Preston Robertson
Papers
1
Total Citations
26
H-Index
1
About
Preston Robertson is a leading researcher in wearable robotics and human biomechanics, with a focus on advancing human gait recognition and assistive technologies. His work bridges soft robotics and deep learning to create innovative solutions for movement analysis and rehabilitation. Robertson’s most cited paper, “Closing the Wearable Gap—Part VI: Human Gait Recognition Using Deep Learning Methodologies” (2020, 26 citations), introduces a novel wearable system that employs soft robotic sensors (SRS) to model foot-ankle kinematics during gait cycles. By quantifying SRS capacitance in relation to basic foot-ankle movements across 20 participants on flat and cross-sloped surfaces, this study demonstrates a significant leap in real-time, non-invasive gait monitoring. This contribution has implications for personalized prosthetics, athletic performance, and fall prevention in aging populations. Robertson’s work is part of a broader “Closing the Wearable Gap” series, underscoring his commitment to integrating soft robotics with machine learning for practical, user-friendly wearable devices. His research continues to inspire new directions in human-machine interaction and biomechanical sensing.
Research Focus
Key Achievements
Top Papers
- 1