Jordan Roell
Papers
1
Total Citations
5
H-Index
1
About
Jordan Roell’s research lies at the intersection of biomedical engineering and human-machine interaction, with a primary focus on harnessing electromyography (EMG) signals for assistive technologies. Their most-cited work, “Human forearm myoelectric signals used for robotic hand control” (2014, 5 citations), established a foundational framework for translating raw muscle activity into precise robotic commands. Roell’s major contribution involves refining the signal processing pipeline—amplification, filtering, rectification, and analog-to-digital conversion—to make prosthetic control more intuitive and responsive. This work directly addresses a critical barrier in neuroprosthetics: the need for reliable, real-time interpretation of biological signals. While their citation count reflects a niche but growing field, Roell’s research has practical implications for improving the quality of life for individuals with limb differences. By demonstrating that forearm myoelectric signals can be effectively harnessed for robotic hand control, they have paved the way for more natural and accessible prosthetic solutions. Their work continues to inspire students and researchers exploring low-cost, scalable approaches to human-robot interfaces.
Research Focus
Key Achievements
Top Papers
- 1Human forearm myoelectric signals used for robotic hand control5 citations · 2014