I am looking for information related to different methods to estimate the activation of electromyographic activity using surface electromyography. I have found some things in the literature but I do not know if there is any gold standard. I want to know in relation to the classic and new trends.
Thank you for the help and recommendations (literature and/or technical comments).
Unfortunately there is not a gold standard approach. Typically the mean of a window of the baseline signal will be multiplied by a multiple of the standard deviation of the window.
The filtering of the signal, location and size of the window and the multiple of the standard deviation varies. As does the signal acquisition parameters, though I believe the signal acquisition parameters should change depending on the analysis, which will obviously affect the prior parameters.
I guess this isn't the news you were looking for, but there are a reviews you can use to gauge what the typical range of parameters are.
Hi,
There are a number of algorithms, some of them being recent ones. Here is a short list
Analysis of statistical and standard algorithms for detecting muscle onset with surface electromyography, http://dx.doi.org/10.1371/journal.pone.0177312
Robust muscle activity onset detection using an unsupervised electromyogram learning framework., https://doi.org/10.1371/journal.pone.0127990
The concurrent validity of three computerized methods of muscle activity onset detection, http://dx.doi.org/10.1016/j.jelekin.2015.07.009
EMG burst presence probability: A joint time-frequency representation of muscle activity and its application to onset detection, http://dx.doi.org/10.1016/j.jbiomech.2015.02.017
An adaptive algorithm for the determination of the onset and offset of muscle contraction by EMG signal processing, http://dx.doi.org/10.1109/TNSRE.2012.2226916
Novel formulation of a double threshold algorithm for the estimation of muscle activation intervals designed for variable SNR environments, http://dx.doi.org/10.1016/j.jelekin.2012.04.010
EMG Onset Detection Based on Teager–Kaiser Energy Operator and Morphological Close Operation, http://link.springer.com/10.1007/978-3-642-16587-0
Teager-Kaiser energy operator signal conditioning improves EMG onset detection, http://dx.doi.org/10.1007/s00421-010-1521-8
Dear Gabriel Carreño-Zillmann;
There are a lot of algorithms in the literature, however there is not a gold standard approach for superficial methods. Mr. Şayli listed some references, and ı suggest our method as well.
https://www.ncbi.nlm.nih.gov/pubmed/25356122
- Badges
- Science topic
- Similar topics
- Engineering
- Electrical Engineering
- Signal Processing