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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.09057 |
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| _version_ | 1866929283897753600 |
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| author | Hannigan, Brett C. Cuthbert, Tyler J. Ahmadizadeh, Chakaveh Menon, Carlo |
| author_facet | Hannigan, Brett C. Cuthbert, Tyler J. Ahmadizadeh, Chakaveh Menon, Carlo |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_09057 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Distributed Sensing Along Fibres for Smart Clothing Hannigan, Brett C. Cuthbert, Tyler J. Ahmadizadeh, Chakaveh Menon, Carlo Signal Processing Machine Learning 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. |
| title | Distributed Sensing Along Fibres for Smart Clothing |
| topic | Signal Processing Machine Learning |
| url | https://arxiv.org/abs/2402.09057 |