Papers
6
Total Citations
325
H-Index
6
About
Benedetta Cesqui is a leading researcher in neurorehabilitation engineering, specializing in robot-mediated therapy for upper limb recovery following stroke and neurological injury. Her work focuses on integrating electromyographic (EMG) signals with robotic systems to enhance motor rehabilitation. In her landmark 2013 study, cited over 170 times, she demonstrated the feasibility of using EMG-based pattern recognition to predict patient intentions during post-stroke robot-aided therapy, paving the way for more intuitive, patient-driven rehabilitation protocols. Cesqui has also made significant contributions to understanding spasticity reduction, showing in a 2010 study with 43 citations that active robot-mediated training can effectively decrease upper limb spasticity in chronic hemiparesis patients. Her innovative exploration of divergent force fields—robotic training that enhances errors to stimulate motor learning—has opened new avenues for rehabilitation strategies. With over 325 cumulative citations across her most influential works, Cesqui’s research bridges engineering and clinical practice, offering evidence-based approaches to improve motor recovery and quality of life for patients with chronic neurological conditions.
Research Focus
Key Achievements
Top Papers
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- 4On the Use of Divergent Force Fields in Robot-Mediated Neurorehabilitation35 citations · 2008
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