Advancing Nuerorehabilitation through data-driven Healthcare: New Sensors and computational approaches

Abstract

Current practices in neurorehabilitation are defined by an abundance of subjective assessments, limited quantifiable metrics, and poorly understood changes to the neurological system due to disease and recovery. For example, up to 50% of spinal-cord injury patients see divergent outcomes 1-year following injury, while 20% of stroke patients see drastic declines in ability after completing therapy. To improve the quality of care, fully quantifiable metrics must be used to understand the impact of a diseased state, and the patient’s progress through rehabilitation. For example, high-density electromyography enables a non-invasive pathway to track performance at the motor unit level to measure recruitment order, fatigue, and longitudinal adaptation in recovery. Similarly, the electrical characteristics of the affected tissues, such as tissue impedance, provide a quantifiable indication for inflammation, atrophy and muscle strengthening. When tracking these features over time, detailed physiological and neurophysiological mappings of motor recovery can be extracted to uncover the complex dynamics of neuroplasticity. Together, these approaches provide new assessment tools for personalized healthcare, new technology development, and improved data-driven workflows in neurorehabilitation.

Biography

Dr. Filip Stefanovic is an Assistant Professor of Biomedical Engineering at the University at Buffalo. Prior to this he was an Associate Professor of Teaching at UB. His research interests include the development of wearable neurorehabilitation technologies, computational neurophysiology in rehabilitation, and high-density sensors. Filip is the recipient of four awards at UB, including the SUNY Chancellor’s Award for Excellence in Teaching (2025), UB Teaching Innovation (2024), Teaching Accessibility (2020), and Best Teaching Faculty of the Year (2018). His lab currently includes 2 PhD students and 13 Master’s students, and his research is funded by NSF DARE to explore neurostimulation and neuroplasticity – he also works with industry to develop new wearable technologies for rehabilitation. Filip has experience working in industry as an R&D Engineer for Autonomous IoT system, and as a Research Scientist developing new electromyography-based medical devices. Filip received his PhD at McGill University in Montreal, Canada, his Master’s degree at the University of Belgrade, Serbia, in conjunction with Aalborg University, Denmark, and his BASc at the University of Toronto.