Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Measurements of Gas Phase Velocity in Liquid Metal by Means of Ultrasonic Pulse-Echo Method Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

The Mechatronic Device for the Hand and Forearm Rehabilitation

verfasst von : Jacek S. Tutak, Wojciech Kłos

Erschienen in: Methods and Techniques of Signal Processing in Physical Measurements

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The mechatronic device has been designed and implemented based on the comprehensive rehabilitation of the paretic upper limb. This system has been prepared for an individual approach to the recovery process including diagnostics, passive or active exercises with biofeedback and reports. The mechatronic device consists of a three basic cooperating parts: mechatronic frame with module for hand and forearm rehabilitation, glove for the hand rehabilitation and module for health hand. This mechatronic device was developed in order to realize a passive exercises and active exercises with paralysed limb using the healthy limb to conduct these exercises. A very important part of rehabilitation is to introduce biofeedback (e.g. visual and auditory) to motion exercises. This paper presents the main technical characteristics of the project, especially design, kinematics and dynamics of the device and the details of the hardware/software system. This paper suggests a new approach to the rehabilitation device for the spastic upper limb of stroke survivors. The functionality of the mechatronic device for hand and forearm rehabilitation have been presented during the first tests, and preliminary assessment of usability and acceptance is promising.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Differential Measurements of TGS Samples – Unbalanced Bridge Concept and Model
Nächstes Kapitel The Mechatronic Device Which Provides Comfort and Safety for the Elderly and Disabled People
Literatur
1.
Kwakkel, G., Kollen, B.J., Grond, J., et al.: Probability of regaining dexterity in the flaccid upper limb: impact of severity of paresis and time since onset in acute stroke. Stroke 34(9), 2181–2186 (2003)CrossRef
2.
3.
Dobkin, B.H.: Strategies for stroke rehabilitation. Lancet Neurol. 3(9), 528–536 (2004)CrossRef
4.
Tutak, J.S.: Virtual reality and exercises for paretic upper limb of stroke survivors. TV-TG 24(2), 451–458 (2017)
5.
Hesse, S., Schmidt, H., Werner, C.: Machines to support motor rehabilitation after stroke: 10 years of experience in Berlin. J. Rehabil. Res. Dev. 43(5), 671–678 (2006)CrossRef
6.
Budzik, G., Turek, P., Traciak, J.: The influence of change in slice thickness on the accuracy of reconstruction of cranium geometry. J Eng. Med. 231(3), 197–202 (2017)CrossRef
7.
Fazekas, G., Horvath, M., Troznai, T., et al.: Robot-mediated upper limb physiotherapy for patients with spastic hemiparesis: a preliminary study. JJRM 39(7), 580–582 (2007)
8.
Lum, P., Burger, C.G., Van der Loos, M., et al.: MIME robotic device for upper-limb neurorehabilitation in subacute stroke subjects: a follow-up study. JRRD 43(5), 631–642 (2006)CrossRef
9.
Gunasekara, M., Gopura, R., Jayawardena, S.: 6-REXOS: upper limb exoskeleton robot with improved pHRI. IJARS 4, 1–13 (2015)
10.
Kudasik, T., Libura, M., Markowska, O., Miechowicz, S.: Methods of reconstructing complex multi-structural anatomical objects with RP techniques. Bull. Polish Acad. Sci. Techn. Sci. 64(2), 315–323 (2016)
11.
Hesse, S.: Recovery of gait and other motor functions after stroke: novel physical and pharmacological treatment strategies. Restor. Neurol. Neurosci. 22(3–5), 359–369 (2004)
12.
Lo, H.S., Xie, S.Q.: Exoskeleton robots for upper-limb rehabilitation: state of the art and future prospects. Med. Eng. Phys. 34(3), 261–268 (2012)CrossRef
13.
Pistohl, T., Joshi, D., Ganesh, G., et al.: Artificial proprioceptive feedback for myoelectric control. TNSRE 3, 498–507 (2015)
14.
Ozkul, F., Barkana, D.E.: Upper-extremity rehabilitation robot RehabRoby: methodology, design, usability and validation. IJARS 10, 1–13 (2013)
15.
Vieira, A., Gabriel, J., Melo, C., et al.: Kinect system in home-based cardiovascular rehabilitation. J Eng. Med. 231(1), 40–47 (2016)CrossRef
16.
Kurc, K., Szybicki, D., Burghardt, A., et al.: The application of virtual prototyping methods to determine the dynamic parameters of mobile robot. Open Eng. 6(1), 55–63 (2016)CrossRef
17.
Heinen, F., Lund, M.E., Rasmussen, J., et al.: Muscle–tendon unit scaling methods of Hill-type musculoskeletal models: an overview. J Eng. Med. 230(10), 976–984 (2016)CrossRef
18.
Seung, S., Choi, H., Jang, J., et al.: Virtual wall–based haptic-guided teleoperated surgical robotic system for single-port brain tumor removal surgery. J. Eng. Med. 231(1), 3–19 (2016)CrossRef
19.
Tutak, J.S., Wiech, J.: Horizontal automated storage and retrieval system. Adv. Sci. Technol. Res. J. 11(1), 82–95 (2017)CrossRef
20.
Szuster, M., Gierlak, P.: Approximate dynamic programming in tracking control of a robotic manipulator. Int. J. Adv. Robot. Syst. 13(16), 1–18 (2016)
21.
Dong-Yuan, G., Xi-Fan, Y., Qing-He, Y., et al.: Robot sensor calibration via neural network and particle swarm optimization enhanced with crossover and mutation. TV-TG 21(5), 1025–1033 (2014)
22.
Kowalczyk, A., Szlachta, A., Hanus, R., Chorzępa, R.: Estimation of conditional expected value for expone ntially autocorrelated data. Metrol. Meas. Syst. 24(1), 67–69 (2017)CrossRef
23.
Hendzel, Z., Burghardt, A., Gierlak, P., et al.: Conventional and fuzzy force control in robotised machining. Solid State Phenom. Trans. Tech. Publ. 210, 178–185 (2014)CrossRef
24.
Tutak, J.S.: Design of ELISE robot for the paretic upper limb of stroke survivors. J. Vibroengineering 18(6), 4069–4085 (2016)CrossRef
25.
Kowalczyk, A., Hanus, R., Szlachta, A.: Investigation of the statistical method of time delay estimation based on conditional averaging of delayed signal. Metrol. Meas. Syst. 18(2), 335–342 (2011)CrossRef
26.
Hendzel, Z., Burghardt, A., Szuster, M.: Reinforcement learning in discrete neural control of the underactuated system. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, Lotfi A., Zurada, Jacek M. (eds.) ICAISC 2013. LNCS (LNAI), vol. 7894, pp. 64–75. Springer, Heidelberg (2013). https://​doi.​org/​10.​1007/​978-3-642-38658-9_​6CrossRefMATH
Metadaten
Titel
The Mechatronic Device for the Hand and Forearm Rehabilitation
verfasst von
Jacek S. Tutak
Wojciech Kłos
Copyright-Jahr
2019
Buch
Methods and Techniques of Signal Processing in Physical Measurements

Print ISBN: 978-3-030-11186-1

Electronic ISBN: 978-3-030-11187-8

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-11187-8_31

Neuer Inhalt

    Bildnachweise