The Effect that Auxiliary Taxonomized Auditory Distractions have on a P300 Speller while utilising Low Fidelity Equipment

Abstract

In this paper, we ensue on the development of a taxonomy aimed at categorizing distractions in the P300b domain. Explicitly, we investigate the effect that auditory distractions, distinctively that of ambient noise (AN), passive talking (PT), and active listening (AL) have on the signal of a visual P300 Speller in terms of accuracy, amplitude, latency, user preference, signal morphology, and overall signal quality. This work is part of a larger EEG based project and is based on the P300 speller BCI (oddball) paradigm and the xDAWN algorithm, with eight healthy subjects; while using a non-invasive Brain-Computer Interface based on low fidelity electroencephalographic (EEG) equipment. Our results show that the accuracy was best for the Lab (LC) at 100%, followed by AN at 92.5%, PT at 90% and last AL at 87.5%, which results were in identical order to the subjects’ preferences. In addition, the amplitude and latency did not show any statistical significance in all settings. This paper provides additional results that impart insight into the practicability of the aforementioned P300 speller methodology and low-cost equipment to be used in real-world applications.