This paper presents a wearable brain–computer interface relying on neurofeedback in extended reality for the enhancement of motor imagery training. Visual and vibrotactile feedback modalities were evaluated when presented either singularly or simultaneously. Only three acquisition channels and state-of-the-art vibrotactile chest-based feedback were employed. Experimental validation was carried out with eight subjects participating in two or three sessions on different days, with 360 trials per subject per session. Neurofeedback led to statistically significant improvement in performance over the two/three sessions, thus demonstrating for the first time functionality of a motor imagery-based instrument even by using an utmost wearable electroencephalograph and a commercial gaming vibrotactile suit. In the best cases, classification accuracy exceeded 80 % with more than 20 % improvement with respect to the initial performance. No feedback modality was generally preferable across the cohort study, but it is concluded that the best feedback modality may be subject-dependent.
Visual and haptic feedback in detecting motor imagery within a wearable brain-computer interface / Arpaia, Pasquale; Coyle, Damien; Donnarumma, Francesco; Esposito, Antonio; Natalizio, Angela; Parvis, Marco. - In: MEASUREMENT. - ISSN 0263-2241. - STAMPA. - 206:(2023), p. 112304. [10.1016/j.measurement.2022.112304]
Visual and haptic feedback in detecting motor imagery within a wearable brain-computer interface
Angela Natalizio;Marco Parvis
2023
Abstract
This paper presents a wearable brain–computer interface relying on neurofeedback in extended reality for the enhancement of motor imagery training. Visual and vibrotactile feedback modalities were evaluated when presented either singularly or simultaneously. Only three acquisition channels and state-of-the-art vibrotactile chest-based feedback were employed. Experimental validation was carried out with eight subjects participating in two or three sessions on different days, with 360 trials per subject per session. Neurofeedback led to statistically significant improvement in performance over the two/three sessions, thus demonstrating for the first time functionality of a motor imagery-based instrument even by using an utmost wearable electroencephalograph and a commercial gaming vibrotactile suit. In the best cases, classification accuracy exceeded 80 % with more than 20 % improvement with respect to the initial performance. No feedback modality was generally preferable across the cohort study, but it is concluded that the best feedback modality may be subject-dependent.File | Dimensione | Formato | |
---|---|---|---|
1-s2.0-S0263224122015007-main.pdf
non disponibili
Tipologia:
2a Post-print versione editoriale / Version of Record
Licenza:
Non Pubblico - Accesso privato/ristretto
Dimensione
1.54 MB
Formato
Adobe PDF
|
1.54 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Measurement__MI_BCI_with_feedback (1).pdf
embargo fino al 05/12/2024
Tipologia:
2. Post-print / Author's Accepted Manuscript
Licenza:
Creative commons
Dimensione
2.23 MB
Formato
Adobe PDF
|
2.23 MB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11583/2974774