@inproceedings{b4938e8334d349a7afdffa857954ea1e,
title = "Recognition of myoelectric activity based on Teager-Kaiser energy operator",
abstract = "A challenge in myoelectric control for electrical prosthesis is to obtain information from myoelectric signals to activate the degrees of freedom of the prosthesis. When only a little muscular surface is disposable to detect the myoelectric signal the problem is not easy to solve because only one or two channels can be recorded. So, when only a pair of electrodes or one channel is used to record the signal, strategies to extract more information from the signals should be developed. Then more than one function could be activated in a myoelectric prosthesis. In this paper the Teager-Kaiser energy operator is evaluated in the task of myoelectric signal recognition. Specifically two levels of signal were identified: level 1 (87.37 percent of classification) and level 2 (84.09 percent of classification).",
keywords = "Teager-Kaiser energy operator, electromyographic signal, myoelectric control",
author = "A. Ram{\'i}rez-Garc{\'i}a and I. Baz{\'a}n",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2015 ; Conference date: 26-10-2015 Through 30-10-2015",
year = "2015",
month = dec,
day = "14",
doi = "10.1109/ICEEE.2015.7357962",
language = "Ingl{\'e}s",
series = "2015 12th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 12th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2015",
address = "Estados Unidos",
}