Human Motion Analysis via Whole-Body Marker Tracking Control
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Human Motion Analysis via Whole-Body Marker Tracking Control Emel Demircan PhD Adviser: Professor Oussama Khatib Artificial Intelligence Laboratory, Stanford University Why study human movement? • It is amazing! • Study and optimize athletic performance and sports equipment • Basis for successful surgical design • Help manage CNS disorders • Can serve as biofeedback for rehabilitation • Help manage musculoskeletal disease (arthritis, osteoporosis) and injuries.. Methodology Apply the methods in robotics and biocomputation to the problems in orthopedics and sports medicine Feasible Set of Operational Space Accelerations Effort Expenditure in terms of Musculoskeletal Parameters Musculoskeletal Modeling Motion Characterization Resulting Framework • Real-time motion dynamics • Subject-specific • Flexible • Multi-modal feedback • Generic Model: 83 joints 193 dofs 154 muscles • Subject- specific scaling Whole-Body Control Hierarchy Constraint s Marker Tasks Posture Additional Behaviors Motion Capture Real-time Reconstructi on Largest Acceleration Lines Smallest Effort Lines
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Human Motion Analysis via Whole-Body Marker Tracking Control. Emel Demircan PhD Adviser: Professor Oussama Khatib Artificial Intelligence Laboratory, Stanford University. Methodology Apply the methods in robotics and b iocomputation to the problems in - PowerPoint PPT Presentation
Transcript of Human Motion Analysis via Whole-Body Marker Tracking Control
Human Motion Analysis via Whole-Body Marker Tracking Control
Emel DemircanPhD Adviser: Professor Oussama Khatib
Artificial Intelligence Laboratory, Stanford University
Why study human movement?• It is amazing!
• Study and optimize athletic performance
and sports equipment• Basis for successful surgical design
• Help manage CNS disorders
• Can serve as biofeedback for rehabilitation
• Help manage musculoskeletal disease (arthritis, osteoporosis) and injuries..
MethodologyApply the methods in robotics and
biocomputation to the problems in
orthopedics and sports medicine
Feasible Set of
Operational Space AccelerationsEffort Expenditure in terms of
Musculoskeletal Parameters
Musculoskeletal Modeling
Motion Characterization
Resulting Framework• Real-time motion dynamics
• Subject-specific• Flexible• Multi-modal feedback
• Generic Model:
83 joints
193 dofs
154 muscles
• Subject-specific scaling
Whole-Body Control Hierarchy
Constraints
Marker Tasks
Posture
Additional
Behaviors
Motion
Capture
Real-time
Reconstruction
Largest
Acceleration
Lines
Smallest
Effort
Lines
