PORTFOLIO

Stroke is the most common cause of adult disability and often affects upper limb function on one side of the body, resulting in a reduction of independence and quality of life. The choice of the therapy plan for each patient relies on the outcomes of clinical assessment tests. These are also used to determine the amount of therapy reimbursed by the insurance and when a patient is ready to leave the hospital. However, despite important advances in medical technology over the past decades, these tests still make use of rudimentary tools as well as the subjective judgment of the therapist to evaluate upper limb function. Furthermore, the measures can vary depending on the therapist performing the evaluation and are often time consuming to apply.

The Rehabilitation Engineering Lab (RELab) at ETH Zurich has developed the Virtual Peg Insertion Test (VPIT), an assessment test combining robotics and virtual reality to objectively evaluate arm and hand sensorimotor functions in stroke patients. The VPIT acquires quantitative data reflecting diverse impairments, such as muscle weakness, poor coordination, tremor, abnormal muscle tone, etc., through the measurement of position, orientation and interaction forces during a functionally relevant motor task. Feature extraction algorithms provide an immediate evaluation of arm and hand sensorimotor function after the completion of the test and allow reducing the assessment time by about 75%. This novel assessment tool has the potential to improve current clinical diagnostics by providing objective and repeatable measurements. Patients suffering from neurological diseases would largely benefit from early and accurate diagnosis and the establishment of a well-adapted therapy.

The field of rehabilitation robotics is still in its infancy and there is currently no product providing feature extraction algorithms to evaluate impairment levels similar to those proposed by the VPIT. It thus has a great potential to improve current rehabilitation practice and provide novel insights to researchers.

A prototype has been developed and used for clinical trials in major rehabilitation centers in Switzerland, Belgium and Canada. Data has been collected from 120 healthy subjects of different age groups, to establish baseline performance, as well as from patients with neurologically injury suffering from stroke, spinal cord injury, and multiple sclerosis to develop an assessment scale for upper limb sensorimotor function. With the help of the Gebert Rüf Stiftung, both hardware and software have been improved in terms of usability and robustness.

Lambercy, O., Fluet, M-C., Lamers, I., Kerkhofs, L., Feys, P. and Gassert, R. (2013). Assessment of upper limb motor function in patients with Multiple Sclerosis using the Virtual Peg Insertion Test: a pilot study. IEEE International Conference on Rehabilitation Robotics (ICORR), accepted;
Fluet, M.-C., Lambercy, O. and Gassert, R. (2012). Effects of 2D/3D Visual Feedback and Visuomotor Collocation on Motor Performance in a Virtual Peg Insertion Test. Proc. IEEE Engineering in Medicine and Biology Conference (EMBC), pp. 4776-4779;
Fluet, M.-C., Lambercy, O., and Gassert, R. (2011). Upper limb assessment using a virtual peg insertion test. Proc. IEEE International Conference on Rehabilitation Robotics (ICORR), pages 1-6;
Emery, C., Samur, E., Lambercy, O., Bleuler, H. and Gassert, R. (2010). Haptic/VR Clinical Assessment Tool for Fine Motor Control. In Proc. Eurohaptics 2010, pages 186–193.