A Review of Brain-Computer Interface Technologies: Signal Acquisition Methods and Interaction Paradigms

Abstract

The authors characterize their work as providing an in-depth analysis of various BCI paradigms — including classic and contemporary approaches — while examining signal acquisition methods categorized as non-implantation, intervention, and implantation techniques. The review emphasizes the synergy between paradigm design and signal acquisition techniques as essential for developing efficient and user-friendly BCI systems.

Key Contributions

• Comprehensive categorization of BCI paradigms: Motor Imagery, P300, SSVEP, and hybrid approaches
• Classification of signal acquisition methods across three invasiveness levels (non-implantation, intervention, implantation)
• Analysis of interdependencies between paradigm design and acquisition technologies
• Exploration of emerging paradigms including auditory, olfactory, and tactile BCIs
• Discussion of passive BCI approaches for state monitoring (fatigue, attention, emotion)

Methodology

Systematic literature review examining BCI development from historical foundations (1924 EEG recording) through contemporary applications. Analyzes classical and current BCI paradigm classifications alongside corresponding signal acquisition techniques, investigating their reciprocal influence on system performance and development trajectories.

Results

• Motor Imagery BCIs enable intuitive control but require individualized training
• P300 paradigms offer rapid user adaptation with high accuracy potential
• SSVEP systems demonstrate robust performance but cause visual fatigue concerns
• Non-invasive methods (EEG, fNIRS) prioritize safety while sacrificing spatial resolution
• Emerging intervention techniques (stentrodes, in-ear bioelectronics) balance invasiveness with signal quality
• Implantation methods achieve superior signal fidelity at increased surgical risk

Limitations

EEG demonstrates low spatial resolution, sensitivity to artifacts, and limited ability to detect deep brain activity. Paradigm effectiveness varies significantly between individuals. Prolonged SSVEP exposure causes user discomfort. Emerging technologies require further validation for long-term biocompatibility and clinical viability.

Source: A Review of Brain-Computer Interface Technologies: Signal Acquisition Methods and Interaction Paradigms by Yifan Wang, Cheng Jiang, Chenzhong Li, The Chinese University of Hong Kong, Shenzhen