A brain-computer interface based on bilateral transcranial Doppler ultrasound.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Medical Imaging

Background:

• Brain-computer interfaces (BCIs) enable communication and control through brain activity.
• Current BCI methods often rely on electroencephalography (EEG), which can be limited by signal quality and setup complexity.
• Cerebral blood flow velocity monitoring offers a potential alternative for BCI signal acquisition.

Purpose of the Study:

• To investigate the feasibility of using transcranial Doppler ultrasound (TCD) for BCI applications.
• To determine if changes in cerebral blood flow velocity can be reliably classified during specific cognitive tasks.
• To assess the potential of TCD as a non-invasive measurement modality for BCI research.

Main Methods:

• Nine healthy adults participated in the study.
• Cerebral blood flow velocity was measured using TCD in the middle cerebral arteries.
• Participants alternated between two mental tasks (word generation and mental rotation) and a resting state.
• Linear discriminant analysis was applied to time-domain features of the TCD signals for classification.

Main Results:

• Classification accuracies for word generation and mental rotation tasks were 82.9%±10.5 and 85.7%±10.0, respectively.
• These accuracies significantly exceeded chance levels across all participants.
• The study demonstrated successful classification of distinct mental tasks based on TCD-measured cerebral blood flow velocity.

Conclusions:

• Transcranial Doppler ultrasound (TCD) is a feasible and promising measurement modality for BCI research.
• TCD can detect and classify cerebral blood flow velocity changes associated with cognitive tasks.
• This non-invasive technique offers a potential new avenue for developing advanced brain-computer interfaces.