Proposal of a Stance Postural Control Model with Vestibular and Proprioceptive Somatosensory Sensory Input

Maintenance of upright stance is one of the basic requirements in human daily life. Stance postural control is achieved based on multisensory inputs such as visual, vestibular and proprioceptive somatosensory inputs. In this paper, we proposed a stance postural control model including a neural controller with feed-forward inputs (muscle stiffness regulation) and sensory feedback of vestibular and proprioceptive somatosensory sensation. Through the optimization, variables of neural controller were designed to keep a musculoskeletal model standing during a 5 s forward dynamics simulation. From the results, we found that when both vestibular and proprioceptive somatosensory sensory input are available, low muscle stiffness is enough to maintain the balance of a musculoskeletal model in a stance posture. However, when vestibular sensory input get lost, higher muscle stiffness will be desired to keep the musculoskeletal model standing.

[1]  Peter Agada,et al.  Dynamic Reweighting of Three Modalities for Sensor Fusion , 2014, PloS one.

[2]  Scott L. Delp,et al.  Predictive Simulation Generates Human Adaptations during Loaded and Inclined Walking , 2015, PloS one.

[3]  Herman van der Kooij,et al.  A multisensory integration model of human stance control , 1999, Biological Cybernetics.

[4]  Thomas Mergner,et al.  A neurological view on reactive human stance control , 2010, Annu. Rev. Control..

[5]  R. Peterka Sensorimotor integration in human postural control. , 2002, Journal of neurophysiology.

[6]  Matthew Millard,et al.  Flexing computational muscle: modeling and simulation of musculotendon dynamics. , 2013, Journal of biomechanical engineering.

[7]  Jun Ota,et al.  Stance postural control of a musculoskeletal model able to compensate neurological time delay , 2014, 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014).

[8]  D. B. Lockhart,et al.  Optimal sensorimotor transformations for balance , 2007, Nature Neuroscience.

[9]  Milos R Popovic,et al.  Controlling balance during quiet standing: proportional and derivative controller generates preceding motor command to body sway position observed in experiments. , 2006, Gait & posture.

[10]  Jack M. Winters,et al.  An improved muscle-reflex actuator for use in large-scale neuromusculoskeletal models , 1995, Annals of Biomedical Engineering.

[11]  Jun Ota,et al.  Generation of biped stance motion in consideration of neurological time delay through forward dynamics simulation , 2015, 2015 International Symposium on Micro-NanoMechatronics and Human Science (MHS).

[12]  Motoki Kouzaki,et al.  Importance of body sway velocity information in controlling ankle extensor activities during quiet stance. , 2003, Journal of neurophysiology.

[13]  Jun Ota,et al.  Muscle Activities Changing Model by Difference in Sensory Inputs on Human Posture Control , 2012, IAS.

[14]  Sungho Jo,et al.  A model of cerebellum stabilized and scheduled hybrid long-loop control of upright balance , 2004, Biological Cybernetics.

[15]  Yoshiyuki Asai,et al.  A Model of Postural Control in Quiet Standing: Robust Compensation of Delay-Induced Instability Using Intermittent Activation of Feedback Control , 2009, PloS one.