تقرير
An Analysis of the Accuracy of the P300 BCI
| العنوان: | An Analysis of the Accuracy of the P300 BCI |
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| المؤلفون: | Artzi, Nitzan S., Shriki, Oren |
| سنة النشر: | 2018 |
| المجموعة: | Computer Science Quantitative Biology Statistics |
| مصطلحات موضوعية: | Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning, Quantitative Biology - Neurons and Cognition, Statistics - Machine Learning |
| الوصف: | The P300 Brain-Computer Interface (BCI) is a well-established communication channel for severely disabled people. The P300 event-related potential is mostly characterized by its amplitude or its area, which correlate with the spelling accuracy of the P300 speller. Here, we introduce a novel approach for estimating the efficiency of this BCI by considering the P300 signal-to-noise ratio (SNR), a parameter that estimates the spatial and temporal noise levels and has a significantly stronger correlation with spelling accuracy. Furthermore, we suggest a Gaussian noise model, which utilizes the P300 event-related potential SNR to predict spelling accuracy under various conditions for LDA-based classification. We demonstrate the utility of this analysis using real data and discuss its potential applications, such as speeding up the process of electrode selection. |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1080/2326263X.2018.1552357 |
| URL الوصول: | http://arxiv.org/abs/1901.03299 |
| رقم الأكسشن: | edsarx.1901.03299 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1080/2326263X.2018.1552357 |
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