Special Session 15

Human motion analysis plays a crucial role as a support for prevention, diagnosis, and monitoring of the effectiveness of treatments, progression of disease conditions, and, in general, people's lifestyle with significant impact in many applications such as in clinical, sports, and occupational fields. Applying wearable sensors, contactless, or marker-based motion capture systems for measuring human motion adds value to objective assessments and increases engagement or adherence to treatment. As measurement systems, these must fulfill adequate metrological properties such as accuracy, reliability, precision, repeatability, and reproducibility. In this context, artificial intelligence-based techniques and computational models are highly employed in human movement simulation, classification, and predictive analysis, starting from data retrieved by specialized measurement systems. The design and performance evaluation of algorithms are crucial factors for their applicability in real-world settings.

Paper submissions are welcome on (but not limited to) the following topics:

• Wearable systems for monitoring human motion;
• Characterization and validation of measurement systems for monitoring human kinematics;
• Motion capture systems;
• Artificial Intelligence for human motion recognition;
• Human motion analysis in clinical applications;
• Sports science;
• Occupational biomechanics and ergonomics;
• Musculoskeletal rehabilitation.

Eduardo Palermo, Ph.D. is an Assistant Professor and PhD advisor in the Department of Mechanical and Aerospace Engineering of Sapienza University of Rome. He received his Ph.D. in February 2014 in Industrial Production Engineering at Sapienza University. From June 2014 to June 2015 he had a Postdoc appointment at New York University Tandon School of Engineering. He currently teaches Biomechanics and Mechanical and Thermal Measurement courses. Dr. Palermo's research interest is the design, implementation, and validation of new technologies in Experimental Biomechanics and Robotics for Rehabilitation, with focus on human gait and motion analysis. His research activity involved wearable inertial sensors, machine learning algorithms, mechatronics, human-computer interactions, bio-signal processing. The studies he conducted included in-vivo clinical experimentation in cooperation with clinical research partners.

Arianna Carnevale, (Ph.D.) is a biomedical engineer at Fondazione Policlinico Universitario Campus Bio-Medico in Rome. Her research interests focus on the design, development, characterization, application, and performance evaluation of measurement tools (e.g., wearable systems, virtual reality, stereophotogrammetry) for assessing human joint kinematics in the orthopaedic field. She has been involved in several national and international projects. She is the author of several publications in peer-reviewed journals and conference proceedings on topics related to sensors and algorithms for human motion analysis, with a particular focus on the shoulder joint.