Paper Info
Title
A Snr-Independent Formulation Of A Double Threshold Algorithm For The Estimation Of Muscle Activation Intervals
Abstract
The aim of this work is to propose an improvement to the double threshold algorithm for muscular activation intervals estimation developed by Bonato and his co-workers. The proposed method has been designed in order to be adaptive also when the Signal to Noise ratio (SNR) of the sEMG signal changes during the trial, by re-evaluating the parameters of the algorithm according to the estimated local SNR and the desired detection and false alarm probabilities. This novel implementation is also suitable for working in pseudo real-time since it can give information on burst estimation shortly after the end of the current muscular activity. The proposed method was tested on simulated signals taking into account changes in the SNR during the trial, and results were compared with those obtained with the classical implementation of the algorithm.
Year
DOI
Venue
2011
10.1109/IEMBS.2011.6091849
2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Keywords
DocType
Volume
estimation,muscle,signal to noise ratio,algorithm design,real time,interval estimation,algorithm design and analysis
Conference
2011
ISSN
Citations 
PageRank 
1557-170X
0
0.34
References 
Authors
3
5
Name
Order
Citations
PageRank
G Severini111.70
Silvia Conforto29419.87
Cristiano De Marchis3125.89
Maurizio Schmid48916.32
T D'Alessio511.11