Decreasing the interference of visual-based P300 BCI using facial expression changes

Lists

Tools

Jin, J., Zhang, Y., Wang, X., Daly, I. and Cichocki, A. (2014) Decreasing the interference of visual-based P300 BCI using facial expression changes. In: Proceeding of the 11th World Congress on Intelligent Control and Automation, June 29 - July 4 2014, Shenyang, China, pp. 2407-2411.

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Official URL: http://dx.doi.org/10.1109/WCICA.2014.7053098

Abstract/Summary

Interferences from the spatially adjacent non-target stimuli evoke ERPs during non-target sub-trials and lead to false positives. This phenomenon is commonly seen in visual attention based BCIs and affects the performance of BCI system. Although, users or subjects tried to focus on the target stimulus, they still could not help being affected by conspicuous changes of the stimuli (flashes or presenting images) which were adjacent to the target stimulus. In view of this case, the aim of this study is to reduce the adjacent interference using new stimulus presentation pattern based on facial expression changes. Positive facial expressions can be changed to negative facial expressions by minor changes to the original facial image. Although the changes are minor, the contrast will be big enough to evoke strong ERPs. In this paper, two different conditions (Pattern_1, Pattern_2) were used to compare across objective measures such as classification accuracy and information transfer rate as well as subjective measures. Pattern_1 was a “flash-only” pattern and Pattern_2 was a facial expression change of a dummy face. In the facial expression change patterns, the background is a positive facial expression and the stimulus is a negative facial expression. The results showed that the interferences from adjacent stimuli could be reduced significantly (P<;0.05) by using the facial expression change patterns. The online performance of the BCI system using the facial expression change patterns was significantly better than that using the “flash-only” patterns in terms of classification accuracy (p<;0.01), bit rate (p<;0.01), and practical bit rate (p<;0.01). Subjects reported that the annoyance and fatigue could be significantly decreased (p<;0.05) using the new stimulus presentation pattern presented in this paper.

Item Type:	Conference or Workshop Item (Paper)
Refereed:	Yes
Divisions:	Life Sciences > School of Biological Sciences > Department of Bio-Engineering
ID Code:	39909
Uncontrolled Keywords:	Brain computer interface, face expression change, P300

Deposit Details

References

[1] N. Xu, X. R. Gao, B. Hong, X. B. Miao,S. K. Gao, F. S. “Yang.BCI competition 2003 - Data set IIb: Enhancing P300 wave detection using ICA-based subspace projections for BCI applications.” IEEE Trans. Biomed. Eng, 2004, vol. 51, no. 6 pp.1067-1072, Jun 2004. [2] F. Lotte, M. Congedo, A. Lecuyer, F. Lamarche, B. Arnaldi, “A review of classification algorithms for EEG-based brain-computer interfaces.” J. Neural Eng,vol. 4, pp. R1-R13, Jan, 2007. [3] U. Hoffmann, J. M. Vesin, T. Ebrahimi, K. Diserens “An efficient P300- based brain–computer interface for disabled subjects.” J. Neurosci. Meth, vol. 167, no. 1, pp. 115-125. Jan 2008. [4] A. Cichocki, N. Y. Washizawa, T. Rutkowski, H. Bakardjian, A. H. Phan, S. Choi, H. Lee, Q. Zhao, L. Zhang, Y. Q. Li, “Noninvasive BCIs: Multiway signal-processing array decompositions.” IEEE Computer, vol. 41, pp. 34-42, 2008. [5] B. Blankertz, S. Lemm, M. Treder, S. Haufe, K. R. Muller, “Single-trial analysis and classification of ERP components - A tutorial.” NeuroImage, vol. 56, no. 2, pp. 814-825. May, 2011. [6] Y. Liu, Z. T. Zhou, D. W. Hu, “Gaze independent brain-computer speller with convert visual search tasks.” Clin. Neurophysiol, vol. 112, no. 6, pp. 1127-1136. Jun, 2010. [7] M. S. Trede, N. M. Schmidt, B. Blankertz, “Gaze-independent braincomputer interfaces based on covert attention and feature attention.” J. Neural En, vol. 8, pp. 066003, Dec, 2011. [8] G. Townsend, B. K. LaPallo, C. B. Boulay, D. J. Krusienski, G. E. Frye, C. K. Hauser, N. E. Schwartz, T. M. Vaughan, J. R. Wolpaw, E. W. Sellers, “A novel P300-based brain-computer interface stimulus presentation paradigm: moving beyond rows and columns.” Clin. Neurophysiol. vol. 121, no. 7, pp. 1109-20, Jul, 2010. [9] J. Jin, B. Z. Allison, E. W. Sellers, C. Brunner, P. Horki, X. Wang, C. Neuper, “Adaptive P300 based control system.” J. Neural Eng, vol. 8, pp. 036006. Jun, 2011. [10]F. Guo, B. Hong, X. Gao, S. Gao, “A brain-computer interface using montion-onset visual evoked potential.” J. Neural Eng, vol. 5, pp. 475- 485, Dec, 2008. [11]T. Liu, l. Goldberg, S. Gao, B. Hong, “An online brain-computer interface using non-flashing visual evoked potentials.” J. Neural Eng, vol. 7, no. 3, pp. 036003, Jun, 2010. [12]B. Hong, F. Guo, T. Liu, S. Gao, “N200-speller using motion-onset visual response." Clin. Neurophysiol, vol. 120, no. 9, pp.1658-1666. Sep, 2009. [13]J. Jin, B. Z. Allison, X. Wang, C. Neuper, “A combined brain computer interface based on P300 potentials and motion-onset visual evoked potentials.” J Neurosci. Methods, vol. 205, no. 2, pp. 265-276. Apr. 2012 [14]T. Kaufmann, S. M. Schulz, C. Grünzinger, A. Kübler, “Flashing characters with famous faces improves ERP-Based brain-computer interface performance.” J Neural Eng, vol. 8, no. 5, pp. 056016. Oct, 2011. [15]Y. Zhang, Q, Zhao, J. Jin, X. Wang, A, Cichocki, “A novel BCI based on ERP components sensitive to configural processing of human faces.” J. Neural Eng, vol. 9, no. 2, pp. 026018. Apr, 2012. [16]G. E. Frye, C. K. Hauser, G. Townsend, E. W. Sellers, “Suppressing flashes of items surrounding targets during calibration of a P300-based brain-computer interface improves performance.” J. neural Eng, vol. 8, no. 2, pp. 025024, Apr, 2011. [17]C. Guger, S. Daban, E. W. Sellers, C. Holzner, G. Krausz, R. Carabalona, F. Gramatica, G. Edlinge, “How many people are able to control a P300- based brain-computer interface (BCI).” Neurosci. Lett, vol.462, no. 1, pp. 94–98, Oct, 2009. [18]J. Jin, B. Z. Allison, T. Kaufmann, A. Kübler, Y. Zhang, X. Wang, A. Cichocki, “The changing face of P300 BCIs: A comparison of stimulus changes in a P300 BCI involving faces, emotion, and movement.” PLoS ONE vol. 7, no. 11, pp. e49688, Nov, 2012. [19]J. Jin, P. Horki, C. Brunner, X. Wang, C. Neuper, G. Pfurtscheller, “A new P300 stimulus presentation pattern for EEG-based spelling systems.” Biomed. Tec, vol. 55, no. 4, pp. 203-210, Aug, 2010. [20]B. H. Jansen, A. Allam, P. Kota, K. Lachance, A. Osho, K. Sundarean, “An exploratory study of factors affecting single trial P300 detection.” IEEE Trans. Biomed Eng, vol. 51, no. 6, pp. 975-78, Jun, 2004. [21]V. H. Kolev, T. Demiralp, J. Yordanova, A. Ademoglu, U. Isoglu-Alka, “Time-frequency analysis reveals multiple functional components during oddball P300.” NeuroReport, vol. 8, no.8, pp. 2061-2065, May, 1997. [22]J. Polich, “Updating P300: An integrative theory of P3a and P3b.” Clin. Neurophysiol. vol. 118, no. 10, pp. 2128-2148, Oct, 2007. [23]N. K. Squires,K. C. Squires, S. A. Hillyard, “Two varieties of longlatency positive waves evoked by unpredictable auditory stimuli in man.” Electroencephalogr. Clin. Neurophysiol. vol. 38, no. 4, pp. 387-401, Apr, 1975. [24]R, J. Itier, M. J. Taylor “Inversion and contrast polarity reversal affect both encoding and recognition processes of unfamiliar faces: a repetition study using ERPs.” NeuroImage, vol. 15, no. 2, pp. 353–372. Feb, 2002. [25]S. Ikegami, K. Takano, N. Saeki, K. Kansaku, “Operation of a P300- based brain-computer interface by individuals with cervical spinal cord injury.” Clin. Neurophysiol. vol. 122, no. 5, pp. 991-996, May, 2011.

University Staff: Request a correction | Centaur Editors: Update this record

University of Reading

CentAUR: Central Archive at the University of Reading

Accessibility navigation

Decreasing the interference of visual-based P300 BCI using facial expression changes

Abstract/Summary

Page navigation

See also

Footer navigation