Recently, wearable electronic products and gadgets have developed quickly with the aim of catching up to or perhaps surpassing the ability of human skin to perceive information from the external world, such as pressure and strain. In this study, by first treating the cellulosic fiber (modal textile) substrate with (3-aminopropyl) triethoxysilane (APTES) and then covering it with conductive nanocomposites, a bionic corpuscle layer is produced. The sandwich structure of tactile corpuscle-inspired bionic (TCB) piezoresistive sensors created with the layer-by-layer (LBL) technology consists of a pressure-sensitive module (a bionic corpuscle), interdigital electrodes (a bionic sensory nerve), and a PU membrane (a bionic epidermis). The synergistic mechanism of hydrogen bond and coupling agent helps to improve the adhesive properties of conductive materials, and thus improve the pressure sensitive properties. The TCB sensor possesses favorable sensitivity (1.0005 kPa-1), a wide linear sensing range (1700 kPa), and a rapid response time (40 ms). The sensor is expected to be applied in a wide range of possible applications including human movement tracking, wearable detection system, and textile electronics.

Wearable humidity sensors are attracting strong attention as they allow for real-time and continuous monitoring of important physiological information by enabling activity tracking as well as air quality assessment. Amongst 2Dimensional (2D) materials, graphene oxide (GO) is very attractive for humidity sensing due to its tuneable surface chemistry, high surface area, processability in water, and easy integration onto flexible substrates. However, strong hysteresis, low sensitivity, and cross-sensitivity issues limit the use of GO in practical applications, where continuous monitoring is preferred. Herein, a wearable and wireless impedance-based humidity sensor made with pyrene-functionalized hexagonal boron nitride (h-BN) nanosheets is demonstrated. The device shows enhanced sensitivity towards relative humidity (RH) (>1010 Ohms/%RH in the range from 5% to 100% RH), fast response (0.1 ms), no appreciable hysteresis, and no cross-sensitivity with temperature in the range of 25-60 °C. The h-BN-based sensor is able to monitor the whole breathing cycle process of exhaling and inhaling, hence enabling to record in real-time the subtlest changes of respiratory signals associated with different daily activities as well as various symptoms of flu, without requiring any direct contact with the individual.

Biosensors that sense the concentration of a specified target and produce a specific signal output have become important technology for biological analysis. Recently, intelligent biosensors have received great interest due to their adaptability to meet sophisticated demands. Advances in developing standard modules and carriers in synthetic biology have shed light on intelligent biosensors that can implement advanced analytical processing to better accommodate practical applications. This review focuses on intelligent synthetic biology-enabled biosensors (SBBs). First, we illustrate recent progress in intelligent SBBs with the capability of computation, memory storage, and self-calibration. Then, we discuss emerging applications of SBBs in point-of-care testing (POCT) and wearable monitoring. Finally, future perspectives on intelligent SBBs are proposed.

As a vital biomarker, glucose plays an important role in multiple physiological and pathological processes. Thus, glucose detection has become an important direction in the electrochemical analysis field. In order to realize more convenient, real-time, comfortable and accurate monitoring, smartphone-based portable, wearable and implantable electrochemical glucose monitoring is progressing rapidly. In this review, we firstly introduce technologies integrated in smartphones and the advantages of these technologies in electrochemical glucose detection. Subsequently, this overview illustrates the advances of smartphone-based portable, wearable and implantable electrochemical glucose monitoring systems in diverse biofluids over the last ten years (2012-2022). Specifically, some interesting and innovative technologies are highlighted. In the last section, after discussing the challenges in this field, we offer some future directions, such as application of advanced nanomaterials, novel power sources, simultaneous detection of multiple markers and a closed-loop system.

MXene based composite conductive aerogels have been extensively investigated as sensitive materials for wearable pressure sensors owing to their effective 3D network microstructures and the excellent conductivity of MXene. In this work, we fabricated a 3D porous Ti3C2Tx MXene/poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) composite aerogel (MPCA) with a controllable patterning property utilizing the Cu-assisted electrogelation method. The prepared composite aerogel can be assembled into pressure sensors for wearable physical monitoring and high-resolution sensor microarrays for robotic tactile sensing. The multi-interactions between MXene and PEDOT:PSS enable the MPCA to have a stable 3D conductive network, which consequently enhances both the mechanical flexibility and the piezoresistive property of the MPCA. Thus, the fabricated pressure sensor demonstrating high sensitivity (26.65 kPa-1 within 0-2 kPa), fast response ability (106 ms), and excellent stability can be further applied for wearable physical monitoring. Moreover, due to the controllable patterning property of the electrogelation preparation method, a high-resolution pressure sensor microarray was successfully prepared as an artificial tactile interface, which can be attached to a robotic fingertip to directly recognize the tactile stimuli from human fingers and identify braille letters like human fingers. The proposed MPCA, endowed with a remarkable comprehensive property, particularly the highly sensitive sensing performance and controllable patterning property, demonstrates an enormous advantage and a great potentiality toward wearable electronics.