Alessandro Mengarelli

Alessandro Mengarelli is a Research Fellow at the Department of Information Engineering (DII) of Università Politecnica delle Marche. He holds a Ph.D. in Information Engineering (2017) from the same institution, focusing on balance and motor control in dynamic tasks under Prof. Sandro Fioretti's supervision. His research integrates biomechanics, biosignal processing, and wearable technologies, with a focus on neuromuscular control strategies and assistive systems.

Key research areas include motion analysis, muscle co-contraction patterns, gait biomechanics, and the application of machine learning to biomedical data. He is actively involved in IEEE societies (EMBS, CTSoc, RAS) and the Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System (IUC BOHNES). His work spans from wearable sensor development to clinical applications in diabetic neuropathy and neuro-rehabilitation.

Mengarelli's recent publications emphasize innovations in gait phase recognition, EMG-based intent detection for prosthetics, and IoT-driven health monitoring. His articles highlight advancements in sensor fusion, deep learning models for biomechanical analysis, and minimal setup solutions for practical clinical use.

He has contributed as a reviewer and Guest Editor for peer-reviewed journals, reflecting his engagement in advancing the field. His research bridges theoretical models (e.g., intermittent control theory) with practical applications, aiming to improve human-machine interfaces and assistive technologies.