Motion Neural Monitoring Based on Flexible Materials: From Signal Acquisition to Training Enhancement

Area of Science:

• Biomedical Engineering
• Neuroscience
• Materials Science

Background:

• Acquiring microvolt-level neural signals (EEG/EMG) during intense physical activity is hindered by motion artifacts and unstable interfaces.
• Existing flexible electronics struggle with the dynamic and demanding nature of motion-based neural monitoring.

Purpose of the Study:

• To review how advanced flexible bioelectronics address challenges in motion-induced neural signal acquisition.
• To elucidate mechanisms for optimizing electrode-interface stability and signal quality during movement.

Main Methods:

• Systematic examination of engineered materials and electrode structures for enhanced dynamic interface electrochemistry.
• Summarization of strategies to suppress electrochemical noise (half-cell potential fluctuations, ionic shunts, piezoresistive noise).
• Exploration of multimodal systems integrating kinematic sensors for artifact decoupling.

Main Results:

• Engineered flexible bioelectronics demonstrate potential to overcome macroscopic mechanical compliance issues.
• Strategies for localized dielectric control (e.g., sweat management) and dynamic percolation networks effectively reduce artifacts.
• Integration with kinematic sensors allows for effective artifact decoupling.

Conclusions:

• Advanced flexible bioelectronics offer a pathway to precision motion-neural platforms beyond passive wearables.
• Future directions include enhancing long-term electrochemical robustness, standardizing artifact evaluation, and developing AI-driven digital twins.
• This work provides fundamental insights for developing robust neural interfaces for dynamic applications.