ME Seminar: Dr. Eni Halilaj
Portable and Integrative Biomechanics Labs for Precision Rehabilitation
Dr. Eni Halilaj
Carnegie Mellon University
Musculoskeletal conditions are the leading cause of disability worldwide, costing the United States’ economy $950 billion per year in direct and indirect costs. In this talk, I will share our work on key challenges toward precision rehabilitation for musculoskeletal injuries and diseases. I will first describe how we are combining deep learning with physics-based modeling to democratize motion capture for all researchers, clinicians, and patients, making it accessible from personal smartphones and inexpensive wearable sensors. These portable tools will strengthen the feedback loop between research and clinical practice, enabling large-scale research-grade data to be collected outside of specialized gait laboratories. I will then talk about the importance of understanding interactions between mechanical loading (e.g., in response to exercise, injury, assistive wearables) and biological factors (i.e., deep patient phenotyping) when personalizing rehabilitation protocols and assistive devices. Our ultimate goal is to build smart rehabilitation technologies that can capture meaningful biomechanical outcomes in natural environments, reason about what these biomechanics mean for a particular patient, and guide the delivery of personalized feedback in real-time. Toward this vision, we are studying flexible sensors that can be embedded into smart garments for continuous monitoring and haptic feedback. In this last part of my talk, I will share our collaborative work on characterizing capacitive sensing as a biomechanics-monitoring tool.
Eni Halilaj is an assistant professor in Mechanical Engineering, with courtesy appointments in Biomedical Engineering and the Robotics Institute, at Carnegie Mellon University. She also holds an adjunct appointment in Orthopaedic Surgery at the University of Pittsburgh School of Medicine. Her research combining wearables, musculoskeletal modeling, machine learning, medical imaging, and deep patient phenotyping aims to accelerate precision rehabilitation for musculoskeletal injuries and diseases. Prior to joining Carnegie Mellon, Eni was a Distinguished Postdoctoral Fellow at Stanford University. She is the recipient of the NSF CAREER Award, NIH K12 Career Development Scholarship in Movement and Rehabilitation Sciences, and the American Society of Biomechanics Early Career Achievement Award.
Zoom Details:
https://columbiauniversity.zoom.us/j/99154071251?pwd=Sm5BSlY5TjBDaThyRGVna2w1dFJZZz09
Meeting ID: 991 5407 1251
Security: 567175
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