Brain-Computer Interfaces in Parkinson's Disease Rehabilitation.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Neurology

Background:

• Parkinson's disease (PD) presents significant motor and non-motor challenges inadequately managed by current treatments.
• Non-invasive electroencephalography-based brain-computer interfaces (eBCIs) offer a novel approach for personalized neurorehabilitation in PD.

Purpose of the Study:

• To review the clinical potential of BCIs in managing Parkinson's disease.
• To explore BCI applications in signal acquisition, processing, and control for PD.
• To discuss emerging biomarkers and their role in adaptive therapies and diagnosis.

Main Methods:

• A narrative review synthesizing current research on BCIs for PD.
• Structured literature search identifying 11 studies with 64 PD patients using BCIs.
• Analysis of BCI applications including adaptive deep brain stimulation (aDBS), neurofeedback, and cognitive rehabilitation.

Main Results:

• BCIs demonstrated improvements in motor function, cognitive abilities, and patient engagement across reviewed studies.
• Identified neurophysiological biomarkers (e.g., beta-band synchrony) can inform adaptive therapies.
• BCIs show potential for aiding PD diagnosis and personalized treatment strategies.

Conclusions:

• BCIs represent a transformative tool for Parkinson's disease management, offering continuous, brain-responsive therapy.
• Clinical translation necessitates advancements in electrode design and user-centered interfaces.
• Addressing ethical considerations like data privacy and access is crucial for widespread adoption.