A generic model of real-world non-ideal behaviour of FES-induced muscle contractions: simulation tool

Functional electrical stimulation (FES) applications are frequently evaluated in simulation prior to testing in human subjects. Such simulations are usually based on the typical muscle responses to electrical stimulation, which may result in an overly optimistic assessment of likely real-world performance. We propose a novel method for simulating FES applications that includes non-ideal muscle behaviour during electrical stimulation resulting from muscle fatigue, spasms and tremors. A 'non-idealities' block that can be incorporated into existing FES simulations and provides a realistic estimate of real-world performance is described. An implementation example is included, showing how the non-idealities block can be incorporated into a simulation of electrically stimulated knee extension against gravity for both a proportional-integral-derivative controller and a sliding mode controller. The results presented in this paper illustrate that the real-world performance of a FES system may be vastly different from the performance obtained in simulation using nominal muscle models. We believe that our non-idealities block should be included in future simulations that involve muscle response to FES, as this tool will provide neural engineers with a realistic simulation of the real-world performance of FES systems. This simulation strategy will help engineers and organizations save time and money by preventing premature human testing. The non-idealities block will become available free of charge at www.toronto-fes.ca in late 2011.

[1]  N.A.C. Hatcher,et al.  Control of leg-powered paraplegic cycling using stimulation of the lumbo-sacral anterior spinal nerve roots , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[2]  Richard M. Murray,et al.  Feedback Systems An Introduction for Scientists and Engineers , 2007 .

[3]  Vadim I. Utkin,et al.  Sliding Modes in Control and Optimization , 1992, Communications and Control Engineering Series.

[4]  Alfred D. Grant Gait Analysis: Normal and Pathological Function , 2010 .

[5]  Anthony S Wexler,et al.  Mathematical model that predicts lower leg motion in response to electrical stimulation. , 2006, Journal of biomechanics.

[7]  C. Lynch,et al.  A stochastic model of knee angle in response to electrical stimulation of the quadriceps and hamstrings muscles. , 2011, Artificial organs.

[8]  V. Dietz,et al.  Transcutaneous functional electrical stimulation for grasping in subjects with cervical spinal cord injury , 2005, Spinal Cord.

[9]  William Holderbaum,et al.  Development and Experimental Identification of a Biomechanical Model of the Trunk for Functional Electrical Stimulation Control in Paraplegia , 2008, Neuromodulation : journal of the International Neuromodulation Society.

[10]  R. Triolo,et al.  Effects of regular use of neuromuscular electrical stimulation on tissue health. , 2003, Journal of rehabilitation research and development.

[11]  J. Abbas,et al.  Feedback control of coronal plane hip angle in paraplegic subjects using functional neuromuscular stimulation , 1991, IEEE Transactions on Biomedical Engineering.

[12]  K. Hunt,et al.  Sliding-mode control of knee-joint angle: experimental results , 2002 .

[13]  M.R. Popovic,et al.  Neural-Mechanical Feedback Control Scheme Generates Physiological Ankle Torque Fluctuation During Quiet Stance , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[14]  Thomas Sinkjær,et al.  Control of Movement for the Physically Disabled: Control for Rehabilitation Technology , 2000 .

[15]  Tadej Bajd,et al.  Sensory supported FES control in gait training of incomplete spinal cord injury persons. , 2005, Artificial organs.

[16]  Z. Matjacic,et al.  Paraplegic standing supported by FES-controlled ankle stiffness , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[17]  B J Andrews,et al.  Reduction of seating pressure using FES in patients with spinal cord injury. A preliminary report , 1992, Paraplegia.

[18]  R Riener,et al.  Biomechanical model of the human knee evaluated by neuromuscular stimulation. , 1996, Journal of biomechanics.

[19]  Fabio Previdi,et al.  Identification of black-box nonlinear models for lower limb movement control using functional electrical stimulation , 2002 .

[20]  Arash Ajoudani,et al.  A Neuro-Sliding-Mode Control With Adaptive Modeling of Uncertainty for Control of Movement in Paralyzed Limbs Using Functional Electrical Stimulation , 2009, IEEE Transactions on Biomedical Engineering.

[21]  Robert Riener,et al.  Walking with WALK! , 2008, IEEE Engineering in Medicine and Biology Magazine.

[22]  J. Perry,et al.  Gait Analysis , 2024 .

[23]  Gideon F. Inbar,et al.  The development of a model reference adaptive controller to control the knee joint of paraplegics , 1991 .

[24]  Maury L Hull,et al.  Predicting fatigue during electrically stimulated non‐isometric contractions , 2010, Muscle & nerve.

[25]  Jörg Raisch,et al.  Online identification and nonlinear control of the electrically stimulated quadriceps muscle , 2005 .

[26]  Thierry Keller,et al.  Sliding mode closed-loop control of FES controlling the shank movement , 2004, IEEE Transactions on Biomedical Engineering.

[27]  Brian J. Andrews,et al.  Fuzzy logic control of FES rowing exercise in paraplegia , 2004, IEEE Transactions on Biomedical Engineering.

[28]  Vadim I. Utkin,et al.  A control engineer's guide to sliding mode control , 1999, IEEE Trans. Control. Syst. Technol..

[29]  J. Perry,et al.  Rate and range of knee motion during ambulation in healthy and arthritic subjects. , 1985, Physical therapy.

[30]  K.J. Hunt,et al.  New results in feedback control of unsupported standing in paraplegia , 2004, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[31]  P. H. Peckham,et al.  An implanted upper-extremity neuroprosthesis using myoelectric control. , 2008, The Journal of hand surgery.

[32]  Michael E. Miller,et al.  Implanted electrical stimulation of the trunk for seated postural stability and function after cervical spinal cord injury: a single case study. , 2009, Archives of physical medicine and rehabilitation.

[33]  M. Ferrarin,et al.  A pilot study of myoelectrically controlled FES of upper extremity , 2001, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[34]  A. Pedotti,et al.  The relationship between electrical stimulus and joint torque: a dynamic model. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[35]  Z Matjacić,et al.  Arm-free paraplegic standing--Part II: Experimental results. , 1998, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[36]  Michael E. Miller,et al.  Standing After Spinal Cord Injury With Four-Contact Nerve-Cuff Electrodes for Quadriceps Stimulation , 2008, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[37]  Zlatko Matjacic,et al.  Arm-free paraplegic standing. II. Experimental results , 1998 .

[38]  P E Crago,et al.  Closed-loop wrist stabilization in C4 and C5 tetraplegia. , 1997, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[39]  M. Hull,et al.  Predicting the effect of muscle length on fatigue during electrical stimulation , 2009, Muscle & nerve.