Convex Computation of the Basin of Stability to Measure the Likelihood of Falling: A Case Study on the Sit-to-Stand Task

Locomotion in the real world involves unexpected perturbations, and therefore requires strategies to maintain stability to successfully execute desired behaviours. Ensuring the safety of locomoting systems therefore necessitates a quantitative metric for stability. Due to the difficulty of determining the set of perturbations that induce failure, researchers have used a variety of features as a proxy to describe stability. This paper utilises recent advances in dynamical systems theory to develop a personalised, automated framework to compute the set of perturbations from which a system can avoid failure, which is known as the basin of stability. The approach tracks human motion to synthesise a control input that is analysed to measure the basin of stability. The utility of this analysis is verified on a Sit-to-Stand task performed by 15 individuals. The experiment illustrates that the computed basin of stability for each individual can successfully differentiate between less and more stable Sit-to-Stand strategies.

[1]  Daniel Koditschek,et al.  Quantifying Dynamic Stability and Maneuverability in Legged Locomotion1 , 2002, Integrative and comparative biology.

[2]  L. Nyberg,et al.  “Stops walking when talking” as a predictor of falls in elderly people , 1997, The Lancet.

[3]  M. Speechley,et al.  Use of the Berg Balance Scale for Predicting Multiple Falls in Community-Dwelling Elderly People: A Prospective Study , 2008, Physical Therapy.

[4]  Alexandre M. Bayen,et al.  A time-dependent Hamilton-Jacobi formulation of reachable sets for continuous dynamic games , 2005, IEEE Transactions on Automatic Control.

[5]  Nobuhiro Kito,et al.  The Clarification of the Strategy during Sit-to-Stand Motion from the Standpoint of Mechanical Energy Transfer , 2012 .

[6]  B. E. Maki,et al.  The role of limb movements in maintaining upright stance: the "change-in-support" strategy. , 1997, Physical therapy.

[7]  A. Shumway-cook,et al.  Predicting the probability for falls in community-dwelling older adults. , 1997, Physical therapy.

[8]  Ruzena Bajcsy,et al.  Convex computation of the reachable set for controlled polynomial hybrid systems , 2014, 53rd IEEE Conference on Decision and Control.

[9]  Didier Henrion,et al.  Convex Computation of the Region of Attraction of Polynomial Control Systems , 2012, IEEE Transactions on Automatic Control.

[10]  M A Hughes,et al.  Chair rise strategies in the elderly. , 1994, Clinical biomechanics.

[11]  P. Parrilo Structured semidefinite programs and semialgebraic geometry methods in robustness and optimization , 2000 .

[12]  R. Full,et al.  Tail-assisted pitch control in lizards, robots and dinosaurs , 2012, Nature.

[13]  Y-C Pai,et al.  Role of feedforward control of movement stability in reducing slip-related balance loss and falls among older adults. , 2003, Journal of neurophysiology.

[14]  Ian M. Mitchell,et al.  Lagrangian methods for approximating the viability kernel in high-dimensional systems , 2013, Autom..

[15]  C. Hargraves,et al.  DIRECT TRAJECTORY OPTIMIZATION USING NONLINEAR PROGRAMMING AND COLLOCATION , 1987 .

[16]  Emanuel Todorov,et al.  Evidence for the Flexible Sensorimotor Strategies Predicted by Optimal Feedback Control , 2007, The Journal of Neuroscience.

[17]  A. Campbell,et al.  Risk factors for falls in a community-based prospective study of people 70 years and older. , 1989, Journal of gerontology.

[18]  Jonathan B. Dingwell,et al.  Do Humans Optimally Exploit Redundancy to Control Step Variability in Walking? , 2010, PLoS Comput. Biol..

[19]  R. Newton,et al.  Use of the Berg Balance Test to predict falls in elderly persons. , 1996, Physical therapy.

[20]  Rachid Aissaoui,et al.  Biomechanical analysis and modelling of sit to stand task: a literature review , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[21]  Diane Podsiadlo,et al.  The Timed “Up & Go”: A Test of Basic Functional Mobility for Frail Elderly Persons , 1991, Journal of the American Geriatrics Society.

[22]  A Cappozzo,et al.  Sit-to-stand motor strategies investigated in able-bodied young and elderly subjects. , 2000, Journal of biomechanics.

[23]  W. Rudin Principles of mathematical analysis , 1964 .

[24]  Y. Pai,et al.  Center of mass velocity-position predictions for balance control. , 1997, Journal of biomechanics.

[25]  Li-Shan Chou,et al.  Region of Stability Derived by Center of Mass Acceleration Better Identifies Individuals with Difficulty in Sit-to-Stand Movement , 2013, Annals of Biomedical Engineering.

[26]  A. M. Lyapunov The general problem of the stability of motion , 1992 .

[27]  A. Hof,et al.  Balance responses to lateral perturbations in human treadmill walking , 2010, Journal of Experimental Biology.

[28]  Michael I. Jordan,et al.  Optimal feedback control as a theory of motor coordination , 2002, Nature Neuroscience.

[29]  Ufuk Topcu,et al.  Local stability analysis using simulations and sum-of-squares programming , 2008, Autom..

[30]  L. Mollinger,et al.  Age- and gender-related test performance in community-dwelling elderly people: Six-Minute Walk Test, Berg Balance Scale, Timed Up & Go Test, and gait speeds. , 2002, Physical therapy.

[31]  M. Woollacott,et al.  Predicting the probability for falls in community-dwelling older adults using the Timed Up & Go Test. , 2000, Physical therapy.

[32]  Russ Tedrake,et al.  Convex optimization of nonlinear feedback controllers via occupation measures , 2013, Int. J. Robotics Res..

[33]  H J Grootenboer,et al.  An inverse dynamics model for the analysis, reconstruction and prediction of bipedal walking. , 1995, Journal of Biomechanics.

[34]  Nancy Devlin,et al.  Effectiveness and economic evaluation of a nurse delivered home exercise programme to prevent falls. 1: Randomised controlled trial , 2001, BMJ : British Medical Journal.

[35]  Jonathan B Dingwell,et al.  Trial-to-trial dynamics and learning in a generalized, redundant reaching task. , 2013, Journal of neurophysiology.

[36]  R J Full,et al.  Distributed mechanical feedback in arthropods and robots simplifies control of rapid running on challenging terrain , 2007, Bioinspiration & biomimetics.

[37]  T. Flash,et al.  The coordination of arm movements: an experimentally confirmed mathematical model , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[38]  A. Prochazka,et al.  Neuromuscular responses to gait perturbations in freely moving cats , 2004, Experimental Brain Research.

[39]  Ali Jadbabaie,et al.  Safety Verification of Hybrid Systems Using Barrier Certificates , 2004, HSCC.

[40]  A Cappozzo,et al.  A telescopic inverted-pendulum model of the musculo-skeletal system and its use for the analysis of the sit-to-stand motor task. , 1999, Journal of biomechanics.

[41]  K. Berg Measuring balance in the elderly: preliminary development of an instrument , 1989 .

[42]  M. Kawato,et al.  Formation and control of optimal trajectory in human multijoint arm movement , 1989, Biological Cybernetics.

[43]  C. Desoer,et al.  Linear System Theory , 1963 .

[44]  T. M. Owings,et al.  Body segment inertial parameter estimation for the general population of older adults. , 2002, Journal of biomechanics.

[45]  Jonathan B Dingwell,et al.  Movement variability near goal equivalent manifolds: fluctuations, control, and model-based analysis. , 2013, Human movement science.

[46]  L Nyberg,et al.  Attention, Frailty, and Falls: The Effect of a Manual Task on Basic Mobility , 1998, Journal of the American Geriatrics Society.

[47]  Shankar Mohan,et al.  Convex computation of the reachable set for hybrid systems with parametric uncertainty , 2016, 2016 American Control Conference (ACC).

[48]  F. Horak Postural orientation and equilibrium: what do we need to know about neural control of balance to prevent falls? , 2006, Age and ageing.

[49]  J. P. Paul,et al.  What is balance? , 2000, Clinical rehabilitation.

[50]  Wynne A. Lee,et al.  Evaluation of a model that determines the stability limits of dynamic balance. , 1999, Gait & posture.

[51]  Mitsuo Kawato,et al.  Internal models for motor control and trajectory planning , 1999, Current Opinion in Neurobiology.