Yanlin Ma

Papers

2

Total Citations

7

H-Index

2

About

Yanlin Ma is an emerging researcher specializing in human-computer interaction, gesture recognition, and multimodal signal processing, with a particular focus on advancing the communication interface between humans and robotic systems. Ma's work addresses a fundamental challenge in modern robotics: enabling machines to interpret natural human gestures in real time, thereby making human-machine communication more intuitive and interpersonal in quality. Among Ma's notable contributions is a 2021 adaptive real-time gesture detection method that integrates electromyography (EMG) and inertial measurement unit (IMU) data for robot control, demonstrating a sophisticated fusion of biosignal and motion data to accurately capture dynamic sign language gestures. Complementing this, a 2020 study introduced a multimodal signal-based gesture recognition framework designed to translate gestural commands directly into robotic movements, broadening the communication channels available between humans and machines. While Ma's citation counts remain modest — with 4 and 3 citations respectively — this reflects the early stage of a research career with clear momentum and growing relevance. As robotics and assistive technology continue to evolve, Ma's contributions to naturalistic, signal-driven gesture interfaces position this work as a meaningful foundation for future advances in intelligent human-robot interaction systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
7
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
An Adaptive Real-time Gesture Detection Method Using EMG and IMU Series for Robot Control
4 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 6

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
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