Positive Feedback in Powered Exoskeletons: Improved Metabolic Efficiency at the Cost of Reduced Stability?

A broad objective of many lower extremity exoskeletons is to allow the wearer to expend less of their own energy for locomotion. Existing exoskeleton control algorithms are based on positive feedback. Forces are generated to augment movement initiated by the wearer. Positive feedback, however, can have destabilizing effects in dynamic systems. In fact, stability in these lower extremity exoskeletons is achieved by relying on the wearer’s neuromuscular system. Relying on the wearer to maintain stability may increase metabolic demand, which is counter productive to increasing efficiency. Thus, the goal of this study was to measure how a simple form of positive feedback that augments ankle push-off power affects both metabolic efficiency and dynamic walking stability. We developed a pair of powered ankle-foot orthoses (PAFOs) similar in design to Ferris, et al. (J. Appl. Biomech. 21, 189–197, 2005). Nine young healthy adults (23.3±1.6 years) walked on a treadmill in the PAFOs under two conditions: (1) with and (2) without push-off power assistance. Metabolic energy expenditure was calculated using indirect calorimetry. Walking stability was quantified using techniques for studying stability of dynamic system trajectories. The maximum Lyapunov exponent for assessing local dynamic stability, and the maximum Floquet multiplier magnitude for assessing orbital stability were calculated from foot and shank kinematics for each condition. Greater Lyapunov exponents and Floquet multipliers indicate decreased stability. Walking with mechanically generated push-off power increased metabolic efficiency (2.58±0.39 to 2.97±0.38, p<0.01), did not affect local dynamic stability (0.14±0.02 to 0.14±0.02, p = 0.77), but decreased orbital dynamic stability (0.43±0.03 to 0.48±0.06, p = 0.05). This study provides evidence that positive feedback can negatively affect stability. Further investigations into understanding stability of movement will be necessary for the design of controllers for powered lower extremity exoskeletons.Copyright © 2007 by ASME

[1]  J. Dingwell,et al.  Kinematic variability and local dynamic stability of upper body motions when walking at different speeds. , 2006, Journal of biomechanics.

[2]  P. Matthews.  The human stretch reflex and the motor cortex , 1991, Trends in Neurosciences.

[3]  V. Tucker.  The energetic cost of moving about. , 1975, American Scientist.

[4]  Y. Hurmuzlu,et al.  On the measurement of dynamic stability of human locomotion. , 1994, Journal of biomechanical engineering.

[5]  F. Zajac,et al.  Contributions of the individual ankle plantar flexors to support, forward progression and swing initiation during walking. , 2001, Journal of biomechanics.

[6]  A. Wolf,et al.  Determining Lyapunov exponents from a time series , 1985 .

[7]  James A. Norris,et al.  Effect of augmented plantarflexion power on preferred walking speed and economy in young and older adults. , 2007, Gait & posture.

[8]  Jonathan B Dingwell,et al.  The effects of sensory loss and walking speed on the orbital dynamic stability of human walking. , 2007, Journal of biomechanics.

[9]  N. Stergiou,et al.  Nonlinear dynamics indicates aging affects variability during gait. , 2003, Clinical biomechanics.

[10]  H. Kazerooni,et al.  Biomechanical design of the Berkeley lower extremity exoskeleton (BLEEX) , 2006, IEEE/ASME Transactions on Mechatronics.

[11]  Yoshiyuki Sankai,et al.  Control method of robot suit HAL working as operator's muscle using biological and dynamical information , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[12]  Yu. A. Kuznetsov,et al.  Applied nonlinear dynamics: Analytical, computational, and experimental methods , 1996 .

[13]  J. Donelan,et al.  Mechanical and metabolic requirements for active lateral stabilization in human walking. , 2004, Journal of biomechanics.

[14]  Daniel P. Ferris,et al.  An ankle-foot orthosis powered by artificial pneumatic muscles. , 2005, Journal of applied biomechanics.

[15]  J. Czerniecki,et al.  The role of ankle plantar flexor muscle work during walking. , 1998, Scandinavian journal of rehabilitation medicine.

[16]  Blake Hannaford,et al.  Artificial Muscles : Actuators for Biorobotic Systems , 1999 .

[17]  M. Savi,et al.  Evaluating Noise Sensitivity on the Time Series Determination of Lyapunov Exponents Applied to the Nonlinear Pendulum , 2003 .

[18]  Jonathan B. Dingwell,et al.  A direct comparison of local dynamic stability during unperturbed standing and walking , 2006, Experimental Brain Research.

[19]  J. Brockway.  Derivation of formulae used to calculate energy expenditure in man. , 1987, Human nutrition. Clinical nutrition.

[20]  Daniel P Ferris,et al.  The effects of powered ankle-foot orthoses on joint kinematics and muscle activation during walking in individuals with incomplete spinal cord injury , 2006, Journal of NeuroEngineering and Rehabilitation.

[21]  M. Rosenstein,et al.  A practical method for calculating largest Lyapunov exponents from small data sets , 1993 .

[22]  Yoshiyuki Sankai.  The Leading Edge of Future Technology "Cybernics": Project HAL - Toward Robot Suits and Cyber Suits? , 2005, SEMWEB.

[23]  Homayoon Kazerooni,et al.  Exoskeletons for human power augmentation , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[24]  H. Goldstein,et al.  The rise of the body bots [robotic exoskeletons] , 2005, IEEE Spectrum.

[25]  M. Lauk,et al.  Pathological tremors: Deterministic chaos or nonlinear stochastic oscillators? , 2000, Chaos.

[26]  D. Winter,et al.  Kinetic analysis of the lower limbs during walking: what information can be gained from a three-dimensional model? , 1995, Journal of biomechanics.