Title: Hybrid Feature Subset Selection for the Quantitative Assessment of Skills of Stroke Patients in the Activity of Daily Living Tasks
Authors: Van Dijck, Gert
Van Hulle, Marc
Van Vaerenbergh, Jozef #
Issue Date: Aug-2006
Publisher: IEEE
Host Document: Proceedings of the 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society pages:5699-5703
Conference: Annual International Conference of the IEEE Engineering in Medicine and Biology Society edition:28 location:New York, USA date:30 August - 3 September 2006
Abstract: Stroke patients have a decreased ability in performing Activity of Daily Living (ADL) tasks such as in ‘drinking a glass of water’, ‘turning a key’, ‘picking up a spoon’, ‘lifting a bag’, ‘reaching a bottle’ and ‘lifting and carrying a bottle’. These tasks can be quantified by measuring forces and torques exerted on the objects. However, the resulting force and torque time series represent information at a very low level of abstraction and don’t inform clinicians what really distinguishes patients from normal controls in performing these tasks. We conduct an extensive quantitative analysis of these tasks and derive interesting features from the time signals that characterize the differences in behavior between patients and normal controls. We show that ‘drinking a glass’ and ‘turning a key’ are the most discriminative tasks; furthermore we show that the ability or disability to synchronize the thumb and the middle finger is one of the most important features.
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Laboratory for Neuro- and Psychofysiology
Research Group Neurophysiology
# (joint) last author

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