  Empirical Mode Decomposition is an adaptive and local tool that extracts
underlying analytical components of a non-linear and non-stationary process, in
turn, is the basis of Hilbert Huang transform, however, there are problems such
as interfering modes or ensuring the orthogonality of decomposition. Three
variants of the algorithm are evaluated, with different experimental parameters
and on a set of 10 time series obtained from surface electromyography.
Experimental results show that obtaining low error in reconstruction with the
analytical signals obtained from a process is not a valid characteristic to
ensure that the purpose of decomposition has been fulfilled (physical
significance and no interference between modes), in addition, freedom must be
generated in the iterative processes of decomposition so that it has
consistency and does not generate biased information. This project was
developed within the framework of the research group DIGITI of the Universidad
Distrital Francisco Jos\'e de Caldas.
