“We have a unique interdisciplinary research environment for neurorehabilitation in Zurich” says Prof. Roger Gassert. He and his team develop new robotic assessment and training devices to advance sensory‐motor rehabilitation and support people with impairments. Roger Gassert was recently appointed by the ETH Council as Associate Professor of Rehabilitation Engineering. His chair is financially supported by Hocoma, a spin-off of the University Hospital Balgrist, Zurich. ZNZ News spoke with Professor Gassert about his research plans.
“The first spark for rehabilitation engineering in Zurich was the development of the Lokomat, a robot for locomotion training, at Balgrist. The field and the network was then greatly strengthened by the NCCR Neuro”, says Gassert. “It brought together neuroscientists, biologists, clinicians and engineers and has created an interdisciplinary research environment in Zurich that is unique in its form.” The medical technology company Hocoma has played an important role in this network. The longstanding collaboration with the company has been very fruitful for both sides, with Hocoma translating basic and applied research to the clinic. “Hocoma has certainly thrived on the excellent local research environment and now they have given something back by supporting research in this important field”, Gassert explains.
Robot-assisted home therapy
“A big collaboration project we have just completed with Hocoma and clinical partners from the University Hospital Zurich and Balgrist University Hospital is the ArmeoSenso. It is a sensor-based movement tracking system developed for therapy and monitoring of improvements in arm function in patients that have suffered stroke or spinal cord injury, but it can be used for many other disorders that involve moderately impaired upper limb movement. A prerequisite for its use is that the patient has remaining arm function. The ArmeoSenso is intended for independent home therapy of patients after they have left the clinic. A pilot study demonstrated the feasibility and acceptance of this approach.”
Fine-tuning of therapies
“My group develops novel robotic rehabilitation tools with the goal to optimize training for each individual patient. An important advantage of using robots in rehabilitation therapy is that they are equipped with many sensors and can therefore perform a multitude of objective measurements during therapy. This also enables us to adapt exercise difficulty and thereby optimally challenge patients throughout the training. The exciting thing is that, already now, robot-assisted training is as effective as conventional physiotherapy. The reason we do not reach a higher therapy success, both in conventional and robot-assisted therapy, is that we still do not completely understand what happens in the brains of patients undergoing therapy, nor what the optimal therapy program looks like for individual patients. Therefore one of my research goals is to better understand the relation between movement therapy and brain reorganization in order to fine-tune therapies.
Predicting the effect of therapy using fMRI
Robots enable us to control, quantify and manipulate physical interactions and make a prediction of the effect of the therapy. We can create reproducible experimental conditions between individuals and investigate the neural correlates using non-invasive neuroimaging such as functional MRI. For instance, we have created a robotic tool that moves subjects’ fingers with varying velocities and amplitudes while the subject lies in the MRI scanner bore. We use this tool to examine which brain networks are activated by these movements, and how these kinematic parameters modulate the activation. This could enable us to selectively stimulate brain networks and promote recovery.”
Addressing sensory deficits
“Apart from motor impairments, many patients also suffer from sensory deficits. These deficits are often neglected, but contribute to the success of a therapy. We characterize sensory deficits with dedicated assessment tools, and address them during therapy using a neurocognitive approach. For instance, patients are asked to squeeze the handles of a robot that simulates the mechanical properties of a virtual sponge. They have to rely on the forces they feel during the squeezing movements, in order to identify which of several sponges with varying resistance they are experiencing. In this approach, both motor and sensory function are addressed, and linked through a cognitive task. The robot continuously monitors sensory and motor deficits and adapts the difficulty of the therapy in order to optimally challenge and engage the patient. We are currently testing this robot-assisted therapy concept in the Clinica Hildebrand Centro di Riabilitazione Brissago, and first results are very promising.”
“These are only a few of my ongoing research projects, there are many other fascinating projects in my laboratory”, Gassert concludes. “I enjoy working in this group of people with complementary competences, but common interests. It creates a unique and fruitful network which has allowed us to develop improved therapeutic tools and generate novel insights in collaboration with our colleagues from the basic sciences and clinics.”
Further Reading
Media Release ETH Zurich:
Zurich spin-off enables professorship of rehabilitation engineering.
Assessment-driven selection and adaptation of exercise difficulty in robot-assisted therapy: a pilot study with a hand rehabilitation robot. Metzger JC, Lambercy O, Califfi A, Dinacci D, Petrillo C, Rossi P, Conti FM, Gassert R. J Neuroeng Rehabil. 2014 Nov 15;11(1):154. More
Rehabilitation Engineering Lab