Francesco Missiroli
Papers
17
Total Citations
283
H-Index
9
About
Francesco Missiroli is an emerging force in rehabilitation robotics and wearable assistive technology, whose research sits at the intersection of human-robot interaction, machine learning, and soft exosuit design. His work addresses one of the field's most persistent challenges: enabling intuitive, precise, and responsive control of wearable robotic devices for both clinical rehabilitation and everyday assistance. Missiroli's most influential contributions center on EMG-driven and machine learning-based control systems for soft exoskeletons, with his 2022 paper on myoelectric glove control for grasping assistance accumulating 70 citations — a testament to its significance in the field. His comparative analyses of myoelectric versus force-based control strategies have provided the community with much-needed empirical clarity on intention-detection approaches. Beyond the upper limb, his research spans hip exosuits for gait enhancement, lower limb wearables for mobility support, and soft robotic shorts demonstrated to improve outdoor walking efficiency in older adults. Notably, Missiroli has also explored the integration of brain-computer interfaces with haptic feedback for neurorehabilitation and applied computer vision to industrial exosuits for worker safety. With over 250 total citations across a focused body of work, he represents a researcher whose contributions are reshaping how assistive robotics serves aging populations, neurological patients, and industrial users alike.
Research Focus
Key Achievements
Top Papers
- 1
- 2Myoelectric or Force Control? A Comparative Study on a Soft Arm Exosuit43 citations · 2022
- 3Soft robotic shorts improve outdoor walking efficiency in older adults38 citations · 2024
- 4
- 5
- 6
- 7Adaptive Hybrid FES-Force Controller for Arm Exosuit13 citations · 2022
- 8
- 9
- 10