300 ERP extract with respect to one arm, both arms and under regions with dense nerve fibre. The results are expected to provide a better understanding of the vibrotactile stimuli, as well as improve the paradigm for extraction and classification of the P300 ERP waves in BCI applications. The findings could be extended for further investigation, which includes how the number of tactors affects the performance of the participant, as well as how the tactor configurations jeopardise the participant’s performance on a larger scale with multiple participants.
Keywords: BCI, EEG, ERP, Mobility Control, Paradigm, P300, Stimuli, Tactor, Vibrotactile
Subject: Engineering thesis
Thesis type: Masters
Completed: 2024
School: College of Science and Engineering
Supervisor: Kenneth Pope