Stable Electromyographic Sequence Prediction During Movement Transitions using Temporal Convolutional Networks

Autor: Betthauser, Joseph L., Krall, John T., Kaliki, Rahul R., Fifer, Matthew S., Thakor, Nitish V.

Transient muscle movements influence the temporal structure of myoelectric signal patterns, often leading to unstable prediction behavior from movement-pattern classification methods. We show that temporal convolutional network sequential models leve

Externí odkaz: http://arxiv.org/abs/1901.02442

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Mapping of unknown environments using minimal sensing from a stochastic swarm.

Autor: Dirafzoon, Alireza, Betthauser, Joseph, Schornick, Jeff, Benavides, Daniel, Lobaton, Edgar

Publikováno v: 2014 IEEE/RSJ International Conference on Intelligent Robots & Systems; 2014, p3842-3849, 8p

Electrode-shift Tolerant Myoelectric Movement-pattern Classification using Extreme Learning for Adaptive Sparse Representations.

Autor: Betthauser JL; Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA., Osborn LE; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA., Kaliki RR; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA.; Infinite Biomedical Technologies, LLC., Baltimore, Maryland 21218, USA., Thakor NV; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA.; Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA.

Publikováno v: IEEE Biomedical Circuits and Systems Conference : healthcare technology : [proceedings]. IEEE Biomedical Circuits and Systems Conference [IEEE Biomed Circuits Syst Conf] 2017 Oct; Vol. 2017. Date of Electronic Publication: 2018 Mar 29.