Flexible sensors have the potential to be seamlessly applied to soft and irregularly shaped surfaces such as the human skin or textile fabrics. This benefits conformability dependant applications including smart tattoos, artificial skins and soft robotics. Consequently, materials and structures for innovative flexible sensors, as well as their integration into systems, continue to be in the spotlight of research. This review outlines the current state of flexible sensor technologies and the impact of material developments on this field. Special attention is given to strain, temperature, chemical, light and electropotential sensors, as well as their respective applications.

Textiles enhanced with thin-film flexible sensors are well-suited for unobtrusive monitoring of skin parameters due to the sensors' high conformability. These sensors can be damaged if they are attached to the surface of the textile, also affecting the textiles' aesthetics and feel. We investigate the effect of embedding flexible temperature sensors within textile yarns, which adds a layer of protection to the sensor. Industrial yarn manufacturing techniques including knit braiding, braiding, and double covering were utilised to identify an appropriate incorporation technique. The thermal time constants recorded by all three sensing yarns was <10 s. Simultaneously, effective sensitivity only decreased by a maximum of 14% compared to the uncovered sensor. This is due to the sensor being positioned within the yarn instead of being in direct contact with the measured surface. These sensor yarns were not affected by bending and produced repeatable measurements. The double covering method was observed to have the least impact on the sensors' performance due to the yarn's smaller dimensions. Finally, a sensing yarn was incorporated in an armband and used to measure changes in skin temperature. The demonstrated textile integration techniques for flexible sensors using industrial yarn manufacturing processes enable large-scale smart textile fabrication.

A biocompatible inexpensive strain sensor constituting of an elastomer filled with natural coconut oil (CNO) and carbon black (CB) is presented here. Strain sensors are widely utilized for applications in human activity recognition, health monitoring, and soft robotics. Given that these sensors are envisioned to be present in a plethora of fields, it is important that they are low cost, reliable, biocompatible, and eco‐friendly. This work demonstrates that CNO can be used to create conductive percolation network in elastomers, without the necessity for harmful chemicals or expensive machinery. The sensor has a gauge factor of 0.77 ± 0.01, and the sensing material has a porous morphology filled with an oily suspension formed of CNO and CB. Results indicate that the liquid filled porous structure can improve the reliability of these resistive strain sensors in comparison to sensors fabricated utilizing commonly used non‐polar solvents such as heptane. Consequently, the sensor demonstrates a hysteresis of only 2.41% at 200% strain over 250 stretch/release cycles. Finally, to demonstrate the potential of this fabrication technique, a functionalized glove is developed and used to detect wrist motion. These easily manufacturable and cost‐effective sensors enable wearable on‐skin ergonomic intervention systems with minimal impact on the environment.

Additive manufacturing (AM) is revolutionizing the health industry, where itprovides innovative solutions for the production of personalized devices, such as hand orthoses.However, the scientific research dynamics in this topic have not yet been investigated. Thisstudy aims to fill this gap through the application of a competitive and technology intelligence(CTI) methodology enhanced by a scientometric and network map analysis. Major advances inthe fabrication of hand orthoses using AM, the presence of collaborations, and the mostinfluential authors were determined. Specifically, network map analysis, bibliographicoccurrence and bibliographic coupling were conducted on documents retrieved from Scopus andthe Web of Science (WoS), and on patents from more than 104 authorities. Results showed onlynine published patent families and 34 research articles on this topic from 2006 to 2016. Tenpapers concern static orthoses, while 24 deal with dynamic orthoses and exoskeletons. Theindegree and outdegree parameters and the betweenness centrality of these documents enabledus to determine the most cited authors and instances of collaboration (papers co-authoredbetween institutions). Dr. Paterson A. M. J. was the most influential author, with fourpublications with the highest betweenness centrality in the network (189), which accounted forthe most cited document with five citations. The institution with the most publications wasLoughborough University, with four papers, and the collaboration between affiliations was rare.These documents review important aspects of manufacturing orthoses using AM, andadditionally pay particular attention to the importance of personalised orthoses where AMcontributes. Notably, these papers focused primarily on studies for the development of amethodology for the fabrication of hand orthoses using AM, but they do not present anyapplication. This research provides insights to better understand the dynamics of research anddevelopment in the orthopaedics domain, specifically for hand orthoses.

A scientometric analysis as part of a Competitive Technology Intelligence methodology was used to determine the main research efforts in 3D bioprinting. Papers from Scopus and Web of Science (WoS) published between 2000 and 2017 were analysed. A network map of the most frequently occurring keywords in these articles was created, and their average publication year (APY) was determined. The analysis focused on the most relevant keywords that occurred at least five times. A total of 1,759 keywords were obtained, and a co-occurrence analysis was developed for APYs with more keywords: 2011–2016. The results indicated that Polylactic Acid (PLA) is the material used most often. Applications mainly focused on bone tissue engineering and regeneration. The most frequently used technique was inkjet printing, and the main cell sources were Mesenchymal Stem Cells (MSC). From a general perspective, ‘Treatment’ and ‘Bioink’ were the most frequent keywords. The former was mainly related to cancer, regenerative medicine, and MSC and the latter, to multicellular spheroid deposition and the use of hydrogels like GelMA (gelatin methacryloyl). This analysis provides insights to stakeholders involved in 3D bioprinting research and development who need to keep abreast of scientific progress in the field.

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An inexpensive biocompatible strain sensor constituting of an elastomer filled with natural coconut oil and carbon black is shown by Pasindu Lugoda and co‐workers in article number 2000780. The easily manufacturable and eco‐friendly fabrication technique enables the creation of strain sensors in environments where standard electronic/chemical fabrication facilities are unavailable, like in schools and developing countries. These devices stretch to 1035% and are utilized for smart textile applications.

Capacitive non-contact imaging of electric fields and potentials with micro-metre resolution can provide relevant insights into material characterisation, structural analysis, electrostatic charge imaging and bio-sensing applications. However, scanning electric potential microscopes have been confined to rigid and single-probe devices, making them slow, prone to mechanical damage and complex to fabricate. In this work, we present the design and characterisation of a novel 5-element flexible array of electric potential probes with spatial resolution down to 20 µm to speed up the scanning time. This was achieved by combining flexible thin-film probes for active guarding and shielding with state-of-the art discrete conditioning circuits. The potential of this approach is showcased by using the fabricated array to image latent fingerprints deposited on an insulating surface by contact electrification, obtain the surface topography of conductive samples and to visualise local dielectric variations.