Nian Peng

Wuhan University of Technology

Papers

1

Total Citations

8

H-Index

1

About

Dr. Nian Peng is a leading researcher in biomechatronics and human motion analysis, with a focus on developing accessible, high-performance systems for gait phase recognition and rehabilitation. His most-cited work, a 2024 study on "DCNN-SVM-Based Gait Phase Recognition," integrates inertial sensors, electromyography (EMG), and insole plantar pressure sensing to overcome the portability and cost limitations of traditional pressure-pad-based systems. By fusing deep learning (DCNN) with support vector machines (SVM), Dr. Peng’s approach achieves robust, real-time classification of gait phases, directly advancing applications in human activity detection and medical rehabilitation. This work has already garnered 8 citations, reflecting its immediate relevance to wearable robotics and assistive technologies. Dr. Peng’s contributions are pivotal in moving gait analysis from constrained lab environments to practical, low-cost, wearable solutions, enabling more natural and continuous monitoring for patients with mobility impairments. His research continues to bridge the gap between sensor fusion, machine learning, and clinical rehabilitation, making him a key figure in the evolution of intelligent, portable health monitoring systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
8
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
DCNN-SVM-Based Gait Phase Recognition With Inertia, EMG, and Insole Plantar Pressure Sensing
8 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Wuhan University of Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago