辅助分类听觉干扰对使用低保真设备的P300拼写者的影响

Patrick Schembri, Mariusz Pelc, Jixin Ma
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引用次数: 5

摘要

在本文中,我们继续开发一种分类法,旨在对P300b域中的干扰进行分类。明确地,我们研究了听觉干扰,特别是环境噪声(AN)、被动谈话(PT)和主动倾听(AL)对视觉P300拼写者的信号在准确性、幅度、延迟、用户偏好、信号形态和整体信号质量方面的影响。这项工作是一个更大的基于EEG的项目的一部分,该项目基于P300拼写者BCI (oddball)范式和xDAWN算法,共有8名健康受试者;同时使用基于低保真脑电图(EEG)设备的非侵入性脑机接口。结果表明,Lab (LC)的准确率最高,为100%,其次是AN (92.5%), PT(90%)和AL(87.5%),其结果与受试者的偏好顺序相同。此外,振幅和潜伏期在所有设置下均无统计学意义。本文提供了额外的结果,传授对上述P300拼写方法的实用性和在实际应用中使用的低成本设备的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Effect that Auxiliary Taxonomized Auditory Distractions have on a P300 Speller while utilising Low Fidelity Equipment
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.
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