  The glissadic overshoot is characterized by an unwanted type of movement
known as glissades. The glissades are a short ocular movement that describe the
failure of the neural programming of saccades to move the eyes in order to
reach a specific target. In this paper we develop a procedure to determine if a
specific saccade have a glissade appended to the end of it. The use of the
third partial sum of the Gauss series as mathematical model, a comparison
between some specific parameters and the RMSE error are the steps made to reach
this goal. Finally a machine learning algorithm is trained, returning expected
responses of the presence or not of this kind of ocular movement.
