An automatic saccadic eye movement detection in an optokinetic nystagmus signal.

A saccade is one of the characteristic types of eye movements. The accurate detection and location of saccades in the signal representing the movement activity of the eyes are essential in medical applications. The main purpose of this paper is to present a new, robust approach to the detection of saccadic eye movements. The procedure is based on a so-called detection function, which is the result of the electronystagmographic (ENG) myriad signal filtering, nonlinear operation, and fuzzy median clustering. Smooth peaks of the detection function waveform correspond to the location of saccades in the ENG signal. The median fuzzy clustering-based method allows for calculating the amplitude threshold of the detection function, which improves the accurate saccade recognition. Both of these robust methods provide a two-step protection against outliers. The proposed algorithm was tested using artificial as well as real optokinetic nystagmus signals under different noise conditions. The results show the usefulness of the procedure when the precise detection and location of saccades are necessary.

A new method of saccadic eye movement detection for optokinetic nystagmus analysis.

The analysis of eye movements is valuable in both clinical work and research. One of the characteristic type of eye movements is saccade. The accurate detection of saccadic eye movements is the base for further processing of saccade parameters such as velocity, amplitude and duration. This paper concerns an accurate saccade detection method that is based on pre-processing signal and then the proposed non-linear detection function can be applied. The described method characterizes less sensitivity for any kind of noise due to an application of the robust myriad filter which is used to eliminate baseline drifts and impulsive artifacts. The congenital nystagmus is one of the field where our method can be applied to detect saccades. The proposed detection function is computationally efficient and precisely determines the time position of saccadic eye movements even when the signal-to-noise ratio is low. The presented method may have potential application in automatic ENG signal processing systems for determining visual acuity.