Intelligent and Multifunctional Graphene Nanomesh Electronic Skin with High Comfort.

As the aging population increases in many countries, electronic skin (e-skin) for health monitoring has been attracting much attention. However, to realize the industrialization of e-skin, two factors must be optimized. The first is to achieve high comfort, which can significantly improve the user experience. The second is to make the e-skin intelligent, so it can detect and analyze physiological signals at the same time. In this article, intelligent and multifunctional e-skin consisting of laser-scribed graphene and polyurethane (PU) nanomesh is realized with high comfort. The e-skin can be used as a strain sensor with large measurement range (>60%), good sensitivity (GF≈40), high linearity range (60%), and excellent stability (>1000 cycles). By analyzing the morphology of e-skin, a parallel networks model is proposed to express the mechanism of the strain sensor. In addition, laser scribing is also applied to etch the insulating PU, which greatly decreases the impedance in detecting electrophysiology signals. Finally, the e-skin is applied to monitor the electrocardiogram, electroencephalogram (EEG), and electrooculogram signals. A time- and frequency-domain concatenated convolution neural network is built to analyze the EEG signal detected using the e-skin on the forehead and classify the attention level of testers.

Graphene-based wearable sensors.

The human body is a "delicate machine" full of sensors such as the fingers, nose, and mouth. In addition, numerous physiological signals are being created every moment, which can reflect the condition of the body. The quality and the quantity of the physiological signals are important for diagnoses and the execution of therapies. Due to the incompact interface between the sensors and the skin, the signals obtained by commercial rigid sensors do not bond well with the body; this decreases the quality of the signal. To increase the quantity of the data, it is important to detect physiological signals in real time during daily life. In recent years, there has been an obvious trend of applying graphene devices with excellent performance (flexibility, biocompatibility, and electronic characters) in wearable systems. In this review, we will first provide an introduction about the different methods of synthesis of graphene, and then techniques for graphene patterning will be outlined. Moreover, wearable graphene sensors to detect mechanical, electrophysiological, fluid, and gas signals will be introduced. Finally, the challenges and prospects of wearable graphene devices will be discussed. Wearable graphene sensors can improve the quality and quantity of the physiological signals and have great potential for health-care and telemedicine in the future.