Large-Area 3D Printable Soft Electronic Skin for Biomedical Applications.

Soft electronic skin (soft-e-skin) capable of sensing touch and pressure similar to human skin is essential in many applications, including robotics, healthcare, and augmented reality. However, most of the research effort on soft-e-skin was confined to the lab-scale demonstration. Several hurdles remain challenging, such as highly complex and expensive fabrication processes, instability in long-term use, and difficulty producing large areas and mass production. Here, we present a robust 3D printable large-area electronic skin made of a soft and resilient polymer capable of detecting touch and load, and bending with extreme sensitivity (up to 150 kPa-1) to touch and load, 750 times higher than earlier work. The soft-e-skin shows excellent long-term stability and consistent performance up to almost a year. In addition, we describe a fabrication process capable of producing large areas and in large numbers, yet is cost-effective. The soft-e-skin consists of a uniquely designed optical waveguide and a layer of a soft membrane with an array of soft structures which work as passive sensing nodes. The use of a soft structure gives the liberty of stretching to the soft-e-skin without considering the disjoints among the sensing nodes. We have shown the functioning of the soft-e-skin under various conditions.

On chip optofluidic low-pressure monitoring device.

We present an on chip optofluidic surface deformable liquid Dove prism (LDP) based low-fluid flow pressure monitoring device. The unique design of the device in combination with liquid and soft solid enabled by the total internal reflection of light makes the sensor highly sensitive and compatible with the integration of a microfluidic and/or Lab-on-a-chip device. A layer-by-layer soft lithographic (LSL) and 3D printing technique are exploited to make the device. We have used Polydimethylsiloxane (PDMS) as the layer material and two variety of liquids (a) immersion oil (IO) and (b) di-iodomethane (DI) as refracting medium to construct the LDP sensor. Optical ray tracing simulation is performed to optimize the sensor. The pressure sensor shows sensitivity as high as ±28.5 mV per 50 Pa pressure with an error ± 2.5 mV and repeatability of ~99.56% at full scale. We have shown the applicability of the sensor by capturing and analyzing respiratory pressure signals of some human subjects at numerous conditions.