Flexible wearable sweat sensors allow continuous, real-time, noninvasive detection of sweat analytes, provide insight into human physiology at the molecular level, and have received significant attention for their promising applications in personalized health monitoring. Electrochemical sensors are the best choice for wearable sweat sensors due to their high performance, low cost, miniaturization, and wide applicability. Recent developments in soft microfluidics, multiplexed biosensing, energy harvesting devices, and materials have advanced the compatibility of wearable electrochemical sweat-sensing platforms. In this review, we summarize the potential of sweat for medical detection and methods for sweat stimulation and collection. This paper provides an overview of the components of wearable sweat sensors and recent developments in materials and power supply technologies and highlights some typical sensing platforms for different types of analytes. Finally, the paper ends with a discussion of the challenges and a view of the prospective development of this exciting field.

Pressure sensors with high sensitivity, a wide linear range, and a quick response time are critical for building an intelligent disease diagnosis system that directly detects and recognizes pulse signals for medical and health applications. However, conventional pressure sensors have limited sensitivity and nonideal response ranges. We proposed a multichannel flexible pulse perception array based on polyimide/multiwalled carbon nanotube-polydimethylsiloxane nanocomposite/polyimide (PI/MPN/PI) sandwich-structure pressure sensor that can be applied for remote disease diagnosis. Furthermore, we established a mechanical model at the molecular level and guided the preparation of MPN. At the structural level, we achieved high sensitivity (35.02 kPa^-1) and a broad response range (0-18 kPa) based on a pyramid-like bilayer microstructure with different upper and lower surfaces. A 27-channel (3 × 9) high-density sensor array was integrated at the device level, which can extract the spatial and temporal distribution information on a pulse. Furthermore, two intelligent algorithms were developed for extracting six-dimensional pulse information and automatic pulse recognition (the recognition rate reaches 97.8%). The results indicate that intelligent disease diagnosis systems have great potential applications in wearable healthcare devices.

Flexible tactile sensors have become one of the most attractive research areas because of its great application prospect in electronic skin, healthcare monitoring and artificial intelligence. However, there are still great challenges in mimicking the human skin’s strong ability of tactile perception to the changes of external physical information. Nowadays, in addition to flexible polymers and conductive materials, the microstructure of sensing units is a key factor to improve the performance of tactile sensors such as sensitivity, fast response and robustness. In recent years, a variety of novel microstructure designs have been applied to applications of tactile information perception and numerous corresponding processing methods have also been developed, which provides a wealth of enlightening solutions for the production of electronic skins. Herein, a large number of research results of tactile sensor devices are systematically reviewed according to different three-dimensional geometric shapes of the microstructures which are grouped into several categories. At the same time, relevant processing technologies employed, working principles and chief performance characteristics are also briefly described. Relative merits of different types of microstructure applications are clearly elaborated through the classification and comparison of multiple microstructure geometries in this paper to provide valuable reference for sensing microstructure design and fabrication of tactile sensors in corresponding engineering applications. Moreover, current difficulties and challenges in fabrication of flexible microstructures and future investigative directions pertaining to this field have been discussed.

The cuff-less blood pressure (BP) monitoring method based on photoplethysmo- gram (PPG) makes it possible for long-term BP monitoring to prevent and treat cardiovascular and cerebrovascular events. In this paper, a portable BP prediction system based on feature combination and artificial neural network (ANN) is implemented. The robustness of the model is improved from three aspects. Firstly, an adaptive peak extraction algorithm was used to improve the accuracy of peaks and troughs detection. Secondly, multi-dimensional features were extracted and fused, including three groups of PPG-based features and one group of demographics-based features. Finally, a two-layer feedforward artificial neural networks algorithm was used for regression. Thirty-three subjects distributed in the three BP groups were recruited. The proposed method passed the European Society of Hypertension International Protocol revision 2010 (ESP-IP2). Experimental results show that the proposed method exhibits good accuracy for a diverse population with an estimation error of −0.07 ± 4.47 mmHg for SBP and 0.00 ± 3.61 mmHg for DBP. Moreover, the model tracked the BP of two subjects for half a month, laying the foundation work for daily BP monitoring. This work will contribute to the long-term wellness management and rehabilitation process, enabling timely detection and improvement of the user's physical health.

With the increasing demand for total knee arthroplasty (TKA) surgery, more attention has been paid to the accurate measurement of pressure and adjustment of knee prosthesis. The tightness between artificial meniscus and articular head and the thickness of artificial meniscus will directly affect the matching between knee joint and human body. At present, the installation and adjustment of knee joint during operation largely depends on the personal experience of doctors. In this work, a flexible pressure sensing device with bendable and distortable sensor arrays for force detection in knee arthroplasty is fabricated and characterized to provide quantitative data guidance and reference for knee arthroplasty. The internal pressure of prosthesis knee joint can be effectively detected through real-time obtaining for output voltages of sensor array. The densely distributed measuring points feedback abundant pressure distribution information. The pressure device shows good repeatability, consistency and small hysteresis in large detection range and stability in dynamic response which indicates promising potential in applications of knee arthroplasty.