More Web Proxy on the site http://driver.im/

research-article

A low cost tele-rehabilitation device for training of wrist and finger functions after stroke

Authors:

Marcus Heldmann,

Alexander Gabrecht,

Achim Schweikard,

Thomas M. Münte,

Erik MaehleAuthors Info & Claims

PervasiveHealth '14: Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare

Pages 422 - 425

https://doi.org/10.4108/icst.pervasivehealth.2014.255331

Published: 20 May 2014 Publication History

Abstract

There is a need for robotic rehabilitation devices that improve the outcome while reducing the cost of therapy. This paper presents a device for training of supination/pronation, dorsal wrist extension, and finger manipulation after stroke. The system exhibits modularity in terms of the communication architecture and different optional components. User interfaces (UI) can be implemented on different kinds of devices including a Rasperry Pi single-board computer on which a Qt-based graphical UI was run in this instance. Tele-rehabilitation functionality is included using SSL-encrypted RESTful web services on a three-tier architecture. Expensive sensors were omitted in order to have a cost-effective system which is a requirement for home-based rehabilitation. The current-based torque sensing is evaluated by comparing current measurements to force-torque sensor values. After canceling out the static friction, the low error justified the omission of an additional sensor.

References

[1]

J. Allington, S. J. Spencer, J. Klein, M. Buell, D. J. Reinkensmeyer, and J. Bobrow. Supinator extender (sue): a pneumatically actuated robot for forearm/wrist rehabilitation after stroke. In Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE, pages 1579--1582. IEEE, 2011.

[2]

S. Balasubramanian, J. Klein, and E. Burdet. Robot-assisted rehabilitation of hand function. Current opinion in neurology, 23(6):661, 2010.

[3]

B. R. Brewer, R. Klatzky, and Y. Matsuoka. Visual feedback distortion in a robotic environment for hand rehabilitation. Brain research bulletin, 75(6):804--813, 2008.

[4]

S. Hesse, G. Schulte-Tigges, M. Konrad, A. Bardeleben, and C. Werner. Robot-assisted arm trainer for the passive and active practice of bilateral forearm and wrist movements in hemiparetic subjects. Archives of physical medicine and rehabilitation, 84(6):915--920, 2003.

[5]

P. L. Kolominsky-Rabas, P. U. Heuschmann, D. Marschall, M. Emmert, N. Baltzer, B. Neundörfer, O. Schöffski, K. J. Krobot, et al. Lifetime cost of ischemic stroke in germany: Results and national projections from a population-based stroke registry the erlangen stroke project. Stroke, 37(5):1179--1183, 2006.

[6]

H. I. Krebs, B. T. Volpe, D. Williams, J. Celestino, S. K. Charles, D. Lynch, and N. Hogan. Robot-aided neurorehabilitation: a robot for wrist rehabilitation. Neural Systems and Rehabilitation Engineering, IEEE Transactions on, 15(3):327--335, 2007.

[7]

G. Kwakkel, B. J. Kollen, and H. I. Krebs. Effects of robot-assisted therapy on upper limb recovery after stroke: a systematic review. Neurorehabilitation and neural repair, 22(2):111--121, 2008.

[8]

P. Maciejasz, J. Eschweiler, K. Gerlach-Hahn, A. Jansen-Toy, S. Leonhardt, et al. A survey on robotic devices for upper limb rehabilitation. Journal of neuroengineering and rehabilitation, 11(1):3, 2014.

[9]

J.-C. Metzger, O. Lambercy, D. Chapuis, and R. Gassert. Design and characterization of the rehapticknob, a robot for assessment and therapy of hand function. In Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pages 3074--3080. IEEE, 2011.

[10]

H. Nakayama, H. S. Jgtgensen, H. O. Raaschou, and T. S. Olsen. Recovery of upper extremity function in stroke patients: the copenhagen stroke study. Age (SD), 74:11--2, 1994.

[11]

J. Oblak, I. Cikajlo, and Z. Matjacic. Universal haptic drive: A robot for arm and wrist rehabilitation. Neural Systems and Rehabilitation Engineering, IEEE Transactions on, 18(3):293--302, 2010.

[12]

D. J. Reinkensmeyer, J. L. Emken, and S. C. Cramer. Robotics, motor learning, and neurologic recovery. Annu. Rev. Biomed. Eng., 6:497--525, 2004.

[13]

C. D. Takahashi, L. Der-Yeghiaian, V. Le, R. R. Motiwala, and S. C. Cramer. Robot-based hand motor therapy after stroke. Brain, 131(2):425--437, 2008.

[14]

C. Warlow, J. Van Gijn, P. Sandercock, G. Hankey, M. Dennis, J. Bamford, J. Wardlaw, C. Sudlow, G. Rinkel, and P. Rothwell. Stroke: practical management. 2008.

[15]

P. Weiss, M. Heldmann, T. Münte, A. Schweikard, and E. Maehle. A rehabilitation system for training based on visual feedback distortion. In Converging Clinical and Engineering Research on Neurorehabilitation, pages 297--302. Springer, 2013.

Cited By

Akinsiku AAvellino IGraham YMentis HKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)It’s Not Just the Movement: Experiential Information Needed for Stroke TelerehabilitationProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445663(1-12)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445663
Ivanova ESchrader MLorenz KMinge MHall LTurner P(2017)Developing motivational visual feedback for a new telerehabilitation system for motor relearning after strokeProceedings of the 31st British Computer Society Human Computer Interaction Conference10.14236/ewic/HCI2017.75(1-6)Online publication date: 3-Jul-2017
https://dl.acm.org/doi/10.14236/ewic/HCI2017.75

Recommendations

Robotic wrist training after stroke

In this paper we present a case study in which a 14-year-old, right-handed stroke patient with severe weakness, spasticity, and motor dysfunction of the left upper extremity participated in a three-month distal robotic training program. The robotic ...
Robotics and Tele-Rehabilitation: Recent Advancements, Future Trends

Recently, the use of robots, virtual reality systems and many new technologies has been extensively considered in rehabilitation studies and applications. By the combination of these technologies and new communication systems, a new subfield of ...
Interactive robot-assisted training system using continuous EMG signals for stroke rehabilitation
i-CREATe '09: Proceedings of the 3rd International Convention on Rehabilitation Engineering & Assistive Technology

Active initiation and participation in the rehabilitation is a key of success for stroke rehabilitation. To patients with stroke, the interactive robotic system would motivate them to actively interact with the system during the task-related training ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

PervasiveHealth '14: Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare

May 2014

459 pages

ISBN:9781631900112

General Chair:
Andreas Hein
OFFIS-Institute for IT, Oldenburg, Germany
,
Program Chairs:
Susanne Boll
OFFIS-Institute for IT, Oldenburg, Germany
,
Friedrich Köhler
Charité, Berlin, Germany

In-Cooperation

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering)

Brussels, Belgium

Publication History

Published: 20 May 2014

Check for updates

Author Tags

Qualifiers

Research-article

Conference

PervasiveHealth '14

PervasiveHealth '14: 8th International Conference on Pervasive Computing Technologies for Healthcare

May 20 - 23, 2014

Oldenburg, Germany

Acceptance Rates

Overall Acceptance Rate 55 of 116 submissions, 47%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
162
Total Downloads

Downloads (Last 12 months)8
Downloads (Last 6 weeks)3

Reflects downloads up to 22 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Akinsiku AAvellino IGraham YMentis HKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)It’s Not Just the Movement: Experiential Information Needed for Stroke TelerehabilitationProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445663(1-12)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445663
Ivanova ESchrader MLorenz KMinge MHall LTurner P(2017)Developing motivational visual feedback for a new telerehabilitation system for motor relearning after strokeProceedings of the 31st British Computer Society Human Computer Interaction Conference10.14236/ewic/HCI2017.75(1-6)Online publication date: 3-Jul-2017
https://dl.acm.org/doi/10.14236/ewic/HCI2017.75

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents