Xiaojing Wen

Papers

Total Citations

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About

Xiaojing Wen is a leading researcher in flexible electronics and wearable sensing technologies, with a focus on self-powered systems for human-machine interaction. Her most-cited work, "Flexible hierarchical helical yarn with broad strain range for self-powered motion signal monitoring and human-machine interactive" (2020, 39 citations), introduces a novel yarn-based sensor that combines hierarchical helical structures with triboelectric nanogenerator principles. This innovation enables broad-strain-range, self-powered motion monitoring without external batteries, marking a significant advance in wearable health and robotics interfaces. Wen’s contributions lie in designing scalable, textile-compatible materials that bridge the gap between soft electronics and practical applications, such as real-time gesture recognition and rehabilitation tracking. Her research has garnered attention for its potential to transform how we interact with machines through seamless, energy-autonomous sensors. By integrating material science with device engineering, Wen continues to push the boundaries of flexible electronics, offering sustainable solutions for next-generation wearable systems. Her work is particularly impactful for students and researchers exploring self-powered sensing, smart textiles, and human-machine interfaces.