보행 예측 시뮬레이션 이 제 희 생체운동연구단 서울대학교. 보행 예측 시뮬레이션 수술 전 보행 데이터 취득 모션 캡쳐, 지면 반발력, EMG 개인 별 골격, 근력, 근경직도 수술 계획에 따른 근골격 변형 골격 변형, 근육 길이, insertion, origin, tendon.

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Presentation transcript:

보행 예측 시뮬레이션 이 제 희 생체운동연구단 서울대학교

보행 예측 시뮬레이션 수술 전 보행 데이터 취득 모션 캡쳐, 지면 반발력, EMG 개인 별 골격, 근력, 근경직도 수술 계획에 따른 근골격 변형 골격 변형, 근육 길이, insertion, origin, tendon 길이 수술후 보행 예측 시뮬레이션 시뮬레이션 평가

Newton’s Equation of Motion force mass acceleration

Dynamic Simulation q : state of the body Integrate force over time

Path Tracking PD (Proportional Derivative) Control

Articulated Figure q : Generalized state M : System mass matrix F : Gravity and External forces C : Coriolis and centripetal forces  : Joint forces

Fully-Actuated System Forward dynamics Given (generalized) forces, compute (generalized) accelerations Inverse dynamics Given (generalized) accelerations, compute (generalized) forces

Under-actuated System Forward dynamics Inverse dynamics Given accelerations, we may not be able to compute forces that generate the desired accelerations

Ground Reaction Force (GRF) GRF is passive we actuate our muscles, but we can sense the magnitude of GRF we cannot control GRF precisely GRF is hemi-directional Precisely controllable GRF facilitates the control of underactuated system If GRF were omni-directional, the system is fully-actuated

Muscle Force Three-element Hill muscle model one contractile active element two passive non-linear springs Actuator redundancy

Technical Issues Placing markers for motion capture Acquiring individual skeletal models

Individual Skeletal Models Reconstruct bone shapes from multiview X-ray images Model-based approach collection of 3D bone geometries (from CT) principle component analysis (PCA)