1-D local binary patterns for onset detection of myoelectric signals

Tools

McCool, Paul and Chatlani, Navin and Petropoulakis, Lykourgos and Soraghan, John and Menon, Radhika and Lakany, Heba; (2012) 1-D local binary patterns for onset detection of myoelectric signals. In: 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO). IEEE, ROM, pp. 499-503. ISBN 978-1-4673-1068-0

Full text not available in this repository.Request a copy

Abstract

This paper presents a new 1-D LBP (Local Binary Pattern) based technique for onset detection. The algorithm is tested on forearm surface myoelectric signals that occur due to lower arm gestures. Unlike other onset detection algorithms, the method does not require manual threshold setting and fine-tuning, which makes it faster and easier to implement. The only variables are window size, histogram type and the number of histogram bins. It is also not necessary to measure the properties of the signal during a quiescent period before the algorithm can be used. 1-D LBP Onset Detection is compared with single and double threshold methods and is shown to be more robust and accurate.

ORCID iDs

McCool, Paul, Chatlani, Navin, Petropoulakis, Lykourgos ORCID logoORCID: https://orcid.org/0000-0003-3230-9670, Soraghan, John ORCID logoORCID: https://orcid.org/0000-0003-4418-7391, Menon, Radhika ORCID logoORCID: https://orcid.org/0000-0001-9640-2052 and Lakany, Heba ORCID logoORCID: https://orcid.org/0000-0003-3079-0392;
CORE (COnnecting REpositories)