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Markerless motion capture, computer vision, and wearable sensors in windsurfing biomechanics and motion analysis. Feature engineering and factor investigation to improve the athletes' performance.
Windsurfing motion analysis and wearable sensing
Develop an algorithm to predict ground reaction forces and moments among healthy people and patients after a total knee replacement. The prediction is based on an inexpensive IMU system based on machine learning models.
Machine learning and wearables to fix loads post knee replacement
Collect and assess biomarkers for the early detection of post-traumatic osteoarthritis among people after an ACL reconstruction surgery. Develop a "stress test" and examine a stimulus-response mechanism of the specific biomarkers set.
Biochemical marker analysis- musculoskeletal disorders
Study the ability to distribute the loads better to be carried by a team of soldiers by using a load carriage index (LCI) rather than relying only on the percentage of bodyweight and develop a better understanding of the biomechanical effects of using body composition as a load carrying strategy
Load carriage index in soldiers based on body composition
Compare the immediate and mid-term biomechanical and quality-of-life related changes after using a wearable knee device applying vibratory stimulus during the stance phase among people early after an anterior cruciate (ACL) ligament reconstruction surgery.
ACL surgery assistive device, biomechanics and quality of life
Assistive wearable technology for ankle motion sensing and feedback: design, development, and testing of a novel wearable vibratory stimulus device and algorithm for event detection based on a single IMU sensor that will be used in rehabilitation after ankle sprain.
Design and development of an ankle wearable sensory stimulus device
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