Lei Wen

About

Lei Wen is a leading researcher in wearable electronics and intelligent sensing systems, with a primary focus on flexible sensors for human motion recognition and human–machine interfaces. His major contributions lie in developing novel wearable multimode sensors that can decouple pressure and strain stimuli, enabling precise recognition of different joint motion states. Notably, his 2022 work on a wearable multimode sensor with a seamless integrated structure, enhanced by deep learning algorithms, has garnered 56 citations, demonstrating significant impact in the field. Wen has also advanced the field through comprehensive reviews, such as his 2025 work on porous pressure sensors, and has addressed critical challenges in sensor consistency and stability with hybrid deep-learning-enhanced strain sensors (2023, 7 citations). His research bridges the gap between flexible electronics and practical applications in medical care, soft robotics, and human–machine interfaces, making him a key figure in the development of next-generation wearable recognition systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Wearable multimode sensor with a seamless integrated structure for recognition of different joint motion states with the assistance of a deep learning algorithm

   56 citations · 2022
2. 2
   Porous pressure sensors from mechanisms to application: A review

   13 citations · 2025
3. 3
   Wearable Recognition System for Complex Motions Based on Hybrid Deep‐Learning‐Enhanced Strain Sensors

   7 citations · 2023

Key Collaborators

Contact & Links