Skip to main content
SpringerLink
Log in

Exoskelette und künstliche Intelligenz in der klinischen Rehabilitation

  • Chapter
  • First Online:
Digitale Transformation von Dienstleistungen im Gesundheitswesen V

Zusammenfassung

Das Tragen eines Roboters, also der direkte Kontakt eines potenziell sehr kraftvollen Systems mit dem menschlichen Körper, stellt enorme Anforderungen an die Ergonomie, Sicherheit durch Design und Steuerung sowie an das Zusammenspiel beider Partner – Mensch und Roboter. Letzteres erfordert Regelungsmechanismen, die ein transparentes Verhalten des Roboters für den Menschen ermöglichen (ohne den Menschen zu behindern) und das automatische Erkennen der Intention des Menschen, um ihn situationsgemäß zu unterstützen. Um diese Herausforderungen zu meistern, gilt es, nicht nur neue kinematische und mechanische Designs, Elektroniken und Regelungsansätze zu entwickeln, sondern auch Daten des Menschen, insbesondere psychophysiologische Daten, zu nutzen. Letzteres erfordert den Einsatz sehr fortschrittlicher Signalverarbeitungsverfahren und maschinellen Lernens in Echtzeit. Integriert in das System unter Nutzung von eingebetteter Elektronik und Einbindung in die Regelung des Exoskeletts ergibt sich eine Erweiterung der künstlichen Intelligenz, die den Menschen mit seinem Verhalten, Intentionen und Bedürfnissen einbezieht. Besondere Relevanz und Herausforderung stellt die Nutzung von Exoskeletten für die Neurorehabilitation dar, auf die im Kapitel besonders eingegangen wird.

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

Access this chapter

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

Institutional subscriptions

Literatur

  • Alfven H, Kleinwächter H (1970) Syntelmann – und die möglichen Konsequenzen, Bild der Wissenschaft, Heft 7. Deutsche Verlags-Anstalt, München

    Google Scholar 

  • Anam K, Al-Jumaily AA (2012) Active exoskeleton control systems: state of the art. Proc Eng 41:988–994. ISSN 1877-7058

    Article  Google Scholar 

  • Cobb G (1934) Walking motion. Patent US 2010482 A. United States Patent Office, United States of America (USA)

    Google Scholar 

  • Clark M, Smith D (1999) Psychological correlates of outcome following rehabilitation from stroke. Clin Rehabil 13(2):129–140

    Article  Google Scholar 

  • Dettmers C, Hömberg V, Koenig E (2009) S2e-Leitlinien zur motorischen Rehabilitation des Schlaganfalls. Neurol Rehabil 15(2):71–73

    Google Scholar 

  • Folgheraiter M, Jordan M, Straube S, Seeland A, Kim S-K, Kirchner EA (2012) Measuring the improvement of the interaction comfort of a wearable exoskeleton. Int J Soc Robot 4(3):285–302. Springer, Netherlands

    Article  Google Scholar 

  • Fowers J, Brown G, Cooke P, Stitt G (2012) A performance and energy comparison of FPGAs, GPUs, and multicores for sliding-window applications. In: Association for Computing Machinery (ACM) (Hrsg) Proceedings of the ACM/SIGDA international symposium on field programmable gate arrays (FPGA ’12), 22–24 Feb, New York, S 47–56. https://doi.org/10.1145/2145694.2145704

  • Gancet J, Ilzkovitz M, Cheron G, Ivanenko Y, van der Kooij H, van der Helm F, Zanow F, Thorsteinsson F (2011) MINDWALKER: a brain controlled lower limbs exoskeleton for rehabilitation. Potential applications to space. In: 11th Symposium on advanced space technologies in robotics and automation, 12–15 Apr, European Space Agency (ESA), Noordwijk, S 12–14

    Google Scholar 

  • Golem (Hrsg) (2018) Exoskelett ermöglicht Sitzen ohne Stuhl, Golem. https://www.golem.de/news/noonee-exoskelett-ermoeglicht-sitzen-ohne-stuhl-1704-127527.html. Zugegriffen am 11.02.2018

  • Guizzo E, Goldstein H (2005) The rise of the body bots [robotic exoskeletons]. IEEE Spectr 42(10):50–56

    Article  Google Scholar 

  • Gunasekara JMP, Gopura RARC, Jayawardane TSS, Lalitharathne SWHMTD (2012) Control methodologies for upper limb exoskeleton robots. In: 2012 IEEE/SICE international symposium on system integration (SII), Institute of Electrical and Electronics Engineers/The Society of Instrument and Control Engineers (IEEE, SICE), 16–18 Dec 2012, Fukuoka, S 19–24

    Google Scholar 

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

    Article  Google Scholar 

  • Hogan N (1987) Stable execution of contact tasks using impedance control. In: Proceedings of IEEE international conference on robotics and automation (ICRA), 31 March–3 April 1987, Raleigh (NC), S 1047–1054

    Google Scholar 

  • Jo I, Park Y, Bae J (2013) A teleoperation system with an exoskeleton interface. In: Institute of Electrical and Electronics Engineers/American Society of Mechanical Engineers (IEEE, ASME) (Hrsg) IEEE/ASME international conference on advanced intelligent mechatronics, 9–12 July, Wollongong, S 1649–1654. https://doi.org/10.1109/AIM.2013.6584333

  • Johansson BB (2000) Brain plasticity and stroke rehabilitation: the Willis lecture. Stroke 31(1):223–230

    Article  Google Scholar 

  • Kirchner EA, Drechsler R (2013) A formal model for embedded brain reading. Ind Robot 40(6):530–540. Emerald Group Publishing Limited

    Article  Google Scholar 

  • Kirchner EA, Albiez J, Seeland A, Jordan M, Kirchner F (2013a) Towards assistive robotics for home rehabilitation. In: Proceedings of the 6th international conference on biomedical electronics and devices, BIODEVICES-13, Institute for Systems and Technologies of Information, Control and Communication (INSTICC), 11–14 Feb 2013, Barcelona

    Google Scholar 

  • Kirchner EA, Kim S-K, Straube S, Seeland A, Wöhrle H, Krell MM, Tabie M, Fahle M (2013b) On the applicability of brain reading for predictive human-machine interfaces in robotics. PLoS ONE 8(12):e81732

    Article  Google Scholar 

  • Kirchner EA, Seeland A, Tabie T (2014) Multimodal movement prediction – towards an individual assistance of patients. PLoS ONE 9(1):e85060

    Article  Google Scholar 

  • Kirchner EA, Kim S-K, Wöhrle H, Tabie M, Maurus M, Kirchner F (2016a) An intelligent man-machine interface – multi-robot control adapted for task engagement based on single-trial detectability of P300. Front Hum Neurosci 10:291

    Article  Google Scholar 

  • Kirchner EA, Will N, Simnofske M, Vaca Benitez LM, Bongardt B, Krell MM, Kumar S, Mallwitz M, Seeland A, Tabie M, Wöhrle H, Yüksel M, Heß A, Buschfort R, Kirchner F (2016b) Recupera-Reha: exoskeleton technology with integrated biosignal analysis for sensorimotor rehabilitation. In: 2. Transdisziplinäre Konferenz Technische Unterstützungssysteme, die die Menschen wirklich wollen, 12–13 Dec 2016, Elsevier, Hamburg, S 504–517

    Google Scholar 

  • Kõiva R, Riedenklau E, Viegas C, Castellini C (2015) Shape conformable high spatial resolution tactile bracelet for detecting hand and wrist activity. In: Institute of Electrical and Electronics Engineers (IEEE) (Hrsg) IEEE international conference on rehabilitation robotics (ICORR), 11–14 Aug, Singapore, S 157–162. https://doi.org/10.1109/ICORR.2015.7281192

  • Krell MM, Straube S, Seeland A, Wöhrle H, Teiwes J, Metzen JH, Kirchner EA, Kirchner F (2013) pySPACE – a signal processing and classification environment in Python. Front Neuroinform 7(40):1–11

    Google Scholar 

  • Kumar S, Simnofske M, Bongardt B, Mueller A, Kirchner F (2017) Integrating mimic joints into dynamics algorithms – exemplified by the hybrid recupera exoskeleton. In: Proceedings of the 2017 conference on advances in robotics, AIR-2017, Association for Computing Machinery 28 June–2 July 2017, ACM-ICPS, New Delhi, S 27:1–27:6

    Google Scholar 

  • Lee G, Kim J, Panizzolo FA, Zouh YM, Baker LM, Galiana I, Malcom P, Walsh CJ (2017) Reducing the metabolic cost of running with a tethered soft exosuit. Sci Robot 2(6):eaan6708

    Article  Google Scholar 

  • Lenzi T, De Rossi S, Vitiello N, Carrozza M (2012) Intention-based EMG control for powered exoskeletons. IEEE Trans Biomed Eng 59(8):2180–2190

    Article  Google Scholar 

  • Lew E, Chavarriaga R, Silvoni S, Millan J d R (2012) Detection of self-paced reaching movement intention from EEG signals. Front Neuroeng 5(13):13. https://doi.org/10.3389/fneng.2012.00013

    Article  Google Scholar 

  • Lowes innovation lab (Hrsg) (2018) Exosuit, Lowes innovation. http://www.lowesinnovationlabs.com/exosuits. Zugegriffen am 11.02.2018

  • Mallwitz M, Will N, Teiwes J, Kirchner EA (2015) The CAPIO active upper body exoskeleton and its application for teleoperation. In: European Space Agency (ESA) (Hrsg) Proceedings of the 13th symposium on advanced space technologies in robotics and automation, ASTRA-2015, Noordwijk

    Google Scholar 

  • Neumann J v (1928) Zur Theorie der Gesellschaftsspiele. Math Ann 100:295–320

    Article  Google Scholar 

  • New Atlas (Hrsg) (2018) Exoskeleton helps Ford workers reach up, New Atlas. https://newatlas.com/ford-eksovest/52166/. Zugegriffen am 11.02.2018

  • Nitschke J, Kuhn D, Fischer K, Röhl K (2014) Comparison of the usability of the ReWalk, Ekso and HAL. OrthOpädietechnik 9(14):22

    Google Scholar 

  • noonee (Hrsg) (2018) chairless chair, noonee. https://www.noonee.com/. Zugegriffen am 11.02.2018

  • Planthaber S, Maurus M, Bongardt B, Mallwitz M, Vaca Benitez LM, Christensen L, Cordes F, Sonsalla R, Stark T, Roehr TM (2017) Controlling a semi-autonomous robot team from a virtual environment. In: Association for Computing Machinery/Institute of Electrical and Electronics Engineers (ACM, IEEE) (Hrsg) Proceedings of the HRI conference. ACM/IEEE international conference on human-robot interaction (HRI), 6–9 Mar, Vienna, S 417

    Google Scholar 

  • Platz T (2011) Rehabilitative Therapie bei Armlähmungen nach einem Schlaganfall. S2-Leitlinie der Deutschen Gesellschaft für Neurorehabilitation. NeuroGeriatrie 3(4):104–116

    Google Scholar 

  • Platz T, Roschka S (2009) Rehabilitative Therapie bei Armparese nach Schlaganfall. Neurol Rehabil 15(2):81–106

    Google Scholar 

  • Proietti T, Crocher V, Roby-Brami A, Jarrasse N (2016) Upper-limb robotic exoskeletons for neurorehabilitation: a review on control strategies. IEEE Rev Biomed Eng 9:4–14

    Article  Google Scholar 

  • RKI und DESTATIS (Hrsg) (2015) Gesundheitsberichterstattung des Bundes gemeinsam getragen von RKI und DESTATIS Gesundheit in Deutschland. Robert-Koch Institut, Berlin, S 43

    Google Scholar 

  • Russell S, Norvig P (1995) Artificial intelligence: a modern approach (PDF). Simon & Schuster, Upper Saddle River, S 22–23

    Google Scholar 

  • Sankai Y (2010) HAL: hybrid assistive limb based on cybernics. In: Kaneko M, Nakamura Y (Hrsg) Robotics research. Springer tracts in advanced robotics, Bd 66. Springer, Berlin, S 25–34

    Google Scholar 

  • Simnofske M, Kumar S, Bongardt B, Kirchner F (2016) Active ankle – an almost-spherical parallel mechanism. In: 47th international symposium on robotics (ISR 2016), international symposium on robotics (ISR), 21–22 June, VDE, München, S 37–42.

    Google Scholar 

  • Spada S, Ghibaudo L, Gilotta S, Gastaldi L, Cavatorta MP (2017) Investigation into the applicability of a passive upper-limb exoskeleton in automotive industry. Proc Manuf 11:1255–1262

    Google Scholar 

  • Spada S, Ghibaudo L, Gilotta S, Gastaldi L, Cavatorta MP (2018) Advances in physical ergonomics and human factors. In: Goonetilleke RS, Karwowski W (Hrsg) Analysis of exoskeleton introduction in industrial reality: main issues and EAWS risk assessment. Springer, Berlin, S 236–245

    Google Scholar 

  • Takahashi CD, Der-Yeghiaian L, Le V, Motiwala RR, Cramer SC (2008) Robot-based hand motor therapy after stroke. Brain 131(2):425–437

    Article  Google Scholar 

  • Teich J, Henkel J, Herkersdorf A, Schmitt-Landsiedel D, Schröder-Preikschat W, Snelting G (2011) Invasive computing – an overview. In: Hübner M, Becker J (Hrsg) Multiprocessor system-on-chip – hardware design and tool integration. Springer, Berlin, S 241–268

    Google Scholar 

  • Turing AM (1937) On computable numbers, with an application to the Entscheidungsproblem. Proc Lond Math Soc 42:230–265. https://doi.org/10.1112/plms/s2-42.1.230

    Article  Google Scholar 

  • Turing AM (1950) Computing machinery and intelligence. Mind LIX(236):433–460. https://doi.org/10.1093/mind/LIX.236.433

    Article  Google Scholar 

  • Vaca Benitez LM, Will N, Schmidt S, Jordan M, Kirchner EA (2013) Exoskeleton technology in rehabilitation: towards an EMG-based orthosis system for upper limb neuromotor rehabilitation. J Rob 2013:13. Hindawi Publishing Corporation

    Google Scholar 

  • Volpe B, Krebs H, Hogan N, Edelstein O, Diels C, Aisen M (2000) A novel approach to stroke rehabilitation: robot-aided sensorimotor stimulation. Neurology 54(10):1938–1944

    Article  Google Scholar 

  • Waddington DG, Changhui L (2016) A fast lightweight time-series store for IoT data. Cornell University

    Google Scholar 

  • Wöhrle H, Kirchner EA (2014) Online classifier adaptation for the detection of P300 target recognition processes in a complex teleoperation scenario. In: Physiological computing systems. Lecture notes in computer science (LCNS). Springer, Heidelberg, S 105–119

    Google Scholar 

  • Wöhrle H, Kirchner EA (2017) Eingebettete Biosignalverarbeitung und integrierte Regelung eines Ganzkörper-Exoskelettes für die Neurorehabilitation. In: Proceedings of the 2. VDI Fachkonferenz Humanoide Roboter, 5–6 Dec 2017, VDI Fachkonferenz Humanoide Roboter, München

    Google Scholar 

  • Wöhrle H, Tabie T, Kim S-K, Kirchner F, Kirchner EA (2017) A hybrid FPGA-based system for EEG- and EMG-based online movement prediction. Sensors 17(7):15–52. MDPI

    Article  Google Scholar 

  • Wolpaw J, Wolpaw EW (2012) Brain-computer interfaces: principles and practice. Oxford University Press, Oxford

    Book  Google Scholar 

  • Yagn N (1890) Apparatus for facilitating walking. Patent US 440684 A. United States Patent and Trademark Office, Alexandria

    Google Scholar 

  • Yang C-J, Zhang J-F, Chen Y, Dong Y-M, Zhang Y (2008) A review of exoskeleton-type systems and their key technologies. Proc Inst Mech Eng C J Mech Eng Sci 222(8):1599–1612. https://doi.org/10.1243/09544062JMES936

    Article  Google Scholar 

  • Yeung JHC, Tsang CC, Tsoi KH, Kwan BSH, Cheung CCC, Chan APC, Leong Philip HW (2008) Map-reduce as a programming model for custom computing machines. In: Institute of Electrical and Electronics Engineers (IEEE) (Hrsg) Proceedings of the 2008 16th international symposium on field-programmable custom computing machines (FCCM ’08), 13–15 Apr, IEEE Computer Society, Washington, DC, S 149–159. https://doi.org/10.1109/FCCM.2008.19

  • Zoss A, Kazerooni H, Chu A (2005) On the mechanical design of the Berkeley Lower Extremity Exoskeleton (BLEEX). In: Institute of Electrical and Electronics Engineers/Robotics Society of Japan (IEEE, RSJ) (Hrsg) IEEE/RSJ international conference on intelligent robots and systems (2005), 2–6 Aug, Edmonton, S 3465–3472

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Robotics Innovation Center, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH (DFKI), Bremen, Deutschland

    Elsa A. Kirchner & Frank Kirchner

  2. Fachbereich 3, AG Robotik, Universität Bremen, Bremen, Deutschland

    Elsa A. Kirchner & Frank Kirchner

  3. Robotics Innovation Center (RIC), Deutsches Forschungszentrum für Künstliche Intelligenz GmbH (DFKI), Bremen, Deutschland

    Niels Will, Marc Simnofske, Peter Kampmann, Luis Manuel Vaca Benitez & José de Gea Fernández

Authors
  1. Elsa A. Kirchner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Niels Will
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marc Simnofske
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Peter Kampmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Luis Manuel Vaca Benitez
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. José de Gea Fernández
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Frank Kirchner
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Elsa A. Kirchner .

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

Kirchner, E.A. et al. (2019). Exoskelette und künstliche Intelligenz in der klinischen Rehabilitation. 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_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-658-23987-9_21

  • 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