Relationship between event-related beta synchronization and afferent inputs: Analysis of finger movement and peripheral nerve stimulations

Chen

et al. 2018

Abstract-We proposed a multi-class tactile brain-computer interface that utilizes stimulus-induced oscillatory dynamics. It was hypothesized that somatosensory attention can modulate tactile induced oscillation changes, which can decode different sensation attention tasks. Subjects performed four tactile attention tasks, prompted by cues presented in random order and while both wrists were simultaneously stimulated: 1) selective sensation on left hand (SS-L), 2) selective sensation on right hand (SS-R), 3) bilateral selective sensation (SS-B), and 4) selective sensation suppressed or idle state (SS-S). The classification accuracy between SS-L and SS-R (79.9±8.7%) was comparable with that of a previous tactile BCI system based on selective sensation. Moreover, the accuracy could be improved to an average of 90.3±4.9% by optimal class-pair and frequency-band selection. Three-class discrimination had accuracy of 75.2±8.3%, with the best discrimination reached for the classes SS-L, SS-R and SS-S. Finally, four classes were classified with accuracy of 59.4±7.3%. These results show that the proposed system is a promising new paradigm for multi-class BCI.

Section: Discussionmentioning

confidence: 99%

A Multi-Class Tactile Brain–Computer Interface Based on Stimulus-Induced Oscillatory Dynamics

Chen

et al. 2018

“…It has a frequency specific feature, which is related to the stimulation frequency [34], [38]. In contrast, the ERD/ERS oscillatory dynamics reflects somatosensory processing, and has a non-stimulation frequency specific feature [50]. Therefore, the ERD/ERS oscillatory response and SSSEP response provide complementary information of the somatosensory input processing.…”

Section: A Bci-illiteracy Problem In Tactile Bcimentioning

confidence: 99%

“…BCIs using MI and SS are both based on the dynamics of brain oscillation quantified as ERD/ERS [45], [46], which are modulated during imagined movement [2], [47], [48], and during perceiving sensory stimulation [42], [43], [49], [50]. For instance, motor imagery of hand movements accompanies contralateral ERD and ipsilateral ERS [2], [51], while selective attention modulates somatosensory oscillations in the alpha and beta bands [40], [52], which results in significantly increased beta ERD/ERS due to attentional effects.…”

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confidence: 99%

Performance of Brain–Computer Interfacing Based on Tactile Selective Sensation and Motor Imagery

Mrachacz-Kersting

et al. 2018

-A large proportion of users do not achieve adequate control using current non-invasive Brain-computer Interfaces (BCI). This issue has being coined "BCI-Illiteracy", and is observed among BCI modalities. Here, we compare the performance and BCI-illiteracy rate of tactile selective sensation (SS) and motor imagery (MI) BCI, for 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 to previous results, this tactile BCI outperformed all other tactile BCIs currently available. We also analyzed 63 experiment 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 exceeded 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 R 2 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.

“…This class is represented by auditory steady-state evoked potentials (ASSEP) [12], steady-state visual evoked potentials (SSVEP) [13], and steady-state somatosensory evoked potential (SSSEP) [14]- [16]. In addition to evoked potentials and steady-state responses, sensory stimulation can also induce oscillatory rhythmic activities [17], which may reflect the way in which the brain processes these stimuli [18], [19]. This is the main characteristics of oscillatory BCIs.…”

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confidence: 99%

A Stimulus-Independent Hybrid BCI Based on Motor Imagery and Somatosensory Attentional Orientation

Zhang

et al. 2017

Abstract-We propose and test a novel brain-computer interface (BCI) based on imagined tactile sensation. During an imagined tactile sensation, referred to as somatosensory attentional orientation (SAO), the subject shifts and maintains somatosensory attention on a body part, e.g., left or right hand. The SAO can be detected from EEG recordings for establishing a communication channel. To test for the hypothesis that SAO on different body parts can be discriminated from EEG, 14 subjects were assigned to a group who received an actual sensory stimulation (STE-Group), and 18 subjects were assigned to the SAO only group (SAO-Group). In single trials, the STE-Group received tactile stimulation first (both wrists simultaneously stimulated), and then maintained the attention on the selected body part (without stimulation). The same group also performed the SAO task first and then received the tactile stimulation. Conversely, the SAO-Group performed SAO without any stimulation, neither before nor after the SAO. In both the STE-Group and SAOGroup, it was possible to identify the SAO-related oscillatory activation that corresponded to a contralateral event-related desynchronization (ERD) stronger than the ipsilateral ERD. Discriminative information, represented as R 2 , was found mainly on the somatosensory area of the cortex. In the STE-Group, the average classification accuracy of SAO was 83.6%, and it was comparable with tactile BCI based on selective sensation (paired-t test, P > 0.05). In the SAO-Group the average online performance was 75.7%. For this group, after frequency band selection the offline performance reached 82.5% on average, with ≥80% for 12 subjects and ≥95% for 4 subjects. Complementary to tactile sensation, the SAO does not require sensory stimulation, with the advantage of being completely independent from the stimulus.