Performance of Brain-Computer Interfacing Based on Tactile Selective Sensation and Motor Imagery
File(s)TNSRE_AcceptedVersion.doc (7.9 MB)
Accepted version
Author(s)
Type
Journal Article
Abstract
A large proportion of users do not achieve adequate control using current non-invasive brain–computer interfaces (BCIs). This issue has being coined “BCI-Illiteracy” and is observed among different BCI modalities. Here, we compare the performance and the BCI-illiteracy rate of a tactile selective sensation (SS) and motor imagery (MI) BCI, for a large subject samples. We analyzed 80 experimental sessions from 57 subjects with two-class SS protocols. For SS, the group average performance was 79.8 ± 10.6%, with 43 out of the 57 subjects (75.4%) exceeding the 70% BCI-illiteracy threshold for left- and right-hand SS discrimination. When compared with previous results, this tactile BCI outperformed all other tactile BCIs currently available. We also analyzed 63 experimental sessions from 43 subjects with two-class MI BCI protocols, where the group average performance was 77.2 ± 13.3%, with 69.7% of the subjects exceeding the 70% performance threshold for left- and right-hand MI. For within-subject comparison, the 24 subjects who participated to both the SS and MI experiments, the BCI performance was superior with SS than MI especially in beta frequency band (p < 0.05), with enhanced R2 discriminative information in the somatosensory cortex for the SS modality. Both SS and MI showed a functional dissociation between lower alpha ([8 10] Hz) and upper alpha ([10 13] Hz) bands, with BCI performance significantly better in the upper alpha than the lower alpha (p < 0.05) band. In summary, we demonstrated that SS is a promising BCI modality with low BCI illiteracy issue and has great potential in practical applications reaching large population.
Date Issued
2017-11-03
Date Acceptance
2017-10-30
Citation
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2017, 26 (1), pp.60-68
ISSN
1534-4320
Publisher
Institute of Electrical and Electronics Engineers
Start Page
60
End Page
68
Journal / Book Title
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume
26
Issue
1
Copyright Statement
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Subjects
0903 Biomedical Engineering
0906 Electrical And Electronic Engineering
Biomedical Engineering
Publication Status
Published