The Influence of Posture, Applied Force and Perturbation Direction on Hip Joint Viscoelasticity

Limb viscoelasticity is a critical neuromechanical factor used to regulate the interaction with the environment. It plays a key role in modelling human sensorimotor control, and can be used to assess the condition of healthy and neurologically affected individuals. This paper reports the estimation of hip joint viscoelasticity during voluntary force control using a novel device that applies a leg displacement without constraining the hip joint. The influence of hip angle, applied limb force and perturbation direction on the stiffness and viscosity values was studied in ten subjects. No difference was detected in the hip joint stiffness between the dominant and non-dominant legs, but a small dependency was observed on the perturbation direction. Both hip stiffness and viscosity increased monotonically with the applied force magnitude, with posture being observed to have a slight influence. These results are in line with previous measurements carried out on upper limbs, and can be used as a baseline for lower limb movement simulation and further neuromechanical investigations.

[1]  Daniel Ludvig,et al.  Mechanisms contributing to reduced knee stiffness during movement , 2017, Experimental Brain Research.

[2]  Eric J Perreault,et al.  Voluntary control of static endpoint stiffness during force regulation tasks. , 2002, Journal of neurophysiology.

[3]  Robert Riener,et al.  Model-Based Estimation of Knee Stiffness , 2012, IEEE Transactions on Biomedical Engineering.

[4]  N. Hogan,et al.  Time-Varying Ankle Mechanical Impedance During Human Locomotion , 2015, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[5]  Etienne Burdet,et al.  Cable-Driven Robotic Interface for Lower Limb Neuromechanics Identification , 2019, IEEE Transactions on Biomedical Engineering.

[6]  David A. Winter,et al.  Human balance and posture control during standing and walking , 1995 .

[7]  S. Delp,et al.  How muscle architecture and moment arms affect wrist flexion-extension moments. , 1997, Journal of biomechanics.

[8]  Etienne Burdet,et al.  Human Robotics: Neuromechanics and Motor Control , 2013 .

[9]  Mitsuo Kawato,et al.  Equilibrium-Point Control Hypothesis Examined by Measured Arm Stiffness During Multijoint Movement , 1996, Science.

[10]  Hyunglae Lee,et al.  Multivariable static ankle mechanical impedance with relaxed muscles. , 2011, Journal of biomechanics.

[11]  M. Karataş,et al.  Assessment of spasticity using isokinetic dynamometry in patients with spinal cord injury , 1999, Spinal Cord.

[12]  A. Scremin,et al.  Quantifying muscle tone in spinal cord injury patients using isokinetic dynamometric techniques , 1996, Paraplegia.

[13]  Herman van der Kooij,et al.  LOPES II—Design and Evaluation of an Admittance Controlled Gait Training Robot With Shadow-Leg Approach , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[14]  Hsien-Yung Huang.  Development of the neuromechanics evaluation device (NED) for subject-specific lower limb modelling of spinal cord injury , 2018 .

[15]  Etienne Burdet,et al.  Assisting Human Balance in Standing With a Robotic Exoskeleton , 2019, IEEE Robotics and Automation Letters.

[16]  Elliott J. Rouse,et al.  Estimation of Human Ankle Impedance During the Stance Phase of Walking , 2014, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[17]  Pietro Morasso,et al.  Quiet standing: The Single Inverted Pendulum model is not so bad after all , 2019, PloS one.

[18]  R. Stephenson.  A and V , 1962, The British journal of ophthalmology.

[19]  Neville Hogan,et al.  The mechanics of multi-joint posture and movement control , 1985, Biological Cybernetics.

[20]  E Burdet,et al.  A method for measuring endpoint stiffness during multi-joint arm movements. , 2000, Journal of biomechanics.

[21]  V. Edgerton,et al.  Muscle architecture of the human lower limb. , 1983, Clinical orthopaedics and related research.

[22]  P. Crago,et al.  Effects of voluntary force generation on the elastic components of endpoint stiffness , 2001, Experimental Brain Research.

[23]  R. Triolo,et al.  Effects of spinal cord injury on lower-limb passive joint moments revealed through a nonlinear viscoelastic model. , 2004, Journal of rehabilitation research and development.

[24]  V. Dietz,et al.  Clinical assessments performed during robotic rehabilitation by the gait training robot Lokomat , 2005, 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005..

[25]  Glen M Davis,et al.  Musculo-skeletal modelling of NMES-evoked knee extension in spinal cord injury. , 2006, Journal of biomechanics.

[26]  W. Rymer,et al.  In vivo human knee joint dynamic properties as functions of muscle contraction and joint position. , 1997, Journal of biomechanics.

[27]  Hermano Igo Krebs,et al.  Summary of Human Ankle Mechanical Impedance During Walking , 2016, IEEE Journal of Translational Engineering in Health and Medicine.

[28]  R. Kearney,et al.  Intrinsic and reflex contributions to human ankle stiffness: variation with activation level and position , 2000, Experimental Brain Research.

[29]  Edwin van Asseldonk,et al.  Estimation of Human Hip and Knee Multi-Joint Dynamics Using the LOPES Gait Trainer , 2016, IEEE Transactions on Robotics.