Dr. Bonato served as the Founding Editor-in-Chief of Journal on NeuroEngineering and Rehabilitation. He serves as a Member of the Advisory Board of the IEEE Journal of Biomedical and Health Informatics and as Associate Editor of the IEEE Journal of Translational Engineering in Health and Medicine. Dr. Bonato served as an Elected Member of the IEEE Engineering in Medicine and Biology Society (EMBS) AdCom (2007-2010) and as President of the International Society of Electrophysiology and Kinesiology (2008-2010). Dr. Bonato served as Chair of the IEEE EMBS Technical Committee on Wearable Biomedical Sensors and Systems in 2008 and as founding member of this committee (2004-2012). He also served as Chair of the 33rd Annual International Conference of the IEEE EMBS (2011) and as Co-Chair of the 37th Annual International Conference of the IEEE EMBS (2015). He recently served as IEEE EMBS Vice President for Publications (2013-2016). He received the M.S. degree in electrical engineering from Politecnico di Torino, Turin, Italy in 1989 and the Ph.D. degree in biomedical engineering from Universita` di Roma “La Sapienza” in 1995. Dr. Bonato’s work has received about 7,000 citations (Google Scholar). Additional information about Dr. Bonato’s work can be found at www.srh-mal.net.
“Relying on Robotic and Sensing Technology to Identify Motor-Phenotypes and Develop Patient-Specific Neurorehabilitation Interventions”
Over the past decades, technology has gained a key role in neurorehabilitation. Our research team has focused its efforts on studying the potential use in neurorehabilitation of two technologies that we see as particularly relevant to the implementation of interventions, namely robotics (i.e., assistive devices and systems to retrain motor functions) and motion tracking technology (i.e., traditional camera-based motion analysis systems and recently developed wearable sensor-based systems). The goal of this lecture is to discuss the adoption of these technologies in neurorehabilitation and their potential role in identifying motor-phenotypes thus enabling the implementation of patient-specific interventions.
First, we will present the results of recent research work focused on assessing the interaction between subjects and robotic systems designed for robot-assisted gait retraining. Such interaction can be studied by carrying out motor adaptation experiments in which the ability of subjects to generate a motor adaptation strategy in response to the forces produced by the robot is looked upon as a proxy of the ability of subjects to “learn from a robot”. We will then elaborate on the relationship between motor adaptations and the control of human movement as studied using traditional as well as wearable motion tracking systems. Specifically, we will review associations between the subject’s inability to generate motor adaptations and the biomechanics of motion, including the presence of physiological vs. aberrant muscle synergies. Finally, we will discuss the use of the above-mentioned approaches to identify motor-phenotypes in patients undergoing neurorehabilitation thus enabling the development of patient-specific interventions.