PurposeThe purpose of this paper is to review the challenges present in the development of hand exoskeletons powered by pneumatic artificial muscles. This paper also presents the development of a novel strain sensor and its application in a five‐fingered hand exoskeleton.Design/methodology/approachThe issues of current hand exoskeletons powered by pneumatic artificial muscles are examined by studying the artificial muscles and the human hand anatomy. Traditional sensors are no longer suitable for applications in hand exoskeletons. A novel strain sensor was developed by depositing a conducting polymer called polypyrrole onto a natural rubber substrate through vapor phase polymerization and is used in the authors' five‐fingered hand exoskeleton.FindingsThe error of measurements from the polypyrrole strain sensor in controlling the actuation of pneumatic artificial muscles is within 1.5 mm. The small physical size and weight of the novel polypyrrole strain sensor also helped to keep the exoskeleton's profile (less than 20 mm) and total weight low (<1 kg).Originality/valueThe novel strain sensor allows the realization of hand exoskeletons that are lightweight, portable and low profile. This improves the comfort and practicality of hand exoskeletons to allow their usage outside the research environment.

Demand for highly compliant mechanical sensors for use in the fields of robotics and wearable electronics has been constantly rising in recent times. Carbon based materials, and especially, carbon nanotubes, have been widely studied as a candidate piezoresistive sensing medium in these devices due to their favorable structural morphology. In this paper three different carbon based materials, namely carbon black, graphene nano-platelets, and multi-walled carbon nanotubes, were utilized as large stretch sensors capable of measuring stretches over 250%. These stretch sensors can be used in robotic hands/arms to determine the angular position of joints. Analysis was also carried out to understand the effect of the morphologies of the carbon particles on the electromechanical response of the sensors. Sensors with gauge factors ranging from one to 1.75 for strain up to 200% were obtained. Among these sensors, the stretch sensors with carbon black/silicone composite were found to have the highest gauge factor while demonstrating acceptable hysteresis in most robotic hand applications. The highly flexible stretch sensors demonstrated in this work show high levels of compliance and conformance making them ideal candidates as sensors for soft robotics.

This paper reports on the creation of a low-cost, disposable sensor for low flow velocities, constructed from extruded micro-sized 'hair' of conducting polymer PEDOT. These microstructures are inspired by hair strands found in many arthropods and chordates, which play a prime role in sensing air flows. The paper describes the fabrication techniques and the initial prototype testing results toward employing this sensing mechanism in applications requiring sensing of low flow rates such as a flow sensor in neonatal resuscitators. The fabricated 1000 μm long, 6 μm diameter micro-hairs mimic the bending movement of tactile hair strands to sense the velocity of air flow. The prototype sensor developed is a four-level direct digital-output sensor and is capable of detecting flow velocities of up to 0.97 m s(-1).

The micro-reactive inkjet printing technique and the patterned conductive PANI on a glass substrate using this printing method.

Headspace sorptive extraction technique using silicone based sorptive media coated stir bars is used for the first time here to extract, identify, and quantify heavy volatile organic compounds present in Escherichia coli culture headspace. Detection of infection presence is largely accomplished in laboratories through physical sampling and subsequent growth of cultures for biochemical testing. The use of volatile biomarkers released from pathogens as indicators for pathogenic presence can vastly reduce the time needed whilst improving the success rates for infection detection. To validate this, by using a contactless headspace sorptive extraction technique, the volatile compounds released from E. coli, grown in vitro, have been extracted and identified. Two different sorptive media for extracting these headspace volatiles were compared in this study and the identified volatiles were quantified. The large phase volume and wider retention of this sorptive technique compared to traditional sampling approach enabled preconcentration and collection of wider range of volatiles towards developing an extensive database of such heavy volatiles associated with E. coli. This supplements the existing data of potential bacterial markers and use of internal standards in these tests allows semi-quantitative estimation of these compounds towards the development and optimization of novel pathogen sensing devices.