Neuro-Robotics pp 379-403 | Cite as

Home-Based Rehabilitation: Enabling Frequent and Effective Training

Part of the Trends in Augmentation of Human Performance book series (TAHP, volume 2)


Rehabilitation studies have recently demonstrated that the amount of time spent training is one of the most important factors in one’s ability to regain motor control. The methods employed need to be effective, but individuals need to spend significant amounts of time retraining. One of the most effective ways to enable more training time is for rehabilitation to occur in one’s home so individuals have adequate access to it and there is no cost associated with traveling to the clinic. There are several challenges that need to be overcome to make home rehabilitation more common; for example adapting the methods from the clinical setting to the home setting, ensuring safety, and providing motivation. This chapter outlines existing technologies for upper and lower limb rehabilitation and how they could be adapted for use in one’s home. Although many types of disabilities would benefit from home-based rehabilitation, this discussion will focus on traumatic brain injuries, specifically stroke related. Many of the methods that could be used at home for stroke would also have application for helping in other circumstances.


Home-based rehabilitation Low-cost therapy Stroke rehabilitation Robotic therapy Upper-limb Lower-limb 


  1. 1.
    Huang V, Krakauer J (2009) Robotic neurorehabilitation: a computational motor learning perspective. J Neuroeng Rehabil 6(1):5PubMedCentralPubMedGoogle Scholar
  2. 2.
    Tyson S, Turner G (2000) Discharge and follow-up for people with stroke: what happens and why. Clin Rehabil 14(4):381–392PubMedGoogle Scholar
  3. 3.
    Gregory P, Edwards L, Faurot K, Williams S, Felix A (2010) Patient preferences for stroke rehabilitation. Top Stroke Rehabil 17(5):394–400PubMedGoogle Scholar
  4. 4.
    Merians AS, Jack D, Boian R, Tremaine M, Burdea GC, Adamovich SV, Recce M, Poizner H (2002) Virtual reality-augmented rehabilitation for patients following stroke. Phys Ther 82(9):898–915PubMedGoogle Scholar
  5. 5.
    Legg L, Langhorne P (2004) Rehabilitation therapy services for stroke patients living at home: systematic review of randomised trials. Lancet 363:352–356PubMedGoogle Scholar
  6. 6.
    Ryan T, Enderby P, Rigby AS (2006) A randomized controlled trial to evaluate intensity of community-based rehabilitation provision following stroke or hip fracture in old age. Clin Rehabil 20(2):123–131PubMedGoogle Scholar
  7. 7.
    Corrigan J (1994) Community integration following traumatic brain injury. NeuroRehabilitation 4(2):109–121PubMedGoogle Scholar
  8. 8.
    Benson DM, Elbaum J (2007) Long-term challenges. In: Elbaum J, Benson DM (eds) Acquired brain injury. Springer, New York, pp 286–292Google Scholar
  9. 9.
    Schweighofer N, Han CE, Wolf SL, Arbib MA, Winstein CJ (2009) 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 89(12):1327–1336PubMedCentralPubMedGoogle Scholar
  10. 10.
    Fluet M-C, Lambercy O, Gassert R (2011) Upper limb assessment using a virtual peg insertion test. In: Proceedings of the IEEE international conference on rehabilitation robotics, Zurich, pp 192–197Google Scholar
  11. 11.
    Kollen BJ, Lennon S, Lyons B, Wheatley-Smith L, Scheper M, Buurke JH, Halfens J, Geurts AC, Kwakkel G (2009) The effectiveness of the bobath concept in stroke rehabilitation what is the evidence? Stroke 40(4):e89–e97PubMedGoogle Scholar
  12. 12.
    Kwakkel G, Kollen BJ, Krebs HI (2008) Effects of robot-assisted therapy on upper limb recovery after stroke: a systematic review. Neurorehabil Neural Repair 22(2):111–121PubMedCentralPubMedGoogle Scholar
  13. 13.
    Marchal-Crespo L, Reinkensmeyer D (2009) Review of control strategies for robotic movement training after neurologic injury. J Neuroeng Rehabil 6(1):20PubMedCentralPubMedGoogle Scholar
  14. 14.
    Krebs HI, Hogan N, Aisen ML, Volpe BT (1998) Robot-aided neurorehabilitation. IEEE Trans Rehabil Eng 6:75–87PubMedCentralPubMedGoogle Scholar
  15. 15.
    Trafton A (2010) Robotic therapy helps stroke patients regain function. Accessed 4 Apr 2013
  16. 16.
    Lloyd-Jones D, Adams RJ, Brown TM, Carnethon M, Dai S, De Simone G, Ferguson TB, Ford E, Furie K, Gillespie C et al (2010) Heart disease and stroke statistics–2010 update a report from the american heart association. Circulation 121(7):e46–e215PubMedGoogle Scholar
  17. 17.
    Association AH et al (2005) Heart disease and stroke statistics–2005 update. American Heart Association, Dallas. This is an informative list of recent stroke statistics on incidence, prevalence, and mortality in the United States, 2004Google Scholar
  18. 18.
    Faul M, Xu L, Wald M, Coronado V (2010) Traumatic brain injury in the united states: emergency department visits, hospitalizations and deaths 2002–2006. Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, AtlantaGoogle Scholar
  19. 19.
    Selassie AW, Zaloshnja E, Langlois JA, Miller T, Jones P, Steiner C (2008) Incidence of long-term disability following traumatic brain injury hospitalization, united states, 2003. J Head Trauma Rehabil 23(2):123–131PubMedGoogle Scholar
  20. 20.
    Zaloshnja E, Miller T, Langlois JA, Selassie AW (2008) Prevalence of long-term disability from traumatic brain injury in the civilian population of the united states, 2005. J Head Trauma Rehabil 23(6):394–400PubMedGoogle Scholar
  21. 21.
    Corrigan JD, Selassie AW, Orman JAL (2010) The epidemiology of traumatic brain injury. J Head Trauma Rehabil 25(2):72–80PubMedGoogle Scholar
  22. 22.
    Bobath B (1970) Adult hemiplegia: evaluation and treatment. Heinemann Medical Books, LondonGoogle Scholar
  23. 23.
    Knott M, Voss D (1968) Proprioceptive neuromuscular facilitation: patterns and techniques, 2nd edn. Harper & Row, New YorkGoogle Scholar
  24. 24.
    Oden R (1918) Systematic therapeutic exercises in the management of the paralyses in hemiplegia. JAMA 23:828–833Google Scholar
  25. 25.
    Taub E, Uswatte G, Pidikiti R (1999) Constraint-induced movement therapy: a new family of techniques with broad application to physical rehabilitation–a clinical review. J Rehabil Res 36(3):237–251Google Scholar
  26. 26.
    Wolf SL, Winstein CJ, Miller JP, Taub E, Uswatte G, Morris D, Giuliani C, Light KE, Nichols-Larsen D (2006) Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial. JAMA 296(17):2095–2104PubMedGoogle Scholar
  27. 27.
    Lacquaniti F, Maioli C (1992) Distributed control of limb position and force. In: Stelmach GE, Requin J (ed) Tutorials in motor behavior II. North-Holland, Amsterdam/ New York/Distributors for the U.S. and Canada, Elsevier Science, New York, pp 31–54Google Scholar
  28. 28.
    Karniel A, Meir R, Inbar GF (1999) Exploiting the virtue of redundancy. In: International joint conference on neural networks, Washington, DCGoogle Scholar
  29. 29.
    Glynn S, Fekieta R, Henning R (2001) Use of force-feedback joysticks to promote teamwork in virtual teleoperation. In: Virtual teleoperation proceedings of the human factors and ergonomics society 45th annual meeting, Minneapolis/St. PaulGoogle Scholar
  30. 30.
    Shergill SS, Bays PM, Frith CD, Wolpert DM (2003) Two eyes for an eye: the neuroscience of force escalation. Science 301:187PubMedGoogle Scholar
  31. 31.
    Valles N, Reed KB, To know your own strength: overriding natural force attenuation. IEEE Trans Haptics. doi:10.1109/TOH.2013.55Google Scholar
  32. 32.
    Pan P, Lynch KM, Peshkin MA, Colgate JE (2004) Static single-arm force generation with kinematic constraints. In: Proceedings of the IEEE international conference on robotics and automation ICRA ’04, New Orleans, vol 3, pp 2794–2800Google Scholar
  33. 33.
    Reed KB, Peshkin MA, Hartmann MJ, Grabowecky M, Patton J, Vishton PM (2006) Haptically linked dyads: are two motor-control systems better than one? Psychol Sci 17(5):365–366PubMedGoogle Scholar
  34. 34.
    Reed KB, Peshkin MA (2008) Physical collaboration of human-human and human-robot teams. IEEE Trans Haptics 1(2):108–120Google Scholar
  35. 35.
    Krebs H, Ferraro M, Buerger S, Newbery M, Makiyama A, Sandmann M, Lynch D, Volpe B, Hogan N (2004) Rehabilitation robotics: pilot trial of a spatial extension for mit-manus. J Neuroeng Rehabil 1(1):5PubMedCentralPubMedGoogle Scholar
  36. 36.
    Timmermans A, Seelen H, Willmann R, Kingma H (2009) Technology-assisted training of arm-hand skills in stroke: concepts on reacquisition of motor control and therapist guidelines for rehabilitation technology design. J Neuroeng Rehabil 6(1). doi:10.1186/1743-0003-6-1Google Scholar
  37. 37.
    Kahn L, Zygman M, Rymer WZ, Reinkensmeyer D (2006) Robot-assisted reaching exercise promotes arm movement recovery in chronic hemiparetic stroke: a randomized controlled pilot study. J Neuroeng Rehabil 3(1):12PubMedCentralPubMedGoogle Scholar
  38. 38.
    Liepert J, Uhde I, Gräf S, Leidner O, Weiller C (2001) Motor cortex plasticity during forced-use therapy in stroke patients: a preliminary study. J Neurol 248:315–321PubMedGoogle Scholar
  39. 39.
    Wittenberg GF, Chen R, Ishii K, Bushara KO, Taub E, Gerber LH, Hallett M, Cohen LG (2003) Constraint-induced therapy in stroke: magnetic-stimulation motor maps and cerebral activation. Neurorehabil Neural Repair 17(1):48–57PubMedGoogle Scholar
  40. 40.
    Schmidt RA, Bjork RA (1992) New conceptualizations of practice: common principles in three paradigms suggest new concepts for training. Psychol Sci 3(4):207–217Google Scholar
  41. 41.
    Reed KB (2007) Understanding the haptic interactions of working together. Ph.D. thesis, Northwestern UniversityGoogle Scholar
  42. 42.
    Patton JL, Stoykov ME, Kovic M, Mussa-Ivaldi FA (2006) Evaluation of robotic training forces that either enhance or reduce error in chronic hemiparetic stroke survivors. Exp Brain Res 168:368–383PubMedGoogle Scholar
  43. 43.
    Smith MA, Ghazizadeh A, Shadmehr R (2006) Interacting adaptive processes with different timescales underlie short-term motor learning. PLoS Biol 4(6):e179PubMedCentralPubMedGoogle Scholar
  44. 44.
    Wolpert DM, Diedrichsen J, Flanagan JR (2011) Principles of sensorimotor learning. Nat Rev Neurosci 12(12):739–751PubMedGoogle Scholar
  45. 45.
    Abe M, Schambra H, Wassermann EM, Luckenbaugh D, Schweighofer N, Cohen LG (2011) Reward improves long-term retention of a motor memory through induction of offline memory gains. Curr Biol 21(7):557–562PubMedCentralPubMedGoogle Scholar
  46. 46.
    Huang VS, Haith A, Mazzoni P, Krakauer JW (2011) Rethinking motor learning and savings in adaptation paradigms: model-free memory for successful actions combines with internal models. Neuron 70(4):787–801PubMedCentralPubMedGoogle Scholar
  47. 47.
    Holden MK, Dyar TA, Dayan-Cimadoro L (2007) Telerehabilitation using a virtual environment improves upper extremity function in patients with stroke. IEEE Trans Neural Syst Rehabil Eng 15(1):36–42PubMedGoogle Scholar
  48. 48.
    Weiss P, Rand D, Katz N, Kizony R (2004) Video capture virtual reality as a flexible and effective rehabilitation tool. J Neuroeng Rehabil 1(1):12PubMedCentralPubMedGoogle Scholar
  49. 49.
    Henderson A, Korner-Bitensky N, Levin M (2007) Virtual reality in stroke rehabilitation: a systematic review of its effectiveness for upper limb motor recovery. Top Stroke Rehabil 14(2):52–61PubMedGoogle Scholar
  50. 50.
    Cameirão MS, Bermudez i Badia S, Oller ED, Verschure PF (2008) Using a multi-task adaptive vr system for upper limb rehabilitation in the acute phase of stroke. In: Virtual rehabilitation, Vancouver. IEEE, pp 2–7Google Scholar
  51. 51.
    Broeren J, Sunnerhagen KS, Rydmark M (2007) A kinematic analysis of a haptic handheld stylus in a virtual environment: a study in healthy subjects. J Neuroeng Rehabil 4(1):13PubMedCentralPubMedGoogle Scholar
  52. 52.
    Bouzit M, Burdea G, Popescu G, Boian R (2002) The rutgers master II-new design force-feedback glove. IEEE/ASME Trans Mechatron 7(2):256–263Google Scholar
  53. 53.
    Sanchez RJ, Liu J, Rao S, Shah P, Smith R, Rahman T, Cramer SC, Bobrow JE, Reinkensmeyer DJ (2006) Automating arm movement training following severe stroke: functional exercises with quantitative feedback in a gravity-reduced environment. IEEE Trans Neural Syst Rehabil Eng 14:378–389PubMedGoogle Scholar
  54. 54.
    Housman SJ, Scott KM, Reinkensmeyer DJ (2009) A randomized controlled trial of gravity-supported, computer-enhanced arm exercise for individuals with severe hemiparesis. Neurorehabil Neural Repair 23(5):505–514PubMedGoogle Scholar
  55. 55.
    Rotella MF, Guerin K, He X, Okamura AM (2012) Hapi bands: a haptic augmented posture interface. In: 2012 IEEE haptics symposium (HAPTICS), Vancouver. IEEE, pp 163–170Google Scholar
  56. 56.
    Kuchenbecker KJ, Gurari N, Okamura AM (2007) Effects of visual and proprioceptive motion feedback on human control of targeted movement. In: IEEE 10th international conference on rehabilitation robotics (ICORR 2007), Noordwijk. IEEE, pp 513–524Google Scholar
  57. 57.
    Zheng H, Davies R, Zhou H, Hammerton J, Mawson SJ, Ware PM, Black ND, Eccleston C, Hu H, Stone T, Mountain GA, Harris ND (2006) Smart project: application of emerging information and communication technology to homebased rehabilitation for stroke patients. Int J Disabil Human Dev Spec Issue Adv Virtual Real Ther Rehabil 5(3):271–276Google Scholar
  58. 58.
    Reinkensmeyer DJ, Pang CT, Nessler JA, Painter CC (2001) Java therapy: web-based robotic rehabilitation. Integr Assist Technol Inf Age 9:66–71Google Scholar
  59. 59.
    Feng X, Johnson M, Johnson L, Winters J (2005) A suite of computer-assisted techniques for assessing upper-extremity motor impairments. Conf Proc IEEE Eng Med Biol Soc 7:6867–6870PubMedGoogle Scholar
  60. 60.
    Johnson M, Feng X, Johnson L, Winters J (2007) Potential of a suite of robot/computer-assisted motivating systems for personalized, home-based, stroke rehabilitation. J Neuroeng Rehabil 4(1):6PubMedCentralPubMedGoogle Scholar
  61. 61.
    Johnson M, Van der Loos H, Burgar C, Shor P, Leifer L (2005) Experimental results using force-feedback cueing in robot-assisted stroke therapy. IEEE Trans Neural Syst Rehabil Eng 13:335–348PubMedGoogle Scholar
  62. 62.
    Johnson M, Ramachandran B, Paranjape R, Kosasih J (2006) Feasibility study of theradrive: a low-cost game-based environment for the delivery of upper arm stroke therapy. Proc IEEE Eng Med Biol Soc 1:695–698Google Scholar
  63. 63.
    Westhoff T, Schmidt S, Gross V, Joppke M, Zidek W, der Giet MV, Dimeo F (2008) The cardiovascular effects of upper-limb aerobic exercise in hypertensive patients. J Hypertens 26:1336–1342PubMedGoogle Scholar
  64. 64.
    Diserens K, Perret N, Chatelain S, Bashir S, Ruegg D, Vuadens P, Vingerhoets F (2007) The effect of repetitive arm cycling on post stroke spasticity and motor control: repetitive arm cycling and spasticity. J Neurol Sci 253(3):18–24PubMedGoogle Scholar
  65. 65.
    Zehr EP, Loadman P, Hundza SR (2012) Neural control of rhythmic arm cycling after stroke. J Neurophysiol 108:891–905PubMedCentralPubMedGoogle Scholar
  66. 66.
    Burgar C, Lum P, Shor P, Van der Loos H (2000) Development of robots for rehabilitation therapy: the Palo Alto VA/Stanford experience. J Rehabil Res Dev 37:663–674PubMedGoogle Scholar
  67. 67.
    Wolf SL, LeCraw DE, Barton LA (1989) Comparison of motor copy and targeted biofeedback training techniques for restitution of upper extremity function among patients with neurologic disorders. Phys Ther 69(9):719–735PubMedGoogle Scholar
  68. 68.
    Hesse S, Schulte-Tigges G, Konrad M, Bardeleben A, Werner C (2003) Robot-assisted arm trainer for the passive and active practice of bilateral forearm and wrist movements in hemiparetic subjects. Arch Phys Med Rehabil 84(6):915–920PubMedGoogle Scholar
  69. 69.
    Yang C, Lin K, Chen H, Wu C, Chen C (2012) Pilot comparative study of unilateral and bilateral robotassisted training on upper-extremity performance in patients with stroke. Am J Occup Ther 66(2):198–206PubMedGoogle Scholar
  70. 70.
    Whitall J, Waller S, Silver K, Macko R (2000) Repetitive bilateral arm training with rhythmic auditory cueing improves motor function in chronic hemiparetic stroke. Stroke 31(10):2390–2395PubMedGoogle Scholar
  71. 71.
    Whitall J, Waller S, Sorkin J, Forrester L, Macko R, Hanley D, Goldberg A, Luft A (2011) Bilateral and unilateral arm training improve motor function through differing neuroplastic mechanisms: a single-blinded randomized controlled trial. Neurorehabil Neural Repair 25(2):118–129PubMedCentralPubMedGoogle Scholar
  72. 72.
    Hesse S, Werner C, Pohl M, Mehrholz J, Puzich U, Krebs HI (2008) Mechanical arm trainer for the treatment of the severely affected arm after a stroke: a single-blinded randomized trial in two centers. Am J Phys Med Rehabil 87(10):779–788PubMedGoogle Scholar
  73. 73.
    Jordan K, Sampson M, Hijmans J, King M, Hale L (2011) Imable system for upper limb stroke rehabilitation. In: 2011 international conference on virtual rehabilitation (ICVR), Zurich, June 2011, pp 1–2Google Scholar
  74. 74.
    Malabet HG, Robles RA, Reed KB (2010) Symmetric motions for bimanual rehabilitation. In: Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS), Taipei, pp 5133–5138Google Scholar
  75. 75.
    McAmis S, Reed KB (2011) Symmetry modes and stiffnesses for bimanual rehabilitation. In: Proceedings of the IEEE international conference on rehabilitation robotics, Zurich, June 2011, pp 1106–1111Google Scholar
  76. 76.
    McAmis S, Reed KB (2012) Simultaneous perception of forces and motions using bimanual interactions. IEEE Trans Haptics 5(3):220–230Google Scholar
  77. 77.
    McAmis S, Reed KB (2013) Design and analysis of a compliant bimanual rehabilitation device. In: Proceedings of the IEEE international conference on rehabilitation robotics, Seattle, June 2013Google Scholar
  78. 78.
    McAmis S, Reed KB (2013) Effects of compliant coupling on cooperative and bimanual task performance. J Rehabil Robot 1(2):99–108.Google Scholar
  79. 79.
    Brandstater M, de Bruin H, Gowland C, Clark B (1983) Hemiplegic gait: analysis of temporal variables. Arch Phys Med Rehabil 64:583–587PubMedGoogle Scholar
  80. 80.
    Wall J, Turnbull G (1986) Gait asymmetries in residual hemiplegia. Arch Phys Med Rehabil 67:550–553PubMedGoogle Scholar
  81. 81.
    Belda-Lois JM, del Homo M, Bermejo-Bosch I, Moreno JC, Pons J, Farina D, Losa M, Molinari M, Tamburella F, Ramos A, Caria A, Solis-Escalante T, Brunner C, Rea M (2011) Rehabilitation of gait after stroke: a review towards a top-down approach. J Neuroeng Rehabil 8:66PubMedCentralPubMedGoogle Scholar
  82. 82.
    Teixeira-Salmela L, Nadeau S, Mcbride I, Olney S (2001) Effects of muscle strengthening and physical conditioning training on temporal kinematic and kinetic variables in gait stroke survivors. J Rehabil Med 33:53–60PubMedGoogle Scholar
  83. 83.
    Teixeira-Salmela L, Olney SJ, Nadeau S, Brouwer B (1999) Muscle strengthening and physical conditioning to reduce impairment and disability in chronic stroke survivors. Arch Phys Med Rehabil 80(10):1211–1218PubMedGoogle Scholar
  84. 84.
    Stern P, McDowell F, Miller J, Robinson M (1970) Effects of facilitation exercise techniques in stroke rehabilitation. Arch Phys Med Rehabil 51:526–31PubMedGoogle Scholar
  85. 85.
    Lennon S (1996) The bobath concept: a critical review of the theoretical assumptions that guide physiotherapy practice in stroke rehabilitation. Phys Ther Rev 1:35–45Google Scholar
  86. 86.
    Perfetti C (2001) L’exercice Thérapeutique Cognitif Pour La Rééducation Du Patient Hémiplégique. MassonGoogle Scholar
  87. 87.
    Carr JH, Shepherd RB (2003) Stroke rehabilitation: guidelines for exercice and training to optimiza motor skill, 1st edn. Elsevier Health Sciences. Butterworth-HeinemannGoogle Scholar
  88. 88.
    Hesse S, Bertelt C, Jahnke M, Schaffrin A, Baake P, Malezic M, Mauritz KH (1995) Treadmill training with partial body weight support compared with physiotherapy in nonambulatory hemiparetic patients. Stroke 26:976–81PubMedGoogle Scholar
  89. 89.
    Bates B, Choi J, Duncan P, Glasberg J, Graham G, Katz R, Lamberty K, Reker D, Zorowitz R (2005) Veterans affairs/department of defense clinical practice guideline for the management of adult stroke rehabilitation care. Stroke 36:2049–2056PubMedGoogle Scholar
  90. 90.
    States R, Salem Y, Pappas E (2009) Overground gait training for individuals with chronic stroke: a cochrane systematic review. J Neurol 33:179–86Google Scholar
  91. 91.
    Moseley A, Stark A, Cameron I, Pollock A (2005) Treadmill training and body weight support for walking after stroke. Cochrane Database Syst Rev 19.
  92. 92.
    Jette D, Latham N, Smout R, Gassaway J, Slavin M, Horn S (2005) Physical therapy interventions for patients with stroke in inpatient rehabilitation facilities. Phys Ther 85:238–248PubMedGoogle Scholar
  93. 93.
    Carrillo-de-la-Pena MT et al (2008) Equivalent is not equal: primary motor cortex (mi) activation during motor imagery and execution of sequential movements. Brain Res 1226(0):134–143Google Scholar
  94. 94.
    Dunsky A, Dickstein R, Marcovitz E, Levy S, Deutsch J (2008) Home-based motor imagery training for gait rehabilitation of people with chronic poststroke hemiparesis. Arch Phys Med Rehab 89:1580–1588Google Scholar
  95. 95.
    Malouin F, Richards C (2010) Mental practice for relearning locomotor skills. Phys Ther 90:240–251PubMedGoogle Scholar
  96. 96.
    Dohring M, Janis J (2008) Automatic synchronization of functional electrical stimulation and robotic assisted treadmill training. IEEE Trans Neural Syst Rehabil Eng 16(3):310–313PubMedGoogle Scholar
  97. 97.
    Barbeau H, Visintin M (2003) Optimal outcomes obtained with body-weight support combined with treadmill training in stroke subjects. Arch Phys Med Rehabil 84:1458–1465PubMedGoogle Scholar
  98. 98.
    Riener R, Lunenburger L, Jezernik S, Anderschitz M, Colombo G, Dietz V (2005) Patient-cooperative strategies for robot-aided treadmill training: first experimental results. IEEE Trans Neural Syst Rehabil Eng 13(3):380–394PubMedGoogle Scholar
  99. 99.
    Bogey R, Hornby G (2007) Gait training strategies utilized in poststroke rehabilitation: are we really making a difference? Top Stroke Rehabil 14:1–8PubMedGoogle Scholar
  100. 100.
    Colombo G (2000) The lokomat: a driven ambulatory orthosis. Med Orthop Technol 6:178–181Google Scholar
  101. 101.
    Swinnen E, Duerinck S, Baeyens J, Meeusen R, Kerckhofs E (2010) Effectiveness of robot-assisted gait training in persons with spinal cord injury: a systematic review. J Rehabil 42:520–526Google Scholar
  102. 102.
    Duschau-Wicke A (2010) Path control: a method for patient-cooperative robot-aided gait rehabilitation. Trans Neural Syst Rehabil Eng 18:38–48Google Scholar
  103. 103.
    Kim S, Banala S, Brackbill E, Agrawal S, Krishnamoorthy V, Scholz J (2010) Robot-assisted modifications of gait in healthy individuals. Exp Brain 202(4):809–824Google Scholar
  104. 104.
    Monaco V, Galardi G, Jung J, Bagnato S, Boccagni C, Micera S (2009) A new robotic platform for gait rehabilitation of bedridden stroke patients. In: IEEE international conference on rehabilitation robotics, ICORR 2009, Kyoto, pp 383–388Google Scholar
  105. 105.
    Monaco V, Jung JH, Macrì G, Bagnato S, Micera S, Carrozza MC, Galardi G (2008) Robotic system for gait rehabilitation of stroke patients during the acute phase. Gerontechnology 7:2Google Scholar
  106. 106.
    Kamps A, Schule K (2005) Cyclic movement training of the lower limb in stroke rehabilitation. Neurol Rehabil 11:1–12Google Scholar
  107. 107.
    Laupheimer M, Hartel S, Schmidt S (2011) Forced exercise effects of motomed®training on parkinson’s- typical motor dysfunctions. Neurol Rehabil 17:239–246Google Scholar
  108. 108.
    Diehl W, Schüle K, Kaiser T (2008) Use of an assistive movement training apparatus in the rehabilitation of geriatric patients. NeuroGeriatrie 5(1):3–12Google Scholar
  109. 109.
    Kim SH, Reed KB (2013) Robot-assisted balance training for gait modification. In: Proceedings of the IEEE international conference on rehabilitation robotics, Seattle, June 2013Google Scholar
  110. 110.
    Sulzer J, Gordon K, Hornby TG, Peshkin M, Patton J (2009) Adaptation to knee flexion torque during gait. In: Proceedings of the IEEE international conference on rehabilitation robotics, Kyoto, pp 713–718Google Scholar
  111. 111.
    Reisman D, Wityk R, Silver K, Bastian A (2007) Locomotor adaptation on a split-belt treadmill can improve walking symmetry post-stroke. Brain 130(7):1861–1872PubMedCentralPubMedGoogle Scholar
  112. 112.
    Choi JT, Vining EPG, Reisman DS, Bastian AJ (2009) Walking flexibility after hemispherectomy: split-belt treadmill adaptation and feedback control. Brain 132:722–733PubMedCentralPubMedGoogle Scholar
  113. 113.
    Reisman DS, Wityk R, Silver K, Bastian AJ (2009) Split-belt treadmill adaptation transfers to overground walking in persons poststroke. Neurorehabil Neural Repair 23:735–744PubMedCentralPubMedGoogle Scholar
  114. 114.
    Reisman D, McLean H, Keller J, Danks K, Bastian A (2013) Repeated split-belt treadmill training improves poststroke step length asymmetry. Neurorehabilitation 27:460–468Google Scholar
  115. 115.
    Torres-Oviedo G, Bastian AJ (2010) Seeing is believing: effects of visual contextual cues on learning and transfer of locomotor adaptation. J Neurosci 30(50):17015–17022PubMedCentralPubMedGoogle Scholar
  116. 116.
    Bunday KL, Bronstein AM (2009) Locomotor adaptation and aftereffects in patients with reduced somatosensory input due to peripheral neuropathy. J Neurophysiol 102:3119–3128PubMedCentralPubMedGoogle Scholar
  117. 117.
    Handz̆ić I, Reed KB (2013) Comparison of the passive dynamics of walking on ground, tied-belt and split-belt treadmills, via the gait enhancing mobile shoe (GEMS). In: Proceedings of the IEEE international conference on rehabilitation robotics, Seattle, June 2013Google Scholar
  118. 118.
    de Groot A, Decker R, Reed KB (2009) Gait enhancing mobile shoe (GEMS) for rehabilitation. In: Proceedings of joint eurohaptics conference and symposium on haptic interfaces for virtual environment and teleoperator systems, Salt Lake City, Mar 2009, pp 190–195Google Scholar
  119. 119.
    Handz̆ić I, Barno E, Vasudevan EV, Reed KB (2011) Design and pilot study of a gait enhancing mobile shoe. J Behav Robot 2(4):193–201Google Scholar
  120. 120.
    Handz̆ić I, Reed KB (2011) Motion controlled gait enhancing mobile shoe for rehabilitation. In: Proceedings of the IEEE international conference on rehabilitation robotics, Zurich, June 2011, pp 583–588Google Scholar
  121. 121.
    Handz̆ić I, Reed K (2014) Kinetic shapes: analysis, verification, and applications. J Mech Des 136(6)Google Scholar
  122. 122.
    Gibson-Horn C (2008) Balance-based torso-weighting in a patient with ataxia and multiple sclerosis: a case report. J Neurol Phys Ther 32(3):139–146PubMedGoogle Scholar
  123. 123.
    McGeer T (1990) Passive dynamic walking. Int J Robot Res 9(2):62–82Google Scholar
  124. 124.
    Honeycutt C, Sushko J, Reed KB (2011) Asymmetric passive dynamic walker. In: Proceedings of the IEEE international conference on rehabilitation robotics, Zurich, June 2011, pp 852–857Google Scholar
  125. 125.
    Margaria R (1976) Biomechanics and energetics of muscular exercise. Clarendon, OxfordGoogle Scholar
  126. 126.
    Chen VFH (2005) Passive dynamic walking with knees: a point foot model. Master’s thesis, Massachusetts Institute of TechnologyGoogle Scholar
  127. 127.
    Sushko J, Honeycutt C, Reed KB (2012) Prosthesis design based on an asymmetric passive dynamic walker. In: Proceedings of the IEEE conference on Biorob, Roma, June 2012, pp 1116–1121Google Scholar
  128. 128.
    Handz̆ić I, Reed KB (2013) Validation of a passive dynamic walker model for human gait analysis. In: Proceedings of IEEE engineering in medicine and biology society, Osaka, pp 6945–6948Google Scholar
  129. 129.
    Gregg R, Dhaher Y, Degani A, Lynch K (2012) On the mechanics of functional asymmetry in bipedal walking. IEEE Trans Biomed Eng 59:1310–1318PubMedGoogle Scholar
  130. 130.
    Bogataj U, Gros N, Kljaji M, Malezic M (1995) The rehabilitation of gait in patients with hemiplegia: a comparison between conventional therapy and multichannel functinal electrical stimulation therapy. Phys Ther 75:490–502PubMedGoogle Scholar
  131. 131.
    Stanic U, Acimovi-Janezic R, Gros N, Trnkoczy A, Bajd T, Kljaji M (1978) Multichannel electrical stimulation for correction of hemiplegic gait. Methodology and preliminary results. Scand J Rehabil Med 10:75–92PubMedGoogle Scholar
  132. 132.
    Bogataj U, Gros N, Malezic M, Kelih B, Kljaji M, Acimovi R (1989) Restoration of gait during two to three weeks of therapy with multichannel electrical stimulation. Phys Ther 69:319–327PubMedGoogle Scholar
  133. 133.
    Ng MF, Tong RK, Li LS (2008) A pilot study of randomized clinical controlled trial of gait training in subacute stroke patients with partial body-weight support electromechanical gait trainer and functional electrical stimulation. Stroke 39:154–160PubMedGoogle Scholar
  134. 134.
    Pollock GBA, Pomeroy V, Langhorne P (2007) Physiotherapy treatment approaches for the recovery of postural control and lower limb function following stroke. Cochrane Database Syst Rev 24Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringUniversity of South FloridaTampaUSA

Personalised recommendations