Technologies and combination therapies for enhancing movement training for people with a disability

David J Reinkensmeyer, Michael L Boninger, David J Reinkensmeyer, Michael L Boninger

Abstract

There has been a dramatic increase over the last decade in research on technologies for enhancing movement training and exercise for people with a disability. This paper reviews some of the recent developments in this area, using examples from a National Science Foundation initiated study of mobility research projects in Europe to illustrate important themes and key directions for future research. This paper also reviews several recent studies aimed at combining movement training with plasticity or regeneration therapies, again drawing in part from European research examples. Such combination therapies will likely involve complex interactions with motor training that must be understood in order to achieve the goal of eliminating severe motor impairment.

Figures

Figure 1
Figure 1
The spectrum of complexity in rehabilitation theraphy technology, ranging from simple rehabilitation devices (left) to complex robotic systems (right) (courtesy of Dr. Etienne Burdet, Imperial College, London).
Figure 2
Figure 2
Example upper extremity exoskeletons with at least four degrees of freedom, including ARMIn from ETH Zurich (left, 27), the L-Exos from Scuola Superiore Sant'Anna, Pisa, Italy (middle, 28), and the Able Exoskeleton from CEA/ISIR/Haption in France (right, 29).
Figure 3
Figure 3
Conceptual diagram of competition of task-related motor circuits for new neural resources made available with a plasticity treatment. Neural resources, such as synaptic connections, are represented by blocks. Pre-injury, there are ample resources to support motor control of multiple tasks. Following a neural injury, there are fewer resources and they are disordered. Following a plasticity treatment, there are more resources, but they are still disordered. Training on motor Task A results in ordering of blocks for that task, but leaves no blocks for building a controller for Task B.

References

    1. Brewer BR, McDowell SK, Worthen-Chaudhari LC. Poststroke upper extremity rehabilitation: a review of robotic systems and clinical results. Top Stroke Rehabil. 2007;14:22–44. doi: 10.1310/tsr1406-22.
    1. Burridge JH, Hughes AM. Potential for new technologies in clinical practice. Curr Opin Neurol. 2010;23:671–677. doi: 10.1097/WCO.0b013e3283402af5.
    1. Adamovich SV, Fluet GG, Tunik E, Merians AS. Sensorimotor training in virtual reality: a review. NeuroRehabilitation. 2009;25:29–44.
    1. Hesse S, Schmidt H, Werner C. Machines to support motor rehabilitation after stroke: 10 years of experience in Berlin. J Rehabil Res Dev. 2006;43:671–678. doi: 10.1682/JRRD.2005.02.0052.
    1. Burke JW, McNeill MDJ, Charles DK, Morrow PJ, Crosbie JH, McDonough SM. Optimising engagement for stroke rehabilitation using serious games. Vis Comput. 2009;25:1085–1099. doi: 10.1007/s00371-009-0387-4.
    1. Stein RB, Everaert DG, Thompson AK, Chong SL, Whittaker M, Robertson J, Kuether G. Long-term therapeutic and orthotic effects of a foot drop stimulator on walking performance in progressive and nonprogressive neurological disorders. Neurorehabil Neural Repair. 2010;24:152–167. doi: 10.1177/1545968309347681.
    1. Patton JL, Stoykov ME, Kovic M, Mussa-Ivaldi FA. Evaluation of robotic training forces that either enhance or reduce error in chronic hemiparetic stroke survivors. Exp Brain Res. 2006;168:368–383. doi: 10.1007/s00221-005-0097-8.
    1. Lo AC, Guarino PD, Richards LG, Haselkorn JK, Wittenberg GF, Federman DG, Ringer RJ, Wagner TH, Krebs HI, Volpe BT. et al.Robot-assisted therapy for long-term upper-limb impairment after stroke. N Engl J Med. 2010;362:1772–1783. doi: 10.1056/NEJMoa0911341.
    1. Gladstone DJ, Danells CJ, Black SE. The Fugl-Meyer assessment of motor recovery after stroke: a critical review of its measurement properties. Neurorehabil Neural Repair. 2002;16:232–240. doi: 10.1177/154596802401105171.
    1. Rohrer B, Fasoli S, Krebs HI, Hughes R, Volpe B, Frontera WR, Stein J, Hogan N. Movement smoothness changes during stroke recovery. J Neurosci. 2002;22:8297–8304.
    1. Hornby TG, Campbell DD, Kahn JH, Demott T, Moore JL, Roth HR. Enhanced gait-related improvements after therapist- versus robotic-assisted locomotor training in subjects with chronic stroke: a randomized controlled study. Stroke. 2008;39:1786–1792. doi: 10.1161/STROKEAHA.107.504779.
    1. Israel JF, Campbell DD, Kahn JH, Hornby TG. Metabolic costs and muscle activity patterns during robotic- and therapist-assisted treadmill walking in individuals with incomplete spinal cord injury. Phys Ther. 2006;86:1466–1478. doi: 10.2522/ptj.20050266.
    1. Emken JL, Benitez R, Sideris A, Bobrow JE, Reinkensmeyer DJ. Motor adaptation as a greedy optimization of error and effort. J Neurophysiol. 2007;97:3997–4006. doi: 10.1152/jn.01095.2006.
    1. Cai LL, Fong AJ, Otoshi CK, Liang Y, Burdick JW, Roy RR, Edgerton VR. Implications of assist-as-needed robotic step training after a complete spinal cord injury on intrinsic strategies of motor learning. J Neurosci. 2006;26:10564–10568. doi: 10.1523/JNEUROSCI.2266-06.2006.
    1. Lewek MD, Cruz TH, Moore JL, Roth HR, Dhaher YY, Hornby TG. Allowing intralimb kinematic variability during locomotor training poststroke improves kinematic consistency: a subgroup analysis from a randomized clinical trial. Phys Ther. 2010;89:829–839.
    1. Ziegler MD, Zhong H, Roy RR, Edgerton VR. Why variability facilitates spinal learning. J Neurosci. 2010;30:10720–10726. doi: 10.1523/JNEUROSCI.1938-10.2010.
    1. Housman SJ, Scott KM, Reinkensmeyer DJ. A randomized controlled trial of gravity-supported, computer-enhanced arm exercise for individuals with severe hemiparesis. Neurorehabil Neural Repair. 2009;23:505–514. doi: 10.1177/1545968308331148.
    1. Reinkensmeyer DJ, Housman SJ. "If I can't do it once, why do it a hundred times?": connecting volition to movement success in a virtual environment motivates people to exercise the arm after stroke. Proc Virtual Rehab Conference. 2007;2007:44–48.
    1. Hesse S, Werner C, Pohl M, Rueckriem S, Mehrholz J, Lingnau ML. Computerized arm training improves the motor control of the severely affected arm after stroke: a single-blinded randomized trial in two centers. Stroke. 2005;36:1960–1966. doi: 10.1161/01.STR.0000177865.37334.ce. (Epub 2005 Aug 1918)
    1. Werner C, Von Frankenberg S, Treig T, Konrad M, Hesse S. Treadmill training with partial body weight support and an electromechanical gait trainer for restoration of gait in subacute stroke patients: a randomized crossover study. Stroke. 2002;33:2895–2901. doi: 10.1161/01.STR.0000035734.61539.F6.
    1. Rosati G, Gallina P, Masiero S. Design, implementation and clinical tests of a wire-based robot for neurorehabilitation. IEEE Trans Neural Syst Rehabil Eng. 2007;15:560–569.
    1. Masiero S, Celia A, Rosati G, Armani M. Robotic-assisted rehabilitation of the upper limb after acute stroke. Arch Phys Med Rehabil. 2007;88:142–149. doi: 10.1016/j.apmr.2006.10.032.
    1. Dovat L, Lambercy O, Gassert R, Maeder T, Milner T, Leong TC, Burdet E. HandCARE: a cable-actuated rehabilitation system to train hand function after stroke. IEEE Trans Neural Syst Rehabil Eng. 2008;16:582–591.
    1. Stienen AHA, Hekman EEG, Van der Helm FCT, Prange GB, Jannink MJA, Aalsma AMM, Van der Kooij H. Freebal: dedicated gravity compensation for the upper extremities. IEEE Int Conf Rehabil Robot. 2007;2007:804–808.
    1. Willmann RD, Lanfermann G, Saini P, Timmermans A, te Vrugt J, Winter S. Home stroke rehabilitation for the upper limbs. Proc IEEE Eng Med Biol Soc. 2007;2007:4015–4018.
    1. Burns A, Greene BR, McGrath MJ, O'Shea TJ, Kuris B, Ayer SM, Stroiescu F, Cionca V. SHIMMER™ - A wireless sensor platform for noninvasive biomedical research. IEEE Sens J. 2010;10:1527–1534.
    1. Nef T, Guidali M, Riener R. ARMin III - Arm therapy exoskeleton with an ergonomic shoulder actuation. Appl Bion Biomech. 2009;6:127–142. doi: 10.1080/11762320902840179.
    1. Frisoli A, Bergamasco M, Carboncini MC, Rossi B. Robotic assisted rehabilitation in virtual reality with the L-EXOS. Stud Health Technol Inform. 2009;145:40–54.
    1. Jarrasse N, Tagliabue M, Robertson JVG, Maiza A, Crocher V, Roby-Brami A, Morel G. A methodology to quantify alterations in human upper limb movement during co-manipulation with an exoskeleton. IEEE Trans Neural Syst Rehab Eng. 2010;18:389–397.
    1. Jarrasse N, Morel G. A methodology to design kinematics of fixations between an orthosis and a human member. IEEE/ASME International Conference on Advanced Intelligent Mechatronics. 2009;2009:958–1963.
    1. Stienen A, Hekman E, van der Helm F, van der Kooij H. Self-aligning exoskeleton axes through decoupling of joint rotations and translations. IEEE T Robot. 2009;25(3):628–633.
    1. Schmidt H, Sorowka D, Hesse S, Bernhardt R. Robotic walking simulator for neurological gait rehabilitation. Proceedings of the Second Joint EMBS/BMES Conference. 2002;3:2356–2357.
    1. Schmidt H, Hesse S, Bernhardt R, Kruger J. HapticWalker--a novel haptic foot device. ACM Trans Appl Percept (TAP) 2005;2:166–180. doi: 10.1145/1060581.1060589.
    1. Surdilovic D, Zhang J, Bernhardt R. STRING-MAN: Wire-robot technology for safe, flexible and human-friendly gait rehabilitation. IEEE Int Conf Rehabil Robot. 2007;2007:446–453.
    1. Veneman JF, Kruidhof R, Hekman EE, Ekkelenkamp R, Van Asseldonk EH, van der Kooij H. Design and evaluation of the LOPES exoskeleton robot for interactive gait rehabilitation. IEEE Trans Neural Syst Rehabil Eng. 2007;15:379–386.
    1. Stauffer Y, Allemand Y, Bouri M, Fournier J, Clavel R, Metrailler P, Brodard R, Reynard F. The WalkTrainer--a new generation of walking reeducation device combining orthoses and muscle stimulation. IEEE Trans Neural Syst Rehabil Eng. 2009;17:38–45.
    1. Burridge JH, Haugland M, Larsen B, Svaneborg N, Iversen HK, Christensen PB, Pickering RM, Sinkjaer T. Patients' perceptions of the benefits and problems of using the ActiGait implanted drop-foot stimulator. J Rehabil Med. 2008;40:873–875.
    1. Cullell A, Moreno JC, Rocon E, Forner-Cordero A, Pons JL. Biologically based design of an actuator system for a knee-ankle-foot orthosis. Mechanism and Machine Theory. 2009;44(4):860–872. doi: 10.1016/j.mechmachtheory.2008.04.001.
    1. Moreno JC, Brunetti F, Rocon E, Pons JL. Immediate effects of a controllable knee ankle foot orthosis for functional compensation of gait in patients with proximal leg weakness. Med Biol Eng Comput. 2008;46:43–53. doi: 10.1007/s11517-007-0267-x.
    1. Riener R, Lunenburger L, Jezernik S, Anderschitz M, Colombo G, Dietz V. Patient-cooperative strategies for robot-aided treadmill training: first experimental results. IEEE Trans Neural Syst Rehabil Eng. 2005;13:380–394. doi: 10.1109/TNSRE.2005.848628.
    1. Duschau-Wicke A, Caprez A, Riener R. Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training. J Neuroeng Rehabil. 2010;10:43.
    1. Duschau-Wicke A, von Zitzewitz J, Wellner M, Koenig A, Lunenburger L, Riener R. Path Control a strategy for patient-cooperative training of gait timing. Proc 7th Automed. Workshop Munich. 2007;2007:1–2.
    1. Vallery H, Duschau-Wicke A, Riener R. Hiding robot inertia using resonance. Proc IEEE Eng Med Biol Soc. 2010;1:1271–1274.
    1. Vergaro E, Casadio M, Squeri V, Giannoni P, Morasso P, Sanguineti V. Self-adaptive robot training of stroke survivors for continuous tracking movements. J Neuroeng Rehab. 2010;15:13.
    1. Koenig A, Wellner M, Koneke S, Meyer-Heim A, Lunenburger L, Riener R. Virtual gait training for children with cerebral palsy using the Lokomat gait orthosis. Stud Health Technol Inform. 2008;132:204–209.
    1. Munih M, Riener R, Colombo G, Lunenburger L, Muller F, Slater M, Mihelj M. MIMICS: Multimodal immersive motion rehabilitation of upper and lower extremities by exploiting biocooperation principles. IEEE Int Conf Rehabil Robot. 2009;2009:127–132.
    1. Collinger JL, Wang W, Vinjamuri R, Degenhart AD, Sudre GP, Boninger ML, Tyler-Kabara EC, Weber DJ. Congruent motor activity on electrocorticographic recordings during overt and observed hand movements. Proc IEEE Eng Med Biol Soc. 2011;2011 in review.
    1. Broetz D, Braun C, Weber C, Soekadar SR, Caria A, Birbaumer N. Combination of brain-computer interface training and goal-directed physical therapy in chronic stroke: a case report. Neurorehabil Neural Repair. 2010;24:674–679. doi: 10.1177/1545968310368683.
    1. Daly JJ, Cheng R, Rogers J, Litinas K, Hrovat K, Dohring M. Feasibility of a new application of noninvasive Brain Computer Interface (BCI): a case study of training for recovery of volitional motor control after stroke. J Neurol Phys Ther. 2009;33:203–211.
    1. Courtine G, Gerasimenko Y, van den Brand R, Yew A, Musienko P, Zhong H, Song B, Ao Y, Ichiyama RM, Lavrov I, Roy RR, Sofroniew MV, Edgerton VR. Transformation of nonfunctional spinal circuits into functional states after the loss of brain input. Nat Neurosci. 2009;12:333–342. doi: 10.1038/nn.2261.
    1. Hughes AM, Freeman CT, Burridge JH, Chappell PH, Lewin PL, Rogers E. Feasibility of iterative learning control mediated by functional electrical stimulation for reaching after stroke. Neurorehabil Neural Repair. 2009;23:559–568. doi: 10.1177/1545968308328718.
    1. Reinkensmeyer DJ. How to retrain movement after neurologic injury: a computational rationale for incorporating robot (or therapist) assistance. Conf Proc IEEE Eng Med Biol Soc. 2003;2003:1479–1482.
    1. Han CE, Arbib MA, Schweighofer N. Stroke rehabilitation reaches a threshold. PLoS Comput Biol. 2008;4:e1000133. doi: 10.1371/journal.pcbi.1000133.
    1. Schweighofer N, Han CE, Wolf SL, Arbib MA, Winstein CJ. A functional threshold for long-term use of hand and arm function can be determined: predictions from a computational model and supporting data from the Extremity Constraint-Induced Therapy Evaluation (EXCITE) trial. Phys Ther. 2009;89:1327–1336. doi: 10.2522/ptj.20080402.
    1. Reinkensmeyer DJ, Maier MA, Guigon E, Chan V, Akoner OM, Wolbrecht ET, Cramer SC, Bobrow JE. Do robotic and non-robotic arm movement training drive motor recovery after stroke by a common neural mechanism? experimental evidence and a computational model. Conf Proc IEEE Eng Med Biol Soc. 2009;2009:2439–2441.
    1. Reinkensmeyer DJ, Guigon E, Maier MA. A computational model of use-dependent motor recovery following stroke: optimizing corticospinal activations via reinforcement learning can explain residual capacity and other strength recovery dynamics. Neural Networks. 2012;29-30:60–69.
    1. Franklin DW, Burdet E, Tee KP, Osu R, Chew CM, Milner TE, Kawato M. CNS learns stable, accurate, and efficient movements using a simple algorithm. J Neurosci. 2008;28:11165–11173. doi: 10.1523/JNEUROSCI.3099-08.2008.
    1. Tee KP, Franklin DW, Kawato M, Milner TE, Burdet E. Concurrent adaptation of force and impedance in the redundant muscle system. Biol Cybern. 2010;102:31–44. doi: 10.1007/s00422-009-0348-z.
    1. Ambrosio F, Wolf SL, Delitto A, Fitzgerald GK, Badylak SF, Boninger ML, Russell AJ. The emerging relationship between regenerative medicine and physical therapeutics. Phys Ther. 2010;90:1807–1814. doi: 10.2522/ptj.20100030.
    1. Tetzlaff W, Fouad K, Kwon B. Be careful what you train for. Nat Neurosci. 2009;12:1077–1079. doi: 10.1038/nn0909-1077.
    1. Fawcett JW, Curt A. Damage control in the nervous system: rehabilitation in a plastic environment. Nat Med. 2009;15:735–736. doi: 10.1038/nm0709-735.
    1. García-Alías G, Barkhuysen S, Buckle M, Fawcett JW. Chondroitinase ABC treatment opens a window of opportunity for task-specific rehabilitation. Nat Neurosci. 2009;12:1145–1151. doi: 10.1038/nn.2377.
    1. Whishaw IQ, Gorny B, Sarna J. Paw and limb use in skilled and spontaneous reaching after pyramidal tract, red nucleus and combined lesions in the rat: behavioral and anatomical dissociations. Behav Brain Res. 1998;93:167–183. doi: 10.1016/S0166-4328(97)00152-6.
    1. Krajacic A, Weishaupt N, Girgis J, Tetzlaff W, Fouad K. Training-induced plasticity in rats with cervical spinal cord injury: Effects and side effects. Behav Brain Res. 2010;214:323–331. doi: 10.1016/j.bbr.2010.05.053.
    1. Girgis J, Merrett D, Kirkland S, Metz GA, Verge V, Fouad K. Reaching training in rats with spinal cord injury promotes plasticity and task specific recovery. Brain. 2007;130:2993–3003. doi: 10.1093/brain/awm245.
    1. Maier IC, Ichiyama RM, Courtine G, Schnell L, Lavrov I, Edgerton VR, Schwab ME. Differential effects of anti-Nogo-A antibody treatment and treadmill training in rats with incomplete spinal cord injury. Brain. 2009;132:1426–1440. doi: 10.1093/brain/awp085.
    1. Fang PC, Barbay S, Plautz EJ, Hoover E, Strittmatter SM, Nudo RJ. Combination of NEP 1-40 treatment and motor training enhances behavioral recovery after a focal cortical infarct in rats. Stroke. 2010;41:544–549. doi: 10.1161/STROKEAHA.109.572073.
    1. Harel NY, Song KH, Tang X, Strittmatter SM. Nogo receptor deletion and multimodal exercise improve distinct aspects of recovery in cervical spinal cord injury. J Neurotrauma. 2010;27:2055–2066. doi: 10.1089/neu.2010.1491.

Source: PubMed

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