Skip to main content

Design, development and deployment of a hand/wrist exoskeleton for home-based rehabilitation after stroke - SCRIPT project

  • F. Amirabdollahian (a1), S. Ates (a2), A. Basteris (a1), A. Cesario (a3), J. Buurke (a4), H. Hermens (a4), D. Hofs (a4), E. Johansson (a5), G. Mountain (a6), N. Nasr (a6), S. Nijenhuis (a4), G. Prange (a4), N. Rahman (a1), P. Sale (a3), F. Schätzlein (a6), B. van Schooten (a4) and A. Stienen (a2)...

Changes in world-wide population trends have provided new demands for new technologies in areas such as care and rehabilitation. Recent developments in the the field of robotics for neurorehabilitation have shown a range of evidence regarding usefulness of these technologies as a tool to augment traditional physiotherapy. Part of the appeal for these technologies is the possibility to place a rehabilitative tool in one's home, providing a chance for more frequent and accessible technologies for empowering individuals to be in charge of their therapy.

Objective: this manuscript introduces the Supervised Care and Rehabilitation Involving Personal Tele-robotics (SCRIPT) project. The main goal is to demonstrate design and development steps involved in a complex intervention, while examining feasibility of using an instrumented orthotic device for home-based rehabilitation after stroke.

Methods: the project uses a user-centred design methodology to develop a hand/wrist rehabilitation device for home-based therapy after stroke. The patient benefits from a dedicated user interface that allows them to receive feedback on exercise as well as communicating with the health-care professional. The health-care professional is able to use a dedicated interface to send/receive communications and remote-manage patient's exercise routine using provided performance benchmarks. Patients were involved in a feasibility study (n=23) and were instructed to use the device and its interactive games for 180 min per week, around 30 min per day, for a period of 6 weeks, with a 2-months follow up. At the time of this study, only 12 of these patients have finished their 6 weeks trial plus 2 months follow up evaluation.

Results: with the “use feasibility” as objective, our results indicate 2 patients dropping out due to technical difficulty or lack of personal interests to continue. Our frequency of use results indicate that on average, patients used the SCRIPT1 device around 14 min of self-administered therapy a day. The group average for the system usability scale was around 69% supporting system usability.

Conclusions: based on the preliminary results, it is evident that stroke patients were able to use the system in their homes. An average of 14 min a day engagement mediated via three interactive games is promising, given the chronic stage of stroke. During the 2nd year of the project, 6 additional games with more functional relevance in their interaction have been designed to allow for a more variant context for interaction with the system, thus hoping to positively influence the exercise duration. The system usability was tested and provided supporting evidence for this parameter. Additional improvements to the system are planned based on formative feedback throughout the project and during the evaluations. These include a new orthosis that allows a more active control of the amount of assistance and resistance provided, thus aiming to provide a more challenging interaction.

    • Send article to Kindle

      To send this article to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle.

      Note you can select to send to either the or variations. ‘’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Design, development and deployment of a hand/wrist exoskeleton for home-based rehabilitation after stroke - SCRIPT project
      Available formats
      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about sending content to Dropbox.

      Design, development and deployment of a hand/wrist exoskeleton for home-based rehabilitation after stroke - SCRIPT project
      Available formats
      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about sending content to Google Drive.

      Design, development and deployment of a hand/wrist exoskeleton for home-based rehabilitation after stroke - SCRIPT project
      Available formats
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (, which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Corresponding author
*Corresponding author. E-mail:
Hide All
1.Schaechter J. D., “Motor rehabilitation and brain plasticity after hemiparetic stroke,” Prog. Neurobiology 73 (1), 6172 (2004).
2.Krakauer J. W., “Arm function after stroke: From physiology to recovery,” Semin. Neurology 25 (4), 384395 (2005).
3.Fisher B. E. and Sullivan K. J., “Activity-dependent factors affecting poststroke functional outcomes,” Top. Stroke Rehabil. 8 (3), 3144 (2001).
4.Wagenaar R. C. and Meijer O. G., “Effects of stroke rehabilitation: A critical review of the literature,” Rehabil. Sci. 4 (3), 6173 (1991).
5.Kwakkel G., Wagenaar R. C., Koelman T. W., Lankhorst G. J. and Koetsier J. C., “Effects of intensity of rehabilitation after stroke a research synthesis,” Stroke 28 (8), 15501556 (1997).
6.Kwakkel G., Wagenaar R. C., Twisk J. W. R., Lankhorst G. J. and Koetsier J. C., “Intensity of leg and arm training after primary middle-cerebral-artery stroke: a randomised trial,” Lancet 354 (9174), 191196 (1999).
7.Nelles G., Jentzen W., Jueptner M., Müller S. and Diener H. C., “Arm training induced brain plasticity in stroke studied with serial positron emission tomography,” Neuroimage 13 (6), 11461154 (2001).
8.Platz T., “Evidence-based arm rehabilitation–a systematic review of the literature,” Der Nervenarzt 74 (10), 841 (2003).
9.Kwakkel G., van Peppen R., Wagenaar R. C., Dauphinee S. W., Richards C., Ashburn A., Miller K., Lincoln N., Partridge C., Wellwood al., “Effects of augmented exercise therapy time after stroke a meta-analysis,” Stroke 35 (11), 25292539 (2004).
10.Lo A. C., Guarino P. D., Richards L. G., Haselkorn J. K., Wittenberg G. F., Federman D. G., Ringer R. J., Wagner T. H., Krebs H. I., Volpe B. al., “Robot-assisted therapy for long-term upper-limb impairment after stroke,” New England J. Med. 362 (19), 17721783 (2010).
11.Weiller C., Jüptner M., Fellows S., Rijntjes M., Leonhardt G., Kiebel S., Müller S., Diener H. C. and Thilmann A. F., “Brain representation of active and passive movements,” Neuroimage 4 (2), 105110 (1996).
12.Kaelin-Lang A., Sawaki L. and Cohen L. G., “Role of voluntary drive in encoding an elementary motor memory,” J. Neurophysiol. 93 (2), 10991103 (2005).
13.Feys H. M., De Weerdt W. J., Selz B. E., Steck G. A. C., Spichiger R., Vereeck L. E., Putman K. D. and Van Hoydonck G. A., “Effect of a therapeutic intervention for the hemiplegic upper limb in the acute phase after stroke a single-blind, randomized, controlled multicenter trial,” Stroke 29 (4), 785792 (1998).
14.Barreca S., Wolf S. L., Fasoli S. and Bohannon R., “Treatment interventions for the paretic upper limb of stroke survivors: A critical review,” Neurorehabilitation Neural Repair 17 (4), 220226 (2003).
15.Kahn L. E., Lum P. S., Rymer W. Z. and Reinkensmeyer D. J., “Robot-assisted movement training for the stroke-impaired arm: Does it matter what the robot does?,” J. Rehabil. Res. Dev. 43 (5), 619 (2006).
16.Feydy A., Carlier R., Roby-Brami A., Bussel B., Cazalis F., Pierot L., Burnod Y. and Maier M. A., “Longitudinal study of motor recovery after stroke recruitment and focusing of brain activation,” Stroke 33 (6), 16101617 (2002).
17.Prange G. B., Jannink M. J. A., Groothuis-Oudshoorn C. G. M., Hermens H. J. and IJzerman M. J., “Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke,” J. Rehabil. Res. Dev. 43 (2), 171 (2006).
18.Kwakkel G., Kollen B. J. and Krebs H. I., “Effects of robot-assisted therapy on upper limb recovery after stroke: A systematic review,” Neurorehabilitation Neural Repair 22 (2), 111121 (2008).
19.Mehrholz J., Platz T., Kugler J. and Pohl M., “Electromechanical and robot-assisted arm training for improving arm function and activities of daily living after stroke,” Stroke 40 (5), e392e393 (2009).
20.Hesse S., Schulte-Tigges G., Konrad M., Bardeleben A. and 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), 915920 (2003).
21.Krebs H. I., Celestino J., Williams D., Ferraro M., Volpe B. and Hogan N., “A Wrist Extension for Mit-Manus,” In: Advances in Rehabilitation Robotics (Springer Berlin Heidelberg, Germany, 2004) pp. 377390.
22.Krebs H. I., Volpe B. T., Williams D., Celestino J., Charles S. K., Lynch D. and Hogan N., “Robot-aided neurorehabilitation: A robot for wrist rehabilitation,” IEEE Trans. Neural Syst. Rehabil. Eng. 15 (3), 327335 (2007).
23.Masia L., Krebs H. I., Cappa P. and Hogan N., “Design and characterization of hand module for whole-arm rehabilitation following stroke,” IEEE/ASME Trans. Mechatronics 12 (4), 399407 (2007).
24.Loureiro R. C. V., Lamperd B., Collin C. and Harwin W. S., “Reach & Grasp Therapy: Effects of the gentle/g System Assessing Sub-Acute Stroke Whole-Arm Rehabilitation,” IEEE International Conference on Rehabilitation Robotics, 2009. ICORR 2009, IEEE (2009) pp. 755–760.
25.Carmeli E., Peleg S., Bartur G., Elbo E. and Vatine J.-J., “Handtutortm enhanced hand rehabilitation after stroke?a pilot study,” Physiotherapy Res. Int. 16 (4), 191200 (2011).
26.Winstein C. J. and Stewart J. C., “Conditions of task practice for individuals with neurologic impairments,” Textbook Neural Repair Rehabil. 2, 89102 (2006).
27.Molier B. I., Van Asseldonk E. H. F., Hermens H. J. and Jannink M. J. A., “Nature, timing, frequency and type of augmented feedback; does it influence motor relearning of the hemiparetic arm after stroke? a systematic review,” Disability & Rehabil. 32 (22), 17991809 (2010).
28.Molier B. I., Influence of Augmented Feedback on Learning Upper Extremity Tasks After Stroke (University of Twente, the Netherlands, 2012).
29.Patton J. L. and Mussa-Ivaldi F. A., “Robot-assisted adaptive training: Custom force fields for teaching movement patterns,” IEEE Trans. Biomed. Eng. 51 (4), 636646 (2004).
30.van Asseldonk E. H. F., Wessels M., Stienen A. H. A., van der Helm F. C. T. and van der Kooij H., “Influence of haptic guidance in learning a novel visuomotor task,” J. Physiol.-Paris 103 (3), 276285 (2009).
31.Shea C. H., Lai Q., Black C. and Park J.-H., “Spacing practice sessions across days benefits the learning of motor skills,” Hum. Mov. Sci. 19 (5), 737760 (2000).
32.Krebs H. I., Volpe B. T., Ferraro M., Fasoli S., Palazzolo J., Rohrer B., Edelstein L., Hogan al., “Robot-aided neurorehabilitation: From evidence-based to science-based rehabilitation,” Top. Stroke Rehabil. 8 (4), 5470 (2002).
33.Gaver B., Dunne T. and Pacenti E., “Design: cultural probes,” Interactions 6 (1), 2129 (1999).
34.Cooper A., Reimann R. and Cronin D., About face 3: The Essentials of Interaction Design (John Wiley & Sons, Wiley Publishing Inc, Indianapolis, USA, 2012).
35.Monk A., Davenport L., Haber J. and Wright P., Improving your Human-Computer Interface: A Practical Technique (Prentice Hall London, 1993).
36.Leon B., Basteris A. and Amirabdollahian F., “Comparing Recognition Methods to Identify Different Types of Grasps for Hand Rehabilitation,” 7th International Conference on Advances in Computer-Human Interactions. (ACHI2014) (2014) pp. 109–114.
37.Ates S., Lobo-Prat J., Lammertse P., van der Kooij H. and Stienen A. H. “Script Passive Orthosis: Design and Technical Evaluation of the Wrist and Hand Orthosis for Rehabilitation Training at Home. IEEE. . . International Conference on Rehabilitation Robotics:[proceedings] (2013) pp. 1–6.
38.Magill R. A. and Anderson D. I., Motor Learning and Control: Concepts and Applications, Vol. 11 (McGraw-Hill, New York, 2007).
39.Magermans D. J., Chadwick E. K. J., Veeger H. E. J. and Van Der Helm F. C. T., “Requirements for upper extremity motions during activities of daily living,” Clinical Biomechanics 20 (6), 591599 (2005).
40.van Andel C. J, Wolterbeek N., Doorenbosch C. A. M., Veeger DirkJan H. E. J. and Harlaar J., “Complete 3d kinematics of upper extremity functional tasks,” Gait Posture 27 (1), 120127 (2008).
41.Emken J. L., Bobrow J. E. and Reinkensmeyer D. J., “Adaptive human-robot interaction based on lag-lead modelling for home-based stroke rehabilitation,” IEEE International Conference on Systems, Man and Cybernetics (SMC2013) (IEEE, 2013).
42.Basteris A. and Amirabdollahian F., “Rapid Assessment of Range of Motion and Movement Duration During Human-Robot Interaction,” World Congress for NeuroRehabilitation (WCNR) 2014, Istanbul, Turkey (Apr. 8–12, 2014).
43.Emken J. L., Bobrow J. E. and Reinkensmeyer D. J., “Robotic Movement Training as an Optimization Problem: Designing a Controller that Assists Only as Needed,” Proceedings of the 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005, (IEEE, 2005) pp. 307–312.
44.Chemuturi R., Amirabdollahian F. and Dautenhahn K., “Adaptive training algorithm for robot-assisted upper-arm rehabilitation, applicable to individualised and therapeutic human-robot interaction,” J. Neuroengineering Rehabil. 10 (1), 102 (2013).
45.Guadagnoli M. A. and Lee T. D., “Challenge point: A framework for conceptualizing the effects of various practice conditions in motor learning,” J. Motor Behav. 36 (2), 212224 (2004).
46.Luft A. R., McCombe-Waller S., Whitall J., Forrester L. W., Macko R., Sorkin J. D., Schulz J. B., Goldberg A. P. and Hanley D. F., “Repetitive bilateral arm training and motor cortex activation in chronic stroke: a randomized controlled trial,” Jama 292 (15), 18531861 (2004).
47.Bangor A., Kortum P. and Miller J., “Determining what individual sus scores mean: Adding an adjective rating scale,” J. Usability Stud. 4 (3), 114123 (2009).
48.Coupar F., Pollock A., Legg L. A., Sackley C. and van Vliet P., “Home-based therapy programmes for upper limb functional recovery after stroke,” Cochrane Database Syst Rev. (2012). doi: 10.1002/14651858.CD006755.pub2.
49.Prange G. B., Nijenhuis S. M., Sale P., Cesario A., Nasr N., Mountain G., Amirabdollahian F. and Buurke J. H., “Preliminary Findings of Feasibility and Compliance of Technology-Supported Distal Arm Training at Home after Stroke,” In: Replace, Repair, Restore, Relieve - Bridging Clinical and Engineering Solutions in Neurorehabilitation (Jensen W., Andersen O. K. and Akay M., eds.) (Springer International Publishing, Berlin, 2014) pp. 665673.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

  • ISSN: 0263-5747
  • EISSN: 1469-8668
  • URL: /core/journals/robotica
Please enter your name
Please enter a valid email address
Who would you like to send this to? *



Full text views

Total number of HTML views: 3
Total number of PDF views: 681 *
Loading metrics...

Abstract views

Total abstract views: 841 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 15th December 2017. This data will be updated every 24 hours.