Haptic Stimulation for Improving Training of a Motor Imagery BCI Developed for a Hand-Exoskeleton in Rehabilitation

Missiroli, Francesco; Barsotti, Michele; Leonardis, Daniele; Gabardi, Massimiliano; Rosati, Giulio; Frisoli, Antonio

doi:10.1109/icorr.2019.8779370

Cited by 9 publications

(9 citation statements)

References 28 publications

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“…Since the Pacinian and Meissner mechanoreceptors of human bodies are sensitive to vibrations of frequencies in the range of 20-50 Hz and higher than 100 Hz (Breitwieser et al, 2012). The target stimuli frequency was set as 100 Hz with a duration of 150 ms, the disturbances frequency was set to be 23 Hz with a duration of 200 ms, and intervals between were set to 400 ms. No significant difference in BCI performance was noted between tactile stimulation on finger pads or the wrist, but studies showed that the former has a broader and more stable event-related desynchronization (Missiroli et al, 2019). (1) Vibration stimulus trigger device on the top row: Four-channel DC motor drive (module STM32F103) with a rated power of 2 W. The driving voltage was adjustable from 0 to 5 V, and the vibration frequency was able to be changed from 0 to 300 Hz.…”

Section: Paradigm Designmentioning

confidence: 94%

A P300 Brain-Computer Interface Paradigm Based on Electric and Vibration Simple Command Tactile Stimulation

Chu

Tian

Han

et al. 2021

Front. Hum. Neurosci.

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This paper proposed a novel tactile-stimuli P300 paradigm for Brain-Computer Interface (BCI), which potentially targeted at people with less learning ability or difficulty in maintaining attention. The new paradigm using only two types of stimuli was designed, and different targets were distinguished by frequency and spatial information. The classification algorithm was developed by introducing filters for frequency bands selection and conducting optimization with common spatial pattern (CSP) on the tactile evoked EEG signals. It features a combination of spatial and frequency information, with the spatial information distinguishing the sites of stimuli and frequency information identifying target stimuli and disturbances. We investigated both electrical stimuli and vibration stimuli, in which only one target site was stimulated in each block. The results demonstrated an average accuracy of 94.88% for electrical stimuli and 95.21% for vibration stimuli, respectively.

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Section: Paradigm Designmentioning

confidence: 94%

A P300 Brain-Computer Interface Paradigm Based on Electric and Vibration Simple Command Tactile Stimulation

Chu

Tian

Han

et al. 2021

Front. Hum. Neurosci.

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“…The multi-session influence of vibrotactile feedback remains unknown. To our knowledge, all previous studies using vibrotactile feedback only assessed its impact during a single user training session [16][17][18][19][22][23][24]. Such multi-session influence could be impacted by the fact that negative vibrotactile feedback, that is, vibrations indicating to the user that there is a mismatch between the instructed task and the recognized task by the system, could interfere with the motor imagery task [16].…”

Section: Improving the Feedback Through Its Modalitymentioning

confidence: 99%

“…Related to this evolution of skills in time, an influence of the order of presentation of the feedback on BCI user training outcomes was already explicitly hypothesised in [19], but not formally evaluated. Several experiments testing the influence of two modalities of feedback have randomized their order of presentation [18,21,24], thus implicitly hypothesizing that the order of presentation of the modalities of feedback could influence their results. However, to our knowledge the influence of the order of presentation remains unknown and was never formally investigated.…”

Section: Improving the Feedback Through Its Modalitymentioning

confidence: 99%

“…In the previous Sections, we have highlighted the presence of several gaps in the literature. Previous studies using vibrotactile feedback assessed its influence during only a single training session [16][17][18][19][22][23][24]. Thus, the multi-session influence of vibrotactile feedback on BCI user training outcomes, that is, BCI performances and user experience, remains unknown.…”

Section: Research Hypothesesmentioning

confidence: 99%

“…Thus, the multi-session influence of vibrotactile feedback on BCI user training outcomes, that is, BCI performances and user experience, remains unknown. Also, an influence of the order of presentation of different modalities of feedback was hypothesised and taken into account in previous studies [18,19,21,24]. However, the influence of the order of presentation of the modalities of feedback on BCI user training outcomes, that is, BCI performances and user experience, has never been assessed.…”

Section: Research Hypothesesmentioning

confidence: 99%

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Multi-Session Influence of Two Modalities of Feedback and Their Order of Presentation on MI-BCI User Training

Pillette

N’Kaoua

Sabau

et al. 2021

MTI

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By performing motor-imagery tasks, for example, imagining hand movements, Motor-Imagery based Brain-Computer Interfaces (MI-BCIs) users can control digital technologies, for example, neuroprosthesis, using their brain activity only. MI-BCI users need to train, usually using a unimodal visual feedback, to produce brain activity patterns that are recognizable by the system. The literature indicates that multimodal vibrotactile and visual feedback is more effective than unimodal visual feedback, at least for short term training. However, the multi-session influence of such multimodal feedback on MI-BCI user training remained unknown, so did the influence of the order of presentation of the feedback modalities. In our experiment, 16 participants trained to control a MI-BCI during five sessions with a realistic visual feedback and five others with both a realistic visual feedback and a vibrotactile one. training benefits from a multimodal feedback, in terms of performances and self-reported mindfulness. There is also a significant influence of the order presentation of the modality. Participants who started training with a visual feedback had higher performances than those who started training with a multimodal feedback. We recommend taking into account the order of presentation for future experiments assessing the influence of several modalities of feedback.

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A portable SSVEP-BCI system for rehabilitation exoskeleton in augmented reality environment

Wang

Wen

et al. 2023

Biomedical Signal Processing and Control

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Haptic Stimulation for Improving Training of a Motor Imagery BCI Developed for a Hand-Exoskeleton in Rehabilitation

Cited by 9 publications

References 28 publications

A P300 Brain-Computer Interface Paradigm Based on Electric and Vibration Simple Command Tactile Stimulation

A P300 Brain-Computer Interface Paradigm Based on Electric and Vibration Simple Command Tactile Stimulation

Multi-Session Influence of Two Modalities of Feedback and Their Order of Presentation on MI-BCI User Training

A portable SSVEP-BCI system for rehabilitation exoskeleton in augmented reality environment

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