R.I.P.
๐ป
Ghosted
Machine-knittable, Magnetically-Plug-n-Play E-Textile Prototyping
June 22, 2026 ยท Grace Period ยท + Add venue
Authors
Yifan Li, Ryo Takahashi, Wakako Yukita, Irmandy Wicaksono, Kanata Matsutani, Yuhiro Iwamoto, Sunghoon Lee, Tomoyuki Yokota, Takao Someya, Yoshihiro Kawahara
arXiv ID
2606.22800
Category
cs.HC: Human-Computer Interaction
Citations
0
Abstract
Electronic textiles (e-textiles) integrated with wearable sensors are essential for daily motion monitoring and long-term physiological sensing. For example, capturing optimal kinematic or bio-signals requires aligning sensors with specific anatomical parts, which vary significantly across individuals and application scenarios. This necessity for personalization makes e-textile prototyping inherently iterative, however current fabrication methods, such as manual conductive stitching, rely on permanent bonds that restrict rapid adjustment. This paper introduces Plug-n-play e-knit, a machine-knittable e-textile prototyping platform that enables repeatable, quick adjustment of sensor positions across garments. First, to cover the large area of the textile for prototyping, we use industrial digital knitting of conductive yarn to integrate power and communication buses directly into the large-scale textile. Then, to ensure plug-n-play attachment to the textile, we employ soft-magnetic connectors that enable sensors to be repeatedly plugged into the wiring without damaging the fabric. Furthermore, our LED-positioning system enables the automatic identification and localization of each sensor node. We demonstrate the platform's capabilities through forearm movement calibration and position-aware temperature mapping.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Human-Computer Interaction
R.I.P.
๐ป
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
๐ป
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
๐ป
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
๐ป
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
๐ป
Ghosted