Brain-Computer Music Interfacing (BCMI): From Basic Research to the Real World of Special Needs

TLDR

Ergonomic and design aspects of the system require further refinement to make it more practical for clinical usage. This paper reports on developing a proof‑of‑concept brain‑computer music interfacing system (BCMI) tested with a patient with Locked‑in Syndrome at the Royal Hospital for Neuro‑disability, London. The system uses SSVEP with flashing visual patterns at unique frequencies, allowing the user to select actions by gazing at targets, and it currently requires therapist‑placed electrodes and calibration, but future versions will employ a headset and advanced algorithms to eliminate calibration. The patient quickly grasped the concept, rapidly demonstrated control with minimal practice, varied gaze intensity to modulate EEG amplitude and musical parameters, proving the system is cost‑effective, viable, and useful.

Abstract

This paper reports on the development of a proof-of-concept brain-computer music interfacing system (BCMI), which we built to be tested with a patient with Locked-in Syndrome at the Royal Hospital for Neuro-disability, in London. The system uses the Steady State Visual Evoked Potential (SSVEP) method, whereby targets are presented to a user on a computer monitor representing actions available to perform with the system. Each target is encoded by a flashing visual pattern reversing at a unique frequency. In order to make a selection, the user must direct her gaze at the target corresponding to the action she would like to perform. The patient grasped the concept quickly and rapidly demonstrated her skill at controlling the system with minimal practice. She was able to vary the intensity of her gaze, thus changing the amplitude of her EEG and vary the consequent musical parameters. We have proved the concept that such a BCMI system is cost-effective to build, viable, and useful. However, ergonomic and design aspects of the system require further refinement in order to make it more practical for clinical usage. For instance, the system at present requires a therapist to place individual electrodes and calibrate a user’s response to each stimulus, which can be time consuming. A new version of the system will require just positioning of a headset and, due to advanced algorithms, will require no calibration.