Innovative functional knitwear design with conductive yarns

Pao Yue-kong Library Electronic Theses Database

Innovative functional knitwear design with conductive yarns


Author: Li, Li
Title: Innovative functional knitwear design with conductive yarns
Degree: Ph.D.
Year: 2010
Subject: Hong Kong Polytechnic University -- Dissertations
Smart materials
Textile fabrics -- Technological innovations
Textile fibers -- Technological innovations
Knitwear -- Design
Yarn -- Research
Department: Institute of Textiles and Clothing
Pages: xxxi, 232 leaves : ill. ; 31 cm.
InnoPac Record:
Abstract: The aim of this research is to develop a design model called Knitech for creating wearable electronic textiles which can provide certain functionalities by using conductive yarns. This research focuses on intelligent garments or smart textiles, knitwear design, garment design skill, wearable electronics, and pain management based on Chinese acupuncture therapy. Literatures were reviewed according to three major aspects: expressive design, aesthetic design, and functional design, which cover various knitwear design methods, current knitting technologies, intelligent applications and healthcare products, as well as the existing limitations for wearable electronic textiles. Physical characterization methods have been proposed to examine the conductive materials which are applied for wearable electronic textiles. The characterization includes (i) appearance (ii) electrical resistance (iii) electromechanical analysis (iv) Scanning Electron Microscope (ab. SEM) analysis (v) laundering ability. The conductive yarns or conductive fabrics which met the design requirements were selected for further experiments and prototype development. Conductive knitting stitches can be modeled by a network of length-related resistors and contact resistors. The length-related resistor is linearly proportional to its length and the applied extensile force, whereas the contact resistor is inversely nonlinear to the extensile force. These two competing factors determine the overall resistances of conductive knitting stitches. These resistances are critical elements in designing conductive routing paths of intelligent garments in which different functional units are interconnected. Therefore, two methods have been developed to compute such an equivalent resistance that are a resistive network model and sheet resistance method. The analytical equations were derived to calculate the equivalent resistances of conductive knitting stitches for different courses and wales; an alternative method is proposed based on the sheet resistance by statistical means. Once the resistances are known, the power distribution can be computed for a given resistive network. Furthermore, the resistances of conductive knitting stitches can be varied by using different knitting technologies. The garment design skills also have been incorporated into the intelligent garment design. Different knitting technologies and garment skills, for instance, zippers have been proposed to alter the confining pressures of garments to attain more comfort; a scheme of resistive network optimization is employed to enhance the aesthetics of the clothing by mapping the resistive network into a predefined pattern; and textile electrodes have been developed that are lightweight, compact and washable. To implement the proposed design model and evaluate the functionality, three knitwear prototypes have been developed: two for transcutaneous electrical nerve stimulation (ab. TENS) therapy and one for thermal therapy, on acupuncture points respectively. Besides achieving the required functionalities for different applications, several contemporary fashion design elements have been added to enhance the aesthetics so as to meet the market demand. Finally, new collections of the intelligent garments have been made. All the methods proposed in this thesis have been evaluated and compared with the existing methods. Two final products of intelligent knitwear have been made with TENS function and thermal therapy, on acupuncture points respectively. Experimental results show that our proposed Knitech design model can be applied to intelligent knitwear design.

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