Kris Scicluna
Papers
1
Total Citations
9
H-Index
1
About
Kris Scicluna is a researcher whose work lies at the intersection of biomedical engineering and human-machine interaction, with a primary focus on electromyography (EMG) signal processing and its applications in prosthetics and bio-robotics. His most cited work, "Development of a New Low-Cost EMG Monitoring System for the Classification of Finger Movement" (2018, 9 citations), exemplifies his commitment to making assistive technology more accessible. In this study, Scicluna developed an affordable system capable of classifying individual finger movements from EMG signals—a critical step toward intuitive control of prosthetic limbs and gesture-based interfaces. By prioritizing low-cost hardware without sacrificing classification accuracy, his contribution addresses a key barrier in the widespread adoption of myoelectric prosthetics. This work not only advances the field of kinesiology but also bridges the gap between laboratory research and real-world, practical applications. Scicluna’s research is particularly valuable for students and engineers exploring cost-effective solutions in rehabilitation engineering, demonstrating how clever system design can democratize access to advanced human-machine interfaces.
Research Focus
Key Achievements
Top Papers
- 1