Biomimetic metamaterial-based interface for decoding heterogeneous mechanodermal activity

Area of Science:

• Biomaterials Science
• Biomedical Engineering
• Sensing Technologies

Background:

• Human skin is a dynamic biomechanical interface transmitting physiological and behavioral data via deformations.
• Current sensing technologies inadequately capture the full spectrum of skin's mechanical signals, limiting applications.
• The diversity of mechanical cues from skin, termed mechanodermal activity (MDA), remains largely underutilized.

Purpose of the Study:

• To introduce a novel biomimetic metamaterial-based interface (BMMI) for capturing and decoding mechanodermal activity (MDA).
• To engineer a BMMI that replicates natural skin's microrelief and mechanoreceptor architecture.
• To enable accurate and robust decoding of MDA for advanced applications.

Main Methods:

• Developed an engineered auxetic metamaterial substrate (BMMI) mimicking skin's natural properties.
• Designed the BMMI for selective capture, signal amplification, and noise suppression of MDA.
• Integrated BMMI with bespoke algorithms for wireless decoding of MDA signals.

Main Results:

• The BMMI successfully captures diverse MDA signals from adjacent skin regions.
• Simultaneous signal amplification and noise suppression were achieved with the BMMI.
• Wireless BMMI device accurately and robustly decodes MDA using specialized algorithms.

Conclusions:

• The BMMI represents a significant advancement in sensing skin's mechanical cues.
• This technology unlocks new possibilities for multimodal communication interfaces.
• Applications in health care monitoring and human-machine interaction are greatly enhanced by this innovation.