Flexible pressure sensors have been widely applied in wearable devices, e-skin, and the new generation of robots. However, most of the current sensors use connecting wires for energy supply and signal transmission, which presents an obstacle for application scenarios requiring long endurance and large movement, especially. Flexible sensors combined with wireless technology is a promising research field for realizing efficient state sensing in an active state. Here, we designed and fabricated a soft wireless passive pressure sensor, with a fully flexible Ecoflex substrate and a multi-walled carbon nanotube/polydimethylsiloxane (MWCNT/PDMS) bilayer pyramid dielectric structure. Based on the principle of the radio-frequency resonator, the device achieved pressure sensing with a changeable capacitance. Subsequently, the effect of the pyramid density was simulated by the finite element method to improve the sensitivity. With one-step embossing and spin-coating methods, the fabricated sensor had an optimized sensitivity of 14.25 MHz/kPa in the low-pressure range. The sensor exhibited the potential for application in limb bending monitoring, thus demonstrating its value for long-term wireless clinical monitoring. Moreover, the radio frequency coupling field can be affected by approaching objects, which provides a possible route for realizing non-contact sensing in applications such as pre-collision warning.

Currently, human sensing draws much attention in the field of ubiquitous computing, and human sensing based on WiFi CSI (channel state information) becomes a hot research topic due to the easy deployment and availability of WiFi devices. Although various human sensing applications based on the CSI signal model are emerging, the model-based approach has not been studied thoroughly. This paper provides a comprehensive survey of the latest model-based human sensing methods and their applications. First, the CSI signal and framework of model-based human sensing methods are introduced. Then, related models and fundamental signal preprocessing techniques are described. Next, typical human sensing applications are investigated, and the crucial characteristics are summarized. Finally, the advantages, limitations, and future research trends of model-based human sensing methods are concluded in this paper.

Hybrid rigid-soft electronic system combines the biocompatibility of stretchable electronics and the computing capacity of silicon-based chips, which has a chance to realize a comprehensive stretchable electronic system with perception, control, and algorithm in near future. However, a reliable rigid-soft interconnection interface is urgently required to ensure both the conductivity and stretchability under a large strain. To settle this demand, this paper proposes a graded Mxene-doped liquid metal (LM) method to achieve a stable solid−liquid composite interconnect (SLCI) between the rigid chip and stretchable interconnect lines. To overcome the surface tension of LM, a high-conductive Mxene is doped for the balance between adhesion and liquidity of LM. And the high-concentration doping could prevent the contact failure with chip pins, while the low-concentration doping tends to maintain the stretchability. Based on this dosage-graded interface structure, the solid light-emitting diode (LED) and other devices integrated into the stretchable hybrid electronic system could achieve an excellent conductivity insensitive to the exerted tensile strain. In addition, the hybrid electronic system is demonstrated for skin-mounted and tire-mounted temperature-test applications under the tensile strain up to 100%. This Mxene-doped LM method aims to obtain a robust interface between rigid components and flexible interconnects by attenuating the inherent Young's modulus mismatch between rigid and flexible systems and makes it a promising candidate for effective interconnection between solid electronics and soft electronics.

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