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physiopraxis 2023; 21(09): 32-37
DOI: 10.1055/a-2122-5548
Therapie

Bewusst eingesetzt – Motorisches Lernen mit dem Therapieroboter

Martin Huber
,
Markus Wirz
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Die Robotik eröffnet neue Möglichkeiten in der motorischen Neurorehabilitation. Exoskelette unterstützen Patient*innen nach Schlaganfall beim Gehen, andere Endeffektoren trainieren den betroffenen Arm spielerisch mit Exergames. Basis für die robotergestützte Therapie ist das Motorische Lernen. Der Transfer in den Alltag zeigt allerdings noch diverse Schwächen.



Publication History

Article published online:
12 September 2023

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  • Literaturverzeichnis

  • 1 Robert Koch-Institut. Wie steht es um unsere Gesundheit? Gesundheit in Deutschland 2015. Im Internet (Stand: 07.07.2023): DOI: 10.17886/RKIPUBL-2015-003-2
  • 2 Kleynen M, Beurskens A, Olijve H. et al Application of motor learning in neurorehabilitation: a framework for health-care professionals. Physiother Theory Pract 2018; 36: 1-20 DOI: 10.1080/09593985.2018.1483987.
    CrossrefPubMedGoogle Scholar
  • 3 Winstein C, Lewthwaite R, Blanton SR. et al Infusing Motor Learning Research into Neurorehabilitation Practice: A Historical Perspective With Case Exemplar From the Accelerated Skill Acquisition Program. Journal of Neurologic Physical Therapy 2014; 38: 190-200 DOI: 10.1097/NPT.0000000000000046.
    CrossrefPubMedGoogle Scholar
  • 4 Majsak M. Concepts and Principles of Neurological Rehabilitation. In: Fell D. Lifespan Neurorehabilitation: A Patient-Centered Approach from Examination to Intervention and Outcomes. F.A. Davis 2018
    PubMedGoogle Scholar
  • 5 Huber M, Janssen C, Erzer Lüscher F. et al Motorisches Lernen in der Neuroreha. 1. Auflage. Stuttgart: Thieme; 2022
    Google Scholar
  • 6 Gassert R, Dietz V. Rehabilitation robots for the treatment of sensorimotor deficits: a neurophysiological perspective. J Neuroeng Rehabil 2018; 15: 46 DOI: 10.1186/s12984-018-0383-x.
    CrossrefPubMedGoogle Scholar
  • 7 Reinkensmeyer DJ, Marchal-Crespo L, Dietz V. Neurorehabilitation Technology. 3. Aufl. Heidelberg, Berlin: Springer; 2022
    CrossrefGoogle Scholar
  • 8 Morone G, Paolucci S, Cherubini A. et al Robot-assisted gait training for stroke patients: current state of the art and perspectives of robotics. Neuropsychiatr Dis Treat 2017; 13: 1303-1311 DOI: 10.2147/NDT.S114102.
    CrossrefPubMedGoogle Scholar
  • 9 Nadeau SE. A paradigm shift in neurorehabilitation. The Lancet Neurology 2002; 01: 126-130 DOI: 10.1016/S1474-4422(02)00044-3.
    CrossrefPubMedGoogle Scholar
  • 10 Taub E, Uswatte G. Constraint-induced movement therapy: bridging from the primate laboratory to the stroke rehabilitation laboratory. Journal of Rehabilitation Medicine 2003; 35: 34-40 DOI: 10.1080/16501960310010124.
    CrossrefPubMedGoogle Scholar
  • 11 Dietz V. Human neuronal control of automatic functional movements: interaction between central programs and afferent input. Physiol Rev 1992; 72: 33-69 DOI: 10.1152/physrev.1992.72.1.33.
    CrossrefPubMedGoogle Scholar
  • 12 Marder E, Bucher D. Central pattern generators and the control of rhythmic movements. Current Biology 2001; 11: R986-R996 DOI: 10.1016/S0960-9822(01)00581-4.
    CrossrefPubMedGoogle Scholar
  • 13 van Middendorp JJ, Goss B, Urquhart S. et al Diagnosis and Prognosis of Traumatic Spinal Cord Injury. Global Spine Journal 2011; 01: 001-007 DOI: 10.1055/s-0031-1296049.
    CrossrefPubMedGoogle Scholar
  • 14 Guadagnoli MA, Lee TD. Challenge point: a framework for conceptualizing the effects of various practice conditions in motor learning. J Mot Behav 2004; 36: 212-224 DOI: 10.3200/JMBR.36.2.212-224.
    CrossrefPubMedGoogle Scholar
  • 15 Thimabut N, Yotnuengnit P, Charoenlimprasert J. et al Effects of the Robot-Assisted Gait Training Device Plus Physiotherapy in Improving Ambulatory Functions in Patients With Subacute Stroke With Hemiplegia: An Assessor-Blinded, Randomized Controlled Trial. Archives of Physical Medicine and Rehabilitation 2022; 103: 843-850 DOI: 10.1016/j.apmr.2022.01.146.
    CrossrefPubMedGoogle Scholar
  • 16 Morone G, Cocchi I, Paolucci S. et al Robot-assisted therapy for arm recovery for stroke patients: state of the art and clinical implication. Expert Rev Med Devices 2020; 17: 223-233 DOI: 10.1080/17434440.2020.1733408.
    CrossrefPubMedGoogle Scholar
  • 17 Paolucci T, Agostini F, Mangone M. et al Robotic rehabilitation for end-effector device and botulinum toxin in upper limb rehabilitation in chronic post-stroke patients: an integrated rehabilitative approach. Neurol Sci 2021; 42: 5219-5229 DOI: 10.1007/s10072-021-05185-3.
    CrossrefPubMedGoogle Scholar
  • 18 International Industry Society in Advanced Rehabilitation Technology (iisart). Principles of New Technologies 2023. Im Internet (Stand: 23.03.2023) https://iisart.org/education/
  • 19 Brown DA, Lee TD. Designing Robots That Challenge to Optimize Motor Learning | SpringerLink. In: Neurorehabilitation Technology. Springer International Publishing 2016
    PubMedGoogle Scholar
  • 20 Krakauer JW, Carmichael ST. Broken Movement: The Neurobiology of Motor Recovery after Stroke. Cambridge, MA: MIT Press; 2022
    Google Scholar
  • 21 Mehrholz J, Pohl M, Platz T. et al Electromechanical and robot-assisted arm training for improving activities of daily living, arm function, and arm muscle strength after stroke. Cochrane Database Syst Rev 2018; 09: CD006876 DOI: 10.1002/14651858.CD006876.pub5.
    CrossrefPubMedGoogle Scholar
  • 22 Mehrholz J, Pollock A, Pohl M. et al Systematic review with network meta-analysis of randomized controlled trials of robotic-assisted arm training for improving activities of daily living and upper limb function after stroke. J Neuroeng Rehabil 2020; 17: 83 DOI: 10.1186/s12984-020-00715-0.
    CrossrefPubMedGoogle Scholar
  • 23 Dietz V, Muller R, Colombo G. Locomotor activity in spinal man: significance of afferent input from joint and load receptors. Brain 2002; 125: 2626-2634
    CrossrefPubMedGoogle Scholar
  • 24 Wirz M, Bansi J, Capecci M. et al Robotic Gait Training in Specific Neurological Conditions: Rationale and Application. In: Reinkensmeyer DJ, Marchal-Crespo L, Dietz V, Hrsg. Neurorehabilitation Technology. Cham: Springer International Publishing; 2022: 145-188
    Google Scholar
  • 25 Colombo G, Joerg M, Schreier R. et al Treadmill training of paraplegic patients using a robotic orthosis. Journal of rehabilitation research and development 2000; 37: 693-700
    PubMedGoogle Scholar
  • 26 Plaza A, Hernandez M, Puyuelo G. et al Lower-Limb Medical and Rehabilitation Exoskeletons: A Review of the Current Designs. IEEE Rev Biomed Eng 2023; 16: 278-291 DOI: 10.1109/RBME.2021.3078001.
    CrossrefPubMedGoogle Scholar
  • 27 Zbogar D, Eng JJ, Miller WC. et al Movement repetitions in physical and occupational therapy during spinal cord injury rehabilitation. Spinal Cord 2017; 55: 172-179 DOI: 10.1038/sc.2016.129.
    CrossrefPubMedGoogle Scholar
  • 28 Walker MF, Hoffmann TC, Brady MC. et al Improving the development, monitoring and reporting of stroke rehabilitation research: Consensus-based core recommendations from the Stroke Recovery and Rehabilitation Roundtable. International Journal of Stroke 2017; 12: 472-479 DOI: 10.1177/1747493017711815.
    CrossrefPubMedGoogle Scholar
  • 29 Calafiore D, Negrini F, Tottoli N. et al Efficacy of robotic exoskeleton for gait rehabilitation in patients with subacute stroke : a systematic review. Eur J Phys Rehabil Med 2022: 58 DOI: 10.23736/S1973-9087.21.06846-5
    CrossrefPubMedGoogle Scholar
  • 30 Yamamoto R, Sasaki S, Kuwahara W. et al Effect of exoskeleton-assisted Body Weight-Supported Treadmill Training on gait function for patients with chronic stroke: a scoping review. J NeuroEngineering Rehabil 2022; 19: 143 DOI: 10.1186/s12984-022-01111-6.
    CrossrefPubMedGoogle Scholar
  • 31 Mehrholz J, Thomas S, Kugler J. et al Electromechanical-assisted training for walking after stroke. Cochrane Database Syst Rev 2020; 10: CD006185 DOI: 10.1002/14651858.CD006185.pub5.
    CrossrefPubMedGoogle Scholar
  • 32 Luft A, Bastian AJ, Dietz V. Learning in the damaged brain/spinal cord : neuroplasticity. In: Neurorehabilitation Technology. Heidelberg: Springer; 2022
    Google Scholar
  • 33 Schweighofer N, Wang C Mottet D. et al Dissociating motor learning from recovery in exoskeleton training post-stroke. J Neuroeng Rehabil 2018; 15: 89 DOI: 10.1186/s12984-018-0428-1.
    CrossrefPubMedGoogle Scholar
  • 34 Hornby TG, Moore JL, Lovell L. et al Influence of skill and exercise training parameters on locomotor recovery during stroke rehabilitation. Curr Opin Neurol 2016; 29: 677-683 DOI: 10.1097/WCO.0000000000000397.
    CrossrefPubMedGoogle Scholar
  • 35 Glaister BC, Bernatz GC, Klute GK. et al Video task analysis of turning during activities of daily living. Gait & Posture 2007; 25: 289-294 DOI: 10.1016/j.gaitpost.2006.04.003.
    CrossrefPubMedGoogle Scholar
  • 36 Lo AC, Guarino PD, Richards LG. 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.
    CrossrefPubMedGoogle Scholar