Janick Betz
Papers
1
Total Citations
3
H-Index
1
About
Janick Betz is a researcher at the forefront of biomechatronics and wearable sensing technology, with a focus on developing soft, portable systems for human motion analysis. Their most cited work, "Ferroelectret-Based Insole for Vertical Ground Reaction Force Estimation Using a Convolutional Neural Network" (2025), introduces a novel approach to gait analysis by combining a 3D-printed, ferroelectret-based insole with deep learning. This innovation enables precise, real-time estimation of vertical ground reaction forces—a critical parameter for advancing biomechanical research, rehabilitation, and the control of assistive robots and exoskeletons. By prioritizing low-cost, lightweight, and soft materials, Betz addresses key limitations of traditional force plates and bulky sensors, making high-fidelity gait analysis more accessible. Although early in their career, with 3 citations on this pioneering paper, Betz’s work has already demonstrated significant potential to transform fields from clinical diagnostics to human-robot interaction. Their integration of convolutional neural networks with novel sensor hardware marks a notable achievement, positioning them as an emerging leader in wearable biomechanics and intelligent assistive technology.
Research Focus
Key Achievements
Top Papers
- 1