Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-19808
Vallery, H; van Asseldonk, E H F; Busslinger, M; van der Kooij, H (2009). Reference trajectory generation for rehabilitation robots: complementary limb motion estimation. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 17(1):23-30.
For gait rehabilitation robots, an important question is how to ensure stable gait, while avoiding any interaction forces between robot and human in case the patient walks correctly. To achieve this, the definition of "correct" gait needs to adapted both to the individual patient and to the situation. Recently, we proposed a method for online trajectory generation that can be applied for hemiparetic subjects. Desired states for one (disabled) leg are generated online based on the movements of the other (sound) leg. An instantaneous mapping between legs is performed by exploiting physiological interjoint couplings. This way, the patient generates the reference motion for the affected leg autonomously. The approach, called Complementary Limb Motion Estimation (CLME), is implemented on the LOPES gait rehabilitation robot and evaluated with healthy subjects in two different experiments. In a previously described study, subjects walk only with one leg, while the robot's other leg acts as a fake prosthesis, to simulate complete loss of function in one leg. This study showed that CLME ensures stable gait. In a second study, to be presented in this paper, healthy subjects walk with both their own legs to assess the interference with self-determined walking. Evaluation criteria are: Power delivered to the joints by the robot, electromyography (EMG) distortions, and kinematic distortions, all compared to zero torque control, which is the baseline of minimum achievable interference. Results indicate that interference of the robot is lower with CLME than with a fixed reference trajectory, mainly in terms of lowered exchanged power and less alteration of EMG. This implies that subjects can walk more naturally with CLME, and they are assisted less by the robot when it is not needed. Future studies with patients are yet to show whether these properties of CLME transfer to the clinical domain.
|Item Type:||Journal Article, refereed, original work|
|Communities & Collections:||04 Faculty of Medicine > Balgrist University Hospital, Swiss Spinal Cord Injury Center|
|DDC:||610 Medicine & health|
|Deposited On:||22 Jul 2009 09:50|
|Last Modified:||27 Nov 2013 19:46|
|Additional Information:||© 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE|
|Citations:||Web of Science®. Times Cited: 27|
Scopus®. Citation Count: 33
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