SSVEP-based brain–computer interface for music using a low-density EEG system.
In this paper, we present a bespoke brain–computer interface (BCI), which was developed for a person with severe motor-impairments, who was previously a Violinist, to allow performing and composing music at home. It uses steady-state visually evoked potential (SSVEP) and adopts a dry, low-density, a...
| Publicado en: | Assistive Technology Vol. 35; no. 5; pp. 378 - 389 |
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| Autores principales: | , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=172440891&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 172440891 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10400435 YVP jtl: Assistive Technology issn: 10400435 maglogo: Y pubinfo: dt: 2023 vid: 35 iid: 5 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 172440891 157478338 172440891 172440891 10.1080/10400435.2022.2084182 172440891 ppf: 378 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: SSVEP-based brain–computer interface for music using a low-density EEG system. aug: au: Venkatesh, Satvik Miranda, Eduardo Reck Braund, Edward affil: Interdisciplinary Centre for Computer Music Research (ICCMR), University of Plymouth, Plymouth, UK sug: subj: Electroencephalography Equipment and Supplies Brain-Computer Interfaces Evoked Potentials Instrument Construction Canonical Correlation Analysis Calibration Human Male Female Young Adult Adult Middle Age Funding Source Assistive Technology Motor Skills Disorders Performing Artists Performing Arts Electrodes Adult: 19-44 years Middle Aged: 45-64 years Male Female ab: In this paper, we present a bespoke brain–computer interface (BCI), which was developed for a person with severe motor-impairments, who was previously a Violinist, to allow performing and composing music at home. It uses steady-state visually evoked potential (SSVEP) and adopts a dry, low-density, and wireless electroencephalogram (EEG) headset. In this study, we investigated two parameters: (1) placement of the EEG headset and (2) inter-stimulus distance and found that the former significantly improved the information transfer rate (ITR). To analyze EEG, we adopted canonical correlation analysis (CCA) without weight-calibration. The BCI for musical performance realized a high ITR of 37.59 ± 9.86 bits min−1 and a mean accuracy of 88.89 ± 10.09%. The BCI for musical composition obtained an ITR of 14.91 ± 2.87 bits min−1 and a mean accuracy of 95.83 ± 6.97%. The BCI was successfully deployed to the person with severe motor-impairments. She regularly uses it for musical composition at home, demonstrating how BCIs can be translated from laboratories to real-world scenarios. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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