About: Recurrent Neural Network Based Early Prediction of Future Hand Movements

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type	http://eprints.org/ontology/ConferenceItemEPrint http://eprints.org/ontology/EPrint Article Academic Article
seeAlso	HTML Summary of #72664 Recurrent Neural Network Based Early Prediction of Future Hand Movements
sameAs	Recurrent Neural Network Based Early Prediction of Future Hand Movements
http://eprints.org/ontology/hasAccepted	Recurrent Neural Network Based Early Prediction of Future Hand Movements (PDF)
http://eprints.org/ontology/hasDocument	Recurrent Neural Network Based Early Prediction of Future Hand Movements (PDF) Recurrent Neural Network Based Early Prediction of Future Hand Movements (Other) Recurrent Neural Network Based Early Prediction of Future Hand Movements (Other) Recurrent Neural Network Based Early Prediction of Future Hand Movements (Other) Recurrent Neural Network Based Early Prediction of Future Hand Movements (Other) Recurrent Neural Network Based Early Prediction of Future Hand Movements (Other)
dc:hasVersion	Recurrent Neural Network Based Early Prediction of Future Hand Movements (PDF)
Title	Recurrent Neural Network Based Early Prediction of Future Hand Movements
described by	https://demo.openlinksw.com/about/id/entity/https/www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3
Date	2018-07-21
Creator	Huy Phan Fabrice Katzberg Philipp Koch Marco Maass Afred Mertins
status	peer reviewed published
Publisher	IEEE
abstract	This work focuses on a system for hand prostheses that can overcome the delay problem introduced by classical approaches while being reliable. The proposed approach based on a recurrent neural network enables us to incorporate the sequential nature of the surface electromyogram data and the proposed system can be used either for classification or early prediction of hand movements. Especially the latter is a key to a latency free steering of a prosthesis. The experiments conducted on the first three Ninapro databases reveal that the prediction up to 200 ms ahead in the future is possible without a significant drop in accuracy. Furthermore, for classification, our proposed approach outperforms the state of the art classifiers even though we used significantly shorter windows for feature extraction.
Is Part Of	https://kar.kent.ac.uk/id/repository
list of authors	https://kar.kent.ac.uk/id/eprint/72664#authors
presented at	40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2018)
is topic of	https://www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #72664 Recurrent Neural Network Based Early Prediction of Future Hand Movements

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