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SSVEP-based brain–computer interface for music using a low-density EEG system

  • University of Plymouth

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
1 Downloads (Pure)

Abstract

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.
Original languageEnglish
Pages (from-to)378-388
Number of pages11
JournalAssistive Technology: The Offical Journal of RESNA
Volume35
Issue number5
DOIs
Publication statusPublished - 11 Jul 2022

Keywords

  • Artificial Intelligence
  • Signal Processing
  • brain-neuronal computer interface
  • human-computer interaction
  • brain–computer interface (BCI)
  • musical composition
  • dry electroencephalogram (EEG)
  • computer music
  • musical performance

ASJC Scopus subject areas

  • Physical Therapy, Sports Therapy and Rehabilitation
  • Rehabilitation

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