Events4th International Electronic Conference on Sensors and Applications
Published
This submission belongs to the session E. Applications of the event 4th International Electronic Conference on Sensors and Applications
Published date
14 Nov, 2017
Citation
Pasindu Lugoda, Tilak Dias, Theodore Hughes-Riley, Rob Morris, Refinement of temperature sensing yarns, in Proceedings of 4th International Electronic Conference on Sensors and Applications, 15 November–30 November 2017, MDPI: Basel, Switzerland, doi: 10.3390/ecsa-4-04933
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Refinement of temperature sensing yarns

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1. Advanced Textiles Research Group, School of Art & Design, Nottingham Trent University
2. School of Science and Technology, Nottingham Trent University
Abstract

Body temperature is an important parameter to measure in a number of fields such as medicine and sport. In medicine temperature changes can indicate underlying pathologies such as wound infections, while in sport temperature can be associated to a change in performance. In both cases a wearable temperature monitoring solution is preferable. In earlier work a temperature sensing yarn has been developed and characterised. The yarns were constructed by embedding an off-the-shelf thermistor into a polymer resin micro-pod and then into the fibres of a yarn. This process created a temperature sensing yarn that was conformal, drapeable, mechanically resilient, and washable. This work builds on this early study with the purposes of identifying the steady state error bought about on the temperature measurements as a result of the polymer resin and yarn fibres. Here a wider range of temperatures than previously explored were investigated. Additionally two types of polymer resin with different thermal properties have been tested, with varying thicknesses, for the encapsulation of the thermistor. This provides useful additional information for optimising the temperature sensing yarn design.

Keywords
electronic textiles
wearable electronics
smart textiles
temperature-sensing
diabetic ulcers
thermistor
wound management
sensor network
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