This thesis presents a study of the sensing properties exhibited by textile-based knitted strain sensors. Sensing fabrics were manufactured from silver-plated conductive nylon and non-conducting elastomeric yarns. The component yarns offered similar diameters, bending characteristics and surface friction, but their production parameters differed in respect of the yarn input tension, the number of conductive courses in the sensing structure and the elastomeric yarn extension characteristics. The knitted sensors were manufactured using flat-bed knitting technology, and electro-mechanical tests were performed on the specimens using a tensile testing machine to apply strain whilst the sensor was incorporated into a Wheatstone bridge arrangement to allow electrical monitoring. The novel operational principle relies on the separation under strain of adjacent conducting knitted loops which are normally held in contact by the elastomeric yarn. The results confirm that production parameters play a fundamental role in determining the physical behaviour and the sensing properties of knitted sensors and the response could be engineered by varying the production parameters of specific designs. Results showed that the knitted structures could be manipulated to produce gauge factor values between 2.26 and 0.23 for sensors with working ranges of 8.4 % and 3.3 % respectively when the elastomeric yarn had 8 cN input tension. The generated signals were stable and repeatable, and under cyclic testing proved to be substantially free from long-term drift. A textile-based strain sensor was developed to create a respiration belt; this was realised by bringing together the extensible knitted sensor and a relatively inelastic textile strap. Machine simulations and real time measurements on a human subject were performed to calculate average breathing frequencies under different static and dynamic conditions. Various respiration rates were monitored to simulate different medical conditions and with the belt located either round the torso or in the abdominal area, the sensor yielded a satisfactory response. However, body motion artefacts affected the signal quality under dynamic conditions and an additional signal-processing step was added to separate unwanted interference from the breathing signal. Electro-mechanical modelling was developed by exploiting Peirce`s loop model in order to describe the fabric geometry under static and dynamic conditions. Kirchhoff`s node and loop equations were employed to create a generalised solution for the equivalent electrical resistance of the textile sensor for a given knitted loop geometry and for a specified number of loops. Experimental results were obtained from the sensor for strain levels up to 40% and these correlate well with the modelled data; a maximum error of 2.13 % was found between the experimental and modelled resistance-strain relationships.

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