Distributed Sensing Along Fibres for Smart Clothing
This addresses the challenge of making wearable electronics more reliable and scalable for smart clothing applications, though it appears incremental in improving existing sensing methods.
The paper tackled the problem of unreliable connections and scalability in smart clothing by introducing a prototype garment, compact readout circuit, and algorithm for distributed strain sensing along a single continuous fibre, achieving around 5° error in reconstructing arm joint angles compared to optical motion capture.
Textile sensors transform our everyday clothing into a means to track movement and bio-signals in a completely unobtrusive way. One major hindrance to the adoption of "smart" clothing is the difficulty encountered with connections and space when scaling up the number of sensors. There is a lack of research addressing a key limitation in wearable electronics: connections between rigid and textile elements are often unreliable and they require interfacing sensors in a way incompatible with textile mass production methods. We introduce a prototype garment, compact readout circuit, and algorithm to measure localized strain along multiple regions of a fibre. We employ a helical auxetic yarn sensor with tunable sensitivity along its length to selectively respond to strain signals. We demonstrate distributed sensing in clothing, monitoring arm joint angles from a single continuous fibre. Compared to optical motion capture, we achieve around 5° error in reconstructing shoulder, elbow, and wrist joint angles.