We present eGlove, a wearable and low-cost fabric sensor for recog- nizing a rich context of objects by touching them, including daily necessities, fruits, plants, as well as different body parts. Our sens- ing approach utilizes Swept frequency Capacitive Sensing (SFCS) to provide consistent sensor readings even when the fabric electrode is under varying deformation and stretching degrees. Our work proposes an easy fabrication method and hardware configuration for prototyping the interactive fabric sensor. We evaluated our sys- tem’s classification accuracy through per-user training and found a real-time classification of 96.3%. We also demonstrated novel con- textual interactions enabled by our technical approach with several applications.
zhitongcui/eGlove-CHI2021
eGlove: Designing Interactive Fabric Sensor for Enhancing Contact-Based Interactions
Python