Suppressing flashes of items surrounding targets during calibration of a P300-based brain–computer interface improves performance

Abstract

Since the introduction of the P300 BCI speller by Farwell and Donchin in 1988 speed and accuracy of the system has been significantly improved. Larger electrode montages and various signal processing techniques are responsible for most of the improvement in performance. New presentation paradigms have also led to improvements in bit rate and accuracy (e.g. Townsend et al. 2010). In particular, the checkerboard paradigm for online P300 BCI-based spelling performs well, has started to document what makes for a successful paradigm, and is a good platform for further experimentation. The current paper further examines the checkerboard paradigm by suppressing items which surround the target from flashing during calibration (i.e., the suppression condition). In the online feedback mode the standard checkerboard paradigm is used with a stepwise linear discriminant classifier derived from the suppression condition and one classifier derived from the standard checkerboard condition, counter-balanced. The results of this research demonstrate that using suppression during calibration produces significantly more character selections/min ((6.46) time between selections included) than the standard checkerboard condition (5.55), and significantly fewer target flashes are needed per selections in the SUP condition (5.28) as compared to the RCP condition (6.17). Moreover, accuracy in the SUP and RCP conditions remained equivalent (~90%). Mean theoretical bit rate was 53.62 bits/min in the suppression condition and 46.36 bits/min in the standard checkerboard condition (ns). Waveform morphology also showed significant differences in amplitude and latency.

A survey of the dummy face and human face stimuli used in BCI paradigm

“…However, while these researches succeeded in improving the reliability of identifying target flashes (Liu et al, 2010;Townsend et al, 2012), there was another method that could further increase the ERP-based BCIs. Some studies were focused on decreasing the interference by reducing the number of adjacent flashes (Frye et al, 2011;Liu et al, 2010;Townsend et al, 2010). But increasing the number of flashes of each trial would reduce the speed of the BCI systems.…”

The Changing Face of P300 BCIs: A Comparison of Stimulus Changes in a P300 BCI Involving Faces, Emotion, and Movement

“…Zhang et al (2012) reported that N170 and vertex positive potentials (VPP) also improve classification accuracy in a P300 BCI with stimuli that change to faces [33]. In addition to changing characters to faces, other types of changes may also offer advantages over the conventional “flash” approach in P300 BCIs ([25], [34], [35], [36], [37]). …”

Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future

“…Nonetheless, BCIs may be the only viable option of restoring independent communication and autonomy for some people who are severely disabled. Considerable effort has been invested in improving signal detection, speed, accuracy, and reliability [5–11]. However, studies in target populations are far less common [12].…”