Elisabetta Farella

Papers

Total Citations

H-Index

About

Elisabetta Farella is a leading researcher in human-robot interaction and wearable sensing, with a focus on making technology more intuitive and responsive to human intent. Her work bridges the gap between biological signals and machine control, particularly through myoelectric (EMG) and biomechanical monitoring. She has made major contributions to hand gesture recognition, exploring how arm posture and temporal variability affect the reliability of EMG-based systems—work that has direct applications in advanced prosthetic hands and intuitive robot interfaces. Her highly cited 2018 paper on this topic (37 citations) is foundational for researchers developing robust, real-world interaction devices. Farella also co-authored a seminal 2008 chapter on human–robot cognitive interaction (28 citations), which laid out frameworks for using brain and muscle activity to control exoskeletons and robots. Beyond signal processing, she has contributed to hardware design, including the validation of low-cost attitude and heading reference systems for aerial robots. Her interdisciplinary approach—combining signal processing, biomechanics, and embedded systems—has shaped how researchers design more natural, adaptive interfaces for assistive and collaborative robotics.