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

Assist Technol. 2023 Sep 3;35(5):378-388. doi: 10.1080/10400435.2022.2084182. Epub 2022 Jul 11.


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.

Keywords: brain–computer interface (BCI); computer music; dry electroencephalogram (EEG); musical composition; musical performance.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Brain-Computer Interfaces*
  • Electroencephalography
  • Evoked Potentials
  • Evoked Potentials, Visual
  • Female
  • Humans
  • Music*
  • Photic Stimulation