Developing Tools for Interactive Smart Knitted Textiles

Megan Hofmann

Khoury/MIE Assistant Professor Megan Hofmann was awarded a $550,000 NSF grant for “Tools for Programming and Designing Interactive Machine-Knitted Smart Textiles.”


Abstract Source: NSF

Industrial knitting machines exist on factory floors worldwide and manufacture various textiles for a range of clothing and home goods. However, beyond common textile products, modern machine-knitting manufacturing equipment has the potential to produce complex interactive smart textiles with a variety of useful, innovative applications. For example, fabrics embedded with conductive yarns can be used to make clothes with health sensors. Imagine a sweater that can measure the heart rate of a patient with heart disease and be washed and handled like any other sweater. Such sensors are not produced because the software used to design these smart textiles and control these knitting machines is limited and too complex for many garment designers. This issue makes the production of smart textiles too expensive or complex to put into practice. This project will investigate the user-experience needs of garment designers and hand-knitters for machine-knitting software to help them create these complex smart textiles. This project will promote science by advancing knowledge of the machine knitting design process and how it can be integrated with existing machine knitting tools to produce novel smart textile materials. This advancement will support national health and well-being by providing a new way of manufacturing smart textiles for various applications such as healthcare, sustainable and local, within the United States, manufacturing of clothing.

This project will enable further development of machine-knit materials and the design of smart textile garments. Success will be measured by three outcomes: (1) a comprehensive examination of the design space of machine knitting, (2) the development of two software systems, KnitScript for programmers and KnitCAD for designers, to support the design of machine-knitted smart textiles, and (3) the creation of interactive, health-sensing garments. To engage with stakeholders such as programmers, machine knitting experts, hand-knitters, and textile designers, the research will employ various human-centered methods, including interviews, artifact collection, participatory design, and design probes. System development will draw on concepts from software engineering, programming language design, and interaction design for design tools.

Related Faculty: Megan Hofmann

Related Departments:Mechanical & Industrial Engineering