ETH Summer School on Soft Robotics
Thank you very much for joining SSSR 2012 in Zurich! Recap
1st Swiss rtfMRI Neurofeedback Conference
A big thank you to all the speakers and over 150 participants! Recap
Kaspar Leuenberger presents his PhD project at the ETH Tag.
We welcome Frieder Wittman who joins us from the Technical University Munich.
Mike Rinderknecht receives the 1st prize in the IEEE Region 8 Student Paper Contest
2012 Swiss Brain League research prize awarded to Silvio Ionta and Lukas Heydrich for work in collaboration with RELab.
RELab present at the BrainFair Zurich 2012.
RELab hosts the 1st Swiss rtfMRI Neurofeedback Conference with over 150 participants.
We welcome Auralius Manurung, who joins us from the Gyeongsang National University, South Korea.
Marie-Christine Fluet receives the Best Poster Award at the 2011 International Conference on Rehabilitation Robotics (ICORR 2011)
RELab featured on ETH Life
Our daily activities are dependent on the use of our hands and arms. People suffering from functional deficits of the upper limb following a stroke are often severely limited in the execution of simple tasks. Traditional therapy to regain sensorimotor functions has some limitations, but can be complemented with robotic devices, which allow increasing the intensity of treatment proposed to post-stroke patients and providing objective measures to assess hand function.
We are developing novel robotic devices to train and assess the hand and forearm functions. The HapticKnob is a 2-degrees of freedom (DOF) robot designed to train hand grasping and forearm pronation/supination developed at the National University of Singapore. In a previous study with chronic stroke patients, significant improvement in upper limb motor function was observed after a 6-week therapy with the HapticKnob, suggesting that robot-assisted training of distal segments of the upper limb might be beneficial for restoring arm and hand function..
We developed an improved version of the HapticKnob, called the ReHapticKnob, with the same two DOF to train and assess hand grasping and forearm rotation. This new device is able to render a wider range of impedances (Z-Width) thanks to a novel design concept and state of the art interaction control algorithms. Pilot data have been collected with 6 patients with neurological injuries, and we are currently preparing a clinical study with the ReHatpicKnob, taking advantage of the high fidelity virtual object rendering ability of the robot to propose exercises to train and assess motor and sensory function in stroke patients.
Figure 1: Two generations of hand rehabilitation robots: the HapticKnob (left) and the new ReHapticKnob (right).
Dr. Olivier Lambercy
Rehabilitation Engineering Lab
Rehabilitation Engineering Lab
Dr. med. Dipl. Phys. ETHZ Fabio Conti (Clinica Hildebrand Centro di Riabilitazione Brissago)
Prof. Dr. Marco Santello (Arizona State University)
This work is supported by the NCCR Neural Plasticity and Repair, Swiss National Science Fundation and the ETH CHIRP1 Research Grant on Cortically-Driven Assistance Adaptation during Sensorimotor Training.
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