Abstract
Robotic rehabilitation devices offer prospects in improving the therapy outcome in stroke patients. In particular the combination with tele-rehabilitation functionality may be beneficial to reduce cost, which is especially required for home-based rehabilitation. In this paper a device is presented that allows for exercising supination/pronation, dorsiflexion, and finger training. Its communication architecture follows a modular design approach. The Qt-based graphical UI can be executed on different operating systems and devices including the cost-effective Rasperry Pi single-board computer. Tele-rehabilitation functionality is implemented based on SSL-encrypted RESTful web services following a three-tier architecture. Cost is reduced by omitting expensive sensors. A torque sensor is replaced with current-based torque sensing, used for progress measurement and interactive exercises. The evaluation shows accurate results after compensating the static friction, justifying the omission of an additional torque sensor. Torque measurements during passive exercises showed higher and more asymmetric ratings for a stroke patient than for a healthy subject indicating that this measurement may be used as an estimator of spasticity.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Allington, J., Spencer, S. J., Klein, J., Buell, M., Reinkensmeyer, D. J., Bobrow, J.: Supinator extender (SUE): a pneumatically actuated robot for forearm/wrist rehabilitation after stroke. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1579–1582. IEEE (2011)
Balasubramanian, S., Klein, J., Burdet, E.: Robot-assisted rehabilitation of hand function. Curr. Opin. Neurol. 23(6), 661 (2010)
Brewer, B., Klatzky, R., Matsuoka, Y.: Feedback distortion to overcome learned nonuse: a system overview. In: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 2, pp. 1613–1616. IEEE (2003)
Brewer, B., Klatzky, R., Matsuoka, Y.: Visual feedback distortion in a robotic environment for hand rehabilitation. Brain Res. Bull. 75(6), 804–813 (2008)
Hesse, S., Schulte-Tigges, G., Konrad, M., Bardeleben, A., Werner, C.: Robot-assisted arm trainer for the passive and active practice of bilateral forearm and wrist movements in hemiparetic subjects. Arch. Phys. Med. Rehabil. 84(6), 915–920 (2003)
Kolominsky-Rabas, P.L., Heuschmann, P.U., Marschall, D., Emmert, M., Baltzer, N., Neundörfer, B., Schöffski, O., Krobot, K.J., 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)
Krebs, H.I., Volpe, B.T., Williams, D., Celestino, J., Charles, S.K., Lynch, D., Hogan, N.: Robot-aided neurorehabilitation: a robot for wrist rehabilitation. IEEE Trans. Neural Syst. Rehabil. Eng. 15(3), 327–335 (2007)
Kwakkel, G., Kollen, B.J., Krebs, H.I.: Effects of robot-assisted therapy on upper limb recovery after stroke: a systematic review. Neurorehabil. Neural Repair 22(2), 111–121 (2008)
Maciejasz, P., Eschweiler, J., Gerlach-Hahn, K., Jansen-Toy, A., Leonhardt, S., et al.: A survey on robotic devices for upper limb rehabilitation. J. Neuroeng. Rehabil. 11(1), 3 (2014)
Matsuoka, Y., Allin, S., Klatzky, R.: The tolerance for visual feedback distortions in a virtual environment. Physiol. Behav. 77(4–5), 651–655 (2002)
Metzger, J.-C., Lambercy, O., Chapuis, D., Gassert, R.: Design and characterization of the ReHapticKnob, a robot for assessment and therapy of hand function. In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 3074–3080. IEEE (2011)
Nakayama, H., Jørgensen, H.S., Raaschou, H.O., Olsen, T.S.: Recovery of upper extremity function in stroke patients: the Copenhagen stroke study. Age (SD) 74, 11–2 (1994)
Oblak, J., Cikajlo, I., Matjacic, Z.: Universal haptic drive: a robot for arm and wrist rehabilitation. IEEE Trans. Neural Syst. Rehabil. Eng. 18(3), 293–302 (2010)
Reinkensmeyer, D.J., Emken, J.L., Cramer, S.C.: Robotics, motor learning, and neurologic recovery. Annu. Rev. Biomed. Eng. 6, 497–525 (2004)
Takahashi, C.D., Der-Yeghiaian, L., Le, V., Motiwala, R.R., Cramer, S.C.: Robot-based hand motor therapy after stroke. Brain 131(2), 425–437 (2008)
Van der Lee, J.H., de Groot, V., Beckerman, H., Wagenaar, R.C., Lankhorst, G.J., Bouter, L.M.: The intra-and interrater reliability of the action research arm test: a practical test of upper extremity function in patients with stroke. Arch. Phys. Med. Rehabil. 82(1), 14–19 (2001)
Warlow, C., Van Gijn, J., Sandercock, P., Hankey, G., Dennis, M., Bamford, J., Wardlaw, J., Sudlow, C., Rinkel, G., Rothwell, P.: Stroke: practical management (2008)
Weiss, P., Heldmann, M. Gabrecht, A. Schweikard, A., Münte, T. M., Maehle, E.: A low cost tele-rehabilitation device for training of wrist and finger functions after stroke. In: Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth 2014), pp. 422–425 (2014)
Weiss, P., Heldmann, M., Münte, T., Schweikard, A., Maehle, E.: A rehabilitation system for training based on visual feedback distortion. In: Pons, J.L., Torricelli, D., Pajaro, M. (eds.) Converging Clinical and Engineering Research on Neurorehabilitation, pp. 297–302. Springer, Heidelberg (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Weiss, P., Gabrecht, A., Heldmann, M., Schweikard, A., Maehle, E. (2015). A Cost-Efficient Tele-rehabilitation Device for Training Distal Upper Limb Functions After Stroke. In: Fardoun, H., R. Penichet, V., Alghazzawi, D. (eds) ICTs for Improving Patients Rehabilitation Research Techniques. REHAB 2014. Communications in Computer and Information Science, vol 515. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48645-0_8
Download citation
DOI: https://doi.org/10.1007/978-3-662-48645-0_8
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-48644-3
Online ISBN: 978-3-662-48645-0
eBook Packages: Computer ScienceComputer Science (R0)