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Perturbation-dependent selection of postural feedback gain and its scaling

Push recovery. Perturbation-dependent selection of postural feedback gain and its scaling. Quantification of postural balance. Seyoung Kim, PhD.

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Perturbation-dependent selection of postural feedback gain and its scaling

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  1. Push recovery • Perturbation-dependent selection of • postural feedback gain and its scaling • Quantification of postural balance • Seyoung Kim, PhD Seyoung Kim, Christopher G. Atkeson and Sukyung Park, “Perturbation-dependent selection of postural feedback gain and its scaling”, Journal of Biomechanics (under review)

  2. Postural adjustability described by feedback gain [ Park et al. 2004 ] • Different types of perturbation may lead to • a change of feedback gain set.

  3. Research objective • Objective : • We examined whether the selection of postural feedback gain and its scaling is dependent on the perturbation type. • Hypothesis : • Push recovery strategy might be described with a different gait set in compared to the set of support translation trials. • Forward push may generate dominant hip joint excursion with restricted ankle joint motion. • This balance strategy might be quantified as greater ankle torque gains than those of support translation trials.

  4. Experimental procedure • Measurement • Joint angle captured by Motion capture system (Santa Rosa, California) • 200 Hz sampling rate with cutoff frequency of 10 Hz • Moment & Ground reaction forces measured by a force plate (AMTI) • 200 Hz sampling rate with cutoff frequency of 30 Hz @ Biomimetics Lab 2009 • Subjects • 7 healthy young (25±3 yrs) • Protocols • forward push • (2-10 kg) X 5 set, randomly • Heel-off constraint

  5. Biomechanical model for human postural control [ Feedback control model for postural control ] 2segment inverted pendulum Linearized Joint torques were calculated by inverse dynamics [ Kuo,1998 ]. Full-state feedback control model that represent CNS control Gain parameters calculated by optimization

  6. Calculation of feedback gains by model simulation [ Exp. data and Simulation ] avg. 0.83±0.04

  7. Results and Discussion Push force estimation for various load weights Joint kinematics and kinetics in response to forward push Postural feedback gain and its scaling Model simulation using different gain sets

  8. Push force estimation for various load weights When the impulse is delivered to the subject through the sponge padding, the magnitude of collision force is significantly reduced and the duration of pendulum contact with the body was increased due to the sponge dynamics.

  9. Joint kinematics and kinetics Although ankle joint motion was severely restricted compare to those of the hip joint, significantly greater ankle joint torque was generated. Push perturbations mostly generate hip response, i.e., out-of-phase motion between upper and lower extremity.

  10. Postural feedback gain and its scaling

  11. Simulation using different gain sets

  12. Conclusion • Direct excitation to the upper extremity by a falling pendulum generated dominant hip joint excursion and required more robust support at the ankle joint not to violate the flat-foot constraint, which induced restricted ankle joint motion. • This balance strategy was quantified as greater ankle torque gains than those of support translation trials • The result of different selection of feedback gain set and the gain scaling imply that the nervous system may be aware of body dynamics and biomechanical constraints and selects an appropriate postural feedback gains that satisfy postural stability and feasible joint torques constraints.

  13. Model limitations Our model does not exclude the possibility of the nervous system’s selection of pre-programmed responses. A possible selection of a discrete postural strategy, such as a stepping strategy, was not explicitly modeled in the current feedback-controlled model. The current model did not consider physiological aspects such as time delay in neural signal transfer, muscle mechanics and short latency responses from reflexes.

  14. Acknowledgement • Funds • Postural control study was supported by a Basic Research Fund of the Korea Institute of Machinery and Materials, the second stage of the Brain Korea 21 Project, and a National Institute on Aging. • Walking research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (#2010-0013306) and the Unmanned Technology Research Center (UTRC) at the Korea Advanced Institute of Science and Technology (KAIST), originally funded by DAPA, ADD. • Collaborators • Fay B. Horak (Oregon Health & Science University) • Patricia Carlson-Kuhta (Oregon Health & Science University) • Chris G. Atkeson (Carnegie Mellon University)

  15. Special thanks to…

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