DocumentCode :
83596
Title :
Combining Motor Imagery With Selective Sensation Toward a Hybrid-Modality BCI
Author :
Lin Yao ; Jianjun Meng ; Dingguo Zhang ; Xinjun Sheng ; Xiangyang Zhu
Author_Institution :
State Key Lab. of Mech. Syst. & Vibration, Shanghai Jiao Tong Univ., Shanghai, China
Volume :
61
Issue :
8
fYear :
2014
fDate :
Aug. 2014
Firstpage :
2304
Lastpage :
2312
Abstract :
A hybrid modality brain-computer interface (BCI) is proposed in this paper, which combines motor imagery with selective sensation to enhance the discrimination between left and right mental tasks, e.g., the classification between left/ right stimulation sensation and right/ left motor imagery. In this paradigm, wearable vibrotactile rings are used to stimulate both the skin on both wrists. Subjects are required to perform the mental tasks according to the randomly presented cues (i.e., left hand motor imagery, right hand motor imagery, left stimulation sensation or right stimulation sensation). Two-way ANOVA statistical analysis showed a significant group effect (F (2,20) = 7.17, p = 0.0045), and the Benferroni-corrected multiple comparison test (with α = 0.05) showed that the hybrid modality group is 11.13% higher on average than the motor imagery group, and 10.45% higher than the selective sensation group. The hybrid modality experiment exhibits potentially wider spread usage within ten subjects crossed 70% accuracy, followed by four subjects in motor imagery and five subjects in selective sensation. Six subjects showed statistically significant improvement ( Benferroni-corrected) in hybrid modality in comparison with both motor imagery and selective sensation. Furthermore, among subjects having difficulties in both motor imagery and selective sensation, the hybrid modality improves their performance to 90% accuracy. The proposed hybrid modality BCI has demonstrated clear benefits for those poorly performing BCI users. Not only does the requirement of motor and sensory anticipation in this hybrid modality provide basic function of BCI for communication and control, it also has the potential for enhancing the rehabilitation during motor recovery.
Keywords :
brain-computer interfaces; skin; statistical analysis; Benferroni-corrected multiple comparison test; brain-computer interface; hybrid modality BCI; left mental tasks; motor imagery; right mental tasks; selective sensation; skin; two way ANOVA statistical analysis; wearable vibrotactile rings; wrists; BCI; hybrid modality; motor imagery (MI); selective sensation (SS);
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2013.2287245
Filename :
6656910
Link To Document :
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