Dr Thierry Keller Director of Rehabilitation at TECNALIA Research & Innovation discusses how robotic technologies can help assist rehabilitation

Rehabilitation robotics includes a wide range of stationary and portable electromechanical assisted training devices with the main purpose to train lost body functions caused by neurological or traumatic events. Although a number of systems have already been developed 50 or more years ago rehabilitation robots became wider-spread and clinically accepted only in the last decade.

In neurorehabilitation, robots are mainly used as gait trainers for lower limbs and as arm and hand trainers for reaching and grasping. They primarily support physical therapy as a tool to optimise interventions. So far strongest evidence could be shown for intensive high repetitive task-oriented and task-specific training 1, functions that can be performed by robots with high precision and endurance.

Five years ago more than 80 European or multinational projects on this subject were counted, which led to the implementation of the COST Action TD 1006: European Network on Robotics for Neurorehabilitation.

The main objective has been to enable the development of innovative, efficient, and patient-tailored robot-assisted therapies for neuro-motor recovery, incorporating the latest findings from clinical neurorehabilitation, rehabilitation robotics, computational neuroscience, and motor neuroscience.

More than 100 researchers, clinicians, and engineers from 23 European countries participated in the

Action to:

  • Coordinate, streamline interdisciplinary research to better understand robot mediated rehabilitation and recovery;
  • Facilitate multicenter studies to prove evidence of new approaches;
  • Provide clear, evidence-based guidelines for patient selection and application of robot-aided therapy;
  • Recommend necessary features for new and efficient robot-based therapies.

A number of randomised controlled trials and systematic reviews have recently been published 2,3,4 with the main conclusion: there is evidence that rehabilitation robotics improves recovery of function both in upper and lower extremities. Meta-analyses showed that robot-assisted arm training did improve activities of daily living as well as arm function 3 and that people who receive electromechanical-assisted gait training in combination with physiotherapy after stroke are more likely to achieve independent walking than people who receive gait training without these devices 4. Although these conclusions are all positive many promises and expectations have not been proven yet. There are critical voices that ask for more specific research 5. The role and type of device one still not clear, optimal training duration (dose responses) but also the effects of specific training paradigms (specificity) are unclear, so far it has been shown that the training intensity matters.

In a position paper Action, TD1006 members have listed a number of research directions and combinational therapies to unveil the power of neuroplasticity by using robotic device 6. The combination of specific task-oriented training guided by surrogate markers from the brain and the application of neurostimulation might impact neuroplasticity. Such training strategies may include perturbation/adaptation, assistance control, adaptive gravity support, brain-computer interfaces and targeted/augmented feedback.

Another approach to increase the effectiveness of neurorehabilitation with robotics simply lies in the availability and inclusion of therapy. Here robotic technologies can strongly contribute. As a therapeutic tool, robotics increases training intensity, can be combined with engaging social and gaming features enable a higher patient throughput by allowing the treatment of several patients by one therapist in parallel and can facilitate guided motor training remotely through telerehabilitation. Therefore rehabilitation robotics is considered as a tool to overcome the demographic challenge in neurorehabilitation.

From the economic side, rehabilitation robotics looks attractive. The field is growing with considerable 2-digit growth rates. Some of the conservative market reports estimate a Compound Annual Growth Rate (CAGR) of 20% 7. The most optimistic estimate has been published by the Wintergreen Research report and foresees growth in rehabilitation robotics, active prostheses and exoskeletons from $43.3m (2014) to $1.8bn (2020) US$ (CAGR 86%) 8.

The International Industry Society in Advanced Rehabilitation Technology (IISART) founded in 2011 by a majority of European rehabilitation robotics manufacturers and suppliers have identified 2 main tasks to transfer the field from a research-driven area to a successful Medtech business: Education and Standardisation. With training and competency guidelines, checklists and documentation for therapists and clinicians, and training support for higher education schools and PT/OT programs, the education working group provides tools to ensure proper training and evaluation of therapists on the safe and effective use of these devices. Standards that are for the benefit of the patients but also applicable by the industry and unified (EU wide) regulation and reimbursement policies are necessary for the field to grow. To achieve this IISART offers a platform for promoting the cost-benefits of advanced rehabilitation technologies to care providers and to payers, as well as to position the outcome of advanced rehabilitation technologies to healthcare authorities and health technology assessment agencies.


1 Veerbeek JM, van Wegen E, van Peppen R, van der Wees PJ, Hendriks E, et al. (2014) What Is the Evidence for Physical Therapy Poststroke? A Systematic Review and Meta-Analysis. PLoS ONE 9(2): e87987.

2 Lo A, Guarino P, Richards L, Haselkorn J, Wittenberg G, et al. (2010) Robot-assisted therapy for long-term upper-limb impairment after stroke. N Engl J Med 362: 1772-1783.

3 Mehrholz J, Platz T, Kugler J, Pohl M (2008) Electromechanical and robot-assisted arm training for improving arm function and activities of daily living after stroke. Cochrane Database Syst Rev: CD006876.

4 Mehrholz J, Elsner B, Werner C, Kugler J, Pohl M (2013) Electromechanical- assisted training for walking after stroke. Cochrane Database Syst Rev: CD006185.

5 Dobkin B, Duncan P (2012) Should body weight-supported treadmill training and robotic-assistive steppers for locomotor training trot back to the starting gate? Neurorehabil Neural Repair 26: 308-317.

6 Turner DL, Ramos-Murguialday A, Birbaumer N, Hoffmann U and Luft A (2013) Neurophysiology of robot-mediated training and therapy: a perspective for future use in clinical populations. Front. Neurol. 4:184.

7 Cavuoto J, Cornett G, Grill W, Pope D (2012), The Market for Neurotechnology: 2012-2016, Neurotech Reports.

8 Curtiss ET, Eustis S, et al. (2014) Rehabilitation Robots, Active Prostheses, and Exoskeletons: Market Shares, Strategies, and Forecasts, Worldwide, 2014 to 2020, WinterGreen Research.

Acknowledgement: This publication is supported by COST through the Action TD1006.


Dr Thierry Keller

Director Area Rehabilitation & Head of Rehabilitation

TECNALIA Research & Innovation – European Networks on Robotics for Neuro-rehabilitation

Tel: +34 667 119652





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