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- W2885778863 abstract "This paper presents an approach for monitoring exercises of hand rehabilitation for past stroke patients. The developed solution uses a Leap Motion controller as hand-tracking device and embeds a supervised Machine Learning methodology. Support Vector Machine (SVM) is used in order to assess the correctness of a set of simple rehabilitation exercises performed with a single hand. The basic SVM model was extended with particular interest for defining feature vectors in a continues environment. The proposed method incorporated leap motion data, normalization of angles and gesture recognition. A software system was developed to provide patients with a set of exercise corrections and guidance for rehabilitation." @default.
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- W2885778863 date "2018-07-01" @default.
- W2885778863 modified "2023-09-26" @default.
- W2885778863 title "Hand Rehabilitation via Gesture Recognition Using Leap Motion Controller" @default.
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- W2885778863 doi "https://doi.org/10.1109/hsi.2018.8431349" @default.
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