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affective, active

How can we leverage digital knitting to design responsive knits that display built-in, stitch-dependent affective behavior?

Knitted pneumatics is an emerging research area receiving much interest from fields as diverse as architecture, medicine and automobile design. As wearable prosthetic, artificial muscle, responsive architecture or responsive car interior, inflatable knitted structures can be designed to behave in pre-programmed fashion dependent on internal gas pressure changes. This project is an inquiry into how pneumatic knits can be designed to also exhibit affective characteristics that can play a vital part in the design of active materials. A study of the affective properties of textiles coupled with a study of the structural properties of different knit stitch configurations led to the design of an affective knit structure that reacts to external stimuli in socio-culturally recognizable ways, thus opening up meaningful interaction opportunities. All experimentation and final knitting were done on the Shima Seiki WholeGarment Digital Knitting Machine SWG091N2 10gg with accompanying custom programming for the machine. We envisage a future when knit-based smart toys and robots would be able to display emotions and take on zoomorphic personalities through pneumatic, active knits. 

An affect is the conscious, subjective aspect of an emotion considered apart from bodily changes. In the design of active matter, affects can play a vital role that can help shape our perception of and relationship with such matter.


Knit blocks visualization

Form finding involved experimentation with different knitting techniques and programming approaches by starting from simple block shapes (such as triangles, circles and tubes) and repeating them in different order, scaling them up or down at different sequences, as well by embracing knit errors and randomly created test forms.

Process: test knit programs and sketches

Screenshot (920).png
Screenshot (924).png

Concept video | music credit: As Old Roads by Goldmund

Research collaborators: Tingwei Gu and Zhuldyz Tazhimbetovs

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