PoRi device: portable hand assessment and rehabilitation after stroke
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Karl Wolf
Karl Wolf finished the HTBLVA Anichstraße – Elektrotechnik in 2009 and afterwards worked as a technician at the Bergbahnen Sölden. Subsequently he worked as research technician at MED-EL Elektromedizinische Geräte GmbH and later changed to the role of a development engineer at the same company. He studied mechatronics at the Management Center Innsbruck and received his B.Sc. in 2018. Since 2019 he works as a software developer at Liebherr Werk Telfs GmbH.
Andreas Mayr graduated from the Faculty of Sports Science at the University of Innsbruck in 1999. Since 2002 he led the Laboratory of Gait- and Movement analysis of the hospital Hochzirl (Innsbruck, Austria) as part of the neurological department. Thereafter, he took the lead of therapy in 2012. He finished his PhD at the Medical University of Innsbruck in 2008 (topic: Robotics in Neurorehabilitation). His main interest of research is human movement sciences. The analysis of functional electrophysiological patterns of the upper and lower limbs, the application of therapeutic robots in the field of neurorehabilitation, as well as the integration of biofeedback and VR (virtual reality) strategies in clinical practice are subjects of his main working focus. He is author and co-author of many scientific articles and congress abstracts, and has been invited as speaker in several national and international meetings for neurorehabilitation, gait and movement analysis and motor learning.
Marco Nagiller studied Mechatronics & Smart Technologies at the university of applied sciences MCI in Innsbruck. He received the M.Sc. degree in 2021. He is now studying towards his Dipl.-Ing. degree in Automation Technology Business at Campus 02 University of Applied Sciences 02 in Graz.
Leopold Saltuari has been Medical Director of the Department of Neurology in the Hochzirl Hospital since 1995. He is also Vice-president of the Austrian Neuromodulation Society. From 1988 to 2015 he has been active in the further education of Physical Therapists in Neurorehabilitation at the Scientific Academy of Lower Austria. He was elected President of the Austrian Society for Neuro-rehabilitation in 2002. Since October 2009 he has been the Director of the Research Department for Neurorehabilitation South Tyrol, Bolzano, Italy. Dr. Saltuari has submitted over 80 publications dealing with neurorehabilitative subjects as well as with acute neurological topics. From 1983 to 1995 Dr. Saltuari was Head of Department on the Neurology Ward IIS/IV at the University Clinic in Innsbruck, specializing in post-acute rehabilitation for stroke and brain-injury patients. During this period, eight physicians completed their residency in Neurorehabilitation under his tutelage. Since 1986 Dr. Saltuari has been Lecturer for Neurorehabilitation and Evoked Potentials at the University for Medicine in Innsbruck and since 1995 on the staff of the Institute for Sport Science. Dr. Saltuari introduced new rehabilitation techniques such as cortical facilitation in Austria and developed new therapeutic techniques, e.g. intrathecal application of Baclofen in patients with supraspinal spasticity. The government of South Tyrol (Italy) appointed Dr. Saltuari in 1985 to the Commission for Development of National Laws for Rehabilitation.
Matthias Harders studied computer science with a focus on medical informatics at the University of Hildesheim, Technical University of Braunschweig, and University of Houston, Texas. He received the PhD degree from ETH Zurich, Switzerland, in 2002. He is currently a full professor in computer science at the University of Innsbruck, Austria. His research interests include surgical simulation, virtual reality, and haptic interfaces.
Yeongmi Kim received the M.Sc. and Ph.D. degrees from the Mechatronics Department, Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea, in 2006 and 2010, respectively. She was a Postdoctoral Fellow with the Rehabilitation Engineering Laboratory, ETH Zurich, Switzerland, and the Interactive Graphics and Simulation Group, University of Innsbruck, Austria. She is currently a Professor with the Department of Medical Technologies, MCI, Austria. Her research interests include rehabilitation engineering, assistive technology, humancomputer interaction, psychophysics, and haptic interfaces.
Abstract
Frequent rehabilitation exercises can accelerate the recovery of patient’s hand impairments after stroke. In conjunction with conventional therapy, the use of robot-assisted training has been proposed to increase the frequency of the latter, thus improving the overall recovery of patients. However, the COVID-19 pandemic has reduced or even halted related programs in clinical rehabilitation centers that often utilize costly, complex, and non-transportable robotic devices. A possible therapy alternative is using low-cost in-home solutions which integrate well in home-based settings due to reduced size, weight, and complexity. Therefore, we propose a new portable hand training and assessment device which supports hand opening/closing and wrist exercises. The device also enables tasks related to the identification of vibration stimuli to be used both for training as well as for assessment of sensory-motor hand function of patients. To this end, a cable-driven capstan transmission mechanism, a controller to regulate the extension angle, and touch pads equipped with vibration motors were designed and integrated into a hand-held device. Initial user studies indicate that the prototype can support stroke patients in extending their fingers. In further experiments targeting the identification of vibration stimuli, assessment results comparable with those obtained via a standard clinical somatosensory assessment test were achieved. Given these initial findings, our low-cost system shows the potential to allow in-home rehabilitation exercises in daily life, thus maximizing exposure and frequency, even during a forced lockdown caused by a pandemic.
Zusammenfassung
Die Genesung von PatientInnen, deren Hand nach einem Schlaganfall beeinträchtigt worden ist, kann durch häufige Rehabilitationsübungen beschleunigt werden. Um in Verbindung mit konventioneller Therapie die Häufigkeit dieser Übungen zu erhöhen und somit die Gesamterholung der PatientInnen zu verbessern, wird der Einsatz von robotergestütztem Training vorgeschlagen. Nichtsdestotrotz hat die COVID-19-Pandemie dazu geführt, dass entsprechende Programme in klinischen Rehabilitationszentren reduziert oder vollständig ausgesetzt werden mussten; in letz-teren kommen häufig kostspielige, komplexe und nicht transportable Robotergeräte zum Einsatz. Eine mögliche Therapie-Alternative ist die Verwendung kostengünstiger Lösungen für den Heimgebrauch, welche sich aufgrund geringer Größe, Gewicht und Komplexität gut in eine häusliche Umgebung integrieren lassen. Daher schlagen wir ein neues tragbares Gerät für Hand-Therapie und -Diagnose vor, welches Übungen zur Beugung und Streckung der Finger sowie des Handgelenks unterstützt. Dieses Gerät ermöglicht auch Training basierend auf der Identifizierung von Vibrationsreizen, was sowohl für die Rehabilitation als auch für die Messung sensomotorischer Handfunktion der PatientInnen verwendet werden kann. Zu diesem Zwecke wurden ein kabelgetriebener Capstan-Übertragungsmechanismus, ein Regler zur Re-gulierung des Streckwinkels sowie Touchpads mit Vibrationsmotoren entwickelt, und in ein handgetragenes Gerät integriert. Erste Nutzerstudien deuten darauf hin, dass der Prototyp SchlaganfallpatientInnen bei der Streckung ihrer Finger unterstützen kann. In zusätzlichen Experimenten bzgl. der Identifizierung von Vibrationsreizen wurden somatosensorischen Bewertungen erzielt, die mit denen eines klinischen Standardtests vergleichbar waren. Gemäß dieser ersten Resultate weist unser kostengünstiges System das Potenzial auf, Rehabilitationsübungen im Alltag zu Hause zu ermöglichen und somit die Belastung und Häufigkeit zu maximieren; insbesondere auch während potentieller, durch eine Pandemie verursachter Lockdowns.
Über die Autoren
Karl Wolf finished the HTBLVA Anichstraße – Elektrotechnik in 2009 and afterwards worked as a technician at the Bergbahnen Sölden. Subsequently he worked as research technician at MED-EL Elektromedizinische Geräte GmbH and later changed to the role of a development engineer at the same company. He studied mechatronics at the Management Center Innsbruck and received his B.Sc. in 2018. Since 2019 he works as a software developer at Liebherr Werk Telfs GmbH.
Andreas Mayr graduated from the Faculty of Sports Science at the University of Innsbruck in 1999. Since 2002 he led the Laboratory of Gait- and Movement analysis of the hospital Hochzirl (Innsbruck, Austria) as part of the neurological department. Thereafter, he took the lead of therapy in 2012. He finished his PhD at the Medical University of Innsbruck in 2008 (topic: Robotics in Neurorehabilitation). His main interest of research is human movement sciences. The analysis of functional electrophysiological patterns of the upper and lower limbs, the application of therapeutic robots in the field of neurorehabilitation, as well as the integration of biofeedback and VR (virtual reality) strategies in clinical practice are subjects of his main working focus. He is author and co-author of many scientific articles and congress abstracts, and has been invited as speaker in several national and international meetings for neurorehabilitation, gait and movement analysis and motor learning.
Marco Nagiller studied Mechatronics & Smart Technologies at the university of applied sciences MCI in Innsbruck. He received the M.Sc. degree in 2021. He is now studying towards his Dipl.-Ing. degree in Automation Technology Business at Campus 02 University of Applied Sciences 02 in Graz.
Leopold Saltuari has been Medical Director of the Department of Neurology in the Hochzirl Hospital since 1995. He is also Vice-president of the Austrian Neuromodulation Society. From 1988 to 2015 he has been active in the further education of Physical Therapists in Neurorehabilitation at the Scientific Academy of Lower Austria. He was elected President of the Austrian Society for Neuro-rehabilitation in 2002. Since October 2009 he has been the Director of the Research Department for Neurorehabilitation South Tyrol, Bolzano, Italy. Dr. Saltuari has submitted over 80 publications dealing with neurorehabilitative subjects as well as with acute neurological topics. From 1983 to 1995 Dr. Saltuari was Head of Department on the Neurology Ward IIS/IV at the University Clinic in Innsbruck, specializing in post-acute rehabilitation for stroke and brain-injury patients. During this period, eight physicians completed their residency in Neurorehabilitation under his tutelage. Since 1986 Dr. Saltuari has been Lecturer for Neurorehabilitation and Evoked Potentials at the University for Medicine in Innsbruck and since 1995 on the staff of the Institute for Sport Science. Dr. Saltuari introduced new rehabilitation techniques such as cortical facilitation in Austria and developed new therapeutic techniques, e.g. intrathecal application of Baclofen in patients with supraspinal spasticity. The government of South Tyrol (Italy) appointed Dr. Saltuari in 1985 to the Commission for Development of National Laws for Rehabilitation.
Matthias Harders studied computer science with a focus on medical informatics at the University of Hildesheim, Technical University of Braunschweig, and University of Houston, Texas. He received the PhD degree from ETH Zurich, Switzerland, in 2002. He is currently a full professor in computer science at the University of Innsbruck, Austria. His research interests include surgical simulation, virtual reality, and haptic interfaces.
Yeongmi Kim received the M.Sc. and Ph.D. degrees from the Mechatronics Department, Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea, in 2006 and 2010, respectively. She was a Postdoctoral Fellow with the Rehabilitation Engineering Laboratory, ETH Zurich, Switzerland, and the Interactive Graphics and Simulation Group, University of Innsbruck, Austria. She is currently a Professor with the Department of Medical Technologies, MCI, Austria. Her research interests include rehabilitation engineering, assistive technology, humancomputer interaction, psychophysics, and haptic interfaces.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: This work was partially supported by AWS (Project numbers P2017968).
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
[1] J. Mackay, G. A. Mensah, S. Mendis, and K. Greenlund, The Atlas of Heart Disease and Stroke, Geneva, World Health Organization, 2004.Search in Google Scholar
[2] S. M. Lai, S. Studenski, P. W. Duncan, and S. Perera, “Persisting consequences of stroke measured by the stroke impact scale,” Stroke, vol. 33, no. 7, pp. 1840–1844, 2002. https://doi.org/10.1161/01.str.0000019289.15440.f2.Search in Google Scholar PubMed
[3] N. J, . Seo, W. Z. Rymer, and D. G. Kamper, “Delays in grip initiation and termination in persons with stroke: effects of arm support and active muscle stretch exercise,” J. Neurophysiol., vol. 101, no. 6, pp. 3108–3115, 2009. https://doi.org/10.1152/jn.91108.2008.Search in Google Scholar PubMed
[4] A. E. Merkler, N. S. Parikh, S. Mir, et al.., “Risk of ischemic stroke in patients with coronavirus disease 2019 (COVID-19) vs patients with influenza,” JAMA Neurol., vol. 77, no. 11, pp. 1366–1372, 2020. https://doi.org/10.1001/jamaneurol.2020.2730.Search in Google Scholar PubMed PubMed Central
[5] S. Rudilosso, C. Laredo, V. Vera, et al.., “Acute stroke care is at risk in the era of COVID-19: experience at a comprehensive stroke center in Barcelona,” Stroke, vol. 51, no. 7, pp. 1991–1995, 2020. https://doi.org/10.1161/strokeaha.120.030329.Search in Google Scholar PubMed PubMed Central
[6] J. Zhao, H. Li, D. Kung, M. Fisher, Y. Shen, and R. Liu, “Impact of the COVID-19 epidemic on stroke care and potential solutions,” Stroke, vol. 51, no. 7, pp. 1996–2001, 2020. https://doi.org/10.1161/strokeaha.120.030225.Search in Google Scholar
[7] A. Bersano, M. Kraemer, E. Touzé, et al.., “Stroke care during the COVID-19 pandemic: experience from three large European countries,” Eur. J. Neurol., vol. 27, no. 9, pp. 1794–1800, 2020. https://doi.org/10.1111/ene.14375.Search in Google Scholar PubMed PubMed Central
[8] G. B. Prange, M. J. A. Jannink, C. G. M. Groothuis-Oudshoorn, H. J. Hermens, and M. J. Ijzerman, “Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke,” J. Rehabil. Res. Dev., vol. 43, no. 2, p. 171, 2006. https://doi.org/10.1682/JRRD.2005.04.0076.Search in Google Scholar
[9] S. Mazzoleni, L. Puzzolante, L. Zollo, P. Dario, and F. Posteraro, “Mechanisms of motor recovery in chronic and subacute stroke patients following a robot-aided training,” IEEE Trans. Haptics, vol. 7, no. 2, pp. 175–180, 2014. https://doi.org/10.1109/TOH.2013.73.Search in Google Scholar PubMed
[10] J. H. Villafañ$\tilde{\mathrm{n}}$e, G. Taveggia, S. Galeri, et al.., “Efficacy of short-term robot-assisted rehabilitation in patients with hand paralysis after stroke: a randomized clinical trial,” Hand (N. Y.), vol. 13, no. 1, pp. 95–102, 2018. https://doi.org/10.1177/1558944717692096.Search in Google Scholar PubMed PubMed Central
[11] N. G. Kutner, R. Zhang, A. J. Butler, S. L. Wolf, and J. L. Alberts, “Quality-of-life change associated with robotic-assisted therapy to improve hand motor function in patients with subacute stroke: a randomized clinical trial,” Phys. Ther., vol. 90, no. 4, pp. 493–504, 2010. https://doi.org/10.2522/ptj.20090160.Search in Google Scholar PubMed PubMed Central
[12] T. Nef, M. Guidali, V. Klamroth-Marganska, and R. Riener, “ARMin-exoskeleton robot for stroke rehabilitation,” in World Congress on Medical Physics and Biomedical Engineering, September 7-12, 2009, pp. 127–130.10.1007/978-3-642-03889-1_35Search in Google Scholar
[13] J. Klein, N. Roach, and E. Burdet, “3DOM: a 3 degree of freedom manipulandum to investigate redundant motor control,” IEEE Trans. Haptics, vol. 7, no. 2, 2014, pp. 229–239.10.1109/TOH.2013.59Search in Google Scholar PubMed
[14] J. C. Metzger, O. Lambercy, A. Califfi, F. M. Conti, and R. Gassert, “Neurocognitive robot-assisted therapy of hand function,” IEEE Trans. Haptics, vol. 7, no. 2, pp. 140–149, 2014. https://doi.org/10.1109/TOH.2013.72.Search in Google Scholar PubMed
[15] D. Leonardis, M. Barsotti, C. Loconsole, et al.., “An EMG-controlled robotic hand exoskeleton for bilateral rehabilitation,” IEEE Trans. Haptics, vol. 8, no. 2, pp. 140–151, 2015. https://doi.org/10.1109/toh.2015.2417570.Search in Google Scholar
[16] P. Agarwal, J. Fox, Y. Yun, M. K. O’Malley, and A. D. Deshpande, “An index finger exoskeleton with series elastic actuation for rehabilitation: design, control and performance characterization,” Int. J. Robot. Res., vol. 34, no. 14, pp. 1747–1772, 2015. https://doi.org/10.1177/0278364915598388.Search in Google Scholar
[17] T. L. Zhu, J. Klein, S. Anne Dual, T. C. Leong, and E. Burdet, “reachMAN2: a compact rehabilitation robot to train reaching and manipulation,” in 2014 IEEE/RSJ International Conference on Intelligent Robots And Systems, Chicago, Illinois, USA, IEEE, 2014, pp. 2107–2113.10.1109/IROS.2014.6942845Search in Google Scholar
[18] R. Rätz, F. Conti, R. M. Müri, and L. Marchal-Crespo, “A novel clinical-driven design for robotic hand rehabilitation: combining sensory training, effortless setup, and large range of motion in a palmar device,” Front. Neurorobot., vol. 15, pp. 1–22, 2021. https://doi.org/10.3389/fnbot.2021.748196.Search in Google Scholar PubMed PubMed Central
[19] S. Hesse, H. Kuhlmann, J. Wilk, C. Tomelleri, and S. G. B. Kirker, “A new electromechanical trainer for sensorimotor rehabilitation of paralysed fingers: a case series in chronic and acute stroke patients,” J. NeuroEng. Rehabil., vol. 5, p. 21, 2008. https://doi.org/10.1186/1743-0003-5-21.Search in Google Scholar PubMed PubMed Central
[20] S. Hesse, A. Heß, C. C. Werner, N. Kabbert, and R. Buschfort, “Effect on arm function and cost of robot-assisted group therapy in subacute patients with stroke and a moderately to severely affected arm: a randomized controlled trial,” Clin. Rehabil., vol. 28, no. 7, pp. 637–647, 2014. https://doi.org/10. 1177/0269215513516967.10.1177/0269215513516967Search in Google Scholar PubMed
[21] R. Buschfort, J. Brocke, A. Hess, C. Werner, A. Waldner, and S. Hesse, “Arm studio to intensify the upper limb rehabilitation after stroke: concept, acceptance, utilization and preliminary clinical results,” J. Rehabil. Med., vol. 42, no. 4, pp. 310–314, 2010. https://doi.org/10.2340/16501977-0517.Search in Google Scholar PubMed
[22] E. B. Brokaw, I. Black, R. J. Holley, and P. S. Lum, “Hand Spring Operated Movement Enhancer (HandSOME): a portable, passive hand exoskeleton for stroke rehabilitation,” IEEE Trans. Neural Syst. Rehabil. Eng., vol. 19, no. 4, pp. 391–399, 2011. https://doi.org/10.1109/tnsre.2011.2157705.Search in Google Scholar
[23] S. Balasubramanian, J. Klein, and E. Burdet, “Robot-assisted rehabilitation of hand function,” Curr. Opin. Neurol., vol. 23, no. 6, pp. 661–670, 2010. https://doi.org/10.1097/WCO.0b013e32833e99a4.Search in Google Scholar PubMed
[24] C. J. Nycz, T. Butzer, O. Lambercy, J. Arata, G. S. Fischer, and R. Gassert, “Design and characterization of a lightweight and fully portable remote actuation system for use with a hand exoskeleton,” IEEE Robot. Autom. Lett., vol. 1, no. 2, pp. 976–983, 2016. https://doi.org/10.1109/LRA.2016.2528296.Search in Google Scholar
[25] M. Li, B. He, Z. Liang, et al.., “An attention-controlled hand exoskeleton for the rehabilitation of finger extension and flexion using a rigid-soft combined mechanism,” Front. Neurorobot., vol. 13, p. 34, 2019. https://doi.org/10.3389/fnbot.2019.00034.Search in Google Scholar PubMed PubMed Central
[26] P. S. Smith, H. R. Dinse, T. Kalisch, M. Johnson, and D. Walker-Batson, “Effects of repetitive electrical stimulation to treat sensory loss in persons poststroke,” Arch. Phys. Med. Rehabil., vol. 90, no. 12, pp. 2108–2111, 2009. https://doi.org/10.1016/j.apmr.2009.07.017.Search in Google Scholar PubMed
[27] J. C. Kattenstroth, T. Kalisch, S. Peters, T. Martin, and H. R. Dinse, “Long-term sensory stimulation therapy improves hand function and restores cortical responsiveness in patients with chronic cerebral lesions. Three single case studies,” Front. Hum. Neurosci., vol. 6, p. 244, 2012. https://doi.org/10.3389/fnhum.2012.00244.Search in Google Scholar PubMed PubMed Central
[28] A. Gay, S. Parratte, B. Salazard, et al.., “Proprioceptive feedback enhancement induced by vibratory stimulation in complex regional pain syndrome type I: an open comparative pilot study in 11 patients,” Jt. Bone Spine, vol. 74, no. 5, pp. 461–466, 2007. https://doi.org/10.1016/j.jbspin.2006.10.010.Search in Google Scholar PubMed
[29] T. Noma, S. Matsumoto, M. Shimodozono, S. Etoh, and K. Kawahira, “Anti-spastic effects of the direct application of vibratory stimuli to the spastic muscles of hemiplegic limbs in post-stroke patients: a proof-of-principle study,” J. Rehabil. Med., vol. 44, no. 4, pp. 325–330, 2012. https://doi.org/10.2340/16501977-0946.Search in Google Scholar PubMed
[30] B. Marconi, G. M. Filippi, G. Koch, et al.., “Long-term effects on cortical excitability and motor recovery induced by repeated muscle vibration in chronic stroke patients,” Neurorehabil. Neural Repair, vol. 25, no. 1, pp. 48–60, 2011. https://doi.org/10.1177/1545968310376757.Search in Google Scholar PubMed
[31] E. Tavernese, M. Paoloni, M. Mangone, et al.., “Segmental muscle vibration improves reaching movement in patients with chronic stroke. A randomized controlled trial,” NeuroRehabilitation, vol. 32, no. 3, pp. 591–599, 2013. https://doi.org/10.3233/nre-130881.Search in Google Scholar
[32] T. Platz and S. Roschka, Rehabilitative Therapie bei Armlähmungen nach einem Schlaganfall: Patientenversion der Leitlinie der Deutschen Gesellschaft für Neurorehabilitation, Bad Honnef, Hippocampus-Verl, 2011.Search in Google Scholar
[33] O. Lambercy, Y. Kim, and R. Gassert, “Robot-assisted assessment of vibration perception and localization on the hand,” Disabil. Rehabil. Assist. Technol., vol. 8, no. 2, pp. 129–135, 2013. https://doi.org/10.3109/17483107.2012.737535.Search in Google Scholar PubMed
[34] S. Jong Kim and S. Choi-Kwon, “Discriminative sensory dysfunction after unilateral stroke,” Stroke, vol. 27, no. 4, pp. 677–682, 1996. https://doi.org/10.1161/01.str.27.4.677.Search in Google Scholar PubMed
[35] B. R. Brewer, M. Fagan, R. L. Klatzky, and Y. Matsuoka, “Perceptual limits for a robotic rehabilitation environment using visual feedback distortion,” IEEE Trans. Neural Syst. Rehabil. Eng., vol. 13, no. 1, pp. 1–11, 2005. https://doi.org/10.1109/tnsre.2005.843443.Search in Google Scholar
[36] I. Oakley, Y. Kim, J. Lee, and J. Ryu, “Determining the feasibility of forearm mounted vibrotactile displays,” in 2006 14th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, Alexandria, VA, USA, IEEE, 2006, pp. 27–34.10.1109/HAPTIC.2006.1627079Search in Google Scholar
[37] Y. Kim, M. Harders, and R. Gassert, “Identification of vibrotactile patterns encoding obstacle distance information,” IEEE Trans. Haptics, vol. 8, no. 3, pp. 298–305, 2015. https://doi.org/10.1109/toh.2015.2415213.Search in Google Scholar PubMed
[38] J. B. F. van Erp, “Absolute localization of vibrotactile stimuli on the torso,” Percept. Psychophys., vol. 70, no. 6, pp. 1016–1023, 2008. https://doi.org/10.3758/pp.70.6.1016.Search in Google Scholar PubMed
[39] Y. Kim and M. Harders, “Haptically-assisted interfaces for persons with visual impairments,” in Haptic Interfaces for Accessibility, Health, and Enhanced Quality of Life, Springer, 2020, pp. 35–63.10.1007/978-3-030-34230-2_2Search in Google Scholar
[40] S. Zacher and M. Reuter, Regelungstechnik für Ingenieure: Analyse, Simulation und Entwurf von Regelkreisen; mit 96 Beispielen und 32 Aufgaben. 14., korr. Aufl. Lehrbuch, Wiesbaden, Springer Vieweg, 2014.10.1007/978-3-8348-2216-1Search in Google Scholar
[41] Z. Yue, X. Zhang, and J. Wang, “Hand rehabilitation robotics on poststroke motor recovery,” Behav. Neurol., vol. 2017, p. 3908135, 2017. https://doi.org/10.1155/2017/3908135.Search in Google Scholar PubMed PubMed Central
[42] R. Mazgut, P. Spanik, J. Koscelnik, and P. Sindler, “The measurement of balance by the accelerometer and gyroscope,” in 2014 ELEKTRO, Rajecké Teplice, Slovakia, IEEE, 2014, pp. 192–196.10.1109/ELEKTRO.2014.6847899Search in Google Scholar
[43] C. E. Winward, P. W. Halligan, and D. T. Wade, “The Rivermead assessment of somatosensory performance (RASP): standardization and reliability data,” Clin. Rehabil., vol. 16, no. 5, pp. 523–533, 2002. https://doi.org/10.1191/0269215502cr522oa.Search in Google Scholar PubMed
[44] R. W. Bohannon and M. B. Smith, “Interrater reliability of a modified ashworth scale of muscle spasticity,” Phys. Ther., vol. 67, no. 2, pp. 206–207, 1987. https://doi.org/10.1093/ptj/67.2.206.Search in Google Scholar PubMed
[45] R. Rätz, R. M. Müri, and L. Marchal-Crespo, “Assessment of clinical requirements for a novel robotic device for upper-limb sensorimotor rehabilitation after stroke,” in International Conference on NeuroRehabilitation, VirBELA (virtual platform), Springer, 2020, pp. 171–175.10.1007/978-3-030-70316-5_28Search in Google Scholar
[46] J. C. van den Noort, V. A. Scholtes, J. G. Becher, and J. Harlaar, “Evaluation of the catch in spasticity assessment in children with cerebral palsy,” Arch. Phys. Med. Rehabil., vol. 91, no. 4, pp. 615–623, 2010. https://doi.org/10.1016/j.apmr.2009.12.022.Search in Google Scholar PubMed
[47] G. Vallar, “Spatial frames of reference and somatosensory processing: a neuropsychological perspective,” Philos. Trans. R. Soc. Lond., B, Biol. Sci., vol. 352, no. 1360, pp. 1401–1409, 1997. https://doi.org/10.1098/rstb.1997.0126.Search in Google Scholar PubMed PubMed Central
[48] N. Murillo, J. Valls-Sole, J. Vidal, E. Opisso, J. Medina, and H. Kumru, “Focal vibration in neurorehabilitation,” Eur. J. Phys. Rehabil. Med., vol. 50, no. 2, pp. 231–242, 2014.Search in Google Scholar
[49] I. Schindler, G. Kerkhoff, H. O. Karnath, I. Keller, and G. Goldenberg, “Neck muscle vibration induces lasting recovery in spatial neglect,” J. Neurol. Neurosurg. Psychiatry, vol. 73, no. 4, pp. 412–419, 2002. https://doi.org/10.1136/jnnp.73.4.412.Search in Google Scholar PubMed PubMed Central
[50] K. Kamada, M. Shimodozono, H. Hamada, and K. Kawahira, “Effects of 5 minutes of neck-muscle vibration immediately before occupational therapy on unilateral spatial neglect,” Disabil. Rehabil., vol. 33, nos. 22–23, pp. 2322–2328, 2011. https://doi.org/10.3109/09638288.2011.570411.Search in Google Scholar PubMed
© 2022 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Editorial
- Special issue: AUTOMED 2021: Automation in Medical Technology
- Methods
- Score rectification for online assessments in robot-assisted arm rehabilitation
- Concept for the testing of automated functions in therapeutic medical devices
- Applications
- Model-based analysis and optimization of pressure-controlled ventilation of COPD patients in relation to BMI
- Non-occlusive pumping principle for blood pump application
- Determining relationship between bone screw insertion torque and insertion speed
- Model predictive control for retinal laser treatment at 1 kHz
- PoRi device: portable hand assessment and rehabilitation after stroke
- Hardware development and control of a motorized rollator as an extension for exoskeletons
- Dissertations
- Machine learning with nonlinear state space models
- Perönliches
- Nachruf: Prof. Dr. rer. nat. Henning Tolle verstorben
Articles in the same Issue
- Frontmatter
- Editorial
- Special issue: AUTOMED 2021: Automation in Medical Technology
- Methods
- Score rectification for online assessments in robot-assisted arm rehabilitation
- Concept for the testing of automated functions in therapeutic medical devices
- Applications
- Model-based analysis and optimization of pressure-controlled ventilation of COPD patients in relation to BMI
- Non-occlusive pumping principle for blood pump application
- Determining relationship between bone screw insertion torque and insertion speed
- Model predictive control for retinal laser treatment at 1 kHz
- PoRi device: portable hand assessment and rehabilitation after stroke
- Hardware development and control of a motorized rollator as an extension for exoskeletons
- Dissertations
- Machine learning with nonlinear state space models
- Perönliches
- Nachruf: Prof. Dr. rer. nat. Henning Tolle verstorben
