A self-powered hydrogel electronic skin with decoupled multimodal sensing for closed-loop human-machine interactions

Area of Science:

• Materials Science
• Biomedical Engineering
• Artificial Intelligence

Background:

• Intelligent interfaces require flexible electronics mimicking skin's multifunctionality.
• Current multimodal sensors are often rigid, discrete, and require external power.
• Achieving compact, self-sustained multifunctional e-skin remains a challenge.

Purpose of the Study:

• To develop a single-component hydrogel e-skin for self-powered multimodal sensing.
• To integrate thermogalvanic, piezoionic, and diffusion mechanisms into one material.
• To create a multifunctional human-machine interface for physiological detection and control.

Main Methods:

• Fabrication of a stretchable, low-modulus poly(vinyl alcohol) hydrogel with a prismatic architecture.
• Integration of thermogalvanic, piezoionic, and diffusion sensing mechanisms.
• Development of a temporal machine learning model with local attention for signal decoupling.

Main Results:

• The hydrogel e-skin achieved simultaneous self-powered sensing of skin temperature, arterial pulsation, and sweat secretion.
• The material demonstrated high stretchability and a unique prismatic architecture.
• A multimodal signal generator wristband was created for physiological detection, robotic control, and haptic feedback.

Conclusions:

• The developed hydrogel e-skin is an efficient material platform for intelligent interactions.
• This technology shows significant potential for real-time health monitoring, advanced robotic control, and immersive virtual reality applications.
• The single-component, self-powered approach overcomes limitations of existing multimodal sensors.