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Uncertainty-Resilient Signal Processing in Smart Textiles Using Fuzzy Logic

Uncertainty-Resilient Signal Processing in Smart Textiles Using Fuzzy Logic
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Author(s): Ajoy Kanti Das (Tripura University, India), Nandini Gupta (Bir Bikram Memorial College, India)and Takaaki Fujita (Independent Researcher, Japan)
Copyright: 2026
Pages: 38
Source title: Next-Generation Electronic Textiles and Conductive Materials for Smart Wearables
Source Author(s)/Editor(s): Pranshu Saxena (Bennett University, India), Mandeep Singh (Bennett University, India), Sanjay Kumar Singh (University School of Automation and Robotics, Guru Gobind Singh Indraprastha University, East Delhi, India)and Mamoon Rashid (Bahrain Polytechnic, Bahrain)
DOI: 10.4018/979-8-3373-4287-0.ch010

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Abstract

Smart textiles are increasingly embedded with sensors, actuators, and communication modules to enable intelligent interaction with users and environments. However, signal acquisition in textile-based electronics is inherently uncertain due to variability in fabric conductivity, body movements, environmental factors (humidity, temperature), and sensor noise. Classical signal processing methods often fail to handle such imprecision effectively. This chapter introduces a fuzzy logic-based framework for uncertainty-resilient signal processing in smart textiles. We present the mathematical structures of fuzzy sets, fuzzy soft computing, and fuzzy inference systems (FIS), emphasizing their applications in wearable sensing. The framework integrates multi-criteria fuzzy decision-making, adaptive fuzzy filtering, and fuzzy-based classification models for robust signal interpretation. Finally, we discuss future research directions in merging fuzzy systems with machine learning and quantum-inspired models for next-generation wearable intelligence.

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