semi-elastic textiles with border-based sensors is a B.Tech project topic for Textile Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
semi-elastic textiles with border-based sensors Project Details
| Abstract |
This research addresses the challenge of integrating touch-sensing capabilities into smart textiles without cluttering the active sensing area with embedded electronics. The authors propose a border-based sensor arrangement on semi-elastic textiles, specifically evaluating an elastic Jersey fabric. By placing sensors exclusively along the perimeter of a 125 mm by 125 mm sensing area, the system preserves the natural tactile properties of the fabric. The study evaluates two primary approaches: a visual tracking system using markers to predict a single touch point, and a textile-only prototype designed to classify physical touch. Using machine learning models, the visual sensor arrangement achieved a mean squared error (MSE) of 1.36 mm in predicting touch
coordinates. Furthermore, the textile-only prototype successfully classified touch across three distinct indentation levels (0 mm, 15 mm, and 20 mm) with an accuracy of 82.85%. This methodology offers a practical framework for developing unobtrusive, wearable human-machine interfaces. Fried Engineers provides academic guidance, structural review, and implementation support to help students explore these machine learning models and sensor configurations for smart textile projects.
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| Reference Paper |
Touch Sensing on Semi-Elastic Textiles with Border-Based Sensors |
| Domain |
Textile Engineering |
| Sub-Domain |
Smart Textiles |
| PDF Download |
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| Get Help |
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