Skip to main content
SpringerLink
Log in
Book cover

Digitale Transformation von Dienstleistungen im Gesundheitswesen V pp 279–294Cite as

Innovative, spielerische Therapie mit einem Roboterball bei Schlaganfallpatienten – Erfahrungen und Ergebnisse

  • Chapter
  • First Online:

  • 6726 Accesses

Zusammenfassung

Der Schlaganfall ist für die betroffenen Patienten häufig mit motorischen Einschränkungen der oberen Extremitäten verbunden. Neue Therapieverfahren können bestehende Verfahren ergänzen. Dabei wird verschiedene Hardware genutzt, um digitale Therapieinhalte umzusetzen. Ein Roboterball wurde als geeignetes Therapiemittel im Rahmen der Neurorehabilitation nach Schlaganfall erprobt und ein innovatives, spielerisch motivierendes Therapiekonzept entwickelt. In einer randomisierten, kontrollierten Cross-over-Studie konnten positive Effekte hinsichtlich der Greifkraft, unilateraler Geschicklichkeit und Gesundheitswahrnehmung gezeigt werden. Der Benefit ließ sich zum Teil auf spezifische Alltagssituationen übertragen. Der Therapieansatz ist variabel gestaltbar und bei heterogenem Schwere- und Ausprägungsgrad der bestehenden Symptomatik geeignet. Die Benutzerfreundlichkeit wurde von den Patienten als hervorragend bewertet. Das Steuerungskonzept war nachvollziehbar und der Umgang mit den verbundenen Geräten und Apps unkompliziert.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   49.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   64.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Literatur

  • Abubakar S, Isezuo S (2012) Health related quality of life of stroke survivors: experience of a stroke unit. Int J Biomed Sci 8(3):183–187

    Google Scholar 

  • Alankus G, Lazar A, May M, Kelleher C (2010) Towards customizable games for stroke rehabilitation. In: Proceedings of the twenty-eighth ACM SIGCHI conference on computer human interaction (CHI), 10–15 Apr, Atlanta

    Google Scholar 

  • Allet L, Knols RH, Shirato K, de Bruin ED et al (2010) Wearable systems for monitoring mobility-related activities in chronic disease: a systematic review. Sensors 10(10):9026–9052

    Article  Google Scholar 

  • Anguita D, Ghio A, Oneto L, Parra X, Reyes-Ortiz JL (2012) Human activity recognition on smartphones using a multiclass hardware-friendly support vector machine Ambient assisted living and home care.In: 4th International Workshop, IWAAL, Vitoria-Gasteiz, Spain, 3–5 Dec, Springer, Berlin/Heidelberg, S 216–223

    Google Scholar 

  • Banos O, Damas M, Pomares H, Prieto A, Rojas I (2012) Daily living activity recognition based on statistical feature quality group selection. Expert Syst Appl 39(9):8013–8021

    Article  Google Scholar 

  • Barker R, Brauer S (2005) Upper limb recovery after stroke: the stroke survivors’ perspective. Disabil Rehabil 27(20):1213–1223

    Article  Google Scholar 

  • Bonato P (2010) Wearable sensors and systems. From enabling technology to clinical applications. IEEE Eng Med Biol Mag 29(3):25–36

    Article  Google Scholar 

  • Broeks J, Lankhorst GJ, Rumping K, Prevo AJH (1999) The long-term outcome of arm function after stroke: results of a follow-up study. Disabil Rehabil 21(8):357–364

    Article  Google Scholar 

  • Brown M, Deitch T, O’Conor L (2013) Activity classification with smartphone data. Stanford computer science machine learning, S 1–5

    Google Scholar 

  • Burke J, McNeill MDJ, Charles DK, Morrow PJ, Crosbie JH, McDonough SM (2009) Serious games for upper limb rehabilitation following stroke. In: Proceedings of the 2009 conference in games and virtual worlds for serious applications, 23–24 Mar, Washington, DC, IEEE Computer Society, S 103–110

    Google Scholar 

  • Busch M, Schienkiewitz A, Nowossadeck E, Gößwald A (2013) Prävalenz des Schlaganfalls bei Erwachsenen im Alter von 40 bis 79 Jahren in Deutschland. Bundesgesundheitsbl Gesundheitsforsch Gesundheitsschutz 56(5–6):656–660

    Article  Google Scholar 

  • Cameirão M, Bermúdez S, Duarte E, Verschure PF (2011) Virtual reality based rehabilitation speeds up functional recovery of the upper extremities after stroke: a randomized controlled pilot study in the acute phase of stroke using the rehabilitation gaming system. Restor Neurol Neurosci 29(5):287–298

    Google Scholar 

  • Carabeo CGG, Dalida CMM, Padilla EMZ, Rodrigo MMT (2014) Stroke patient rehabilitation a pilot study of an android-based game. Simul Gaming 45(2):151–166

    Article  Google Scholar 

  • Colombo R, Pisano F, Mazzone A, Delconte C, Micera S, Carrozza MC, Dario P, Minuco G (2007) Design strategies to improve patient motivation during robot-aided rehabilitation. J Neuroeng Rehabil 4(1):1–12

    Article  Google Scholar 

  • Deutsche Gesellschaft für Neurorehabilitation (DGNR) (2009) S2e-Leitlinien der DGNR zur motorischen Rehabilitation der oberen Extremität nach Schlaganfall. Neurol Rehabil 15:71–160

    Google Scholar 

  • Duncan PW, Samsa GP, Weinberger M, Goldstein LB, Bonito A, Witter DM, Enarson C, Matchar D (1997) Health status of individuals with mild stroke. Stroke 28(4):740–745

    Article  Google Scholar 

  • Durham K, Van Vliet PM, Badger F, Sackley C (2009) Use of information feedback and attentional focus of feedback in treating the person with a hemiplegic arm. Physiother Res Int 14(2):77–90

    Article  Google Scholar 

  • Fasoli SE, Trombly CA, Tickle-Degnen L, Verfaellie MH (2002) Effect of instructions on functional reach in persons with and without cerebrovascular accident. Am J Occup Ther 56(4):380–390

    Article  Google Scholar 

  • Ferreira C, Guimarães V, Santos A, Sousa I (2014) Gamification of stroke rehabilitation exercises using a smartphone. In: Proceedings of the 8th international conference on pervasive computing technologies for healthcare. Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering (ICST), 20–23 May, Oldenburg, S 282–285

    Google Scholar 

  • Flores E, Tobon G, Cavallaro E, Cavallaro FI, Perry JC, Keller T (2008) Improving patient motivation in game development for motor deficit rehabilitation. In: Proceedings of the 2008 international conference on advances in computer entertainment technology. Association for Computing Machinery (ACM), 3–5 Dec, Yokohama, S 381–384

    Google Scholar 

  • Flynn S, Palma P, Bender A (2007) Feasibility of using the Sony PlayStation 2 gaming platform for an individual poststroke: a case report. J Neurol Phys Ther 31(4):180–189

    Article  Google Scholar 

  • Göbel S, Hardy S, Steinmetz R, Cha J, El Saddik A (2011) Serious Games zur Prävention und Rehabilitation. Berlin: Demografischer Wandel – Assistenzsysteme aus der Forschung in den Markt, VDE Verlag GmbH, Berlin und Offenbach, 4. Deutscher AAL-Kongress, 25–26 Jan, Berlin, S 1–5

    Google Scholar 

  • Goble DJ, Cone BL, Fling BW (2014) Using the Wii Fit as a tool for balance assessment and neurorehabilitation: the first half decade of „Wii-search“. J Neuroeng Rehabil 11(12):3–11

    Google Scholar 

  • Haghgoo HA, Pazuki ES, Hosseini AS, Rassafiani M (2013) Depression, activities of daily living and quality of life in patients with stroke. J Neurol Sci 328(1):87–91

    Article  Google Scholar 

  • Hauptmann B (2007) Von der Theorie zur Praxis: Grundlagen prozedualen und motorischen Lernens. In: Dettmers C, Bülau P, Weiler C (Hrsg) Schlaganfall Rehabilitation. Hippocampus, Bad Honnef, S 25–52

    Google Scholar 

  • Heuschmann P, Di Carlo A, Bejot Y, Rastenyte D, Ryglewicz D, Sarti C, Torrent M, Wolfe CD (2009) Incidence of stroke in Europe at the beginning of the 21st century. Stroke 40(5):1557–1563

    Article  Google Scholar 

  • Heuschmann P, Busse O, Wagner M, Endres M, Villringer A, Röther J, Kolominsky-Rabas P, Berger K (2010) Schlaganfallhäufigkeit und Versorgung von Schlaganfallpatienten in Deutschland. Akt Neurol 37(7):333–340

    Article  Google Scholar 

  • Johnson L, Burridge JH, Demain SH (2013) Internal and external focus of attention during gait re-education: an observational study of physical therapist practice in stroke rehabilitation. Phys Ther 93(7):957–966

    Article  Google Scholar 

  • Kaur G, English C, Hillier S (2012) How physically active are people with stroke in physiotherapy sessions aimed at improving motor function? A systematic review. Stroke Res Treat 2012:1–9

    Article  Google Scholar 

  • Lang CE, MacDonald JR, Gnip C (2007) Counting repetitions: an observational study of outpatient therapy for people with hemiparesis post-stroke. J Neurol Phys Ther 31(1):3–10

    Article  Google Scholar 

  • Lange B, Chang C-Y, Suma E, Newman B, Rizzo AS, Bolas M (2011) Development and evaluation of low cost game-based balance rehabilitation tool using the microsoft kinect sensor. In: Annual international conference of the IEEE engineering in medicine and biology society. 1 Dec, IEEE, Boston, S 1831–1834

    Google Scholar 

  • Langhorne P, Coupar F, Pollock A (2009) Motor recovery after stroke: a systematic review. Lancet Neurol 8(8):741–754

    Article  Google Scholar 

  • Laver KE, George S, Thomas S, Deutsch JE, Crotty M (2012) Virtual reality for stroke rehabilitation. Stroke 43(2):e20–e21

    Article  Google Scholar 

  • Laver KE, George S, Thomas S, Deutsch JE, Crotty M (2015) Virtual reality for stroke rehabilitation. Cochrane Database Syst Rev (2)

    Google Scholar 

  • Lichy PDC, Hacke W (2010) Schlaganfall. Internist 51(8):1003–1012

    Article  Google Scholar 

  • Llorens R, Alcaniz M, Colomer C, Navarro MD (2012) Balance recovery through virtual stepping exercises using Kinect skeleton tracking: a follow-up study with chronic stroke patients. Stud Health Technol Inform 181:108–112

    Google Scholar 

  • Lohse KR, Hilderman CGE, Cheung KL, Tatla S, Van der Loos HF (2014) Virtual reality therapy for adults post-stroke: a systematic review and meta-analysis exploring virtual environments and commercial games in therapy. PLoS One 9(3):e93318

    Article  Google Scholar 

  • Maclean N, Pound P (2000) A critical review of the concept of patient motivation in the literature on physical rehabilitation. Soc Sci Med 50(4):495–506

    Article  Google Scholar 

  • Masek BJ (1982) Compliance and medicine. In: Doleys DM, Meredith RL, Ciminero AR (Hrsg) Behavioral medicine. Springer, Boston, S 527–545

    Chapter  Google Scholar 

  • McLean DE (2004) Medical complications experienced by a cohort of stroke survivors during inpatient, tertiary-level stroke rehabilitation. Arch Phys Med Rehabil 85(3):466–469

    Article  Google Scholar 

  • McNevin NH, Shea CH, Wulf G (2003) Increasing the distance of an external focus of attention enhances learning. Psychol Res 67(1):22–29

    Google Scholar 

  • Mousavi, Hondori H, Khademi M (2014) A review on technical and clinical impact of microsoft kinect on physical therapy and rehabilitation. J Med Eng 1–16

    Google Scholar 

  • Neuendorf T, Zschäbitz D, Nitzsche N, Schulz H (2016) Therapeutischer Effekt Sensor-gestützter Rehabilitationssysteme bei Schlaganfallpatienten. Therapeutic Effect of Sensor-based Rehabilitation Systems in Stroke Patients. Akt Neurol 43(1):24–31

    Article  Google Scholar 

  • Neuendorf T, Zschäbitz D, Nitzsche N, Schulz H (2017a) Movement therapy of the upper extremities with a robotic ball in stroke patients: results of a randomized controlled crossover study. Neurol Int Open 1(4):E326–E335

    Article  Google Scholar 

  • Neuendorf T, Zschäbitz D, Nitzsche N, Schulz H (2017b) Neurorehabilitation mit einem Roboterball – ein geeignetes Therapiekonzept? Neurorehabilitation with a robotic ball – an applicable therapy concept? Neuroreha 9(1):41–44

    Article  Google Scholar 

  • Neuendorf T, Zschäbitz D, Nitzsche N, Schulz H (2017c) Technik-gestützte Bewegungstherapie der oberen Extremitäten nach Schlaganfall – eine aktuelle Übersicht. NeuroTransmitter 28(9):42–47

    Article  Google Scholar 

  • Neuendorf T, Zschäbitz D, Nitzsche N, Schulz H (2017d) Usability und Barrieren eines im Rahmen der Neurorehabilitation nach Schlaganfall eingesetzten Roboterballs. Neurol Rehabil 23(4):298–303

    Google Scholar 

  • Neuendorf T, Zschäbitz D, Nitzsche N, Schulz H (2018) Bewegungstherapie der oberen Extremitäten mit einem Roboterball bei Schlaganfallpatienten – Ergebnisse einer randomisierten kontrollierten Crossover Studie. Aktuelle Neurologie 45(6): 434-444

    Google Scholar 

  • Nirme J, Rubio B, Duff A, Duarte E, Rodriguez S, Cuxart A, Verschure PFMJ (2013) At home motor rehabilitation in the chronic phase of stroke using the rehabilitation gaming system. In: Converging clinical and engineering research on neurorehabilitation. Springer, Berlin/Heidelberg, S 931–935

    Chapter  Google Scholar 

  • Novak D, Nagle A, Keller U, Riener R (2014) Increasing motivation in robot-aided arm rehabilitation with competitive and cooperative gameplay. J Neuroeng Rehabil 11(1):1–15

    Article  Google Scholar 

  • Patel S, Park H, Bonato P, Chan L, Rodgers M (2012) A review of wearable sensors and systems with application in rehabilitation. J Neuroeng Rehabil 9(12):1–17

    Google Scholar 

  • Prashun P, Hadley G, Gatzidis C, Swain I (2010) Investigating the trend of virtual reality-based stroke rehabilitation systems. In: 14th international conference information visualisation, 13 Sept, IEEE, London, S 641–647

    Google Scholar 

  • Rahman S, Shaheen A (2011) Virtual reality use in motor rehabilitation of neurological disorders: a systematic review. Middle-East J Sci Res 7(1):63–70

    Google Scholar 

  • Rand D, Schejter-Margalit T, Dudkiewicz I, Kizony R, Zeilig G (2013) The use of the iPad for poststroke hand rehabilitation; a pilot study. In: International Conference on Virtual Rehabilitation (ICVR), 26–29 Aug, IEEE, Philadelphia, S 109–113

    Google Scholar 

  • Rand D, Zeilig G, Kizony R (2015) Rehab-let: touchscreen tablet for self-training impaired dexterity post stroke: study protocol for a pilot randomized controlled trial. Trials 16(1):1–7

    Article  Google Scholar 

  • Saposnik G, Teasell R, Mamdani M, Hall J, McIlroy W, Cheung D, Thorpe KE, Cohen LG, Bayley M, Outcome Research Canada (SORCan) Working Group (2010) Effectiveness of virtual reality using Wii gaming technology in stroke rehabilitation a pilot randomized clinical trial and proof of principle. Stroke 41(7):1477–1484

    Article  Google Scholar 

  • Saposnik G, Levin M, Outcome Research Canada (SORCan) Working Group (2011) Virtual reality in stroke rehabilitation a meta-analysis and implications for clinicians. Stroke 42(5):1380–1386

    Article  Google Scholar 

  • Schubert F, Lalouschek W (2006) Schlaganfall. In: Lehrner J, Pusswald G, Fertl E, Strubreither W, Kryspin-Exner I (Hrsg) Klinische Neuropsychologie. Grundlagen – Diagnostik – Rehabilitation. Springer, Wien, S 345–356

    Google Scholar 

  • Shelton F, Reding M (2001) Effect of lesion location on upper limb motor recovery after stroke. Stroke 32(1):107–112

    Article  Google Scholar 

  • Sin H, Lee G (2013) Additional virtual reality training using Xbox Kinect in stroke survivors with hemiplegia. Am J Phys Med Rehabil 92(10):871–880

    Article  Google Scholar 

  • Su X, Tong H, Ji P (2014) Activity recognition with smartphone sensors. Tsinghua Sci Technol 19(3):235–249

    Article  Google Scholar 

  • Teng X-F, Zhang Y-T, Poon CCY, Bonato P (2008) Wearable medical systems for p-health. IEEE Rev Biomed Eng 1:62–74

    Article  Google Scholar 

  • Turolla A, Dam M, Ventura L, Tonin P, Agostini M, Zucconi C, Kiper P, Cagnin A, Piron L (2013) Virtual reality for the rehabilitation of the upper limb motor function after stroke: a prospective controlled trial. J Neuroeng Rehabil 10:1–9

    Article  Google Scholar 

  • Van Vliet PM, Wulf G (2006) Extrinsic feedback for motor learning after stroke: what is the evidence? Disabil Rehabil 28(13–14):831–840

    Article  Google Scholar 

  • Webster D, Celik O (2014) Systematic review of Kinect applications in elderly care and stroke rehabilitation. J Neuroeng Rehabil 11(1):108

    Article  Google Scholar 

  • Weimar C, Diener H-C (2003) Diagnose und Therapie der Schlaganfallbehandlung in Deutschland: Ergebnisse der deutschen Schlaganfalldatenbank. Dtsch Ärztebl 100(40):A2576–A2582

    Google Scholar 

  • Wulf G (2007) Motorisches Lernen: Einflussgrößen und ihre Optimierung. In: Dettmers C, Bülau P, Weiller C (Hrsg) Schlaganfall Rehabilitation. Hippocampus, Bad Honnef, S 3–24

    Google Scholar 

  • Wulf G, Prinz W (2001) Directing attention to movement effects enhances learning: a review. Psychon Bull Rev 8(4):648–660

    Article  Google Scholar 

  • Wulf G, Lauterbach B, Toole T (1999) The learning advantages of an external focus of attention in golf. Res Q Exerc Sport 70(2):120–126

    Article  Google Scholar 

  • Zubiete ED, Luque LF, Rodriguez AVM, Gonzales IG (2011) Review of wireless sensors networks in health applications. In: Annual international conference of the IEEE engineering in medicine and biology society, 30 Aug–3 Sept, IEEE, Boston, S 1789–1793

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institut für Angewandte Bewegungswissenschaften, Professur Sportmedizin/-biologie, Technische Universität Chemnitz, Chemnitz, Deutschland

    Tilo Neuendorf, Daniel Zschäbitz, Nico Nitzsche & Henry Schulz

Authors
  1. Tilo Neuendorf
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daniel Zschäbitz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nico Nitzsche
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Henry Schulz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tilo Neuendorf .

Editor information

Editors and Affiliations

  1. Fakultät Gesundheitsmanagement, Hochschule Neu-Ulm, Neu-Ulm, Germany

    Mario A. Pfannstiel

  2. Fakultät Gesundheitsmanagement, Hochschule Neu-Ulm, Neu-Ulm, Germany

    Patrick Da-Cruz

  3. Hochschule Neu-Ulm, Neu-Ulm, Germany

    Harald Mehlich

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Neuendorf, T., Zschäbitz, D., Nitzsche, N., Schulz, H. (2019). Innovative, spielerische Therapie mit einem Roboterball bei Schlaganfallpatienten – Erfahrungen und Ergebnisse. In: Pfannstiel, M., Da-Cruz, P., Mehlich, H. (eds) Digitale Transformation von Dienstleistungen im Gesundheitswesen V. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-23987-9_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-658-23987-9_14

  • Published:

  • Publisher Name: Springer Gabler, Wiesbaden

  • Print ISBN: 978-3-658-23986-2

  • Online ISBN: 978-3-658-23987-9

  • eBook Packages: Business and Economics (German Language)

Publish with us

Policies and ethics

Search

Navigation