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About

Alessandra Bigioni is a leading researcher at the intersection of human-robot interaction and psychophysiology, with a focus on rehabilitation technologies. Her work centers on understanding how users physically and cognitively respond to exoskeleton-assisted walking, using multimodal physiological monitoring to assess workload and user experience. Bigioni’s major contributions include developing a data-driven Fuzzy Logic method to estimate psycho-physiological (PP) states during motor tasks, a novel approach that enables real-time, personalized assessment of cognitive and physical strain. She also pioneered a new questionnaire for evaluating user experience during exoskeleton-assisted walking, validated through pilot testing. Her studies on the role of visual feedback and physiotherapist-patient interaction in robot-assisted gait training, using eye-tracking and HD-EEG, have provided critical insights into the dynamics of human-robot collaboration in rehabilitation. With her most-cited work accumulating 13 citations since 2024, Bigioni’s research is shaping the future of adaptive, user-centered robotic rehabilitation systems. Her achievements highlight her commitment to improving both the efficacy and comfort of assistive technologies for individuals with motor impairments.