Hybrid FES-robot cooperative control of ambulatory gait rehabilitation exoskeleton

AbstractRobotic and functional electrical stimulation (FES) approaches are used for rehabilitation of walking impairment of spinal cord injured individuals. Although devices are commercially available, there are still issues that remain to be solved. Control of hybrid exoskeletons aims at blending robotic exoskeletons and electrical stimulation to overcome the drawbacks of each approach while preserving their advantages. Hybrid actuation and control have a considerable potential for walking rehabilitation but there is a need of novel control strategies of hybrid systems that adequately manage the balance between FES and robotic controllers. Combination of FES and robotic control is a challenging issue, due to the non-linear behavior of muscle under stimulation and the lack of developments in the field of hybrid control. In this article, a cooperative control strategy of a hybrid exoskeleton is presented. This strategy is designed to overcome the main disadvantages of muscular stimulation: electromechanical delay and change in muscle performance over time, and to balance muscular and robotic actuation during walking.Experimental results in healthy subjects show the ability of the hybrid FES-robot cooperative control to balance power contribution between exoskeleton and muscle stimulation. The robotic exoskeleton decreases assistance while adequate knee kinematics are guaranteed. A new technique to monitor muscle performance is employed, which allows to estimate muscle fatigue and implement muscle fatigue management strategies. Kinesis is therefore the first ambulatory hybrid exoskeleton that can effectively balance robotic and FES actuation during walking. This represents a new opportunity to implement new rehabilitation interventions to induce locomotor activity in patients with paraplegia.Acronym list: 10mWT: ten meters walking test; 6MWT: six minutes walking test; FSM: finite-state machine; t-FSM: time-domain FSM; c-FSM: cycle-domain FSM; FES: functional electrical stimulation; HKAFO: hip-knee-ankle-foot orthosis; ILC: iterative error-based learning control; MFE: muscle fatigue estimator; NILC: Normalized stimulation output from ILC controller; PID: Proportional-Integral-derivative Control; PW: Stimulation pulse width; QUEST: Quebec User Evaluation of Satisfaction with assistive Technology; SCI: Spinal cord injury; TTI: torque-time integral; VAS: Visual Analog Scale.

[1]  F. Reynard,et al.  The WalkTrainer—A New Generation of Walking Reeducation Device Combining Orthoses and Muscle Stimulation , 2009, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[2]  José Luis Pons Rovira,et al.  Online Assessment of Human-Robot Interaction for Hybrid Control of Walking , 2011, Sensors.

[3]  J. G. Ziegler,et al.  Optimum Settings for Automatic Controllers , 1942, Journal of Fluids Engineering.

[4]  L E Olmos,et al.  Comparison of gait performance on different environmental settings for patients with chronic spinal cord injury , 2008, Spinal Cord.

[5]  Eric Rogers,et al.  Iterative learning control of FES applied to the upper extremity for rehabilitation , 2009 .

[6]  N. Hoshimiya,et al.  Joint angle control by FES using a feedback error learning controller , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[7]  Goro Obinata,et al.  State estimation of walking phase and functional electrical stimulation by wearable device , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  S. Jonic,et al.  Three machine learning techniques for automatic determination of rules to control locomotion , 1999, IEEE Transactions on Biomedical Engineering.

[9]  Michael L Boninger,et al.  Outcome Measures for Gait and Ambulation in the Spinal Cord Injury Population , 2008, The journal of spinal cord medicine.

[10]  Robert Riener,et al.  Model-based development of neuroprosthesis for paraplegic patients. , 1999, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[11]  L. Schwirtlich,et al.  Detection and prediction of FES-induced fatigue. , 1997, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[12]  Glen M Davis,et al.  Evoked EMG and Muscle Fatigue During Isokinetic FES‐Cycling in Individuals With SCI , 2011, Neuromodulation : journal of the International Neuromodulation Society.

[13]  P. Veltink,et al.  Cycle-to-cycle control of swing phase of paraplegic gait induced by surface electrical stimulation , 1995, Medical and Biological Engineering and Computing.

[14]  Daniel Graupe,et al.  Walking performance, medical outcomes and patient training in FES of innervated muscles for ambulation by thoracic-level complete paraplegics , 2008, Neurological research.

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

[16]  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.

[17]  Stefania Fatone,et al.  A Review of the Literature Pertaining to KAFOs and HKAFOs for Ambulation , 2006 .

[18]  Goro Obinata,et al.  Control of hybrid FES system for restoration of paraplegic locomotion , 1993, Proceedings of 1993 2nd IEEE International Workshop on Robot and Human Communication.

[19]  L Sykes,et al.  Objective measurement of use of the reciprocating gait orthosis (RGO) and the electrically augmented RGO in adult patients with spinal cord lesions , 1996, Prosthetics and orthotics international.

[20]  Morari,et al.  Increasing muscular participation in robot-assisted gait training using FES , 2011 .

[21]  Hamid-Reza Kobravi,et al.  Decentralized adaptive robust control based on sliding mode and nonlinear compensator for the control of ankle movement using functional electrical stimulation of agonist–antagonist muscles , 2009, Journal of neural engineering.

[22]  W. Durfee,et al.  Surface EMG as a fatigue indicator during FES-induced isometric muscle contractions. , 1997, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[23]  T. A. Thrasher,et al.  Functional electrical stimulation of walking: function, exercise and rehabilitation. , 2008, Annales de readaptation et de medecine physique : revue scientifique de la Societe francaise de reeducation fonctionnelle de readaptation et de medecine physique.

[24]  B. Heller,et al.  A new hybrid spring brake orthosis for controlling hip and knee flexion in the swing phase , 2001, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[25]  D. Wolfe,et al.  Classifying incomplete spinal cord injury syndromes: algorithms based on the International Standards for Neurological and Functional Classification of Spinal Cord Injury Patients. , 2000, Archives of physical medicine and rehabilitation.

[26]  José Luis Pons Rovira,et al.  Immediate effects of a controllable knee ankle foot orthosis for functional compensation of gait in patients with proximal leg weakness , 2007, Medical & Biological Engineering & Computing.

[27]  Michael Goldfarb,et al.  Design of a joint-coupled orthosis for FES-aided gait , 2009, 2009 IEEE International Conference on Rehabilitation Robotics.

[28]  Jose L Pons,et al.  Knee muscle fatigue estimation during isometric artificially elicited contractions in incomplete spinal cord injured subjects , 2013 .

[29]  Henry M. Franken,et al.  Fatigue of intermittently stimulated quadriceps during imposed cyclical lower leg movements , 1992, 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[30]  R. Riener Model-based development of neuroprosthesis for paraplegic patients. , 1999, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[31]  R. Riener,et al.  Patient-cooperative strategies for robot-aided treadmill training: first experimental results , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[32]  L. Schwirtlich,et al.  Hybrid assistive system-the motor neuroprosthesis , 1989, IEEE Transactions on Biomedical Engineering.

[33]  Dejan Popović,et al.  Automatic vs hand-controlled walking of paraplegics. , 2003, Medical engineering & physics.

[34]  Joon-Young Kim,et al.  Closed‐Loop Control of Functional Electrical Stimulation‐Assisted Arm‐Free Standing in Individuals With Spinal Cord Injury: A Feasibility Study , 2009, Neuromodulation : journal of the International Neuromodulation Society.

[35]  T. Bajd,et al.  Gait restoration in paraplegic patients: a feasibility demonstration using multichannel surface electrode FES. , 1983, Journal of rehabilitation R&D.

[36]  A. Botter,et al.  Atlas of the muscle motor points for the lower limb: implications for electrical stimulation procedures and electrode positioning , 2011, European Journal of Applied Physiology.

[37]  E. Marsolais,et al.  Functional electrical stimulation for walking in paraplegia. , 1987, The Journal of bone and joint surgery. American volume.

[38]  Ronald J. Triolo,et al.  Restoration of stance phase knee flexion during walking after spinal cord injury using a variable impedance orthosis , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[39]  José Luis Pons Rovira,et al.  A novel FES control paradigm based on muscle synergies for postural rehabilitation therapy with hybrid exoskeletons , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[40]  S A Binder-Macleod,et al.  Muscle fatigue: clinical implications for fatigue assessment and neuromuscular electrical stimulation. , 1993, Physical therapy.

[41]  M Goldfarb,et al.  Design of a controlled-brake orthosis for FES-aided gait. , 1996, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[42]  Jose L Pons,et al.  A comparison of customized strategies to manage muscle fatigue in isometric artificially elicited muscle contractions for incomplete SCI subjects , 2013 .

[43]  A. Esquenazi,et al.  The ReWalk Powered Exoskeleton to Restore Ambulatory Function to Individuals with Thoracic-Level Motor-Complete Spinal Cord Injury , 2012, American journal of physical medicine & rehabilitation.

[44]  M R Popovic,et al.  Surface-stimulation technology for grasping and walking neuroprosthesis. , 2001, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[45]  Rozita Jailani,et al.  Identification of active properties of knee joint using GA optimization , 2009 .

[46]  R. J. Jefferson,et al.  A comparative trial of two walking systems for paralysed people , 1991, Paraplegia.

[47]  E. Marsolais,et al.  Walking with a hybrid orthosis system , 1999, Spinal Cord.

[48]  G M Davis,et al.  Benefits of FES gait in a spinal cord injured population , 2007, Spinal Cord.

[49]  Cheryl L. Hubley-Kozey,et al.  Effect of a high intensity quadriceps fatigue protocol on knee joint mechanics and muscle activation during gait in young adults , 2012, European Journal of Applied Physiology.

[50]  Martin Buss,et al.  Towards a Hybrid Motor Neural Prosthesis for Gait Rehabilitation: A Project Description , 2005 .

[51]  Antonio J. del Ama,et al.  Hybrid FES-robot cooperative control of ambulatory gait rehabilitation exoskeleton , 2014, Journal of NeuroEngineering and Rehabilitation.

[52]  Strahinja Dosen,et al.  Neural prostheses for walking restoration , 2008 .

[53]  A. J. del-Ama,et al.  Review of hybrid exoskeletons to restore gait following spinal cord injury. , 2012, Journal of rehabilitation research and development.

[54]  G M Davis,et al.  Functional outcomes attained by T9-12 paraplegic patients with the walkabout and the isocentric reciprocal gait orthoses. , 1997, Archives of physical medicine and rehabilitation.

[55]  D. Popović,et al.  Distributed low‐frequency functional electrical stimulation delays muscle fatigue compared to conventional stimulation , 2010, Muscle & nerve.

[56]  Nitin Sharma,et al.  A novel modulation strategy to increase stimulation duration in neuromuscular electrical stimulation , 2011, Muscle & nerve.

[57]  C. Wolfson,et al.  Reliability, validity, and applicability of the Quebec User Evaluation of Satisfaction with assistive Technology (QUEST 2.0) for adults with multiple sclerosis , 2002, Disability and rehabilitation.

[58]  Hugh Herr,et al.  Exoskeletons and orthoses: classification, design challenges and future directions , 2009, Journal of NeuroEngineering and Rehabilitation.

[59]  Jonathan C. Jarvis,et al.  A nonlinear approach to modeling of electrically stimulated skeletal muscle , 2001, IEEE Transactions on Biomedical Engineering.

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

[61]  G. Dudley,et al.  Effects of electrical stimulation parameters on fatigue in skeletal muscle. , 2009, The Journal of orthopaedic and sports physical therapy.

[62]  J P Paul,et al.  Hybrid FES orthosis incorporating closed loop control and sensory feedback. , 1988, Journal of biomedical engineering.

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

[64]  P H Veltink,et al.  Fatigue of intermittently stimulated paralyzed human quadriceps during imposed cyclical lower leg movements. , 1993, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[65]  J. Abbas,et al.  Adaptive control of cyclic movements as muscles fatigue using functional neuromuscular stimulation , 1999, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[66]  Scott Tashman,et al.  Development of hybrid orthosis for standing, walking, and stair climbing after spinal cord injury. , 2009, Journal of rehabilitation research and development.

[67]  A.G. Alleyne,et al.  A survey of iterative learning control , 2006, IEEE Control Systems.