A Size-Cuttable, Skin-Interactive Wearable Sensor for Digital Deciphering of Epidermis Wavy Deformation

Area of Science:

• Biomedical Engineering
• Wearable Technology
• Digital Medicine

Background:

• Body shape and curvature are critical health indicators, yet their measurement is understudied.
• Existing methods for assessing body curvature lack precision and detail.
• Understanding skin deformation is key to developing advanced health monitoring tools.

Purpose of the Study:

• To develop a skin-interactive electronic sticker for digitally decoding epidermis deformation.
• To enable precise measurement of body curvature in static and dynamic modes.
• To explore potential applications in gesture control, rehabilitation, and biophysical state detection.

Main Methods:

• A thin electronic sticker (76 μm thickness, 7.45 mm node pitch) was designed for skin deformation measurement.
• The device operates in two modes: static (body curvature) and dynamic (skin wave fluctuations).
• Feedforward deep learning was employed for data analysis, achieving high accuracy and F1 scores.

Main Results:

• The electronic sticker demonstrated high detection sensitivity in static mode.
• Dynamic mode achieved high accuracy (0.986) and an F1 score (0.966) in deciphering skin wave fluctuations.
• The system successfully deciphered 32 finger folding gestures by analyzing skin depth and position via image segmentation.

Conclusions:

• The developed electronic sticker offers a sensitive and accurate method for measuring body curvature and skin dynamics.
• This technology has significant potential for wearable applications, including gesture control in the metaverse and rehabilitation.
• The device advances digital medicine by providing a novel way to monitor biophysical states related to body shape and curvature.