E-textile microinteractions advance cord-based interfaces by enabling the simultaneous use of precise continuous control and casual discrete gestures. We leverage the recently introduced I/O Braid sensing architecture to enable a series of user studies and experiments which help design suitable interactions and a real-time gesture recognition pipeline. Informed by a gesture elicitation study with 36 participants, we developed a user-dependent classifier for eight discrete gestures with 94% accuracy for 12 participants. In a formal evaluation we show that we can enable precise manipulation with the same architecture. Our quantitative targeting experiment suggests that twisting is faster than existing headphone button controls and is comparable in speed to a capacitive touch surface. Qualitative interview feedback indicates a preference for I/O Braid's interaction over that of in-line headphone controls. Our applications demonstrate how continuous and discrete gestures can be combined to form new, integrated e-textile microinteraction techniques for real-time continuous control, discrete actions and mode switching.
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)