Young Heon Kim, Jongil Ju, Sang-Hoon Lee, Sung Woo Nam, Hyung-Min Chung, Heeyeong Jang, Yongseok Jun, Jonghyun Choi, Dong Han Ha, Won G. Hong, Yong Ju Yun, Soon-Jung Park, Sung-Hwan Moon, Joong Hoon Lee, Geon Hui Lee
Epidermal electronics are extensively explored as an important platform for future biomedical engineering. Epidermal devices are typically fabricated using high-cost methods employing complex vacuum microfabrication processes, limiting their widespread potential in wearable electronics. Here, a low-cost, solution-based approach using electroconductive reduced graphene oxide (RGO) sheets on elastic and porous poly(dimethylsiloxane) (PDMS) thin films for multifunctional, high-performance, graphene-based epidermal bioelectrodes and strain sensors is presented. These devices are fabricated employing simple coatings and direct patterning without using any complicated microfabrication processes. The graphene bioelectrodes show a superior stretchability (up to 150% strain), with mechanical durability up to 5000 cycles of stretching and releasing, and low sheet resistance (1.5 kΩ per square), and the graphene strain sensors exhibit a high sensitivity (a gauge factor of 7 to 173) with a wide sensing range (up to 40% strain). Fully functional applications of dry bioelectrodes in monitoring human electrophysiological signals (i.e., electrocardiogram, electroencephalography, and electromyogram) and highly sensitive strain sensors for precise detection of large-scale human motions are demonstrated. It is believed that our unique processing capability and multifunctional device platform based on RGO/porous PDMS will pave the way for low-cost processing and integration of 2D materials for future wearable electronic skin.
A solution-based approach using electroconductive reduced graphene oxide sheets on elastic and porous PDMS thin films for multifunctional, high-performance graphene-based epidermal bioelectrode/strain sensors is presented. Fully functional applications of bioelectrodes in monitoring electrophysiological signals using human and strain sensors for precisely detecting large-scale human motions are demonstrated.
