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- W2801477779 abstract "This chapter presents a novel approach to recognize fourteen gestures which would help us recognize muscle and joint pains in human body. The subject is acknowledged in a twenty joint skeletal form with the help of Microsoft’s Kinect. In order to extract features from the subject, those twenty body joints are worked on and ten features in the form of distances and angles are calculated. For recognizing unknown sample gestures, a neural network with Levenberg-Marquardt learning rule has been used. The explained methodology provides an accuracy of 88.19%, which is relatively higher than other algorithms previously used in elderly healthcare domain." @default.
- W2801477779 created "2018-05-17" @default.
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- W2801477779 date "2018-01-01" @default.
- W2801477779 modified "2023-09-28" @default.
- W2801477779 title "Neural Network Based Physical Disorder Recognition for Elderly Health Care" @default.
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- W2801477779 doi "https://doi.org/10.1007/978-3-319-89629-8_12" @default.
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