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Human Motion Inverse Optimal Control Constraint Learning and Inertial Measurement Unit Sensor Design for Rehabilitation
During physiotherapy a continuous assessment and progress tracking of a patients performance is of clinical interest. In this project, based on the promising results from the initial prototype, we will redesign the wearable sensors to improve tracking accuracy, communication speed and robustness, incorporate onboard data storage and computation, and minimize cost and size. Furthermore, we will develop automated algorithms for the analysis of the measured data to help physiotherapists identify the causes of changes to the patients’ movement profile.
Faculty Supervisor:
Dana Kulic
Student:
Vladimir Joukov
Partner:
Cardon Rehabilitation and Medical Equipment
Discipline:
Engineering - computer / electrical
Sector:
Medical devices
University:
University of Waterloo
Program:
Accelerate
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