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Session: Poster session I
Session starts: Thursday 24 January, 15:00

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Ard Westerveld (University of Twente)
Alexander Kuck (University of Twente)
Alfred Schouten (Delft University of Technology)
Peter Veltink (University of Twente)
Herman van der Kooij (University of Twente)

Abstract:
Stroke often has a disabling effect on the ability to functionally use the hand. Control of finger and thumb positioning is necessary for many activities in daily life. Functional Electrical Stimulation (FES) can assist patients in relearning movements after stroke [1,2]. Recently, possibilities for activating individual fingers by FES have been explored, showing the need for an individualized approach [3]. We evaluated the feasibility of subject specific approaches for positioning the thumb and fingers for grasp and release of differently sized objects. Assistance based on these approaches may be used in rehabilitation after stroke. A model predictive controller (MPC) was compared with a proportional (P) feedback controller [4]. Both methods were compared on their performance in tracking reference trajectories and in the capability of grasping, holding and releasing objects. Both methods were able to selectively activate the fingers such that differently sized objects, selected from the Action Research Arm test, could be grasped in healthy subjects. The MPC method gave better results and was easier to use in practice, as this method was based on a single identification of a model of the biological system. The P-controller had more parameters which need to be set correctly, and therefore needed more time to initialize. In more severely affected stroke patients, the controller performance in selective activation of fingers was limited, but was still applicable for grasp and release of larger objects. The results of the subject specific control approaches are promising, especially for the MPC. Future research will include optimizing the method for applicability in rehabilitation, by reducing the time needed for set up and initialization and improving the performance even further. In addition, combination with robotic assistance of reaching is planned. This hybrid approach will lead to a novel functional training environment for reach, grasp and release after stroke which is able to adapt its assistance to the needs of the individual patient.