Dr. Annemarie F Laudanski is a Biomedical Engineer, who graduated with a Bachelors of Applied Science in Mechanical Engineering (2011) and a Masters of Applied Science in Biomedical Engineering (2013) here at Queen’s. She worked for 3 years as a lead field applications engineering at Xsens Technologies before returning to complete her PhD in Biomechanics in the Faculty of Applied Health Sciences at the University of Waterloo in 2022. Dr. Laudanski then moved to Dalhousie University as a Killam and Mitacs Accelerate postdoctoral fellow in the School of Biomedical Engineering with Dr. Janie Astephen Wilson. There her research focused on improving alignment and data segmentation algorithms to permit the processing of free-living inertial-sensor data and the statistical modeling of large longitudinal datasets, pioneering developments in the identification of biomechanical biomarkers predictive of patient-specific surgical outcomes following total knee arthroplasty. Dr. Laudanski is currently collaborating with Dr. Eduardo Rocon in the BioRobotics Group at the Spanish National Research Council (CSIC), funded by a NSERC post-doctoral fellowship. She is currently leading collaborations between engineers, neuroscientists, and clinicians towards the modeling of biomechanical markers of lower limb kinematics, kinetics, and neuromuscular activations in children with cerebral palsy undergoing robotic-driven rehabilitation.
Dr. Laudanski’s work has primarily been focused on the application of wearable sensors, both inertial and electromyographic, towards the measurement of pathological movements in free-living. Through her research, Dr. Laudanski seeks to address critical clinical needs by marrying cutting-edge sensor-based technological developments with advanced AI-based modeling. The early career foundational work in sensor fusion and alignment techniques laid the foundation for her current pioneering research in the application of wearable technologies towards the study of motor-learning and re-learning, revealing biomechanical biomarkers indicative of adaptive or maladaptive neuroplasticity. By examining spatiotemporal, kinematic, kinetic, and neuromuscular indicators of neuroplasticity and their modulation based on factors associated with clinical health status, Dr. Laudanski’s research seeks to comprehensively model the evolution of motor control strategies in free-living. Ultimately this research will shape the uptake of innovative technologies for early diagnostics and patient specific treatment planning to assist in the treatment of gait and other motor deficits following musculoskeletal and neurological damage or diseases or the prevention of such damage.
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